Track multi-source dynamic detection data mileage alignment method and device

Abstract

The application discloses a track multi-source dynamic detection data mileage alignment method and device, and relates to the technical field of track transportation; wherein the method comprises the following steps: removing the broken chain of standard mileage data according to the standard mileage data of standard data, a sampling interval, a starting sampling point mileage and line broken chain account information, so as to obtain standard straight development mileage and broken chain position information; performing mileage integration reset on to-be-calibrated mileage data according to train running speed data, a sampling frequency of the to-be-calibrated data and the starting sampling point mileage, so as to obtain to-be-calibrated straight development mileage; configuring calibration parameters; calibrating the to-be-calibrated straight development mileage in sections according to the calibration parameters, first vehicle body acceleration data, second vehicle body acceleration data and the standard straight development mileage, so as to obtain calibration straight development mileage corresponding to the to-be-calibrated straight development mileage; performing broken chain correction on the calibration straight development mileage according to the broken chain position information, so as to obtain calibration mileage data after mileage alignment of the to-be-calibrated mileage data. The application can improve the accuracy of mileage alignment.

Description

Technical Field

[0001] This invention relates to the field of rail transit technology, and in particular to a method and apparatus for aligning mileage data from multi-source dynamic detection of rail transit. Background Technology

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] Track smoothness directly affects the safety and comfort of vehicle operation. To ensure long-term stable and good track smoothness, railway maintenance and repair departments invest significant human, material, and financial resources. Track maintenance costs account for over 70% of the total track lifecycle cost. Therefore, specific track quality evaluation indicators are needed to quantitatively evaluate and predict track conditions, optimize track maintenance operations, prioritize tasks, and ultimately improve maintenance efficiency and reduce costs. Currently, multiple track condition detection systems exist to comprehensively evaluate track smoothness from multiple perspectives. These include track geometric irregularity detection systems, vehicle dynamic response detection systems, and wheel-rail force detection systems. These systems are also installed on high-speed integrated inspection trains and equipped with a spatial positioning integrated system based on the fusion of multi-source mileage information from GNSS, RFID, and photoelectric encoders. This system intermittently transmits integrated mileage information to the aforementioned detection systems, corresponding to the mileage detected by different systems. However, the track geometry irregularity detection system uses an equidistant sampling detection mode to collect detection data such as dynamic track geometry irregularities and other ancillary information. Its detection mileage can be calculated by accumulating the number of encoder pulses, while simultaneously receiving precise mileage positioning calibration GNSS and RFID mileage information provided by the integrated system. In contrast, the vehicle dynamic response detection system and the wheel-rail force detection system use an equidistant sampling detection mode to collect data such as axle box, frame, car body acceleration, wheel-rail lateral and vertical forces, and velocity. Their detection mileage is obtained by continuously receiving mileage information from the integrated mileage system at a specific mileage reception frequency. However, due to the higher sampling frequency of the two detection systems compared to the mileage reception frequency, and the truncation of mileage due to limited number of bits, there are numerous instances where "multiple detection data points correspond to completely identical mileages" in the mileage of the two detection systems. Therefore, although the three track condition detection systems receive mileage information from the same integrated mileage system, differences in data sampling modes and integrated mileage reception triggering mechanisms ultimately lead to mileage discrepancies between different detection systems on the same integrated inspection train. This error seriously affects track smoothness evaluation work, such as on-site location of detected defects and analysis and prediction of track condition evolution patterns based on long-term detection data.

[0004] The existing solution involves equipping the same inspection vehicle with different inspection systems to simultaneously inspect the track condition of the same line. Approximate mileage alignment is achieved based on the similarity between speed curves in the multi-source inspection data. However, the matching results are relatively coarse for two reasons: First, constrained by the characteristic of "mostly constant speed and few speed changes" in actual vehicle operation, this method can only align the speed curves in the speed change section, thereby indirectly adjusting the mileage in the constant speed section. Furthermore, the sub-segment length used in the calibration process should not be too short, otherwise waveform distortion may occur. Second, due to the high sampling frequency of the vehicle dynamic response and wheel-rail force detection systems, and the rounding of speed sampling, the corresponding speed data exhibits significant "sawtooth" fluctuations, which to some extent affects the similarity matching of the speed waveforms in the corresponding sections. Summary of the Invention

[0005] This invention provides a method for mileage alignment of multi-source dynamic track detection data, to improve the accuracy of mileage alignment of multi-source track detection data and the reliability of mileage in the second detection system. The method includes:

[0006] Acquire the data to be calibrated and the standard data; the data to be calibrated and the standard data are data collected by different detection systems on the same train during the same train operation, and the standard data is the calibrated data; the standard data includes standard mileage data and the first car body acceleration data corresponding to the standard mileage data, and the data to be calibrated includes the mileage data to be calibrated, the second car body acceleration data corresponding to the mileage data to be calibrated, and the train running speed data corresponding to the mileage data to be calibrated.

[0007] Based on the sampling interval of the standard data, the starting sampling point mileage of the standard data, and the broken chain ledger information corresponding to the standard data, the broken chain is removed from the standard mileage data to obtain the standard extended mileage and broken chain location information corresponding to the standard mileage data.

[0008] Based on the train speed data, the sampling frequency of the data to be calibrated, and the starting sampling point mileage of the data to be calibrated, the mileage data to be calibrated is reset by mileage integration to obtain the initial calibrated sequential mileage, and the initial calibrated sequential mileage is assigned to the calibrated sequential mileage.

[0009] Configure calibration parameters, which include: preset similarity threshold, first initial segment length to be calibrated, second initial segment length to be calibrated, first initial segment mileage translation correction threshold, second initial segment mileage translation correction threshold, segment sampling frequency correction threshold, segment mileage translation correction threshold sampling step size threshold, segment sampling frequency correction threshold sampling step size threshold, initial segment extension times, segment extension times threshold, and mileage data resampling interval in similarity calculation;

[0010] Based on the calibration parameters, the first vehicle body acceleration data, the second vehicle body acceleration data, and the standard stretch mileage, the stretch mileage to be calibrated is extracted and calibrated segment by segment. After the entire line is calibrated segment by segment, the calibrated stretch mileage corresponding to the stretch mileage to be calibrated is obtained.

[0011] Based on the standard mileage data and the chain breakage location information, the chain breakage correction is performed on the calibration mileage data to obtain the calibration mileage data after mileage alignment.

[0012] This invention also provides a track multi-source dynamic detection data mileage alignment device to improve the accuracy of track multi-source detection data mileage alignment and the reliability of the second detection system mileage. The device includes:

[0013] The acquisition module is used to acquire data to be calibrated and standard data. The data to be calibrated and the standard data are data collected by different detection systems on the same train during the same train operation. The standard data is the calibrated data. The standard data includes standard mileage data and the first vehicle body acceleration data corresponding to the standard mileage data. The data to be calibrated includes mileage data to be calibrated, the second vehicle body acceleration data corresponding to the mileage data to be calibrated, and the train running speed data corresponding to the mileage data to be calibrated.

[0014] The first processing module is used to remove broken links from the standard mileage data based on the sampling interval of the standard data, the starting sampling point mileage of the standard data, and the broken link ledger information corresponding to the standard mileage data, so as to obtain the standard continuous mileage and broken link location information corresponding to the standard mileage data.

[0015] The second processing module is used to reset the mileage data to be calibrated by integrating the mileage data according to the train running speed data, the sampling frequency of the data to be calibrated, and the mileage of the starting sampling point of the data to be calibrated, to obtain the initial mileage to be calibrated, and to assign the initial mileage to be calibrated to the mileage to be calibrated.

[0016] The parameter configuration module is used to configure calibration parameters, which include: preset similarity threshold, first initial calibrated segment length, second initial calibrated segment length, first initial segment mileage translation correction threshold, second initial segment mileage translation correction threshold, segment sampling frequency correction threshold, segment mileage translation correction threshold sampling step size threshold, segment sampling frequency correction threshold sampling step size threshold, initial calibrated segment extension times, segment extension times threshold, and mileage data resampling interval in similarity calculation;

[0017] The third processing module is used to extract and calibrate the stretch mileage to be calibrated segment by segment based on the calibration parameters, the first vehicle body acceleration data, the second vehicle body acceleration data, and the standard stretch mileage. After the full line is calibrated segment by segment, the calibrated stretch mileage corresponding to the stretch mileage to be calibrated is obtained.

[0018] The fourth processing module is used to correct the chain breakage of the calibration mileage based on the standard mileage data and the chain breakage location information, so as to obtain the calibration mileage data after the mileage data to be calibrated is aligned.

[0019] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described method for mileage alignment of multi-source dynamic detection data of orbits.

[0020] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for mileage alignment of multi-source dynamic detection data of orbits.

[0021] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for mileage alignment of multi-source dynamic detection data of orbits.

[0022] In this embodiment of the invention, data to be calibrated and standard data are acquired. The data to be calibrated and the standard data are data collected by different detection systems on the same train during the same train operation. The standard data is the calibrated data. The standard data includes standard mileage data and the first vehicle body acceleration data corresponding to the standard mileage data. The data to be calibrated includes mileage data to be calibrated, the second vehicle body acceleration data corresponding to the mileage data to be calibrated, and the train running speed data corresponding to the mileage data to be calibrated. Based on the sampling interval of the standard data, the starting sampling point mileage of the standard data, and the chain breakage log information corresponding to the standard data, the standard mileage data is processed to remove chain breaks, obtaining the standard sequential mileage corresponding to the standard mileage data and the chain breakage location information. Based on the train running speed data, the sampling frequency of the data to be calibrated, and the starting sampling point mileage of the data to be calibrated, the mileage data to be calibrated is reset by mileage integration to obtain the initial sequential mileage to be calibrated. The calibration stretch mileage is assigned to the stretch mileage to be calibrated; calibration parameters are configured, including: a preset similarity threshold, the length of the first initial segment to be calibrated, the length of the second initial segment to be calibrated, the first initial segment mileage translation correction threshold, the second initial segment mileage translation correction threshold, the segment sampling frequency correction threshold, the sampling step size threshold of the segment mileage translation correction threshold, the sampling step size threshold of the segment sampling frequency correction threshold, the number of extensions of the initial segment to be calibrated, the threshold for the number of extensions, and the mileage data resampling interval in similarity calculation; based on the calibration parameters, the first vehicle acceleration data, the second vehicle acceleration data, and the standard stretch mileage, the stretch mileage to be calibrated is extracted and calibrated segment by segment. After the entire line is calibrated segment by segment, the calibration stretch mileage corresponding to the stretch mileage to be calibrated is obtained; based on the standard stretch mileage corresponding to the standard mileage data and the chain break location information, the calibration stretch mileage is corrected for chain breakage to obtain the calibration mileage data after mileage alignment of the stretch mileage data to be calibrated. In this way, the vehicle acceleration waveforms from different detection systems are used as reference channels for mileage synchronization and alignment. Supplemented by train speed data sequences, time integration is performed to reconstruct continuous mileage. Based on standard data and data to be calibrated, mileage calibration is performed segment by segment to achieve mileage alignment. This achieves automatic, efficient, and accurate mileage alignment of multi-source detection data, with strong applicability to calibration sections, improving the accuracy of mileage alignment of multi-source track detection data and the reliability of the second detection system's mileage. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0024] Figure 1 This is a flowchart of a method for aligning track multi-source dynamic detection data mileage provided in an embodiment of the present invention;

[0025] Figure 2 This invention provides a flowchart of a method for extracting and calibrating the stretch mileage to be calibrated segment by segment based on calibration parameters, first vehicle acceleration data, second vehicle acceleration data, and standard stretch mileage, and obtaining the calibration stretch mileage corresponding to the stretch mileage to be calibrated after the entire line is calibrated segment by segment.

[0026] Figure 3 This is a flowchart of a method for determining a combination of multiple segment mileage translation correction values ​​and sampling frequency correction values ​​based on a segment mileage translation correction threshold, a segment sampling frequency correction threshold, a sampling step size threshold of the segment mileage correction threshold, and a sampling step size threshold of the segment sampling frequency correction threshold, provided in an embodiment of the present invention.

[0027] Figure 4 This is a schematic diagram of a track multi-source dynamic detection data mileage alignment device provided in an embodiment of the present invention;

[0028] Figure 5 This is a schematic diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0030] The acquisition, storage, use, and processing of data in this application comply with relevant laws and regulations.

[0031] In this document, the term "and / or" merely describes a relationship, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0032] In the description of this specification, the terms "comprising," "including," "having," and "containing" are open-ended terms, meaning that they include but are not limited to. The terms "an embodiment," "a specific embodiment," "some embodiments," and "for example," etc., refer to specific features, structures, or characteristics described in connection with that embodiment or example that are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. The order of steps involved in the various embodiments is used to illustrate the implementation of this application, and the order of steps is not limited and can be adjusted appropriately as needed.

[0033] Research has revealed that existing mileage alignment methods involve using the same inspection vehicle equipped with different inspection systems to simultaneously monitor the track status of the same line. Approximate mileage alignment is achieved based on the similarity between speed curves in the multi-source inspection data. However, the matching results are relatively coarse for two reasons: First, constrained by the characteristic of "mostly constant speed and few speed changes" in actual vehicle operation, this method can only align speed curves in speed-changing sections, thereby indirectly adjusting the mileage in constant-speed sections. Furthermore, the sub-segment length used in the calibration process should not be too short, otherwise waveform distortion may occur. Second, due to the high sampling frequency of vehicle dynamic response and wheel-rail force detection systems, and the rounding of speed sampling, the corresponding speed data exhibits significant "sawtooth" fluctuations, which to some extent affects the similarity matching of speed waveforms in corresponding sections.

[0034] In response to the above research, embodiments of the present invention provide a method for mileage alignment of multi-source dynamic detection data of orbits, such as... Figure 1 As shown, it includes:

[0035] S101: Acquire the data to be calibrated and the standard data; wherein, the data to be calibrated and the standard data are data collected by different detection systems on the same train during the same train operation, and the standard data is the calibrated data; the standard data includes standard mileage data and the first car body acceleration data corresponding to the standard mileage data, and the data to be calibrated includes the mileage data to be calibrated, the second car body acceleration data corresponding to the mileage data to be calibrated, and the train running speed data corresponding to the mileage data to be calibrated;

[0036] S102: Based on the sampling interval of the standard data, the starting sampling point mileage of the standard data, and the broken chain ledger information corresponding to the standard data, the broken chain is removed from the standard mileage data to obtain the standard extended mileage and broken chain location information corresponding to the standard mileage data.

[0037] S103: Based on the train speed data, the sampling frequency of the data to be calibrated, and the starting sampling point mileage of the data to be calibrated, the mileage data to be calibrated is reset by mileage integration to obtain the initial calibrated sequential mileage, and the initial calibrated sequential mileage is assigned to the calibrated sequential mileage.

