Quantitative evaluation method, device, equipment and storage medium for roadbed contamination status

Abstract

This paper provides a quantitative evaluation method, device, equipment and storage medium for the contamination state of the roadbed, wherein the method includes: determining the roadbed contamination rate corresponding to the roadbed of the target mileage according to the radar echo signal corresponding to the roadbed of the target mileage; selecting a representative value of the contamination rate from the roadbed contamination rate, and calculating the estimated contamination rate interval corresponding to the representative value of the contamination rate according to the representative value of the contamination rate; determining the representative value position point of the representative value of the contamination rate in the target mileage, and the actual contamination rate corresponding to the representative value position point; judging whether the actual contamination rate belongs to the estimated contamination rate interval; if so, outputting the roadbed contamination rate corresponding to the roadbed of the target mileage; if not, updating the roadbed contamination rate corresponding to the roadbed of the target mileage according to the representative value position point and the actual contamination rate corresponding to the roadbed, and outputting the updated roadbed contamination rate corresponding to the roadbed of the target mileage. This paper can improve the efficiency of roadbed contamination state evaluation and reduce the waste of manpower and material costs.

Description

Technical Field

[0001] The present invention relates to the field of track detection, and in particular to a quantitative evaluation method, device, equipment and storage medium for the contamination state of a track bed. Background Art

[0002] Gravel ballast is an important structural form of railway track. The condition of the gravel ballast affects the transportation speed, safety and comfort of the railway line. As the gravel ballast increases in service time, the ballast breaks and powders, dirt accumulates on the ballast, and the condition of the ballast continues to deteriorate.

[0003] There is a method in the prior art for inverting the railway track bed uncleanness rate through ground penetrating radar. The method performs segmented imaging on the preprocessed radar profile data according to the railway mileage intervals. In each segmented interval, the energy value of the imaging result of a set depth interval is used as the track bed uncleanness rate corresponding to the mileage point. Finally, the uncleanness rates corresponding to the mileage points in the segmented interval are averaged, and this average value is used as the estimated value of the track bed uncleanness rate in the segmented interval.

[0004] The existing evaluation method of the roadbed unclean rate requires the calculation of the imaging results of each segmented interval. When major changes occur in the railway, such as overhaul, screening, ballast replenishment, ballast replacement, etc., or when a long time has passed since the last evaluation of the roadbed unclean rate, it is necessary to recalculate the imaging results of each segmented interval. However, in fact, the roadbed unclean rate may not change, and the new evaluation result is the same as the previous evaluation result, resulting in the recalculation and evaluation process being a redundant step, which consumes a lot of manpower and material costs.

[0005] Therefore, there is an urgent need for a quantitative evaluation method for the dirtiness of the roadbed, which can improve the efficiency of the evaluation of the dirtiness of the roadbed and reduce the waste of manpower and material costs. Summary of the invention

[0006] The purpose of the embodiments of this document is to provide a method, device, equipment and storage medium for quantitatively evaluating the contamination status of a roadbed, so as to improve the efficiency of evaluating the contamination status of a roadbed and reduce the waste of manpower and material costs.

[0007] To achieve the above objectives, on the one hand, the embodiments of this invention provide a quantitative evaluation method for the contamination state of the roadbed, including:

[0008] According to the radar echo signal corresponding to the roadbed of the target mileage, the roadbed contamination rate corresponding to the roadbed of the target mileage is determined;

[0009] Selecting a representative value of the dirtiness rate from the dirtiness rate of the ballast, and calculating an estimated dirtiness rate interval corresponding to the representative value of the dirtiness rate according to the representative value of the dirtiness rate;

[0010] Determine a representative value position point of the dirtiness rate representative value in the target mileage, and an actual dirtiness rate corresponding to the representative value position point;

[0011] Determining whether the actual dirtiness rate falls within the estimated dirtiness rate range;

[0012] If yes, then output the roadbed contamination rate corresponding to the roadbed of the target mileage;

[0013] If not, the roadbed contamination rate corresponding to the roadbed of the target mileage is updated according to the representative value position point and the actual contamination rate corresponding thereto, and the updated roadbed contamination rate corresponding to the roadbed of the target mileage is output.

