Track waveform detection method, device and equipment and storage medium
By automatically filtering and correcting waveform data using track waveform detection equipment, the problem of data inaccuracy caused by deviations during the manufacturing and operation of track waveform detection equipment is solved, achieving efficient data correction and accuracy improvement.
Patent Information
- Application Number
- CN202511149699.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-15
- Publication Date
- 2025-10-31
AI Technical Summary
Existing track waveform detection equipment is affected by various factors during manufacturing, installation and operation, resulting in deviations in actual distance values, affecting the accuracy of waveform data. Furthermore, the manual calibration process reduces detection efficiency and may introduce human error.
The actual distance value is continuously collected by the track waveform detection device as it moves along the track. The mileage position data is divided into multiple candidate waveform sequences. Straight waveform sequences are selected, straightness is calculated, and the sequence with the smallest straightness is selected as the track deviation correction value to automatically correct the waveform data.
Without manual calibration, the accuracy of waveform data and computational efficiency were improved, computational complexity was reduced, and the accuracy of track deviation correction values was increased.
Smart Images
Figure CN120863709A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of rail transit technology, and in particular to a method, apparatus, equipment and storage medium for detecting track waveforms. Background Technology
[0002] As the fundamental structure for train operation, the track directly bears the dynamic loads of the train. Its waveform data is used to describe the geometric changes of the track along the mileage direction and is an important basis for judging whether the track is smooth.
[0003] Track waveform data reflects the irregularities detected by track waveform detection equipment at different track mileage locations. Ideally, the actual distance value equals the sum of the standard distance value and the irregularity value at the corresponding mileage location, where the standard distance value refers to the distance when the track is in ideal geometric condition. However, track waveform detection equipment may be affected by various factors during manufacturing, installation, and operation, and the actual distance value usually contains a certain deviation, thus affecting the accuracy of the track waveform data.
[0004] In related technologies, track waveform detection equipment is typically calibrated periodically using manual calibration to correct deviations in the track waveform. However, the manual calibration process not only reduces the detection efficiency of the track waveform detection equipment but may also introduce human error due to inconsistent operation, further affecting the accuracy of the waveform data. Summary of the Invention
[0005] This application provides a method, apparatus, device, and storage medium for detecting track waveforms, which corrects the deviation of the actual distance value and improves the accuracy of waveform data without manual calibration.
[0006] The first aspect of this application provides a method for detecting track waveforms.
[0007] If this method is applied to a track waveform detection device, then the method includes:
[0008] As the track waveform detection device moves along the track, it continuously collects the actual distance value of the track and obtains the track waveform data based on the actual distance value collected at each mileage position. The actual distance value is equal to the sum of the preset standard distance value, the unevenness value at the corresponding mileage position, and the track deviation correction value.
[0009] According to the preset first mileage interval, the waveform data is divided into multiple sets of candidate waveform sequences, and multiple sets of straight line waveform sequences are selected from the multiple sets of candidate waveform sequences.
[0010] Calculate the straightness of each group of straight waveform sequences, and based on the straightness of each group of straight waveform sequences, select the straight waveform sequence with the smallest straightness from multiple groups of straight waveform sequences.
[0011] The track deviation correction value is obtained from the straight waveform sequence with the minimum straightness, and the waveform data is corrected based on the track deviation correction value.
[0012] In one possible design, each set of candidate waveform sequences includes multiple discrete coordinate points; each discrete coordinate point is used to indicate the waveform data value at the corresponding mileage position.
[0013] Based on the straight waveform sequence with the minimum straightness, the track deviation correction value is obtained, including:
[0014] The straight waveform sequence with the minimum straightness is determined as the target waveform sequence;
[0015] The average waveform data value of the target waveform sequence is obtained by taking the waveform data value at each discrete coordinate point of the target waveform sequence.
[0016] If the average waveform data value of the target waveform sequence is less than the preset correction threshold, then the average waveform data value of the target waveform sequence will be determined as the track deviation correction value.
[0017] In one possible design, if the average waveform data value of the target waveform sequence is greater than or equal to the correction threshold, the method further includes:
[0018] Acquire historical waveform data of the track; the historical waveform data includes historical deviation correction values;
[0019] The historical deviation correction value is determined as the track deviation correction value.
[0020] In one possible design, the first waveform sequence is any one of multiple sets of straight-line waveform sequences;
[0021] For the first waveform sequence, calculate the straightness of each group of straight waveform sequences, including:
[0022] By using the least squares method, multiple discrete coordinate points of the first waveform sequence are fitted to obtain the fitted straight line of the first waveform sequence.