[0038] S104: Configure calibration parameters, which include: preset similarity threshold, first initial calibrated segment length, second initial calibrated segment length, first initial segment mileage translation correction threshold, second initial segment mileage translation correction threshold, segment sampling frequency correction threshold, segment mileage translation correction threshold sampling step size threshold, segment sampling frequency correction threshold sampling step size threshold, initial calibrated segment extension times, segment extension times threshold, and mileage data resampling interval in similarity calculation;

[0039] S105: Based on the calibration parameters, the first vehicle body acceleration data, the second vehicle body acceleration data, and the standard stretch mileage, the stretch mileage to be calibrated is extracted and calibrated segment by segment. After the entire line is calibrated segment by segment, the calibration stretch mileage corresponding to the stretch mileage to be calibrated is obtained.

[0040] S106: Based on the standard mileage data corresponding to the standard mileage data and the chain breakage location information, perform chain breakage correction on the calibration mileage data to obtain the calibration mileage data after mileage alignment of the mileage data to be calibrated.

[0041] Acquire the data to be calibrated and the standard data. The data to be calibrated and the standard data are data collected by different detection systems on the same train during the same train operation. The standard data is the calibrated data. The standard data includes standard mileage data and the corresponding first car body acceleration data. The data to be calibrated includes the mileage data to be calibrated, the corresponding second car body acceleration data, and the corresponding train speed data. Based on the sampling interval of the standard data, the starting sampling point mileage of the standard data, and the corresponding chain breakage log information, the standard mileage data is processed to remove chain breaks, obtaining the standard extended mileage and chain breakage location information. Based on the train speed data, the sampling frequency of the data to be calibrated, and the starting sampling point mileage of the data to be calibrated, the mileage to be calibrated is reset by mileage integration to obtain the initial extended mileage to be calibrated. The mileage is assigned to the mileage to be calibrated; calibration parameters are configured, including: a preset similarity threshold, the length of the first initial segment to be calibrated, the length of the second initial segment to be calibrated, the mileage translation correction threshold of the first initial segment, the mileage translation correction threshold of the second initial segment, the segment sampling frequency correction threshold, the sampling step size threshold of the segment mileage translation correction threshold, the sampling step size threshold of the segment sampling frequency correction threshold, the number of extensions of the initial segment to be calibrated, the threshold of the number of extensions, and the mileage data resampling interval in similarity calculation; based on the calibration parameters, the first vehicle acceleration data, the second vehicle acceleration data, and the standard mileage, the mileage to be calibrated is extracted and calibrated segment by segment. After the entire line is calibrated segment by segment, the calibrated mileage corresponding to the mileage to be calibrated is obtained; based on the standard mileage corresponding to the standard mileage data and the chain break location information, the calibrated mileage is corrected for chain breakage to obtain the calibrated mileage data after mileage alignment. In this way, the vehicle acceleration waveforms from different detection systems are used as reference channels for mileage synchronization and alignment. Supplemented by train speed data sequences, time integration is performed to reconstruct continuous mileage. Based on standard data and data to be calibrated, mileage calibration is performed segment by segment to achieve mileage alignment. This achieves automatic, efficient, and accurate mileage alignment of multi-source detection data, with strong applicability to calibration sections, improving the accuracy of mileage alignment of multi-source track detection data and the reliability of the second detection system's mileage.

[0042] The following section provides a detailed introduction to the above-mentioned method for aligning the mileage of multi-source dynamic detection data of the track.

[0043] Regarding S101 above, the data to be calibrated and the standard data are data collected by different detection systems on the same train during the same train operation. For example, the first detection system on the train collects the standard data, and the second detection system on the train collects the data to be calibrated.

[0044] Here, the first detection system includes, for example, a track geometry detection system, and the second detection system includes, for example, a vehicle dynamic response detection system and a wheel-rail force detection system.

[0045] Specifically, the standard data is data that has been calibrated in advance using other methods, so the data to be calibrated can be calibrated with reference to the standard data. In one embodiment of the present invention, the standard data includes standard mileage data and first vehicle body acceleration data corresponding to the standard mileage data, and the data to be calibrated includes mileage data to be calibrated, second vehicle body acceleration data corresponding to the mileage data to be calibrated, and train running speed data corresponding to the mileage data to be calibrated.

[0046] Among them, the first vehicle body acceleration data and the second vehicle body acceleration data include, for example, lateral vehicle body acceleration data and vertical vehicle body acceleration data, and either one can be selected as the calibration reference.

[0047] Regarding S102 above, in one embodiment of the present invention, based on the sampling interval of the standard data, the starting sampling point mileage of the standard data, and the broken chain ledger information corresponding to the standard data, the broken chain data is processed to remove broken chains, thereby obtaining the standard continuous mileage corresponding to the standard mileage data and the broken chain location information, including:

[0048] Based on the sampling interval and the starting sampling point mileage of the standard data, the following formula is used to remove chain breaks from the standard mileage data, yielding the corresponding standard extended mileage:

[0049]

[0050] Where m 1st (1) is the mileage of the starting sampling point for the standard data; dL samp The sampling interval for standard data;

[0051] The standard extended mileage is obtained after removing broken chains; i is the index value of the standard data, with a value range of i = 1, 2, ..., P, where P is the number of standard mileage data in the standard data;

[0052] Based on the broken chain type, starting mileage, and ending mileage in the broken chain ledger information, the standard mileage data is traversed to determine the index values ​​of the starting and ending mileages of the broken chain within the standard mileage data. These index values, along with their corresponding standard mileages and sequential mileages, are used as the broken chain location information. For example, Table 1 below shows a broken chain ledger information table provided in an embodiment of the present invention, and Table 2 shows a correspondence table for marking broken chain locations in standard mileage data based on the broken chain ledger information.

[0053] Table 1. Chain Breakage Ledger Information Table

[0054]

[0055] Table 2

[0056]

[0057] First, chain break marking is performed: Iterate through each chain break entry in Table 1 and mark the break location in Table 2 using the standard mileage. For example, for the first chain break entry in Table 1, this chain type is short, with a starting mileage of 0.01km and an ending mileage of 0.011km. Searching the standard mileage column in Table 2, the 4th and 5th standard mileage entries match the starting and ending mileages of this chain break, respectively. Mark the break location as short (i.e., value -1). Next, query the second chain break entry, this chain type is long, with a starting mileage of 0.0125km and an ending mileage of 0.0130km. Searching the standard mileage column in Table 2, the 13th and 14th standard mileage entries match the starting and ending mileages of this chain break, respectively. Mark the break location as short (i.e., value 1). If more chain breaks are found, repeat the above rules until all entries are traversed.

[0058] Next, the chain break removal process is carried out: referring to the starting sampling point mileage and sampling interval of the standard mileage, the standard mileage is extended, and the resulting standard extended mileage is shown in the "Standard Extended Mileage" column of Table 3.

[0059] Table 3

[0060]

[0061] Regarding S103 above, based on the train speed data, the sampling frequency of the data to be calibrated collected by the second detection system, and the mileage of the starting sampling point, the mileage data to be calibrated is reset by mileage integration to obtain the mileage to be calibrated. For example, this includes: using the sampling frequency of the data to be calibrated, the mileage of the starting sampling point of the data to be calibrated, and the train speed data, the mileage data to be calibrated is reset by mileage integration using the following formula to obtain the initial mileage to be calibrated:

[0062]

[0063] Where, m 2nd (1) represents the mileage of the starting sampling point of the data to be calibrated; F0 represents the sampling frequency of the data to be calibrated; V 2nd For train speed data; The initial calibrated mileage is obtained after resetting the mileage data by mileage integration; j is the index value of the data to be calibrated, with a value range of j = 1, 2, ..., Q, where Q is the number of calibrated mileage data in the data to be calibrated.

[0064] The initial calibrated mileage is assigned to the calibrated mileage using the following formula:

[0065]

[0066] in, The mileage to be calibrated.

[0067] For example, Table 4 shows an example table of resetting the mileage integral of the mileage to be calibrated and obtaining the initial mileage to be calibrated according to an embodiment of the present invention:

[0068] Table 4

[0069]

[0070] For the above S104, the calibration parameters include, for example: a preset similarity threshold, the length of the first initial segment to be calibrated, the length of the second initial segment to be calibrated, the first initial segment mileage translation correction threshold, the second initial segment mileage translation correction threshold, the segment sampling frequency correction threshold, the sampling step size threshold of the segment mileage translation correction threshold, the sampling step size threshold of the segment sampling frequency correction threshold, the number of times the initial segment to be calibrated is extended, the threshold for the number of times the segment is extended, and the mileage data resampling interval in similarity calculation.

[0071] The preset similarity threshold is used to measure whether the second vehicle acceleration data of each segment of the extended mileage to be calibrated matches the first vehicle acceleration data of the corresponding standard extended mileage when performing segment-by-segment calibration of the extended mileage to be calibrated. The first initial segment length and the second initial segment length are used to determine the data range of the next segment to be calibrated based on the different calibration conditions of the previous segment when performing segment-by-segment calibration of the extended mileage to be calibrated. The first initial segment mileage translation correction threshold and the second initial segment mileage translation correction threshold are used to determine the range of segment mileage translation correction for the next segment to be calibrated based on the different calibration conditions of the previous segment when performing segment-by-segment calibration of the extended mileage to be calibrated. The sampling step size threshold of the segment mileage translation correction threshold refers to the minimum sampling step size that can be used in the processing steps of determining multiple segment mileage translation correction values ​​based on the range of segment mileage translation correction. The segment sampling frequency correction threshold is used to determine the range of segment sampling frequency correction for the next segment to be calibrated based on the different calibration conditions of the previous segment when performing segment-by-segment calibration of the extended mileage to be calibrated. The sampling step size threshold for the segment sampling frequency correction threshold refers to the minimum sampling step size that can be used in the processing steps of determining multiple segment sampling frequency correction values ​​based on the range of segment sampling frequency correction. The initial number of extensions for the segment to be calibrated is used to reset the current number of extensions when changing the segment to be calibrated during the segment-by-segment calibration of the calibrated extended mileage. The segment extension number threshold is used to determine whether to extract a new segment of calibrated extended mileage for subsequent calibration steps or to extend the current segment of calibrated extended mileage before subsequent calibration steps when performing segment-by-segment calibration of the calibrated extended mileage. The mileage data resampling interval in similarity calculation refers to the sampling step size used when resampling the second vehicle body acceleration corresponding to the corrected extended mileage of the current segment to be calibrated and the first vehicle body acceleration corresponding to the standard extended mileage at equal intervals during the segment-by-segment calibration of the calibrated extended mileage, calculated under each segment translation correction value and sampling frequency correction value. For a detailed explanation of the function of each calibration parameter, please refer to the detailed introduction of segment-by-segment calibration of the calibrated extended mileage below.

[0072] The specific values ​​for each calibration parameter can be set according to the actual application scenario, and there are no restrictions here.

[0073] Regarding the aforementioned S105, such as Figure 2 The diagram illustrates a method provided by an embodiment of the present invention for extracting and calibrating the stretch mileage to be calibrated segment by segment based on calibration parameters, first vehicle acceleration data, second vehicle acceleration data, and standard stretch mileage. After the segment-by-segment calibration of the entire line is completed, the calibration stretch mileage corresponding to the stretch mileage to be calibrated is obtained. The method includes: performing the following steps based on calibration parameters, first vehicle acceleration, second vehicle acceleration, and standard stretch mileage to obtain the calibration stretch mileage corresponding to the stretch mileage to be calibrated:

[0074] Step 1: Based on the mileage to be calibrated and the standard mileage, determine the starting point mileage of the common mileage segment between the mileage to be calibrated and the standard mileage. Assign the starting point mileage of the common mileage segment between the mileage to be calibrated and the standard mileage to the starting point mileage of the segment to be calibrated. Assign the first initial length of the segment to be calibrated to the length of the segment to be calibrated.

[0075] For example, if the standard mileage is 5m to 25m and the mileage to be calibrated is 3m to 20m, then the common mileage section between the standard mileage and the mileage to be calibrated is 5m to 20m, and the starting point of the mileage is 5m.

[0076] Step 2: Based on the starting mileage, length, and calibrated mileage of the section to be calibrated, determine the corresponding section to be calibrated. Use the data corresponding to the section to be calibrated as the data for the section to be calibrated. The data for the section to be calibrated includes: the index value of the starting point, the index value of the ending point, the calibrated mileage, the second car body acceleration data, and the train speed data for the section to be calibrated.

[0077] For example, if the length of the first initial section to be calibrated is 5m, then the section from 5m to 10m of the extended mileage to be calibrated is extracted as the first section to be calibrated.

[0078] In one embodiment of the present invention, a corresponding section to be calibrated is determined based on the starting mileage of the section to be calibrated, the length of the section to be calibrated, and the mileage to be calibrated. The data corresponding to the section to be calibrated is used as the data of the section to be calibrated. For example, this includes: retrieving the index value of a first mileage point in the current mileage to be calibrated that has the smallest deviation from the starting mileage of the current mileage to be calibrated and whose mileage deviation is not greater than the mileage data resampling interval; using the index value of the first mileage point as the index value of the starting point of the section to be calibrated; and determining whether the sum of the starting mileage of the current mileage to be calibrated and the length of the current mileage to be calibrated is greater than the total mileage to the end point of the mileage to be calibrated. If yes, use the index value of the entire end point as the index value of the end point of the section to be calibrated; if no, retrieve the index value of the second mileage point in the current mileage to be calibrated where the deviation between the mileage to the start point of the current mileage to be calibrated and the sum of the length of the section to be calibrated is the smallest and the mileage deviation is not greater than the mileage data resampling interval, and use the index value of the second mileage point as the index value of the end point of the section to be calibrated; based on the index values ​​of the start point and the end point of the section to be calibrated, extract the mileage to be calibrated, the second car body acceleration data, and the train running speed data between the index values ​​of the start point and the end point of the section to be calibrated.

[0079] Step 3: Determine whether the current section to be calibrated is the first time a calibration calculation is performed. If yes, proceed to step 5; otherwise, proceed to step 4.

[0080] Step 4: Determine if there is an uncalibrated segment before the current segment to be calibrated. If yes, proceed to step 5; otherwise, proceed to step 8.

[0081] Step 5: Determine if there is a calibrated section before the current section to be calibrated. If not, proceed to step 6; if yes, proceed to step 7.

[0082] Step 6: Determine the segment sampling frequency correction threshold as the initial segment sampling frequency correction threshold, the segment mileage translation correction threshold as the first initial segment mileage translation correction threshold, and the third initial calibrated segment length as the first initial calibrated segment length, then proceed to step 9.