[0014] On the other hand, the embodiments of the present invention provide a device for quantitatively evaluating the dirty state of a roadbed, the device comprising:

[0015] A roadbed contamination rate determination module is used to determine the roadbed contamination rate corresponding to the roadbed of the target mileage according to the radar echo signal corresponding to the roadbed of the target mileage;

[0016] A calculation module, used for selecting a representative value of the dirtiness rate from the dirtiness rate of the roadbed, and calculating an estimated dirtiness rate interval corresponding to the representative value of the dirtiness rate according to the representative value of the dirtiness rate;

[0017] An actual dirtiness rate determination module, used to determine a representative value position point of the dirtiness rate representative value in the target mileage, and an actual dirtiness rate corresponding to the representative value position point;

[0018] A judgment module, used to judge whether the actual dirtiness rate belongs to the estimated dirtiness rate interval;

[0019] If yes, then output the roadbed contamination rate corresponding to the roadbed of the target mileage;

[0020] If not, the roadbed contamination rate corresponding to the roadbed of the target mileage is updated according to the representative value position point and the actual contamination rate corresponding thereto, and the updated roadbed contamination rate corresponding to the roadbed of the target mileage is output.

[0021] On the other hand, the embodiments of the present invention further provide a computer device, including a memory, a processor, and a computer program stored in the memory, wherein when the computer program is executed by the processor, the instructions of any one of the above methods are executed.

[0022] On the other hand, the embodiments of the present invention further provide a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor of a computer device, the computer program executes instructions of any one of the above-described methods.

[0023] It can be seen from the technical solution provided in the above embodiments of this article that, after selecting a representative value of the dirtiness rate from the roadbed dirtiness rate, the embodiments of this article further calculate the estimated dirtiness rate interval, judge whether the actual dirtiness rate corresponding to the representative value position point is in the estimated dirtiness rate interval, and then determine whether the roadbed dirtiness rate in this article needs to be updated. The roadbed dirtiness rate can be updated by only using the representative value of the dirtiness rate. The method of this article improves the efficiency of the evaluation of the roadbed dirtiness status and reduces the waste of manpower and material costs.

[0024] In order to make the above and other purposes, features and advantages of this article more obvious and easy to understand, the following specifically cites preferred embodiments and describes them in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of this article or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of this article. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 A schematic flow chart of a method for quantitatively evaluating the dirty state of a roadbed provided in an embodiment of this invention is shown;

[0027] Figure 2 A schematic diagram of a process for determining a roadbed contamination rate corresponding to a roadbed of a target mileage provided in an embodiment of the present invention is shown;

[0028] Figure 3 A schematic diagram for indicating the installation position of a radar antenna provided in an embodiment of this document is shown;

[0029] Figure 4 A schematic diagram of a flow chart of a sequence of characterization values ​​for determining a dirty state of a ballast provided in an embodiment of the present invention is shown;

[0030] Figure 5 A schematic diagram of a flow chart for determining a signal time domain scanning area of ​​a radar echo signal for setting a ballast bed depth at each position point provided in an embodiment of the present invention is shown;

[0031] Figure 6 A schematic diagram of a sampling point sequence for indicating a set ballast bed depth provided in an embodiment of the present invention is shown;

[0032] Figure 7 A schematic diagram of a process for calibrating a characterization value sequence provided in an embodiment of this invention is shown;

[0033] Figure 8A schematic diagram of a process for determining a selected characterization value corresponding to a target mileage according to a characterization value sequence provided in an embodiment of the present invention is shown;

[0034] Fig. 9 A schematic diagram of a process for determining a multi-level selection interval according to a characterization value sequence provided in an embodiment of this invention is shown;

[0035] Fig.10 A schematic diagram of a process for obtaining a selected characterization value corresponding to a target mileage according to an embodiment of the present invention is shown;

[0036] Fig.11 A schematic diagram for representing a first selected characterization value of each level in a multi-level selection interval provided by an embodiment of the present invention is shown;

[0037] Fig.12 A schematic diagram of a process for selecting a first selected characterization value in each level provided in an embodiment of the present invention is shown;

[0038] Fig.13 A schematic diagram of a process for obtaining a ballast bed contamination model provided in an embodiment of this invention is shown;

[0039] Fig.14 A schematic diagram of the enclosure equipment required at the sampling hole for determining the actual dirtiness rate provided in the embodiment of this invention is shown;

[0040] Fig.15 A schematic diagram of a process for calculating an estimated soiling rate interval corresponding to a soiling rate representative value provided in an embodiment of the present invention is shown;

[0041] Fig.16 A schematic diagram of a process for updating the roadbed contamination rate corresponding to the roadbed of the target mileage provided in the embodiment of this document is shown;

[0042] Fig.17 A schematic diagram of the process of performing update and replacement provided in the embodiment of this article is shown;

[0043] Fig.18 Another schematic diagram of a process for updating and replacing provided in an embodiment of this invention is shown;

[0044] Fig.19 A schematic diagram of the module structure of a device for quantitatively evaluating the dirty state of a roadbed provided in an embodiment of the present invention is shown;

[0045] Fig. 20 A schematic diagram showing the structure of a computer device provided in an embodiment of this invention is shown;

[0046] Fig.21 The overall structure schematic diagram of the first test device provided in the embodiment of this article is shown;

[0047] Fig. 22The overall structural schematic diagram of the second test device provided in the embodiment of this article is shown.