[0023] Calculate the Euclidean distance between each discrete coordinate point of the first waveform sequence and the fitted line;
[0024] The average Euclidean distance of the first waveform sequence is obtained based on the Euclidean distance value of each discrete coordinate point of the first waveform sequence;
[0025] The average Euclidean distance value is used to determine the straightness of the first waveform sequence.
[0026] In one possible design, the second waveform sequence is any one of a plurality of candidate waveform sequences;
[0027] For the second waveform sequence, multiple sets of linear waveform sequences are selected from multiple candidate waveform sequences, including:
[0028] Calculate the radius of each discrete coordinate point in the second waveform sequence;
[0029] The average radius of the second waveform sequence is obtained based on the radius of each discrete coordinate point of the second waveform sequence.
[0030] If the average radius is greater than the preset radius threshold, the second waveform sequence will be determined as a straight-line waveform sequence.
[0031] In one possible design, the formula for calculating the radius r of each discrete coordinate point in the second waveform sequence is:
[0032]
[0033] Where L refers to the length of the track waveform detection device, and h refers to the waveform data value of the corresponding discrete coordinate point.
[0034] In one possible design, after dividing the waveform data into multiple candidate waveform sequences according to a preset first mileage interval, the method further includes:
[0035] If the mileage of the last candidate waveform sequence in a plurality of candidate waveform sequences is less than the preset second mileage interval, then the last candidate waveform sequence is removed from the plurality of candidate waveform sequences.
[0036] A second aspect of this application provides a track waveform detection device, the device comprising:
[0037] The first acquisition module is used to continuously collect the actual distance value of the track when the track waveform detection device moves along the track, and obtain the waveform data of the track based on the actual distance value collected at each mileage position; wherein, the actual distance value is equal to the sum of the preset standard distance value, the unevenness value at the corresponding mileage position, and the track deviation correction value;
[0038] The first filtering module is used to split the waveform data into multiple sets of candidate waveform sequences according to the preset first mileage interval, and to filter out multiple sets of straight line waveform sequences from the multiple sets of candidate waveform sequences.
[0039] The second filtering module is used to calculate the straightness of each group of straight waveform sequences, and based on the straightness of each group of straight waveform sequences, to filter out the straight waveform sequence with the smallest straightness from multiple groups of straight waveform sequences.
[0040] The data correction module is used to obtain the track deviation correction value based on the straightness of the straight waveform sequence with the minimum straightness, and to correct the waveform data based on the track deviation correction value.
[0041] A third aspect of this application provides an electronic device, including: a memory, and a memory communicatively connected to a processor;
[0042] The memory stores instructions that the computer executes;
[0043] When the processor executes computer execution instructions stored in memory, it is used to implement the orbit waveform detection method of any of the first aspects.
[0044] The fourth aspect of this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the track waveform detection method of any one of the first aspects.
[0045] The fifth aspect of this application provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the track waveform detection method of any one of the first aspects.
[0046] This application provides a method, apparatus, device, and storage medium for detecting track waveforms. The method includes: continuously collecting actual distance values of the track as the track waveform detection device moves along the track, and obtaining track waveform data based on the actual distance values collected at each mileage position; dividing the waveform data into multiple sets of candidate waveform sequences according to a first mileage interval, and selecting multiple sets of straight waveform sequences from the multiple sets of candidate waveform sequences; calculating the straightness of each set of straight waveform sequences, and selecting the straight waveform sequence with the smallest straightness from the multiple sets of straight waveform sequences based on the straightness of each set of straight waveform sequences; obtaining a track deviation correction value based on the straight waveform sequence with the smallest straightness, and correcting the waveform data accordingly. This achieves the following technical effects: by using the straight waveform sequence with the smallest straightness to deduce the track deviation correction value and correct the waveform data accordingly, the deviation value of the track waveform can be corrected without manual calibration, improving the accuracy of the waveform data and the calculation efficiency; by dividing the waveform data, the calculation complexity is reduced, and the focus is on smooth straight waveform sequences, improving the accuracy of the track deviation correction value. Attached Figure Description
[0047] To more clearly illustrate the technical solutions in the embodiments of this application 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 some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0048] Figure 1 This is a schematic diagram illustrating the principle of actual distance values in the prior art;
[0049] Figure 2 A flowchart illustrating the track waveform detection method provided in this application embodiment. Figure 1 ;
[0050] Figure 3 The schematic diagram provided in this application is for illustrating the principle of waveform data. Figure 1 ;
[0051] Figure 4 The schematic diagram provided in this application is for illustrating the principle of waveform data. Figure 2 ;
[0052] Figure 5 The schematic diagram provided in this application is for illustrating the principle of waveform data. Figure 3 ;
[0053] Figure 6 The schematic diagram provided in this application is for illustrating the principle of waveform data. Figure 4 ;
[0054] Figure 7 A flowchart illustrating the track waveform detection method provided in this application embodiment. Figure 2 ;
[0055] Figure 8 The schematic diagram provided in this application is for illustrating the principle of waveform data. Figure 5 ;
[0056] Figure 9 This is a schematic diagram of the track waveform detection device provided in the embodiments of this application;
[0057] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.