[0083] Step 7: Determine the section sampling frequency correction threshold as the initial section sampling frequency correction threshold; determine the first difference between the starting mileage of the current section to be calibrated and the ending mileage of the previous calibrated section; based on the section sampling frequency correction threshold, perform mileage integration on the train running speed data within the range from the ending point of the previous calibrated section to the starting point of the current section to be calibrated, and obtain the first integral value; determine the minimum value between the first difference and the first integral value as the mileage translation correction threshold of the current section to be calibrated; determine the third initial section length to be calibrated as the second initial section length to be calibrated; and jump to step 9.

[0084] The first difference is the absolute value of the mileage difference between the starting point of the current calibrated section and the ending point of the previous calibrated section.

[0085] Step 8: Determine the section sampling frequency correction threshold as the initial section sampling frequency correction threshold, determine the section mileage translation correction threshold as the second initial section mileage translation correction threshold, and determine the third initial calibrated section length as the second initial calibrated section length.

[0086] Step 9: Determine multiple combinations of segment mileage translation correction values ​​and sampling frequency correction values ​​based on the segment mileage translation correction threshold, the segment sampling frequency correction threshold, the sampling step size threshold of the segment mileage translation correction threshold, and the sampling step size threshold of the segment sampling frequency correction threshold; wherein each combination contains one segment mileage translation correction value and one segment sampling frequency correction value.

[0087] Step 10: Calculate the corrected mileage of the current section to be calibrated under each combination; calculate the similarity between the second vehicle acceleration data corresponding to the corrected mileage of the section to be calibrated under each combination and the first vehicle acceleration data corresponding to the standard mileage; select the maximum similarity from the similarity corresponding to each combination, as well as the section mileage translation correction value and the section sampling frequency correction value corresponding to the maximum similarity.

[0088] like Figure 3 The diagram shows a method for determining a combination of multiple segment mileage translation correction values ​​and sampling frequency correction values ​​based on a segment mileage translation correction threshold, a segment sampling frequency correction threshold, a sampling step size threshold for the segment mileage translation correction threshold, and a sampling step size threshold for the segment sampling frequency correction threshold, according to an embodiment of the present invention. The method includes:

[0089] S301: Determine multiple segment mileage translation correction values ​​based on the segment mileage translation correction threshold and the sampling step size threshold of the segment mileage translation correction threshold.

[0090] In one embodiment of the present invention, multiple segment mileage translation correction values ​​are determined based on a segment mileage translation correction threshold and a sampling step size threshold for the segment mileage translation correction threshold, including:

[0091] The following formula is used to determine multiple segment mileage translation correction values ​​based on the segment mileage translation correction threshold and the sampling step size threshold of the segment mileage translation correction threshold:

[0092] ΔL(m)=[m-(ceil(D_L / Thr_d_D_L)+1)]×Thr_d_D_L

[0093] Where D_L is the segment mileage translation correction threshold, Thr_d_D_L is the sampling step size threshold of the segment mileage translation correction threshold; m is the number of possible values ​​for the segment mileage translation correction value, with a value range of m=1,2,...,2×ceil(D_L / Thr_d_D_L)+1, where ceil() indicates rounding up; ΔL(m) is the m-th segment mileage translation correction value of the calibrated extended mileage of the segment to be calibrated.

[0094] S302: Determine multiple segment sampling frequency correction values ​​based on the segment sampling frequency correction threshold and the sampling step size threshold of the segment sampling frequency correction threshold.

[0095] In one embodiment of the present invention, multiple segment sampling frequency correction values ​​are determined based on a segment sampling frequency correction threshold and a sampling step size threshold of the segment sampling frequency correction threshold, including:

[0096] The following formula is used to determine multiple segment sampling frequency correction values ​​based on the segment sampling frequency correction threshold and the sampling step size threshold of the segment sampling frequency correction threshold:

[0097] ΔF(n)=[n-(ceil(D_f / Thr_d_D_f)+1)]×Thr_d_D_f

[0098] Where D_f is the segment sampling frequency correction threshold, Thr_d_D_f is the sampling step size threshold of the segment sampling frequency correction threshold; n is the number of possible values ​​for the segment sampling frequency correction value, and the value range is n=1,2,...,2×ceil(D_f / Thr_d_D_f)+1; ceil() means rounding up; ΔF(n) is the nth segment sampling frequency correction value of the calibrated mileage of the segment to be calibrated.

[0099] S303: Arrange and combine multiple segment mileage translation correction values ​​and multiple segment sampling frequency correction values ​​to obtain multiple combinations of segment mileage translation correction values ​​and sampling frequency correction values. Each combination contains one segment mileage translation correction value and one segment sampling frequency correction value.

[0100] In addition, in one embodiment of the present invention, calculating the corrected extension mileage of the current section to be calibrated under each combination includes:

[0101] For each combination, the corrected extension mileage of the current section to be calibrated is calculated using the following formula:

[0102]

[0103] in, The starting point of the section to be calibrated is the extended mileage. This refers to the (m,n)th corrected mileage set of the current segment to be calibrated, obtained by correcting the mileage translation correction value of the m-th segment and the sampling frequency correction value of the n-th segment; V 2nd For train speed data; F0 is the sampling frequency of the data to be calibrated; j is the index value of the data to be calibrated, with a value range of... The ranges of m and n are: m = 1, 2, ..., 2 × ceil(D_L / Thr_d_D_L) + 1, n = 1, 2, ..., 2 × ceil(D_f / Thr_d_D_f) + 1; This is the index value of the starting point of the section to be calibrated; N is the index value of the end point of the section to be calibrated; + It represents the set of positive integers.

[0104] In one embodiment of the present invention, calculating the similarity between the second vehicle acceleration data corresponding to the corrected extended mileage of the section to be calibrated under each combination and the first vehicle acceleration data corresponding to the standard extended mileage includes: according to the mileage data resampling interval in the similarity calculation, cyclically extracting a resampled equally spaced mileage point sequence for the corrected extended mileage of the current section to be calibrated corresponding to the combination of the section mileage translation correction value and the section sampling frequency correction value; for the standard extended mileage and the first vehicle acceleration data corresponding to the standard extended mileage, resampling is performed according to the resampled equally spaced mileage point sequence corresponding to each combination to obtain multiple first vehicle acceleration resampling sequences; for the corrected extended mileage of the current section to be calibrated under each combination and the second vehicle acceleration data corresponding to the corrected extended mileage, resampling is performed according to the resampled equally spaced mileage point sequence corresponding to each combination to obtain multiple second vehicle acceleration resampling sequences.

[0105] Based on multiple first vehicle acceleration resampling sequences and multiple second vehicle acceleration resampling sequences, the first similarity between the second vehicle acceleration resampling sequence and the first vehicle acceleration resampling sequence of the current calibration segment is calculated using the following similarity formula:

[0106]

[0107] in, The first vehicle acceleration resampled sequence is obtained by resampling the resampled equally spaced mileage point sequence obtained from the (m,n)th combination of [ΔL(m),ΔF(n)]. Let p(s1) be the second vehicle acceleration resampled sequence obtained by resampling the resampled equally spaced mileage point sequence obtained from the (m,n)th [ΔL(m),ΔF(n)] combination; p(s1) is the correlation coefficient between the first vehicle acceleration resampled sequence and the second vehicle acceleration resampled sequence obtained from the (m,n)th [ΔL(m),ΔF(n)] combination, representing the similarity between the first and second vehicle acceleration resampled sequences; W(m,n)' is the number of sampling points in the first vehicle acceleration resampled sequence, and the number of sampling points in the first and second vehicle acceleration resampled sequences is the same; s1 is the sequence number corresponding to different [ΔL(m),ΔF(n)] combinations, and the value range of s1 is s1=1,2,...,(2×ceil(D_L / Thr_d_D_L)+1)×(2×ceil(D_f / Thr_d_D_f)+1). The maximum similarity and the corresponding segment mileage translation correction value and segment sampling frequency correction value are selected from the similarity values ​​corresponding to each combination. This includes selecting the maximum first similarity and the corresponding segment mileage translation correction value and segment sampling frequency correction value from the first similarity values ​​corresponding to each combination.

[0108] Furthermore, to obtain a suitable combination of segment mileage translation correction values ​​and segment sampling frequency correction values ​​more quickly and reduce computational load, in another embodiment of the present invention, multiple combinations of segment mileage translation correction values ​​and sampling frequency correction values ​​are determined based on the segment mileage translation correction threshold, the segment sampling frequency correction threshold, the sampling step size threshold of the segment mileage translation correction threshold, and the sampling step size threshold of the segment sampling frequency correction threshold. The corrected extended mileage of the current segment to be calibrated under each combination is calculated. The second vehicle body acceleration data and the standard extended mileage corresponding to the corrected extended mileage of the segment to be calibrated under each combination are calculated. The similarity between the first vehicle body acceleration data corresponding to the process; from the similarity corresponding to each combination, the maximum similarity, and the segment mileage translation correction value and segment sampling frequency correction value corresponding to the maximum similarity are selected, including: assigning the mileage to be calibrated to the cyclic correction record mileage; assigning the sampling frequency of the data to be calibrated to the cyclic record sampling frequency; determining the maximum value among the second preset ratio segment mileage translation correction threshold and the sampling step size threshold of the segment mileage translation correction threshold as the sampling step size of the segment mileage translation correction threshold, and obtaining multiple mileage translation correction values ​​using the following formula:

[0109] ΔL(m1)=[m1-(ceil(D_L / d_D_L)+1)]×d_D_L;

[0110] Where D_L is the segment mileage translation correction threshold, d_D_L is the sampling step size of the segment mileage translation correction threshold; m1 is the number of possible values ​​for the segment mileage translation correction value, and the value range is m1=1,2,...,2×ceil(D_L / d_D_L)+1, ceil() means rounding up; ΔL(m1) is the m1th segment mileage translation correction value of the calibrated extended mileage of the segment to be calibrated;

[0111] The maximum value between the second preset ratio segment sampling frequency correction threshold and the sampling step size threshold of the segment sampling frequency correction threshold is determined as the sampling step size of the segment sampling frequency correction threshold. Multiple sampling frequency correction values ​​are obtained using the following formula:

[0112] ΔF(n1)=[n1-(ceil(D_f / d_D_f)+1)]×d_D_f

[0113] Where D_f is the segment sampling frequency correction threshold, d_D_f is the sampling step size of the segment sampling frequency correction threshold; n1 is the number of possible values ​​for the segment sampling frequency correction value, and the value range is n1=1,2,...,2×ceil(D_f / d_D_f)+1; ceil() means rounding up; ΔF(n1) is the n1th segment sampling frequency correction value of the calibrated mileage of the segment to be calibrated;

[0114] Multiple mileage shift correction values ​​and multiple sampling frequency correction values ​​are combined, where each combination contains a segment start mileage shift correction value and a segment sampling frequency correction value; the corrected extended mileage of the current segment to be calibrated under each combination is calculated using the following formula:

[0115]

[0116] in, This is the starting mileage for the cyclic correction record of the current section to be calibrated; This refers to the (m1,n1)th set of corrected mileage extensions for the current segment to be calibrated, obtained by correcting the mileage translation correction value of the m1th segment and the sampling frequency correction value of the n1th segment; V 2nd For train speed data; F is the cyclic recording sampling frequency; j is the index value of the data to be calibrated, with a value range of [value missing]. The ranges of m1 and n1 are respectively: m1 = 1, 2, ..., 2 × ceil(D_L / d_D_L) + 1, n1 = 1, 2, ..., 2 × ceil(D_f / d_D_f) + 1; This is the index value of the starting point of the section to be calibrated; N is the index value of the end point of the section to be calibrated; + Represents the set of positive integers;

[0117] Based on the mileage data resampling interval in the similarity calculation, a resampled equally spaced mileage point sequence is extracted from the corrected extended mileage of the current calibrated segment corresponding to the combination of the segment mileage translation correction value and the segment sampling frequency correction value. For the standard extended mileage and the corresponding first vehicle acceleration data, resampling is performed according to the resampled equally spaced mileage point sequence for each combination, resulting in multiple first vehicle acceleration resampling sequences. For the corrected extended mileage of the current calibrated segment under each combination, and the corresponding second vehicle acceleration data, resampling is performed according to the resampled equally spaced mileage point sequence for each combination. Resampling is performed to obtain multiple second vehicle acceleration resampling sequences. Based on the multiple first vehicle acceleration resampling sequences and the multiple second vehicle acceleration resampling sequences, a similarity formula is used to calculate the second similarity between the second vehicle acceleration resampling sequence and the first vehicle acceleration resampling sequence of the current calibration segment. The maximum second similarity and the combination of segment mileage translation correction value and segment sampling frequency correction value corresponding to the maximum second similarity are selected. The following formula is used to correct the cyclic correction record mileage of the current calibration segment once using the segment mileage translation correction value and segment sampling frequency correction value corresponding to the maximum second similarity.

[0118]

[0119] in, This is the starting mileage for the cyclic correction record of the current section to be calibrated; The cyclically corrected mileage record of the current segment to be calibrated is obtained by performing a correction based on the segment starting mileage translation correction value and the segment sampling frequency correction value corresponding to the maximum second similarity; V 2nd Here, F represents the train speed data, F represents the cyclic recording sampling frequency, and j represents the index value of the data to be calibrated, with values ​​of [values ​​to be filled in]. is the index value of the starting point of the current section to be calibrated; M1 and N1 are the permutation and combination numbers of the section starting point mileage translation correction value and the section sampling frequency correction value corresponding to the maximum second similarity, respectively, i.e., [ΔL(M1), ΔF(N1)]; N + Represents the set of positive integers;

[0120] The sampling frequency of the segment cyclic recording is accumulated by adding the segment sampling frequency correction value corresponding to the maximum second similarity; it is determined whether the sampling step size of the segment mileage translation correction threshold is not greater than the sampling step size threshold of the segment mileage correction threshold, and whether the sampling step size of the segment frequency correction threshold is not greater than the sampling step size threshold of the segment frequency correction threshold; if so, the maximum second similarity is recorded, and the segment mileage translation correction value and segment sampling frequency correction value corresponding to the maximum second similarity are calculated and reset; wherein, the segment mileage translation correction value corresponding to the maximum second similarity is equal to the starting mileage of the current segment cyclic correction record mileage to be calibrated and the current mileage of the segment cyclic correction record mileage. The difference in mileage from the starting point of the section to be calibrated, and the section sampling frequency correction value corresponding to the maximum second similarity are equal to the difference between the sampling frequency of the section cyclic record and the sampling frequency of the data to be calibrated; if not, modify the current section mileage translation correction threshold to a preset multiple of the current section mileage translation correction threshold sampling step size; modify the current section sampling frequency correction threshold to a preset multiple of the current section sampling frequency correction threshold sampling step size, and return to the step of determining the maximum value among the second preset ratio of the section mileage translation correction threshold and the sampling step size threshold of the section mileage translation correction threshold as the sampling step size of the section mileage translation correction threshold.

[0121] Step 11: Determine whether the maximum similarity is greater than the preset similarity threshold. If yes, proceed to step 12; otherwise, proceed to step 20.

[0122] Step 12: Reset the number of times the section to be calibrated is extended to the initial number of times the section to be calibrated is extended.

[0123] Step 13: Use the segment mileage translation correction value and segment sampling frequency correction value corresponding to the maximum similarity to correct the calibrated extension mileage of the current segment to be calibrated.

[0124] In one embodiment of the present invention, the mileage to be calibrated of the current calibrated segment is corrected once using the segment mileage translation correction value and the segment sampling frequency correction value corresponding to the maximum similarity. This includes: using the following formula to correct the mileage to be calibrated of the current calibrated segment using the segment mileage translation correction value and the segment sampling frequency correction value corresponding to the maximum similarity:

[0125]

[0126] in, The starting point of the section to be calibrated is the extended mileage. The calibrated mileage of the current calibrated segment is obtained by first correcting the segment starting mileage translation correction value and the segment sampling frequency correction value corresponding to the maximum similarity; V 2nd Here, F0 represents the sampling frequency of the data to be calibrated, and j represents the index value of the data to be calibrated, with values ​​of [values ​​to be filled in]. The index value of the starting point of the section to be calibrated; ΔL optm and ΔF optm These are the segment mileage translation correction value and segment sampling frequency correction value corresponding to the maximum similarity, respectively; N + It represents the set of positive integers.

[0127] Step 14: Determine if there is an uncalibrated segment before the current segment to be calibrated. If yes, proceed to step 15; otherwise, proceed to step 16.

[0128] Step 15: Correct the uncalibrated mileage of the sections that were not calibrated before the current section to be calibrated.

[0129] In one embodiment of the present invention, correcting the uncalibrated mileage of segments preceding the current calibrated segment includes: determining whether there is a calibrated segment preceding the current calibrated segment; if so, correcting the uncalibrated mileage of segments preceding the current calibrated segment using the following first-segment translation correction formula:

[0130]

[0131] in, The initial extended mileage to be calibrated is obtained after resetting the mileage data by mileage integration. The mileage to be calibrated is denoted as j; j is the index value of the data to be calibrated, with a value range of 1. N is the index value of the starting point of the current section to be calibrated; + Represents the set of positive integers;

[0132] If not, use the following linear transformation correction formula to correct the uncalibrated mileage of the sections to be calibrated before the current section to be calibrated;

[0133]

[0134] in, The initial extended mileage to be calibrated is obtained after resetting the mileage data by mileage integration. For the mileage to be calibrated; This is the index value of the end point of the previous calibrated segment; is the index value of the starting point of the current calibration segment; j is the index value of the data to be calibrated, and its value range is... N + It represents the set of positive integers.

[0135] Step 16: Use the end-segment translation correction formula to correct the uncalibrated extension mileage of the uncalibrated section between the end of the current calibrated section and the end of the entire line.

[0136] In one embodiment of the present invention, the uncalibrated mileage of the uncalibrated section between the end point of the current calibrated section and the end point of the entire line is corrected using the end-segment translation correction formula, including: correcting the uncalibrated mileage of the uncalibrated section between the end point of the current calibrated section and the end point of the entire line using the following end-segment translation correction formula:

[0137]

[0138] in, The initial extended mileage to be calibrated is obtained after resetting the mileage data by mileage integration. The mileage to be calibrated is denoted as j; j is the index value of the data to be calibrated, with a value range of 1. Where Q represents the number of mileage data to be calibrated in the calibration data; N is the index value of the end point of the current section to be calibrated; + It represents the set of positive integers.

[0139] Step 17: Determine whether the end point of the current section to be calibrated is the end point of the entire line. If yes, proceed to step 19; otherwise, proceed to step 18.

[0140] Step 18: Reset the starting mileage of the section to be calibrated to the ending mileage of the current section to be calibrated, reset the length of the section to be calibrated to the second initial length of the section to be calibrated, and return to step 2.

[0141] Step 19: Assign the updated calibrated mileage to the calibration mileage and end the execution.

[0142] Step 20: Determine whether the end point of the current section to be calibrated is the end point of the entire line. If yes, proceed to step 19; otherwise, proceed to step 21.

[0143] Step 21: Keep the starting mileage of the section to be calibrated unchanged, add the length of the section to be calibrated to the third initial length of the section to be calibrated by the first preset ratio, and add the extension number of the section to be calibrated by 1.

[0144] Step 22: Determine whether the number of extensions of the section to be calibrated is greater than the threshold number of extensions. If yes, proceed to step 23; otherwise, return to step 2.

[0145] Step 23: Move the starting point of the section to be calibrated backward by the first preset ratio of the third initial length of the section to be calibrated; assign the third initial length of the section to be calibrated to the length of the section to be calibrated, reset the number of times the section to be calibrated is extended to the initial number of times the section to be calibrated is extended, and return to step 2.

[0146] Regarding S106 above, after obtaining the standard extended mileage corresponding to the standard mileage data, the chain breakage correction is performed on the calibration extended mileage based on the standard extended mileage corresponding to the standard mileage data and the chain breakage location information, to obtain the calibration mileage data after the mileage of the mileage data to be calibrated is aligned.

[0147] In addition, in one embodiment of the present invention, in order to improve the accuracy of data alignment, the calibration parameters further include: the low-pass filter cutoff frequency of vehicle body acceleration; before performing segment-by-segment extraction and calibration of the stretching mileage to be calibrated based on the calibration parameters, the first vehicle body acceleration data, the second vehicle body acceleration data, and the standard stretching mileage, the method further includes: performing low-pass filtering on the initial first vehicle body acceleration data and the initial second vehicle body acceleration data with a cutoff frequency equal to the low-pass filter cutoff frequency of vehicle body acceleration, to obtain the first vehicle body acceleration data and the second vehicle body acceleration data.

[0148] This invention also provides a track multi-source dynamic detection data mileage alignment device, as described in the following embodiments. Since the principle by which this device solves the problem is similar to that of the track multi-source dynamic detection data mileage alignment method, the implementation of this device can refer to the implementation of the track multi-source dynamic detection data mileage alignment method, and repeated details will not be elaborated further.

[0149] like Figure 4 The diagram shown is a schematic of a track multi-source dynamic detection data mileage alignment device provided in an embodiment of the present invention, comprising:

[0150] The acquisition module 401 is used to acquire data to be calibrated and standard data. The data to be calibrated and the standard data are data collected by different detection systems on the same train during the same train operation. The standard data is the calibrated data. The standard data includes standard mileage data and the first vehicle body acceleration data corresponding to the standard mileage data. The data to be calibrated includes mileage data to be calibrated, the second vehicle body acceleration data corresponding to the mileage data to be calibrated, and the train running speed data corresponding to the mileage data to be calibrated.

[0151] The first processing module 402 is used to remove broken links from the standard mileage data based on the sampling interval of the standard data, the starting sampling point mileage of the standard data, and the broken link ledger information corresponding to the standard mileage data, so as to obtain the standard continuous mileage and broken link location information corresponding to the standard mileage data.

[0152] The second processing module 403 is used to reset the mileage data to be calibrated by mileage integration based on the train running speed data, the sampling frequency of the data to be calibrated, and the starting sampling point mileage of the data to be calibrated, to obtain the initial mileage to be calibrated, and to assign the initial mileage to be calibrated to the mileage to be calibrated.

[0153] The parameter configuration module 404 is used to configure calibration parameters, which include: a preset similarity threshold, a first initial segment length to be calibrated, a second initial segment length to be calibrated, a first initial segment mileage translation correction threshold, a second initial segment mileage translation correction threshold, a segment sampling frequency correction threshold, a sampling step size threshold for the segment mileage translation correction threshold, a sampling step size threshold for the segment sampling frequency correction threshold, the number of times the initial segment to be calibrated is extended, a segment extension number threshold, and a mileage data resampling interval in similarity calculation;

[0154] The third processing module 405 is used to extract and calibrate the stretch mileage to be calibrated segment by segment based on the calibration parameters, the first vehicle body acceleration data, the second vehicle body acceleration data, and the standard stretch mileage. After the full line is calibrated segment by segment, the calibrated stretch mileage corresponding to the stretch mileage to be calibrated is obtained.

[0155] The fourth processing module 406 is used to correct the chain breakage of the calibration mileage based on the standard mileage data corresponding to the standard mileage data and the chain breakage location information, so as to obtain the calibration mileage data after the mileage data to be calibrated is aligned.

[0156] In one possible implementation, the first processing module is specifically used to perform chain break removal processing on the standard mileage data according to the sampling interval of the standard data and the mileage of the starting sampling point of the standard data, using the following formula to obtain the standard continuous mileage corresponding to the standard mileage data:

[0157]

[0158] Where m 1st (1) is the mileage of the starting sampling point for the standard data; dL samp The sampling interval for standard data;

[0159] The standard extended mileage is obtained after removing broken chains; i is the index value of the standard data, with a value range of i = 1, 2, ..., P, where P is the number of standard mileage data in the standard data;

[0160] Based on the broken chain type, starting mileage, and ending mileage in the broken chain ledger information, the standard mileage data is traversed to determine the index values ​​of the starting mileage and ending mileage in the standard mileage data. The index values ​​of the starting mileage, ending mileage, and corresponding standard mileages are used as the broken chain location information.

[0161] In one possible implementation, the second processing module is specifically used to perform mileage integration reset on the mileage data to be calibrated using the sampling frequency of the data to be calibrated, the mileage of the starting sampling point of the data to be calibrated, and the train running speed data, and to obtain the initial mileage to be calibrated:

[0162]

[0163] Where, m 2nd (1) represents the mileage of the starting sampling point of the data to be calibrated; F0 represents the sampling frequency of the data to be calibrated; V 2nd For train speed data; The initial calibrated mileage is obtained after resetting the mileage data by mileage integration; j is the index value of the data to be calibrated, and the value range is j = 1, 2, ..., Q, where Q is the number of calibrated mileage data in the data to be calibrated;

[0164] The initial calibrated mileage is assigned to the calibrated mileage using the following formula:

[0165]

[0166] in, The mileage to be calibrated.

[0167] In one possible implementation, the third processing module is specifically used to perform the following steps based on the calibration parameters, the first vehicle body acceleration, the second vehicle body acceleration, and the standard extended mileage to obtain the calibration extended mileage corresponding to the extended mileage to be calibrated: Step 1: Based on the extended mileage to be calibrated and the standard extended mileage, determine the starting point mileage of the common mileage segment between the extended mileage to be calibrated and the standard extended mileage, assign the starting point mileage of the common mileage segment between the extended mileage to be calibrated and the standard extended mileage to the starting extended mileage of the extended mileage to be calibrated, and assign the first initial length of the extended mileage to be calibrated to the length of the extended mileage to be calibrated; Step 2: Based on the starting extended mileage of the extended mileage to be calibrated, the length of the extended mileage to be calibrated, and the extended mileage to be calibrated, determine the corresponding extended mileage to be calibrated, and assign the first initial length of the extended mileage to be calibrated to the length of the extended mileage to be calibrated; The data corresponding to the section to be calibrated is used as the data for the section to be calibrated. This data includes: the index value of the starting point of the section to be calibrated, the index value of the ending point of the section to be calibrated, the calibrated mileage of the section to be calibrated, the second car body acceleration data of the section to be calibrated, and the train speed data of the section to be calibrated. Step 3: Determine whether the current section to be calibrated is undergoing its first calibration calculation. If yes, proceed to step 5; otherwise, proceed to step 4. Step 4: Determine whether there is an uncalibrated section before the current section to be calibrated. If yes, proceed to step 5; otherwise, proceed to step 8. Step 5: Determine whether there is a calibrated section before the current section to be calibrated. If no, proceed to step 6; if yes, proceed to step 7. Step 6 Step 7: Determine the initial segment sampling frequency correction threshold as the segment sampling frequency correction threshold, the first initial segment mileage translation correction threshold as the segment mileage translation correction threshold, and the third initial length of the segment to be calibrated as the first initial length of the segment to be calibrated. Proceed to step 9. Step 8: Determine the initial segment sampling frequency correction threshold as the segment sampling frequency correction threshold, and determine the first difference between the starting mileage of the current segment to be calibrated and the ending mileage of the previous calibrated segment. Based on the segment sampling frequency correction threshold, perform mileage integration on the train speed data within the range from the ending point of the previous calibrated segment to the starting point of the current segment to be calibrated to obtain the first integral value. Determine the minimum value between the first difference and the first integral value as the length of the current segment mileage translation correction threshold. A positive threshold is set, and the length of the third initial calibrated segment is determined to be the length of the second initial calibrated segment. Proceed to step 8. Step 8: Determine the segment sampling frequency correction threshold as the initial segment sampling frequency correction threshold, determine the segment mileage shift correction threshold as the second initial segment mileage shift correction threshold, and determine the length of the third initial calibrated segment as the length of the second initial calibrated segment. Step 9: Based on the segment mileage shift correction threshold, the segment sampling frequency correction threshold, the sampling step size threshold of the segment mileage shift correction threshold, and the sampling step size threshold of the segment sampling frequency correction threshold, determine multiple combinations of segment mileage shift correction values ​​and sampling frequency correction values; where each combination contains one segment mileage shift correction value and one segment sampling frequency correction value.Step 10: Calculate the corrected extended mileage of the current section to be calibrated under each combination; calculate the similarity between the second vehicle acceleration data corresponding to the corrected extended mileage of the section to be calibrated under each combination and the first vehicle acceleration data corresponding to the standard extended mileage; select the maximum similarity, and the section mileage translation correction value and section sampling frequency correction value corresponding to the maximum similarity from the similarity values ​​corresponding to each combination; Step 11: Determine whether the maximum similarity is greater than the preset similarity threshold. If yes, proceed to step 12; otherwise, proceed to step 20; Step 12: Reset the number of extensions of the section to be calibrated to [number missing]. Initial number of times the section to be calibrated is extended; Step 13: Using the section mileage translation correction value and section sampling frequency correction value corresponding to the maximum similarity, the mileage to be calibrated of the current section to be calibrated is corrected once; Step 14: Determine whether there are uncalibrated sections before the current section to be calibrated. If yes, proceed to Step 15; otherwise, proceed to Step 16; Step 15: Correct the mileage to be calibrated of the uncalibrated sections before the current section to be calibrated; Step 16: Use the end-segment translation correction formula to correct the mileage to be calibrated of the uncalibrated sections between the end point of the current section to be calibrated and the end point of the entire line; Step 17: Determine if the end point of the current section to be calibrated is the end point of the entire line. If yes, proceed to step 1; otherwise, proceed to step 18. Step 18: Reset the starting mileage of the section to be calibrated to the ending mileage of the current section to be calibrated, reset the length of the section to be calibrated to the second initial length of the section to be calibrated, and return to step 2. Step 19: Assign the calibrated mileage obtained from the iterative calculation to the calibration mileage, and end execution. Step 20: Determine if the end point of the current section to be calibrated is the end point of the entire line. If yes, proceed to step 19; otherwise, proceed to step 21. Step 21: The section to be calibrated... The starting point mileage remains unchanged. The length of the section to be calibrated is increased by a first preset proportion equal to the third initial length of the section to be calibrated, and the number of extensions of the section to be calibrated is incremented by 1. Step 22: Determine whether the number of extensions of the section to be calibrated is greater than the threshold number of extensions. If yes, proceed to step 23; otherwise, return to step 2. Step 23: The starting point mileage of the section to be calibrated is moved backward by a first preset proportion equal to the third initial length of the section to be calibrated. The third initial length of the section to be calibrated is assigned to the length of the section to be calibrated, the number of extensions of the section to be calibrated is reset to the initial number of extensions of the section to be calibrated, and the process returns to step 2.