[0058] Figure label:
[0059] 910 - First Acquisition Module; 920 - First Filtering Module; 930 - Second Filtering Module; 940 - Data Correction Module;
[0060] 1010 - Processor; 1020 - Memory; 1030 - Communication components; 1040 - Bus. Detailed Implementation
[0061] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.
[0062] In this application, the terms "first" and "second" are used to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, nor do they necessarily imply difference. It should be noted that in this application, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner. In this application, "at least one" means one or more, and "more than one" means two or more.
[0063] It should be noted that the phrase "at the moment when..." in this application can refer to the instant at which a certain situation occurs, or to a period of time after the occurrence of a certain situation; this application does not impose a specific limitation on this. Furthermore, the track waveform detection method provided in this application is merely an example, and the track waveform detection method may include more or less content. The user information (including but not limited to user device information and user personal information) and data (including but not limited to data used for analysis, stored data, and displayed data) involved in one or more embodiments of this application are all information and data authorized by the user or fully authorized by all parties. The collection, use, and processing of related data must comply with relevant laws, regulations, and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.
[0064] To clearly understand the technical solution of this application, the solutions of the prior art will be described in detail first.
[0065] As the fundamental structure for train operation, the track directly bears the dynamic loads of the train. Its waveform data is used to describe the geometric changes of the track along the mileage direction and is an important basis for judging whether the track is smooth.
[0066] Track waveform data can be obtained using track waveform detection equipment. Specifically, this equipment is equipped with distance sensors, such as laser distance sensors, which can be installed at positions opposite the top and / or sides of the track. As the equipment moves along the track, the distance sensors collect the actual distance value of the track at preset sampling steps. Based on these multiple collected distance values, the equipment obtains the track waveform data.
[0067] Figure 1 This is a schematic diagram illustrating the principle of actual distance values in existing technology. Ideally, such as... Figure 1 The figure shows the curve of the actual distance value d changing with mileage position. Track waveform data reflects the irregularities detected by the track waveform detection equipment at different mileage positions on the track. The actual distance value d is equal to the sum of the standard distance value H and the irregularity value h at the corresponding mileage position. The standard distance value refers to the distance when the track is in an ideal geometric state, i.e., when the track has not undergone geometric changes; it is a known value. However, track waveform detection equipment may be affected by various factors during manufacturing, installation, and operation, and the actual distance value usually contains a certain deviation, thus affecting the accuracy of the track waveform data.
[0068] In related technologies, track waveform detection equipment is typically calibrated periodically using manual calibration to correct deviations in the track waveform. For example, each irregularity value is corrected based on preset first and second correction coefficients, resulting in multiple corrected irregularity values. The first and second correction coefficients are, respectively, the slope and intercept of a straight line obtained by fitting multiple sets of gauge blocks of different thicknesses to the corresponding first historical irregularity values when gauge blocks of different thicknesses were placed directly below the track waveform detection equipment in the past. The first historical irregularity value is the deviation between the first historical distance value collected by the track waveform detection equipment and a set standard distance value.
[0069] However, the manual calibration process not only reduces the detection efficiency of track waveform detection equipment, but may also introduce human error due to inconsistent operation, further affecting the accuracy of waveform data.
[0070] Based on the aforementioned technical problems, the technical solution of this application is proposed.
[0071] The technical solutions of this application will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.
[0072] Figure 2A flowchart illustrating the track waveform detection method provided in this application embodiment. Figure 1 .like Figure 2 As shown in the embodiments of this application, the executing entity can be a track waveform detection device, which can be located in an electronic device, and the electronic device can be located in a track waveform detection device; the track waveform detection device is installed on the track, and the type of track can be a subway track, light rail track, tram track, or maglev track, etc. The track waveform detection method provided in the embodiments of this application includes the following steps:
[0073] S201. When the track waveform detection device moves along the track, it continuously collects the actual distance value of the track and obtains the waveform data of the track based on the actual distance value collected at each mileage position.