[0168] In one possible implementation, the third processing module is specifically used to retrieve the first mileage point index value in the current extended mileage to be calibrated where the deviation from the starting point of the current extended mileage to be calibrated is the smallest and the mileage deviation is not greater than the mileage data resampling interval, and use the first mileage point index value as the index value of the starting point of the extended mileage to be calibrated.

[0169] Determine whether the sum of the starting mileage and the length of the current section to be calibrated is greater than the total ending mileage of the total mileage to be calibrated. If so, use the total ending index as the index of the ending point of the section to be calibrated. If not, retrieve the index of the second mileage point in the current mileage to be calibrated that has the smallest deviation from the sum of the starting mileage and the length of the section to be calibrated and whose mileage deviation is not greater than the mileage data resampling interval. Use the index of the second mileage point as the index of the ending point of the section to be calibrated. Based on the index of the starting point and the index of the ending point of the section to be calibrated, extract the total mileage to be calibrated, the second car body acceleration data, and the train speed data between the index of the starting point and the index of the ending point of the section to be calibrated.

[0170] In one possible implementation, the third processing module is specifically used to determine multiple segment mileage translation correction values ​​based on the segment mileage translation correction threshold and the sampling step size threshold of the segment mileage translation correction threshold; determine multiple segment sampling frequency correction values ​​based on the segment sampling frequency correction threshold and the sampling step size threshold of the segment sampling frequency correction threshold; and arrange and combine the multiple segment mileage translation correction values ​​and the multiple segment sampling frequency correction values ​​to obtain multiple combinations of segment mileage translation correction values ​​and sampling frequency correction values, wherein each combination contains one segment mileage translation correction value and one segment sampling frequency correction value.

[0171] In one possible implementation, the third processing module is specifically used to determine multiple segment mileage translation correction values ​​using the following formula based on the segment mileage translation correction threshold and the sampling step size threshold of the segment mileage translation correction threshold:

[0172] ΔL(m)=[m-(ceil(D_L / Thr_d_D_L)+1)]×Thr_d_D_L

[0173] Where D_L is the segment mileage translation correction threshold, Thr_d_D_L is the sampling step size threshold of the segment mileage translation correction threshold; m is the number of possible values ​​for the segment mileage translation correction value, with a value range of m=1,2,...,2×ceil(D_L / Thr_d_D_L)+1, where ceil() indicates rounding up; ΔL(m) is the m-th segment mileage translation correction value of the calibrated extended mileage of the segment to be calibrated.

[0174] In one possible implementation, the third processing module is specifically used for

[0175] The following formula is used to determine multiple segment sampling frequency correction values ​​based on the segment sampling frequency correction threshold and the sampling step size threshold of the segment sampling frequency correction threshold:

[0176] ΔF(n)=[n-(ceil(D_f / Thr_d_D_f)+1)]×Thr_d_D_f

[0177] Where D_f is the segment sampling frequency correction threshold, Thr_d_D_f is the sampling step size threshold of the segment sampling frequency correction threshold; n is the number of possible values ​​for the segment sampling frequency correction value, and the value range is n=1,2,...,2×ceil(D_f / Thr_d_D_f)+1; ceil() means rounding up; ΔF(n) is the nth segment sampling frequency correction value of the calibrated mileage of the segment to be calibrated.

[0178] In one possible implementation, the third processing module is specifically used to calculate the corrected extension mileage of the current section to be calibrated for each combination using the following formula:

[0179]

[0180] in, The starting point of the section to be calibrated is the extended mileage. This refers to the (m,n)th corrected mileage set of the current segment to be calibrated, obtained by correcting the mileage translation correction value of the m-th segment and the sampling frequency correction value of the n-th segment; V 2nd For train speed data; F0 is the sampling frequency of the data to be calibrated; j is the index value of the data to be calibrated, with a value range of... The ranges of m and n are: m = 1, 2, ..., 2 × ceil(D_L / Thr_d_D_L) + 1, n = 1, 2, ..., 2 × ceil(D_f / Thr_d_D_f) + 1; This is the index value of the starting point of the section to be calibrated; N is the index value of the end point of the section to be calibrated; + It represents the set of positive integers.

[0181] In one possible implementation, the third processing module is specifically used to extract a sequence of resampled mileage points at equal intervals from the corrected extended mileage of the current segment to be calibrated, based on the mileage data resampling interval in the similarity calculation, for each segment mileage translation correction value and segment sampling frequency correction value combination.

[0182] For the standard extended mileage and the first vehicle body acceleration data corresponding to the standard extended mileage, resampling is performed according to the resampled equally spaced mileage point sequence corresponding to each combination to obtain multiple first vehicle body acceleration resampling sequences.

[0183] For each combination, the corrected extended mileage of the current section to be calibrated and the second vehicle acceleration data corresponding to the corrected extended mileage are resampled according to the resampled equally spaced mileage point sequence corresponding to each combination to obtain multiple second vehicle acceleration resampling sequences.

[0184] Based on multiple first vehicle acceleration resampling sequences and multiple second vehicle acceleration resampling sequences, the first similarity between the second vehicle acceleration resampling sequence and the first vehicle acceleration resampling sequence of the current calibration segment is calculated using the following similarity formula:

[0185]

[0186] in, The first vehicle acceleration resampled sequence is obtained by resampling the resampled equally spaced mileage point sequence obtained from the (m,n)th combination of [ΔL(m),ΔF(n)]. Let be the second vehicle acceleration resampled sequence obtained by resampling the resampled equally spaced mileage point sequence obtained from the (m,n)th combination of [ΔL(m), ΔF(n)]; p(s1) is the correlation coefficient between the first and second vehicle acceleration resampled sequences obtained from the (m,n)th combination of [ΔL(m), ΔF(n)], representing the similarity between the first and second vehicle acceleration resampled sequences; W(m,n)' is the sampled value in the first vehicle acceleration resampled sequence. The number of sampling points is the same in the first and second vehicle acceleration resampling sequences; s1 is the sequential number corresponding to different combinations of [ΔL(m), ΔF(n)], and the value range of s1 is s1=1,2,...,(2×ceil(D_L / Thr_d_D_L)+1)×(2×ceil(D_f / Thr_d_D_f)+1); the maximum first similarity and the segment mileage translation correction value and segment sampling frequency correction value corresponding to the maximum first similarity are selected from the first similarity corresponding to each combination.

[0187] In one possible implementation, the third processing module is specifically used to assign the mileage to be calibrated to the cyclic correction record mileage; assign the sampling frequency of the data to be calibrated to the cyclic recording sampling frequency; determine the maximum value of the second preset ratio segment mileage shift correction threshold and the sampling step size threshold of the segment mileage shift correction threshold as the sampling step size of the segment mileage shift correction threshold, and obtain multiple mileage shift correction values ​​using the following formula:

[0188] ΔL(m1)=[m1-(ceil(D_L / d_D_L)+1)]×d_D_L;

[0189] Where D_L is the segment mileage translation correction threshold, d_D_L is the sampling step size of the segment mileage translation correction threshold; m1 is the number of possible values ​​for the segment mileage translation correction value, and the value range is m1=1,2,...,2×ceil(D_L / d_D_L)+1, ceil() means rounding up; ΔL(m1) is the m1th segment mileage translation correction value of the calibrated extended mileage of the segment to be calibrated;

[0190] The maximum value between the second preset ratio segment sampling frequency correction threshold and the sampling step size threshold of the segment sampling frequency correction threshold is determined as the sampling step size of the segment sampling frequency correction threshold. Multiple sampling frequency correction values ​​are obtained using the following formula:

[0191] ΔF(n1)=[n1-(ceil(D_f / d_D_f)+1)]×d_D_f

[0192] Where D_f is the segment sampling frequency correction threshold, d_D_f is the sampling step size of the segment sampling frequency correction threshold; n1 is the number of possible values ​​for the segment sampling frequency correction value, and the value range is n1=1,2,...,2×ceil(D_f / d_D_f)+1; ceil() means rounding up; ΔF(n1) is the n1th segment sampling frequency correction value of the calibrated mileage of the segment to be calibrated;

[0193] Multiple mileage shift correction values ​​and multiple sampling frequency correction values ​​are combined, where each combination contains a segment start mileage shift correction value and a segment sampling frequency correction value; the corrected extended mileage of the current segment to be calibrated under each combination is calculated using the following formula:

[0194]

[0195] in, This is the starting mileage for the cyclic correction record of the current section to be calibrated; This refers to the (m1,n1)th set of corrected mileage extensions for the current segment to be calibrated, obtained by correcting the mileage translation correction value of the m1th segment and the sampling frequency correction value of the n1th segment; V 2nd For train speed data; F is the cyclic recording sampling frequency; j is the index value of the data to be calibrated, with a value range of [value missing]. The ranges of m1 and n1 are respectively: m1 = 1, 2, ..., 2 × ceil(D_L / d_D_L) + 1, n1 = 1, 2, ..., 2 × ceil(D_f / d_D_f) + 1; This is the index value of the starting point of the section to be calibrated; N is the index value of the end point of the section to be calibrated; + Represents the set of positive integers;

[0196] Based on the mileage data resampling interval in the similarity calculation, a resampled equally spaced mileage point sequence is extracted from the corrected extended mileage of the current calibrated segment corresponding to the combination of the segment mileage translation correction value and the segment sampling frequency correction value. For the standard extended mileage and the corresponding first vehicle acceleration data, resampling is performed according to the resampled equally spaced mileage point sequence for each combination, resulting in multiple first vehicle acceleration resampling sequences. For the corrected extended mileage of the current calibrated segment under each combination, and the corresponding second vehicle acceleration data, resampling is performed according to the resampled equally spaced mileage point sequence for each combination. Resampling is performed to obtain multiple second vehicle acceleration resampling sequences. Based on the multiple first vehicle acceleration resampling sequences and the multiple second vehicle acceleration resampling sequences, a similarity formula is used to calculate the second similarity between the second vehicle acceleration resampling sequence and the first vehicle acceleration resampling sequence of the current calibration segment. The maximum second similarity and the combination of segment mileage translation correction value and segment sampling frequency correction value corresponding to the maximum second similarity are selected. The following formula is used to correct the cyclic correction record mileage of the current calibration segment once using the segment mileage translation correction value and segment sampling frequency correction value corresponding to the maximum second similarity.

[0197]

[0198] in, This is the starting mileage for the cyclic correction record of the current section to be calibrated; The cyclically corrected mileage record of the current segment to be calibrated is obtained by performing a correction based on the segment starting mileage translation correction value and the segment sampling frequency correction value corresponding to the maximum second similarity; V 2nd Here, F represents the train speed data, F represents the cyclic recording sampling frequency, and j represents the index value of the data to be calibrated, with values ​​of [values ​​to be filled in]. Let M1 be the index value of the starting point of the current section to be calibrated; M1 and N1 are the permutation and combination numbers of the section starting point mileage translation correction value and the section sampling frequency correction value corresponding to the maximum second similarity, respectively, i.e., [ΔL(M1), ΔF(N1)]; N +Represents the set of positive integers; accumulate the sampling frequency of the segment cyclic records, corresponding to the segment sampling frequency correction value corresponding to the maximum second similarity; determine whether the sampling step size of the segment mileage translation correction threshold is not greater than the sampling step size threshold of the segment mileage correction threshold, and whether the sampling step size of the segment frequency correction threshold is not greater than the sampling step size threshold of the segment frequency correction threshold; if so, record the maximum second similarity, and calculate and reset the segment mileage translation correction value and the segment sampling frequency correction value corresponding to the maximum second similarity; wherein, the segment mileage translation correction value corresponding to the maximum second similarity is equal to the starting point of the current segment cyclic correction record mileage to be calibrated. The difference between the mileage and the mileage extending from the starting point of the current section to be calibrated, and the section sampling frequency correction value corresponding to the maximum second similarity is equal to the difference between the sampling frequency of the section cyclic record and the sampling frequency of the data to be calibrated; if not, modify the current section mileage translation correction threshold to a preset multiple of the current section mileage translation correction threshold sampling step size; modify the current section sampling frequency correction threshold to a preset multiple of the current section sampling frequency correction threshold sampling step size, and return to the step of determining the maximum value among the second preset ratio of the section mileage translation correction threshold and the sampling step size threshold of the section mileage translation correction threshold as the sampling step size of the section mileage translation correction threshold.

[0199] In one possible implementation, the third processing module is specifically used to correct the calibrated mileage of the current calibrated segment using the segment mileage translation correction value and the segment sampling frequency correction value corresponding to the maximum similarity, according to the following formula:

[0200]

[0201] in, The starting point of the section to be calibrated is the extended mileage. The calibrated mileage of the current calibrated segment is obtained by first correcting the segment starting mileage translation correction value and the segment sampling frequency correction value corresponding to the maximum similarity; V 2nd Here, F0 represents the sampling frequency of the data to be calibrated, and j represents the index value of the data to be calibrated, with values ​​of [values ​​to be filled in]. The index value of the starting point of the section to be calibrated; ΔL optm and ΔF optm These are the segment mileage translation correction value and segment sampling frequency correction value corresponding to the maximum similarity, respectively; N + It represents the set of positive integers.

[0202] In one possible implementation, the third processing module is specifically used to determine whether there is a calibrated segment preceding the current calibrated segment; if so, the uncalibrated mileage of the uncalibrated segments preceding the current calibrated segment is corrected using the following first-segment translation correction formula:

[0203]

[0204] in, The initial extended mileage to be calibrated is obtained after resetting the mileage data by mileage integration. The mileage to be calibrated is denoted as j; j is the index value of the data to be calibrated, with a value range of 1. N is the index value of the starting point of the current section to be calibrated; + Represents the set of positive integers;

[0205] If not, use the following linear transformation correction formula to correct the uncalibrated mileage of the sections to be calibrated before the current section to be calibrated;

[0206]

[0207] in, The initial extended mileage to be calibrated is obtained after resetting the mileage data by mileage integration. For the mileage to be calibrated; This is the index value of the end point of the previous calibrated segment; is the index value of the starting point of the current calibration segment; j is the index value of the data to be calibrated, and its value range is... It represents the set of positive integers.

[0208] In one possible implementation, the third processing module is specifically used to correct the uncalibrated mileage of the uncalibrated section between the end point of the current calibrated section and the end point of the entire line using the following end-segment translation correction formula:

[0209]

[0210] in, The initial extended mileage to be calibrated is obtained after resetting the mileage data by mileage integration. The mileage to be calibrated is denoted as j; j is the index value of the data to be calibrated, with a value range of 1. Where Q represents the number of mileage data to be calibrated in the calibration data; N is the index value of the end point of the current section to be calibrated; + It represents the set of positive integers.

[0211] In one possible implementation, the calibration parameters further include: the vehicle body acceleration low-pass filter cutoff frequency; and also include: a fifth processing module, used to perform low-pass filtering on the initial first vehicle body acceleration data and the initial second vehicle body acceleration data with a cutoff frequency equal to the vehicle body acceleration low-pass filter cutoff frequency, to obtain the first vehicle body acceleration data and the second vehicle body acceleration data.

[0212] Based on the aforementioned inventive concept, such as Figure 5 As shown, the present invention also proposes a computer device 500, including a memory 510, a processor 520, and a computer program 530 stored in the memory 510 and executable on the processor 520. When the processor 520 executes the computer program 530, it implements the aforementioned method for mileage alignment of multi-source dynamic detection data of orbits.

[0213] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a method for mileage alignment of multi-source dynamic detection data of orbits.

[0214] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for mileage alignment of multi-source dynamic detection data of orbits.

[0215] In this embodiment of the invention, data to be calibrated and standard data are acquired. The data to be calibrated and the standard data are data collected by different detection systems on the same train during the same train operation. The standard data is the calibrated data. The standard data includes standard mileage data and the first vehicle body acceleration data corresponding to the standard mileage data. The data to be calibrated includes mileage data to be calibrated, the second vehicle body acceleration data corresponding to the mileage data to be calibrated, and the train running speed data corresponding to the mileage data to be calibrated. Based on the sampling interval of the standard data, the starting sampling point mileage of the standard data, and the chain breakage log information corresponding to the standard data, the standard mileage data is processed to remove chain breaks, obtaining the standard sequential mileage corresponding to the standard mileage data and the chain breakage location information. Based on the train running speed data, the sampling frequency of the data to be calibrated, and the starting sampling point mileage of the data to be calibrated, the mileage data to be calibrated is reset by mileage integration to obtain the initial sequential mileage to be calibrated. The calibration stretch mileage is assigned to the stretch mileage to be calibrated; calibration parameters are configured, including: a preset similarity threshold, the length of the first initial segment to be calibrated, the length of the second initial segment to be calibrated, the first initial segment mileage translation correction threshold, the second initial segment mileage translation correction threshold, the segment sampling frequency correction threshold, the sampling step size threshold of the segment mileage translation correction threshold, the sampling step size threshold of the segment sampling frequency correction threshold, the number of extensions of the initial segment to be calibrated, the threshold for the number of extensions, and the mileage data resampling interval in similarity calculation; based on the calibration parameters, the first vehicle acceleration data, the second vehicle acceleration data, and the standard stretch mileage, the stretch mileage to be calibrated is extracted and calibrated segment by segment. After the entire line is calibrated segment by segment, the calibration stretch mileage corresponding to the stretch mileage to be calibrated is obtained; based on the standard stretch mileage corresponding to the standard mileage data and the chain break location information, the calibration stretch mileage is corrected for chain breakage to obtain the calibration mileage data after mileage alignment of the stretch mileage data to be calibrated. In this way, the vehicle acceleration waveforms from different detection systems are used as reference channels for mileage synchronization and alignment. Supplemented by train speed data sequences, time integration is performed to reconstruct continuous mileage. Based on standard data and data to be calibrated, mileage calibration is performed segment by segment to achieve mileage alignment. This achieves automatic, efficient, and accurate mileage alignment of multi-source detection data, with strong applicability to calibration sections, improving the accuracy of mileage alignment of multi-source track detection data and the reliability of the second detection system's mileage.

[0216] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0217] This invention is described in terms of flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowcharts and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0218] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0219] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0220] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for track multi-source dynamic detection data alignment, characterized in that, The method comprises the following steps: acquiring calibration data and standard data, wherein the calibration data and the standard data are data collected by different detection systems on the same train during the same train operation, and the standard data is calibrated data; the standard data comprises standard mileage data and first vehicle body acceleration data corresponding to the standard mileage data, and the calibration data comprises calibration mileage data, second vehicle body acceleration data corresponding to the calibration mileage data, and train operation speed data corresponding to the calibration mileage data; performing broken link removal processing on the standard mileage data according to the sampling interval of the standard data, the starting sampling point mileage of the standard data, and broken link accounting information corresponding to the standard data, to obtain standard straight mileage corresponding to the standard mileage data and broken link position information; performing mileage integration reset on the calibration mileage data according to the train operation speed data, the sampling frequency of the calibration data, and the starting sampling point mileage of the calibration data, to obtain initial calibration straight mileage, and assigning the initial calibration straight mileage to the calibration straight mileage; configuring calibration parameters, wherein the calibration parameters comprise a preset similarity threshold, a first initial calibration section length, a second initial calibration section length, a first initial section mileage translation correction threshold, a second initial section mileage translation correction threshold, a section sampling frequency correction threshold, a sampling step threshold of the section mileage translation correction threshold, a sampling step threshold of the section sampling frequency correction threshold, an initial calibration section lengthening number, a section lengthening number threshold, and a mileage data resampling interval in similarity calculation; performing section-by-section extraction calibration on the calibration straight mileage according to the calibration parameters, the first vehicle body acceleration data, the second vehicle body acceleration data, and the standard straight mileage, to obtain calibration straight mileage corresponding to the calibration mileage data after completing section-by-section calibration of the entire line; performing broken link correction on the calibration straight mileage according to the standard straight mileage corresponding to the standard mileage data and the broken link position information, to obtain calibration mileage data after mileage alignment of the calibration mileage data.

2. The track multi-source dynamic inspection data alignment method of claim 1, wherein, The method comprises the following steps: performing broken link removal processing on the standard mileage data according to the sampling interval of the standard data, the starting sampling point mileage of the standard data, and broken link accounting information corresponding to the standard data, to obtain standard straight mileage corresponding to the standard mileage data and broken link position information, which comprises the following steps: where m 1st (1) is the starting sampling point mileage of the standard data; dL samp is the sampling interval of the standard data; is the standard unbroken mileage obtained after the broken link removal process; i is the index value of the standard data, and the value range is i = 1, 2, …, P, wherein P is the number of standard mileage data in the standard data; performing broken link removal processing on the standard mileage data according to the sampling interval of the standard data and the starting sampling point mileage of the standard data, to obtain standard straight mileage corresponding to the standard mileage data, by using the following formula: traversing the standard mileage data according to the broken link type, the starting point mileage of the broken link, and the end point mileage of the broken link in the broken link accounting information, to determine the index value of the starting point mileage of the broken link in the standard mileage data and the index value of the end point mileage of the broken link in the standard mileage data, and taking the index value of the starting point mileage of the broken link, the index value of the end point mileage of the broken link, the index value of the starting point mileage of the broken link corresponding standard mileage, the index value of the starting point mileage of the broken link corresponding standard straight mileage, the index value of the end point mileage of the broken link corresponding standard mileage, and the index value of the end point mileage of the broken link corresponding standard straight mileage as the broken link position information.

3. The track multi-source dynamic inspection data alignment method of claim 1, wherein, According to the train running speed data, the sampling frequency of the to-be-calibrated data, and the starting sampling point mileage of the to-be-calibrated data, the mileage integration reset is performed on the to-be-calibrated mileage data to obtain an initial to-be-calibrated developed mileage, and the initial to-be-calibrated developed mileage is assigned to the to-be-calibrated developed mileage, including: According to the train running speed data, the sampling frequency of the to-be-calibrated data, and the starting sampling point mileage of the to-be-calibrated data, the mileage integration reset is performed on the to-be-calibrated mileage data to obtain an initial to-be-calibrated developed mileage, and the initial to-be-calibrated developed mileage is assigned to the to-be-calibrated developed mileage, including: wherein m 2nd (1) is the starting sampling point mileage of the data to be calibrated; F0 is the sampling frequency of the data to be calibrated; V 2nd is the train running speed data; is the initial calibrated straight mileage obtained after mileage integration reset of the mileage data to be calibrated; j is an index value of the data to be calibrated, and the value range is j = 1, 2, …, Q, wherein Q is the number of the mileage data to be calibrated in the data to be calibrated. According to the train running speed data, the sampling frequency of the to-be-calibrated data, and the starting sampling point mileage of the to-be-calibrated data, the mileage integration reset is performed on the to-be-calibrated mileage data to obtain an initial to-be-calibrated developed mileage, and the initial to-be-calibrated developed mileage is assigned to the to-be-calibrated developed mileage, including: wherein, is the to-be-calibrated true range.

4. The track multi-source dynamic inspection data alignment method of claim 1, wherein, According to the calibration parameters, the first car body acceleration data, the second car body acceleration data, and the standard developed mileage, the to-be-calibrated developed mileage is extracted and calibrated section by section, and after the whole-line section-by-section calibration is completed, the calibration developed mileage corresponding to the to-be-calibrated developed mileage is obtained, including: According to the calibration parameters, the first car body acceleration data, the second car body acceleration data, and the standard developed mileage, the to-be-calibrated developed mileage is extracted and calibrated section by section, and after the whole-line section-by-section calibration is completed, the calibration developed mileage corresponding to the to-be-calibrated developed mileage is obtained, including: Step 1: According to the to-be-calibrated developed mileage and the standard developed mileage, the starting point mileage of the common mileage section of the to-be-calibrated developed mileage and the standard developed mileage is determined, the starting point mileage of the common mileage section of the to-be-calibrated developed mileage and the standard developed mileage is assigned to the to-be-calibrated section starting point developed mileage, and the first initial to-be-calibrated section length is assigned to the to-be-calibrated section length; Step 2: According to the to-be-calibrated section starting point developed mileage, the to-be-calibrated section length, and the to-be-calibrated developed mileage, the corresponding to-be-calibrated section is determined, the data corresponding to the to-be-calibrated section is taken as the to-be-calibrated section data, and the to-be-calibrated section data includes: the index value of the starting point of the to-be-calibrated section, the index value of the terminal point of the to-be-calibrated section, the to-be-calibrated developed mileage of the to-be-calibrated section, and the second car body acceleration data of the to-be-calibrated section and the train running speed data of the to-be-calibrated section; Step 3: It is determined whether the current to-be-calibrated section is the initial calibration calculation, if yes, step 5 is executed, and if not, step 4 is executed; Step 4: It is determined whether there is an uncalibrated section before the current to-be-calibrated section, if yes, step 5 is executed, and if not, step 8 is executed; Step 5: It is determined whether there is a calibrated section before the current to-be-calibrated section, if not, step 6 is executed, and if yes, step 7 is executed; Step 6: The section sampling frequency correction threshold is the initial section sampling frequency correction threshold, the section mileage translation correction threshold is the first initial section mileage translation correction threshold, and the third initial to-be-calibrated section length is the first initial to-be-calibrated section length, and the step 9 is jumped to; Step 7: Determine the segment sampling frequency correction threshold as the initial segment sampling frequency correction threshold, determine the first difference between the current to-be-calibrated segment start point forward mileage and the previous calibrated segment end point forward mileage; according to the segment sampling frequency correction threshold, mileage integration is performed on the train running speed data within the range from the previous calibrated segment end point to the current to-be-calibrated segment start point, to obtain a first integrated value; the minimum value of the first difference and the first integrated value is determined as the current to-be-calibrated segment mileage translation correction threshold, the third initial to-be-calibrated segment length is determined as the second initial to-be-calibrated segment length, and step 9 is jumped to; Step 8: Determine the segment sampling frequency correction threshold as the initial segment sampling frequency correction threshold, determine the segment mileage translation correction threshold as the second initial segment mileage translation correction threshold, and determine the third initial to-be-calibrated segment length as the second initial to-be-calibrated segment length; Step 9: According to the segment mileage translation correction threshold, the segment sampling frequency correction threshold, the sampling step threshold of the segment mileage translation correction threshold, and the sampling step threshold of the segment sampling frequency correction threshold, determine a plurality of combinations of segment mileage translation correction values and sampling frequency correction values; each combination contains a segment mileage translation correction value and a segment sampling frequency correction value; Step 10: Calculate the corrected forward mileage of the current to-be-calibrated segment under each combination; calculate the similarity between the second car body acceleration data corresponding to the corrected forward mileage of the to-be-calibrated segment under each combination and the first car body acceleration data corresponding to the standard forward mileage; select the maximum similarity and the segment mileage translation correction value and the segment sampling frequency correction value corresponding to the maximum similarity from the similarities corresponding to each combination; Step 11: Determine whether the maximum similarity is greater than a preset similarity threshold, if yes, execute step 12, and if no, execute step 20; Step 12: Reset the to-be-calibrated segment lengthening number as the initial to-be-calibrated segment lengthening number; Step 13: Use the segment mileage translation correction value and the segment sampling frequency correction value corresponding to the maximum similarity to correct the to-be-calibrated forward mileage of the current to-be-calibrated segment once; Step 14: Determine whether there is an uncalibrated segment before the current to-be-calibrated segment, if yes, execute step 15, and if no, execute step 16; Step 15: Correct the to-be-calibrated forward mileage of the uncalibrated segment before the current to-be-calibrated segment; Step 16: Use the end segment translation correction formula to correct the to-be-calibrated forward mileage of the uncalibrated segment between the end point of the current to-be-calibrated segment and the end point of the whole line; Step 17: Determine whether the end point of the current to-be-calibrated segment is the end point of the whole line, if yes, jump to step 19, and if no, execute step 18; Step 18: Reset the to-be-calibrated segment start point forward mileage as the end point forward mileage of the current to-be-calibrated segment, reset the to-be-calibrated segment length as the second initial to-be-calibrated segment length, and return to step 2; Step 19: Assign the to-be-calibrated forward mileage updated by the loop calculation to the calibrated forward mileage, and end the execution; Step 20: Determine whether the end point of the current to-be-calibrated segment is the end point of the whole line, if yes, execute step 19, and if no, execute step 21; Step 21: Reset the to-be-calibrated segment start point forward mileage as the end point forward mileage of the current to-be-calibrated segment, reset the to-be-calibrated segment length as the second initial to-be-calibrated segment length, and return to step 2. Step 21: the start point of the to-be-calibrated section is kept unchanged, the length of the to-be-calibrated section is accumulated by a first preset proportion of the third initial to-be-calibrated section length, and the to-be-calibrated section length is accumulated by 1 time; Step 22: it is determined whether the to-be-calibrated section length is greater than the section length threshold value, if yes, step 23 is executed, and if no, step 2 is returned; Step 23: the start point of the to-be-calibrated section is moved backward by a first preset proportion of the third initial to-be-calibrated section length, the third initial to-be-calibrated section length is assigned to the to-be-calibrated section length, the to-be-calibrated section length is reset to the initial to-be-calibrated section length, and step 2 is returned.