[0074] Specifically, as the track waveform detection device moves along the track, it collects the actual distance value of the track every preset sampling step. The sampling step can be every multiple sampling pulses; the actual distance value is equal to the sum of the preset standard distance value, the unevenness value at the corresponding mileage position, and the track deviation correction value.
[0075] Figure 3 The schematic diagram provided in this application is for illustrating the principle of waveform data. Figure 1 During or after data acquisition, the track waveform detection equipment calculates the waveform data value for each mileage location based on the actual distance value. This waveform data value equals the difference between the actual distance value *d* and the standard distance value *H*, and also equals the sum of the irregularity value *h* and the track deviation correction value *Δh*. Therefore, based on the waveform data value for each mileage location, the following can be obtained: Figure 3 The waveform data of the track shown is as follows. Figure 3 The x-axis represents the mileage location, which can be in meters; the y-axis represents the waveform data value, which can be in millimeters.
[0076] S202. According to the preset first mileage interval, the waveform data is divided into multiple sets of candidate waveform sequences, and multiple sets of straight line waveform sequences are selected from the multiple sets of candidate waveform sequences.
[0077] Specifically, set the first mileage interval S1, for example, S1 can be 100m.
[0078] Figure 4 The schematic diagram provided in this application is for illustrating the principle of waveform data. Figure 2 Then, according to the first mileage interval S1, Figure 3 The waveform data is split into, for example Figure 4 The mileage length shown is equal to S1, and the multiple candidate waveform sequences are named group 1, group 2, and so on, up to group n.
[0079] Next, the sequence radius of each candidate waveform sequence is calculated, and based on the sequence radius, each candidate waveform sequence is divided into either a curved waveform sequence or a straight waveform sequence. The curved waveform sequence can be longitudinally curved, corresponding to an uphill or downhill track segment where the train moves uphill or downhill; it can also be laterally curved, corresponding to a left-turn or right-turn track segment where the train turns left or right; a curved waveform sequence can also be a combination of both types of curvature. Then, from the multiple candidate waveform sequences, based on the division results of each candidate waveform sequence, multiple straight waveform sequences are selected.
[0080] S203. Calculate the straightness of each group of straight waveform sequences, and based on the straightness of each group of straight waveform sequences, select the straight waveform sequence with the smallest straightness from multiple groups of straight waveform sequences.
[0081] Specifically, for each set of straight waveform sequences, the mileage position is used as the abscissa and the waveform data value is used as the ordinate. The least squares method is used to fit the corresponding straight waveform sequence to obtain the fitted straight line. Then, based on the straight waveform sequence and its fitted straight line, the straightness of the corresponding straight waveform sequence is obtained.
[0082] Figure 5 The schematic diagram provided in this application is for illustrating the principle of waveform data. Figure 3 Straightness describes the smoothness of a corresponding straight-line waveform sequence. Higher straightness indicates a smoother waveform sequence and a smoother track segment. Therefore, from multiple sets of straight-line waveform sequences, the sequence with the lowest straightness is selected. For example, ... Figure 5 As shown, the second group of candidate waveform sequences is selected as the straight waveform sequence with the smallest straightness. The second group of candidate waveform sequences corresponds to the optimal track segment. The overall irregularity values of the multiple mileage positions of the second group of candidate waveform sequences are optimal.
[0083] S204. Obtain the track deviation correction value based on the straight waveform sequence with the minimum straightness, and correct the waveform data based on the track deviation correction value.
[0084] Specifically, based on the straight waveform sequence with the least straightness, the track deviation correction value is deduced, and the waveform data is corrected according to the track deviation correction value. Specifically, the waveform data is offset to zero to eliminate the zero point offset of the equipment and improve the accuracy of the waveform data.
[0085] Figure 6 The schematic diagram provided in this application is for illustrating the principle of waveform data. Figure 4 .right Figure 3 The waveform data shown is corrected to obtain the following: Figure 6The corrected waveform data is shown.
[0086] This application provides a method for detecting track waveforms. The method includes: continuously collecting actual distance values of the track as the track waveform detection device moves along the track, and obtaining track waveform data based on the actual distance values at each mileage position; dividing the waveform data into multiple sets of candidate waveform sequences according to a first mileage interval, and selecting multiple sets of straight waveform sequences from these sets; calculating the straightness of each set of straight waveform sequences, and selecting the straight waveform sequence with the smallest straightness from these sets; obtaining a track deviation correction value based on the straight waveform sequence with the smallest straightness, and using this value to correct the waveform data. This achieves the following technical effects: by using the straight waveform sequence with the smallest straightness to deduce the track deviation correction value and use it to correct the waveform data, the deviation value of the track waveform can be corrected without manual calibration, improving the accuracy and computational efficiency of the waveform data; by dividing the waveform data, the computational complexity is reduced, and focusing on smooth straight waveform sequences improves the accuracy of the track deviation correction value.
[0087] Figure 7 A flowchart illustrating the track waveform detection method provided in this application embodiment. Figure 2 ,like Figure 7 As shown, the track waveform detection method provided in this application embodiment is... Figure 2 This embodiment of the track waveform detection method is further refined. Each candidate waveform sequence includes multiple discrete coordinate points; each discrete coordinate point is used to indicate the waveform data value at the corresponding mileage position. Therefore, the track waveform detection method provided in this application embodiment includes the following steps.
[0088] S701. When the track waveform detection device moves along the track, it continuously collects the actual distance value of the track and obtains the waveform data of the track based on the actual distance value collected at each mileage position.
[0089] S702. Based on the preset first mileage interval, the waveform data is divided into multiple sets of candidate waveform sequences.
[0090] In one possible design, after S702 is executed, the method further includes:
[0091] If the mileage of the last candidate waveform sequence in a plurality of candidate waveform sequences is less than the preset second mileage interval, then the last candidate waveform sequence is removed from the plurality of candidate waveform sequences.
[0092] In one possible design, a second mileage interval S2 is set, for example, S2 can be 80m.
[0093] For example, if the mileage of the nth candidate waveform sequence is 70m, which is less than S2, then the nth candidate waveform sequence is removed from the multiple candidate waveform sequences, and the waveform data is updated. The updated waveform data consists of n-1 candidate waveform sequences.
[0094] S703. Select multiple sets of linear waveform sequences from multiple sets of candidate waveform sequences.
[0095] In one possible design, the second waveform sequence is any one of a plurality of candidate waveform sequences; for the second waveform sequence, S703 includes:
[0096] S7031. Calculate the radius of each discrete coordinate point of the second waveform sequence.
[0097] In one possible design, the formula for calculating the radius r of each discrete coordinate point in the second waveform sequence is:
[0098]
[0099] Where L refers to the length of the track waveform detection device, and h refers to the waveform data value of the corresponding discrete coordinate point.
[0100] Figure 8 The schematic diagram provided in this application is for illustrating the principle of waveform data. Figure 5 .like Figure 8 As shown, r, rh, and L / 2 form a right triangle (discrete coordinate points where h is 0 can be discarded). Therefore, according to the Pythagorean theorem, we can obtain:
[0101]
[0102] After conversion, we get:
[0103]
[0104] By iterating through each discrete coordinate point of the second waveform sequence, the radius of each discrete coordinate point is obtained.
[0105] S7032. Based on the radius of each discrete coordinate point of the second waveform sequence, obtain the average radius of the second waveform sequence.
[0106] If the average radius is greater than the preset radius threshold, then continue executing S7033; otherwise, continue executing S7034.
[0107] S7033. Determine the second waveform sequence as a linear waveform sequence.
[0108] S7034. Determine the second waveform sequence as a curve waveform sequence.
[0109] In the embodiments of this application, for the other waveform sequences besides the second waveform sequence among multiple candidate waveform sequences, the calculation method of their average radius and the judgment logic of the straight waveform sequence can refer to the relevant method of the second waveform sequence, and will not be repeated here.
[0110] S704. Calculate the straightness of each group of straight waveform sequences.
[0111] In one possible design, the first waveform sequence is any one of multiple sets of linear waveform sequences; for the first waveform sequence, S704 includes:
[0112] S7041. By using the least squares method, multiple discrete coordinate points of the first waveform sequence are fitted to obtain the fitted straight line of the first waveform sequence.
[0113] S7042. Calculate the Euclidean distance between each discrete coordinate point of the first waveform sequence and the fitted straight line.
[0114] S7043. Based on the Euclidean distance value of each discrete coordinate point of the first waveform sequence, obtain the average Euclidean distance value of the first waveform sequence.
[0115] S7044. The average Euclidean distance value is used as the straightness of the first waveform sequence.
[0116] Specifically, the multiple discrete coordinate points of the first waveform sequence are represented as (x1, h1), (x2, h2), and so on up to (xn, hn). Here, x1 to xn refer to the mileage positions of the corresponding discrete coordinate points, and h1 to hn refer to the waveform data values of the corresponding discrete coordinate points.
[0117] By using the least squares method, the fitted line of the first waveform sequence is obtained by fitting (x1,h1) up to (xn,hn), which is represented as y=kx+b.
[0118] The formula for the distance between a point and a line:
[0119]
[0120] Substitute each discrete coordinate point of the first waveform sequence into the distance formula to obtain the Euclidean distance value between each discrete coordinate point of the first waveform sequence and the fitted line, and represent them as d1, d2, and so on up to dn.