5. The track multi-source dynamic inspection data alignment method of claim 4, wherein, According to the start point of the to-be-calibrated section, the to-be-calibrated section length, and the to-be-calibrated mileage, a corresponding to-be-calibrated section is determined, and data corresponding to the to-be-calibrated section is taken as to-be-calibrated section data, including: In the current to-be-calibrated mileage, a first mileage point index value with the smallest deviation from the start point of the current to-be-calibrated section and a mileage deviation not greater than a mileage data resampling interval is searched, and the first mileage point index value is taken as an index value of the start point of the to-be-calibrated section; It is determined whether the sum of the start point of the current to-be-calibrated section and the current to-be-calibrated section length is greater than the end point of the to-be-calibrated mileage; If yes, an end point index value of the whole line is taken as an index value of the end point of the to-be-calibrated section; If no, a second mileage point index value with the smallest deviation from the sum of the start point of the current to-be-calibrated section and the to-be-calibrated section length and a mileage deviation not greater than a mileage data resampling interval is searched in the current to-be-calibrated mileage, and the second mileage point index value is taken as an index value of the end point of the to-be-calibrated section; According to the index value of the start point of the to-be-calibrated section and the index value of the end point of the to-be-calibrated section, the to-be-calibrated mileage, the second vehicle body acceleration data, and the train running speed data between the index value of the start point of the to-be-calibrated section and the index value of the end point of the to-be-calibrated section are extracted.

6. The track multi-source dynamic inspection data alignment method of claim 4, wherein, According to the section mileage translation correction threshold value, the section sampling frequency correction threshold value, the sampling step threshold value of the section mileage translation correction threshold value, and the sampling step threshold value of the section sampling frequency correction threshold value, a plurality of combinations of section mileage translation correction values and sampling frequency correction values are determined; wherein each combination contains a section mileage translation correction value and a section sampling frequency correction value, including: According to the section mileage translation correction threshold value and the sampling step threshold value of the section mileage translation correction threshold value, a plurality of section mileage translation correction values are determined; According to the section sampling frequency correction threshold value and the sampling step threshold value of the section sampling frequency correction threshold value, a plurality of section sampling frequency correction values are determined; The plurality of section mileage translation correction values and the plurality of section sampling frequency correction values are arranged and combined to obtain a plurality of combinations of section mileage translation correction values and sampling frequency correction values, and each combination contains a section mileage translation correction value and a section sampling frequency correction value.

7. The track multi-source dynamic inspection data alignment method of claim 6, wherein, According to the section mileage translation correction threshold value and the sampling step threshold value of the section mileage translation correction threshold value, a plurality of section mileage translation correction values are determined, including: The segment mileage translation correction threshold is corrected according to the following formula: ΔL(m) = [m - (ceil(D_L / Thr_d_D_L) + 1)] * Thr_d_D_L Wherein, D_L is the segment mileage translation correction threshold, Thr_d_D_L is the sampling step threshold of the segment mileage translation correction threshold; m is the number of values that the segment mileage translation correction value can take, and the value range is m = 1, 2,..., 2*ceil(D_L / Thr_d_D_L) + 1, ceil() represents the upward rounding calculation; ΔL(m) is the mth segment mileage translation correction value of the to-be-calibrated straight development mileage of the to-be-calibrated segment.

8. The track multi-source dynamic inspection data alignment method of claim 6, wherein, According to the segment sampling frequency correction threshold and the sampling step threshold of the segment sampling frequency correction threshold, a plurality of segment sampling frequency correction values are determined, including: The segment sampling frequency correction threshold is corrected according to the following formula: ΔF(n) = [n - (ceil(D_f / Thr_d_D_f) + 1)] * Thr_d_D_f Wherein, D_f is the segment sampling frequency correction threshold, Thr_d_D_f is the sampling step threshold of the segment sampling frequency correction threshold; n is the number of values that the segment sampling frequency correction value can take, and the value range is n = 1, 2,..., 2*ceil(D_f / Thr_d_D_f) + 1; ceil() represents the upward rounding calculation; ΔF(n) is the n th segment sampling frequency correction value of the to-be-calibrated straight development mileage of the to-be-calibrated segment.

9. The track multi-source dynamic detection data alignment method of claim 4, wherein, The corrected straight development mileage of the current to-be-calibrated segment under each combination is calculated, including: For each combination, the corrected straight development mileage of the current to-be-calibrated segment is calculated according to the following formula: wherein, is the start developed mileage of the current calibration section; is the (m, n) group of corrected developed mileage of the current calibration section according to the translation correction value of the mth section mileage and the sampling frequency correction value of the nth section; 2nd is the train running speed data; F0 is the sampling frequency of the calibration data; j is the index value of the calibration data, and the value range is The value ranges of m and n are respectively: m = 1, 2, …, 2 × ceil(D_L / Thr_d_D_L) + 1, n = 1, 2, …, 2 × ceil(D_f / Thr_d_D_f) + 1; is the index value of the start of the calibration section; is the index value of the end of the calibration section; N + represents a set of positive integers.

10. The track multi-source dynamic inspection data alignment method of claim 4, wherein, The similarity between the second vehicle body acceleration data corresponding to the corrected straight development mileage of the to-be-calibrated segment and the first vehicle body acceleration data corresponding to the standard straight development mileage is calculated, including: According to the similarity calculation mileage data resampling interval, the resampling equal-interval mileage point sequence corresponding to each combination of the segment mileage translation correction value and the segment sampling frequency correction value is extracted for the corrected straight development mileage of the current to-be-calibrated segment; According to the resampling equal-interval mileage point sequence corresponding to each combination, a plurality of first vehicle body acceleration resampling sequences are obtained for the standard straight development mileage and the first vehicle body acceleration data corresponding to the standard straight development mileage; According to the resampling equal-interval mileage point sequence corresponding to each combination, a plurality of second vehicle body acceleration resampling sequences are obtained for the corrected straight development mileage of the current to-be-calibrated segment and the second vehicle body acceleration data corresponding to the corrected straight development mileage; According to the plurality of first vehicle body acceleration resampling sequences and the plurality of second vehicle body acceleration resampling sequences, the first similarity between the second vehicle body acceleration resampling sequence and the first vehicle body acceleration resampling sequence of the current to-be-calibrated segment is calculated according to the following similarity formula: wherein, is a first vehicle body acceleration resampling sequence obtained by resampling the resampled equidistant mileage point sequence obtained according to the (m, n)th [ΔL(m), ΔF(n)] combination; is a second vehicle body acceleration resampling sequence obtained by resampling the resampled equidistant mileage point sequence obtained according to the (m, n)th [ΔL(m), ΔF(n)] combination; p(s1) is a correlation coefficient between the first vehicle body acceleration resampling sequence and the second vehicle body acceleration resampling sequence obtained according to the (m, n)th [ΔL(m), ΔF(n)] combination, representing the similarity between the first vehicle body acceleration resampling sequence and the second vehicle body acceleration resampling sequence; W(m, n)' is the number of sampling points in the first vehicle body acceleration resampling sequence, and the number of sampling points in the first and second vehicle body acceleration resampling sequences is the same; s1 is a sequential number corresponding to different [ΔL(m), ΔF(n)] combinations, and s1 takes a value range of s1 = 1, 2, …, (2 × ceil(D_L / Thr_d_D_L) + 1) × (2 × ceil(D_f / Thr_d_D_f) + 1); screening the maximum similarity from the similarities corresponding to the combinations, and the section mileage translation correction value and the section sampling frequency correction value corresponding to the maximum similarity, comprising: screening the maximum first similarity from the first similarities corresponding to the combinations, and the section mileage translation correction value and the section sampling frequency correction value corresponding to the maximum first similarity.

11. The track multi-source dynamic detection data alignment method of claim 4, wherein, determining the combinations of the plurality of section mileage translation correction values and the sampling frequency correction values according to the section mileage translation correction threshold value, the section sampling frequency correction threshold value, the sampling step threshold value of the section mileage translation correction threshold value, and the sampling step threshold value of the section sampling frequency correction threshold value; calculating the corrected linear mileage of the current calibration section under each combination; calculating the similarity between the second vehicle body acceleration data corresponding to the corrected linear mileage of the calibration section under each combination and the first vehicle body acceleration data corresponding to the standard linear mileage; screening the maximum similarity from the similarities corresponding to the combinations, and the section mileage translation correction value and the section sampling frequency correction value corresponding to the maximum similarity, comprising: assigning the calibration linear mileage to the loop correction record mileage; assigning the sampling frequency of the calibration data to the loop record sampling frequency; determining the sampling step of the section mileage translation correction threshold value as the maximum value of the section mileage translation correction threshold value and the sampling step threshold value of the section mileage translation correction threshold value in the second preset proportion, and obtaining the plurality of mileage translation correction values using the following formula: ΔL(m1) = [m1-(ceil(D_L / d_D_L)+1)]×d_D_L; wherein, D_L is the section mileage translation correction threshold value, d_D_L is the sampling step of the section mileage translation correction threshold value; m1 is the number of values that the section mileage translation correction value can take, and the value range is m1 = 1, 2, …, 2×ceil(D_L / d_D_L)+1, ceil() represents upward rounding calculation; ΔL(m1) is the m1th section mileage translation correction value of the calibration linear mileage of the calibration section; determining the sampling step of the section sampling frequency correction threshold value as the maximum value of the section sampling frequency correction threshold value and the sampling step threshold value of the section sampling frequency correction threshold value in the second preset proportion, and obtaining the plurality of sampling frequency correction values using the following formula: ΔF(n1) = [n1-(ceil(D_f / d_D_f)+1)]×d_D_f wherein, D_f is the section sampling frequency correction threshold value, d_D_f is the sampling step of the section sampling frequency correction threshold value; n1 is the number of values that the section sampling frequency correction value can take, and the value range is n1 = 1, 2, …, 2×ceil(D_f / d_D_f)+1; ceil() represents upward rounding calculation; ΔF(n1) is the n1th section sampling frequency correction value of the calibration linear mileage of the calibration section; arranging and combining the plurality of mileage translation correction values and the plurality of sampling frequency correction values, wherein each combination contains a section start mileage translation correction value and a section sampling frequency correction value; calculating the corrected linear mileage of the current calibration section under each combination using the following formula: wherein, is the start mileage of the current to-be-calibrated section; is the (m1, n1)th modified development mileage of the current to-be-calibrated section, which is modified according to the m1th section mileage translation correction value and the n1th section sampling frequency correction value; 2nd is the train running speed data; F is the cycle recording sampling frequency; j is the index value of the to-be-calibrated data, and the value range is The value ranges of m1 and n1 are respectively: m1=1, 2, …, 2×ceil(D_L / d_D_L)+1, n1=1, 2, …, 2×ceil(D_f / d_D_f)+1; is the index value of the start of the to-be-calibrated section; is the index value of the end of the to-be-calibrated section; N + represents a set of positive integers; According to the similarity calculation in the mileage data resampling interval, the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected, and the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected. According to the similarity calculation in the mileage data resampling interval, the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected, and the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected. According to the similarity calculation in the mileage data resampling interval, the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected, and the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected. According to the similarity calculation in the mileage data resampling interval, the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected, and the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected. According to the similarity calculation in the mileage data resampling interval, the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected, and the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected. According to the similarity calculation in the mileage data resampling interval, the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected, and the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected. wherein, is the start mileage of the current calibration section; is the start mileage of the current calibration section after the first correction of the start mileage translation correction value and the section sampling frequency correction value corresponding to the maximum second similarity;V 2nd is the train running speed data, F is the cycle record sampling frequency; j is the index value of the calibration data, which is respectively is the index value of the start of the current calibration section; M1 and N1 are respectively the arrangement combination serial numbers corresponding to the start mileage translation correction value and the section sampling frequency correction value corresponding to the maximum second similarity, that is, [ΔL(M1), ΔF(N1)];N + represents a set of positive integers; According to the similarity calculation in the mileage data resampling interval, the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected, and the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected. If yes, record the maximum second similarity and calculate the reset segment mileage translation correction value and segment sampling frequency correction value corresponding to the maximum second similarity; wherein the segment mileage translation correction value corresponding to the maximum second similarity is equal to the difference between the starting point of the current calibration section and the starting point of the current calibration section, and the segment sampling frequency correction value corresponding to the maximum second similarity is equal to the difference between the segment cycle record sampling frequency and the sampling frequency of the calibration data. If no, modify the segment mileage translation correction threshold to the preset multiple of the current segment mileage translation correction threshold sampling step; modify the segment sampling frequency correction threshold to the preset multiple of the current segment sampling frequency correction threshold sampling step, return to the step of determining the sampling step of the segment mileage translation correction threshold as the maximum of the segment mileage translation correction threshold and the sampling step threshold of the segment mileage translation correction threshold. According to the similarity calculation in the mileage data resampling interval, the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected, and the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected.

12. The track multi-source dynamic detection data alignment method of claim 10 or 11, wherein, According to the similarity calculation in the mileage data resampling interval, the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected, and the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected. According to the similarity calculation in the mileage data resampling interval, the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected, and the modified order of the combination of the mileage translation correction value and the segment sampling frequency correction value of each section is corrected. wherein, is the current to-be-calibrated section start unrolled mileage; is the to-be-calibrated unrolled mileage of the current to-be-calibrated section obtained by performing a correction on the section mileage translation correction value and the section sampling frequency correction value corresponding to the maximum similarity according to the section start mileage translation correction value;V 2nd is the train running speed data, F0 is the sampling frequency of the to-be-calibrated data; j is the index value of the to-be-calibrated data, and the values are is the index value of the start of the to-be-calibrated section; ΔL optm and ΔF optm are respectively the section mileage translation correction value and the section sampling frequency correction value corresponding to the maximum similarity; N + represents a set of positive integers.

13. The track multi-source dynamic detection data alignment method of claim 4, wherein, Determine whether there is a calibrated section before the current calibration section; ​ If yes, the following first segment translation correction formula is used to correct the to-be-calibrated straight mileage of the uncalibrated segment before the current to-be-calibrated segment: wherein, is the initial to-be-calibrated unwound mileage obtained after resetting the mileage integration for the to-be-calibrated mileage data; is the to-be-calibrated unwound mileage; j is an index value of the to-be-calibrated data, and the value range is is an index value of the start point of the current to-be-calibrated section; N + represents a set of positive integers; If no, the following linear transformation correction formula is used to correct the to-be-calibrated straight mileage of the uncalibrated segment before the current to-be-calibrated segment: wherein, is the initial uncalibrated distance to be calibrated after resetting the distance integration; is the uncalibrated distance to be calibrated; is the index value of the end point of the previous calibrated section; is the index value of the start point of the current calibration section; j is the index value of the data to be calibrated, and j is in the range of N + represents a set of positive integers.