[0121] Calculate the average from d1 to dn to obtain the average Euclidean distance of the first waveform sequence, and then obtain the straightness of the first waveform sequence, which is expressed as Δx.
[0122] In the embodiments of this application, for the other waveform sequences besides the first waveform sequence among multiple sets of straight waveform sequences, the method for calculating the straightness can refer to the relevant method of the first waveform sequence, and will not be repeated here.
[0123] S705. Based on the straightness of each set of straight waveform sequences, select the straight waveform sequence with the smallest straightness from multiple sets of straight waveform sequences.
[0124] S706. The straight waveform sequence with the smallest straightness is determined as the target waveform sequence.
[0125] S707. Based on the waveform data values of each discrete coordinate point of the target waveform sequence, obtain the average waveform data value of the target waveform sequence.
[0126] Specifically, by substituting each discrete coordinate point of the target waveform sequence into the distance formula between points and lines, the Euclidean distance between each discrete coordinate point of the target waveform sequence and the x-axis is obtained. Then, the average of these Euclidean distance values is calculated to obtain the average waveform data value of the target waveform sequence.
[0127] If the average waveform data value of the target waveform sequence is less than the preset correction threshold, it indicates that its zero-point offset is small and can be used for waveform data correction, then continue to execute S708; otherwise, it indicates that the waveform sequence may have systematic deviations caused by factors such as noise, local errors or equipment drift, then continue to execute S709.
[0128] S708. Take the average waveform data of the target waveform sequence and determine it as the track deviation correction value.
[0129] S709. Obtain historical waveform data of the track.
[0130] Historical waveform data includes historical deviation correction values.
[0131] S710. Determine the historical deviation correction value as the track deviation correction value.
[0132] After executing S708 or S710, continue executing S711.
[0133] S711. Correct the waveform data according to the track deviation correction value.
[0134] In one possible design, after S710 is executed, the method further includes:
[0135] The difference between the average waveform data of the target waveform sequence and the historical deviation correction value is calculated. If the difference is greater than the preset difference threshold, it indicates that the track waveform detection equipment is faulty or that the track has undergone serious deformation, and an alarm is triggered so that technicians can manually inspect the track waveform detection equipment and the track.
[0136] Figure 9 This is a schematic diagram of the track waveform detection device provided in the embodiments of this application, as shown below. Figure 9 As shown in this embodiment, the track waveform detection device can be located in an electronic device. The track waveform detection device includes:
[0137] The first acquisition module 910 is used to continuously collect the actual distance value of the track when the track waveform detection device moves along the track, and obtain the waveform data of the track based on the actual distance value collected at each mileage position; wherein, the actual distance value is equal to the sum of the preset standard distance value, the unevenness value at the corresponding mileage position, and the track deviation correction value;
[0138] The first filtering module 920 is used to split the waveform data into multiple sets of candidate waveform sequences according to the preset first mileage interval, and to filter out multiple sets of straight line waveform sequences from the multiple sets of candidate waveform sequences.
[0139] The second filtering module 930 is used to calculate the straightness of each group of straight waveform sequences, and based on the straightness of each group of straight waveform sequences, to filter out the straight waveform sequence with the smallest straightness from multiple groups of straight waveform sequences.
[0140] The data correction module 940 is used to obtain the track deviation correction value based on the straight waveform sequence with the minimum straightness, and to correct the waveform data based on the track deviation correction value.
[0141] The track waveform detection device provided in this application embodiment can perform... Figure 2 The technical solution of the method embodiment shown has the same implementation principle and technical effect as... Figure 2 The method embodiments shown are similar, and will not be described again in the embodiments of this application.
[0142] Meanwhile, the track waveform detection device provided in this application embodiment is a further refinement based on the track waveform detection device provided in the previous application embodiment.
[0143] In one possible design, each set of candidate waveform sequences includes multiple discrete coordinate points; each discrete coordinate point is used to indicate the waveform data value at the corresponding mileage position.
[0144] Data correction module 940 includes:
[0145] The first determining module is used to determine the straight waveform sequence with the minimum straightness as the target waveform sequence;
[0146] The first calculation module is used to obtain the average waveform data value of the target waveform sequence based on the waveform data value of each discrete coordinate point of the target waveform sequence;
[0147] The second determining module is used to determine the average waveform data value of the target waveform sequence as the track deviation correction value if the average waveform data value of the target waveform sequence is less than the preset correction value threshold.
[0148] In one possible design, if the average waveform data of the target waveform sequence is greater than or equal to the correction threshold, the device further includes:
[0149] The second acquisition module is used to acquire historical waveform data of the track; wherein, the historical waveform data includes historical deviation correction values;
[0150] The third determination module is used to determine the historical deviation correction value as the track deviation correction value.
[0151] In one possible design, the first waveform sequence is any one of multiple sets of straight-line waveform sequences;
[0152] For the first waveform sequence, the second filtering module 930 includes:
[0153] The line fitting module is used to fit multiple discrete coordinate points of the first waveform sequence using the least squares method to obtain the fitted line of the first waveform sequence.
[0154] The second calculation module is used to calculate the Euclidean distance between each discrete coordinate point of the first waveform sequence and the fitted straight line.
[0155] The third calculation module is used to obtain the average Euclidean distance value of the first waveform sequence based on the Euclidean distance value of each discrete coordinate point of the first waveform sequence;
[0156] The fourth determining module is used to determine the average Euclidean distance value as the straightness of the first waveform sequence.
[0157] In one possible design, the second waveform sequence is any one of a plurality of candidate waveform sequences;
[0158] For the second waveform sequence, the first filtering module 920 includes:
[0159] The fourth calculation module is used to calculate the radius of each discrete coordinate point in the second waveform sequence;
[0160] The fifth calculation module is used to obtain the average radius of the second waveform sequence based on the radius of each discrete coordinate point of the second waveform sequence;
[0161] The fifth determining module is used to determine the second waveform sequence as a straight-line waveform sequence if the average radius is greater than a preset radius threshold.
[0162] In one possible design, the formula for calculating the radius r of each discrete coordinate point in the second waveform sequence is:
[0163]
[0164] Where L refers to the length of the track waveform detection device, and h refers to the waveform data value of the corresponding discrete coordinate point.
[0165] In one possible design, the device also includes:
[0166] The sequence elimination module is used to eliminate the last group of candidate waveform sequences from the multiple candidate waveform sequences if the mileage of the last group of candidate waveform sequences is less than the preset second mileage interval.
[0167] The track waveform detection device provided in this application embodiment can perform... Figure 2 and Figure 7 The technical solution of the method embodiment shown has the same implementation principle and technical effect as... Figure 2 and Figure 7 The method embodiments shown are similar, and will not be described again in the embodiments of this application.
[0168] This application also provides an electronic device. Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 10 As shown, the electronic device includes at least one processor 1010 and a memory 1020. The electronic device also includes a communication component 1030. The processor 1010, memory 1020, and communication component 1030 are connected via a bus 1040.
[0169] In the specific implementation process, at least one processor 1010 executes computer execution instructions stored in memory 1020, so that at least one processor 1010 is used to implement the track waveform detection method of the above embodiment.
[0170] The specific implementation process of processor 1010 can be found in the above method embodiments, and its implementation principle and technical effect are similar. The embodiments of this application will not be repeated here.
[0171] In the above embodiments, it should be understood that the processor 1010 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the application can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.
[0172] The memory 1020 may include high-speed RAM memory, and may also include non-volatile memory NVM, such as at least one disk storage.
[0173] Bus 1040 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Bus 1040 can be divided into address bus, data bus, control bus, etc. For ease of illustration, the bus 1040 in the accompanying drawings of this application is not limited to only one bus or one type of bus.
[0174] The above description addresses the functions implemented by electronic devices and main control devices, and introduces the solutions provided in the embodiments of this application. It is understood that, in order to achieve the above functions, the electronic device or main control device includes hardware structures and / or software modules corresponding to the execution of each function. By combining the units and algorithm steps of the various examples described in the embodiments disclosed in this application, the embodiments of this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the technical solutions of the embodiments of this application.
[0175] This application also provides a computer-readable storage medium storing computer-executable instructions. When executed by a processor, these instructions are used to implement the track waveform detection method described above. In the specific implementation of the aforementioned track waveform detection method, each module can be implemented as a processor.
[0176] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.
[0177] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in application-specific integrated circuits (ASICs). Alternatively, the processor and the readable storage medium can exist as discrete components in an electronic device or a host device.
[0178] This application also provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the track waveform detection method of the above embodiments.
[0179] The computer program is stored in a readable storage medium, and at least one processor can read the computer program from the readable storage medium and execute the computer program to perform the scheme provided in any of the above embodiments.
[0180] Those skilled in the art will understand that all or part of the steps in the above-described embodiments can be implemented using hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps included in the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.
[0181] The technical solutions of this application have been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it is readily understood by those skilled in the art that the scope of protection of this application is obviously not limited to these specific embodiments. The above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.