14. The track multi-source dynamic detection data alignment method of claim 4, wherein, The last segment translation correction formula is used to correct the to-be-calibrated straight mileage of the uncalibrated segment between the end point of the current to-be-calibrated segment and the end point of the whole line, including: The following last segment translation correction formula is used to correct the to-be-calibrated straight mileage of the uncalibrated segment between the end point of the current to-be-calibrated segment and the end point of the whole line: wherein, is the initial to-be-calibrated unwound mileage obtained after resetting the mileage integration for the to-be-calibrated mileage data; is the to-be-calibrated unwound mileage; j is an index value of the to-be-calibrated data, and the value range is wherein Q is the number of to-be-calibrated mileage data in the to-be-calibrated data; is an index value of the current to-be-calibrated section endpoint; N + represents a set of positive integers.

15. The track multi-source dynamic inspection data alignment method of claim 1, wherein, The calibration parameters further include a vehicle body acceleration low-pass filter cutoff frequency; Before the to-be-calibrated straight mileage is calibrated segment by segment according to the calibration parameters, the first vehicle body acceleration data, the second vehicle body acceleration data and the standard straight mileage, the method further includes: The initial first vehicle body acceleration data and the initial second vehicle body acceleration data are subjected to low-pass filtering with a cutoff frequency being the vehicle body acceleration low-pass filter cutoff frequency, to obtain the first vehicle body acceleration data and the second vehicle body acceleration data.

16. A device for track multi-source dynamic detection data alignment, characterized in that, The method further includes: The obtaining module is configured to obtain to-be-calibrated data and standard data; the to-be-calibrated data and the standard data are data collected by different detection systems on the same train in the same train operation process, and the standard data is calibrated data; the standard data includes standard mileage data and first vehicle body acceleration data corresponding to the standard mileage data, and the to-be-calibrated data includes to-be-calibrated mileage data, second vehicle body acceleration data corresponding to the to-be-calibrated mileage data and train running speed data corresponding to the to-be-calibrated mileage data; The first processing module is configured to remove a broken link from the standard mileage data according to a sampling interval of the standard data, a starting sampling point mileage of the standard data and broken link account information corresponding to the standard data, to obtain standard straight mileage corresponding to the standard mileage data and broken link position information; The second processing module is configured to reset the to-be-calibrated mileage data according to the train running speed data and a sampling frequency of the to-be-calibrated data and a starting sampling point mileage of the to-be-calibrated data, to obtain initial to-be-calibrated straight mileage, and assign the initial to-be-calibrated straight mileage to the to-be-calibrated straight mileage; The parameter configuration module is configured to configure calibration parameters, wherein the calibration parameters include a preset similarity threshold, a first initial to-be-calibrated segment length, a second initial to-be-calibrated segment length, a first initial segment mileage translation correction threshold, a second initial segment mileage translation correction threshold, a segment sampling frequency correction threshold, a sampling step threshold of the segment mileage translation correction threshold, a sampling step threshold of the segment sampling frequency correction threshold, an initial to-be-calibrated segment lengthening number, a segment lengthening number threshold and a mileage data resampling interval in similarity calculation; The third processing module is configured to calibrate the to-be-calibrated straight mileage segment by segment according to the calibration parameters, the first vehicle body acceleration data, the second vehicle body acceleration data and the standard straight mileage, to obtain calibrated straight mileage corresponding to the to-be-calibrated straight mileage after the whole-line segment-by-segment calibration is completed. The fourth processing module is configured to perform broken link correction on the calibration unwinding mileage according to the standard unwinding mileage corresponding to the standard mileage data and the broken link position information, to obtain calibrated mileage data after mileage alignment of the to-be-calibrated mileage data.

17. The rail multi-source dynamic inspection data alignment apparatus of claim 16, wherein, The first processing module is specifically configured to remove the broken link from the standard mileage data according to the sampling interval of the standard data and the starting sampling point mileage of the standard data, to obtain the standard unwinding mileage corresponding to the standard mileage data, by using the following formula: where m 1st (1) is the starting sampling point mileage of the standard data; dL samp is the sampling interval of the standard data; is the standard unrolling mileage obtained after the broken link removal process; i is the index value of the standard data, and the value range is i = 1, 2, …, P, wherein P is the number of standard mileage data in the standard data; According to the broken link type, the starting point mileage of the broken link, and the end point mileage of the broken link in the broken link account information, the standard mileage data is traversed to determine the index value of the starting point mileage of the broken link in the standard mileage data and the index value of the end point mileage of the broken link in the standard mileage data, and the index value of the starting point mileage of the broken link, the index value of the end point mileage of the broken link, and the index value of the starting point mileage of the broken link corresponding to the standard mileage, the index value of the starting point mileage of the broken link corresponding to the standard unwinding mileage, and the index value of the end point mileage of the broken link corresponding to the standard mileage, the index value of the end point mileage of the broken link corresponding to the standard unwinding mileage are taken as the broken link position information.

18. The track multi-source dynamic detection data mileage alignment device of claim 16, wherein, The second processing module is specifically configured to reset the mileage integration of the to-be-calibrated mileage data by using the sampling frequency of the to-be-calibrated data, the starting sampling point mileage of the to-be-calibrated data, and the train running speed data, to obtain the initial to-be-calibrated unwinding mileage, by using the following formula: wherein m 2nd (1) is the starting sampling point mileage of the data to be calibrated; F0is the sampling frequency of the data to be calibrated; V 2nd is the train running speed data; is the initial calibrated straight mileage obtained after mileage integration reset of the mileage data to be calibrated; j is an index value of the data to be calibrated, and the value range is j = 1, 2, …, Q, wherein Q is the number of the mileage data to be calibrated in the data to be calibrated. The initial to-be-calibrated unwinding mileage is assigned to the to-be-calibrated unwinding mileage by using the following formula: wherein, is the to-be-calibrated true range.

19. The rail multi-source dynamic inspection data alignment apparatus of claim 16, wherein, The third processing module is specifically configured to execute the following steps to obtain the calibration unwinding mileage corresponding to the to-be-calibrated unwinding mileage according to the calibration parameter, the first car body acceleration, the second car body acceleration, and the standard unwinding mileage: Step 1: determining the starting point mileage of the common mileage section of the to-be-calibrated unwinding mileage and the standard unwinding mileage according to the to-be-calibrated unwinding mileage and the standard unwinding mileage, and assigning the starting point mileage of the common mileage section of the to-be-calibrated unwinding mileage and the standard unwinding mileage to the to-be-calibrated section starting point unwinding mileage, and assigning the first initial to-be-calibrated section length to the to-be-calibrated section length; Step 2: determining the corresponding to-be-calibrated section according to the to-be-calibrated section starting point unwinding mileage, the to-be-calibrated section length, and the to-be-calibrated unwinding mileage, and taking the data corresponding to the to-be-calibrated section as the to-be-calibrated section data, wherein the to-be-calibrated section data includes: the index value of the to-be-calibrated section starting point, the index value of the to-be-calibrated section end point, the to-be-calibrated unwinding mileage of the to-be-calibrated section, and the second car body acceleration data of the to-be-calibrated section and the train running speed data of the to-be-calibrated section; Step 3: determining whether the current to-be-calibrated section is the initial calibration calculation, if yes, executing step 5, and if no, executing step 4; Step 4: determining whether there is an uncalibrated section before the current to-be-calibrated section, if yes, executing step 5, and if no, executing step 8; Step 5: determining whether there is a calibrated section before the current to-be-calibrated section, if no, executing step 6, and if yes, executing step 7; Step 5: determining whether there is a calibrated section before the current to-be-calibrated section, if no, executing step 6, and if yes, executing step 7; Step 6: determine the segment sampling frequency correction threshold as the initial segment sampling frequency correction threshold, the segment mileage translation correction threshold as the first initial segment mileage translation correction threshold, and the third initial to-be-calibrated segment length as the first initial to-be-calibrated segment length, and jump to step 9; Step 7: determine the segment sampling frequency correction threshold as the initial segment sampling frequency correction threshold, determine a first difference value between the current to-be-calibrated segment start point forward mileage and the previous calibrated segment end point forward mileage; according to the segment sampling frequency correction threshold, mileage integration is performed on the train running speed data in the range from the end point of the previous calibrated segment to the start point of the current to-be-calibrated segment to obtain a first integrated value; the minimum value of the first difference value and the first integrated value is determined as the current to-be-calibrated segment mileage translation correction threshold, the third initial to-be-calibrated segment length is determined as the second initial to-be-calibrated segment length, and step 8 is jumped to; Step 8: determine the segment sampling frequency correction threshold as the initial segment sampling frequency correction threshold, determine the segment mileage translation correction threshold as the second initial segment mileage translation correction threshold, and determine the third initial to-be-calibrated segment length as the second initial to-be-calibrated segment length; Step 9: according to the segment mileage translation correction threshold, the segment sampling frequency correction threshold, the sampling step threshold of the segment mileage translation correction threshold, and the sampling step threshold of the segment sampling frequency correction threshold, determine a plurality of combinations of segment mileage translation correction values and sampling frequency correction values; each combination includes one segment mileage translation correction value and one segment sampling frequency correction value; Step 10: calculate the corrected forward mileage of the current to-be-calibrated segment under each combination; calculate the similarity between the second train body acceleration data corresponding to the corrected forward mileage of the to-be-calibrated segment under each combination and the first train body acceleration data corresponding to the standard forward mileage; select the maximum similarity and the segment mileage translation correction value and the segment sampling frequency correction value corresponding to the maximum similarity from the similarities corresponding to the combinations; Step 11: determine whether the maximum similarity is greater than a preset similarity threshold, if yes, execute step 12, and if no, execute step 20; Step 12: reset the to-be-calibrated segment lengthening number as the initial to-be-calibrated segment lengthening number; Step 13: use the segment mileage translation correction value and the segment sampling frequency correction value corresponding to the maximum similarity to correct the to-be-calibrated forward mileage of the current to-be-calibrated segment once; Step 14: determine whether there is an uncalibrated segment before the current to-be-calibrated segment, if yes, execute step 15, and if no, execute step 16; Step 15: correct the to-be-calibrated forward mileage of the uncalibrated segment before the current to-be-calibrated segment; Step 16: use the last segment translation correction formula to correct the to-be-calibrated forward mileage of the uncalibrated segment between the end point of the current to-be-calibrated segment and the terminal end of the whole line; Step 17: determine whether the end point of the current to-be-calibrated segment is the terminal end of the whole line, if yes, jump to step 1, and if no, execute step 18; Step 18: reset the to-be-calibrated segment start point forward mileage as the end point forward mileage of the current to-be-calibrated segment, reset the to-be-calibrated segment length as the second initial to-be-calibrated segment length, and return to step 2; Step 19: the updated to-be-calibrated straight development mileage obtained by the loop calculation is assigned to the calibrated straight development mileage, and the execution ends; Step 20: it is determined whether the current to-be-calibrated section end point is the whole line end point, if yes, step 19 is executed, and if not, step 21 is executed; Step 21: the to-be-calibrated section start point straight development mileage remains unchanged, the to-be-calibrated section length is accumulated by the first preset proportion of the third initial to-be-calibrated section length, and the to-be-calibrated section extension number is accumulated by 1 time; Step 22: it is determined whether the to-be-calibrated section extension number is greater than the section extension number threshold value, if yes, step 23 is executed, and if not, step 2 is returned; Step 23: the to-be-calibrated section start point straight development mileage is moved backward by the first preset proportion of the third initial to-be-calibrated section length, the third initial to-be-calibrated section length is assigned to the to-be-calibrated section length, the to-be-calibrated section extension number is reset as the initial to-be-calibrated section extension number, and step 2 is returned.

20. The rail multi-source dynamic inspection data alignment apparatus of claim 19, wherein, The third processing module is specifically configured to search, in the current to-be-calibrated straight development mileage, a first mileage point index value with the minimum mileage deviation from the current to-be-calibrated section start point straight development mileage and with the mileage deviation not greater than a mileage data resampling interval, and take the first mileage point index value as the index value of the to-be-calibrated section start point; It is determined whether the sum of the current to-be-calibrated section start point straight development mileage and the current to-be-calibrated section length is greater than the whole line end point straight development mileage of the to-be-calibrated straight development mileage; If yes, the whole line end point index value is taken as the index value of the to-be-calibrated section end point; If not, a second mileage point index value with the minimum mileage deviation from the sum of the current to-be-calibrated section start point straight development mileage and the to-be-calibrated section length and with the mileage deviation not greater than the mileage data resampling interval is searched in the current to-be-calibrated straight development mileage, and the second mileage point index value is taken as the index value of the to-be-calibrated section end point; According to the index value of the to-be-calibrated section start point and the index value of the to-be-calibrated section end point, the to-be-calibrated straight development mileage, the second vehicle body acceleration data, and the train running speed data between the index value of the to-be-calibrated section start point and the index value of the to-be-calibrated section end point are extracted.

21. The rail multi-source dynamic inspection data alignment apparatus of claim 19, wherein, The third processing module is specifically configured to determine a plurality of section mileage translation correction values according to a section mileage translation correction threshold value and a sampling step threshold value of the section mileage translation correction threshold value; determine a plurality of section sampling frequency correction values according to a section sampling frequency correction threshold value and a sampling step threshold value of the section sampling frequency correction threshold value; arrange and combine the plurality of section mileage translation correction values and the plurality of section sampling frequency correction values to obtain a plurality of combinations of section mileage translation correction values and sampling frequency correction values, each combination containing a section mileage translation correction value and a section sampling frequency correction value.

22. The rail multi-source dynamic inspection data alignment apparatus of claim 21, wherein, The third processing module is specifically configured to determine a plurality of section mileage translation correction values according to a section mileage translation correction threshold value and a sampling step threshold value of the section mileage translation correction threshold value by using the following formula: ΔL(m)=[m-(ceil(D_L / Thr_d_D_L)+1)]×Thr_d_D_L In the formula, D_L is a section mileage translation correction threshold value, Thr_d_D_L is a sampling step threshold value of the section mileage translation correction threshold value, m is a number of values that the section mileage translation correction value can take, and the value range is m = 1, 2, …, 2*ceil(D_L / Thr_d_D_L)+1, ceil() represents upward rounding calculation, and ΔL(m) is the mth section mileage translation correction value of the to-be-calibrated developed mileage of the to-be-calibrated section.

23. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the computer program comprises the steps of: The processor implements the method in any of claims 1-15 when executing the computer program.

24. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program implements the method in any of claims 1-15 when executed by a processor.

25. A computer program product, characterised in that, The computer program product comprises a computer program, and the computer program implements the method in any of claims 1-15 when executed by a processor.

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