Claims
1. A method for detecting track waveforms, characterized in that, If the method is applied to a track waveform detection device, then the method includes: As the track waveform detection device moves along the track, it continuously collects the actual distance value of the track and obtains the waveform data of the track based on the actual distance value collected at each mileage position; wherein, the actual distance value is equal to the sum of the preset standard distance value, the unevenness value at the corresponding mileage position, and the track deviation correction value; According to the preset first mileage interval, the waveform data is divided into multiple sets of candidate waveform sequences, and multiple sets of straight line waveform sequences are selected from the multiple sets of candidate waveform sequences. Calculate the straightness of each group of straight waveform sequences, and based on the straightness of each group of straight waveform sequences, select the straight waveform sequence with the smallest straightness from the multiple groups of straight waveform sequences. The track deviation correction value is obtained based on the straight waveform sequence with the minimum straightness, and the waveform data is corrected based on the track deviation correction value.
2. The method according to claim 1, characterized in that, Each set of candidate waveform sequences includes multiple discrete coordinate points; each discrete coordinate point is used to indicate the waveform data value at the corresponding mileage position. The process of obtaining the track deviation correction value based on the straight waveform sequence with the minimum straightness includes: The straight waveform sequence with the minimum straightness is determined as the target waveform sequence; The average waveform data value of the target waveform sequence is obtained based on the waveform data value of each discrete coordinate point of the target waveform sequence. If the average waveform data value of the target waveform sequence is less than the preset correction value threshold, then the average waveform data value of the target waveform sequence is determined as the track deviation correction value.
3. The method according to claim 2, characterized in that, If the average waveform data value of the target waveform sequence is greater than or equal to the correction threshold, the method further includes: Obtain historical waveform data of the track; wherein, the historical waveform data includes historical deviation correction values; The historical deviation correction value is determined as the orbital deviation correction value.
4. The method according to claim 2, characterized in that, The first waveform sequence is any one of the multiple sets of straight-line waveform sequences; For the first waveform sequence, calculating the straightness of each group of straight waveform sequences includes: By using the least squares method, multiple discrete coordinate points of the first waveform sequence are fitted to obtain a fitted straight line for the first waveform sequence. Calculate the Euclidean distance between each discrete coordinate point of the first waveform sequence and the fitted straight line; The average Euclidean distance value of the first waveform sequence is obtained based on the Euclidean distance value of each discrete coordinate point of the first waveform sequence; The average Euclidean distance value is used to determine the straightness of the first waveform sequence.
5. The method according to claim 2, characterized in that, The second waveform sequence is any one of the multiple sets of candidate waveform sequences; For the second waveform sequence, the step of selecting multiple sets of linear waveform sequences from the multiple sets of candidate waveform sequences includes: Calculate the radius of each discrete coordinate point in the second waveform sequence; The average radius of the second waveform sequence is obtained based on the radius of each discrete coordinate point of the second waveform sequence; If the average radius is greater than a preset radius threshold, then the second waveform sequence is determined to be the straight-line waveform sequence.
6. The method according to claim 5, characterized in that, The formula for calculating the radius r of each discrete coordinate point in the second waveform sequence is: Where L refers to the length of the track waveform detection device, and h refers to the waveform data value of the corresponding discrete coordinate point.
7. The method according to claim 1, characterized in that, After dividing the waveform data into multiple candidate waveform sequences according to a preset first mileage interval, the method further includes: If the mileage of the last group of candidate waveform sequences is less than the preset second mileage interval, then the last group of candidate waveform sequences is removed from the multiple groups of candidate waveform sequences.
8. A track waveform detection device, characterized in that, The device includes: The first acquisition module is used to continuously collect the actual distance value of the track when the track waveform detection device moves along the track, and obtain the waveform data of the track based on the actual distance value collected at each mileage position; wherein, the actual distance value is equal to the sum of the preset standard distance value, the unevenness value at the corresponding mileage position, and the track deviation correction value; The first filtering module is used to split the waveform data into multiple sets of candidate waveform sequences according to a preset first mileage interval, and to filter out multiple sets of straight line waveform sequences from the multiple sets of candidate waveform sequences. The second filtering module is used to calculate the straightness of each group of straight waveform sequences, and based on the straightness of each group of straight waveform sequences, to filter out the straight waveform sequence with the smallest straightness from the multiple groups of straight waveform sequences. The data correction module is used to obtain the track deviation correction value based on the straight waveform sequence with the smallest straightness, and to correct the waveform data based on the track deviation correction value.
9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the orbit waveform detection method as described in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the orbital waveform detection method as described in any one of claims 1 to 7.