[0048] Description of the accompanying symbols:

[0049] 1. first bracket; 2. metal plate; 3. first connecting rod; 4. first antenna; 5. first connecting piece; 6. second bracket; 7. standard ballast model box; 8. second connecting rod; 9. second antenna; 10. second connecting piece; 100. ballast bed dirtiness rate determination module; 200. calculation module; 300. actual dirtiness rate determination module; 400. judgment module; 2002. computer device; 2004. processor; 2006. memory; 2008. driving mechanism; 2010. input / output module; 2012. input device; 2014. output device; 2016. presentation device; 2018. graphical user interface; 2020. network interface; 2022. communication link; 2024. communication bus. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of this article to clearly and completely describe the technical solutions in the embodiments of this article. Obviously, the described embodiments are only part of the embodiments of this article, not all of the embodiments. Based on the embodiments of this article, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this article.

[0051] There is a method in the prior art for inverting the railway track bed uncleanness rate through ground penetrating radar. The method performs segmented imaging on the preprocessed radar profile data according to the railway mileage intervals. In each segmented interval, the energy value of the imaging result of a set depth interval is used as the track bed uncleanness rate corresponding to the mileage point. Finally, the uncleanness rates corresponding to the mileage points in the segmented interval are averaged, and this average value is used as the estimated value of the track bed uncleanness rate in the segmented interval.

[0052] The existing evaluation method of the roadbed unclean rate requires the calculation of the imaging results of each segmented interval. When major changes occur in the railway, such as overhaul, screening, ballast replenishment, ballast replacement, etc., or when a long time has passed since the last evaluation of the roadbed unclean rate, it is necessary to recalculate the imaging results of each segmented interval. However, in fact, the roadbed unclean rate may not change, and the new evaluation result is the same as the previous evaluation result, resulting in the recalculation and evaluation process being a redundant step, which consumes a lot of manpower and material costs.

[0053] In order to solve the above problems, the embodiments of this article provide a quantitative evaluation method for the dirtiness of the roadbed. Figure 1This is a schematic diagram of the steps of a quantitative evaluation method for the dirty state of a roadbed provided in an embodiment of this invention. This specification provides the method operation steps described in the embodiment or flowchart, but may include more or fewer operation steps based on conventional or non-creative labor. The order of steps listed in the embodiment is only one way of executing the steps among many orders, and does not represent the only order of execution. When the actual system or device product is executed, it can be executed in the order of the method shown in the embodiment or the drawings or in parallel.

[0054] Reference Figure 1 , a quantitative evaluation method for the dirty state of the ballast bed, comprising:

[0055] S101: determining a roadbed contamination rate corresponding to the roadbed of the target mileage according to a radar echo signal corresponding to the roadbed of the target mileage;

[0056] S102: selecting a representative value of the dirtiness rate from the dirtiness rate of the ballast, and calculating an estimated dirtiness rate interval corresponding to the representative value of the dirtiness rate according to the representative value of the dirtiness rate;

[0057] S103: Determine a representative value position point of the dirtiness rate representative value in the target mileage, and an actual dirtiness rate corresponding to the representative value position point;

[0058] S104: Determine whether the actual dirtiness rate falls within the estimated dirtiness rate range;

[0059] If yes, then output the roadbed contamination rate corresponding to the roadbed of the target mileage;

[0060] If not, the roadbed contamination rate corresponding to the roadbed of the target mileage is updated according to the representative value position point and the actual contamination rate corresponding thereto, and the updated roadbed contamination rate corresponding to the roadbed of the target mileage is output.

[0061] Railway mileage refers to the length of the railway mainline for passenger and freight transportation. The target mileage mentioned in this article refers to the part of the railway mileage that needs to be quantitatively evaluated for the contamination status of the roadbed. The radar echo signal refers to the echo signal generated by the roadbed after the radar signal is transmitted to the roadbed by the radar test system. Since the radar echo signals generated by different contamination conditions are different, the roadbed contamination rate can be calculated through the radar echo signal, and the roadbed contamination rate can be used to reflect the roadbed contamination status.

[0062] Specifically, the above step S101 is used to determine the roadbed contamination rate of the target mileage. Although the roadbed contamination rate can accurately evaluate the contamination status of the roadbed, if the target mileage has undergone major repairs, screening, ballast replenishment, ballast replacement and other operations, or the roadbed contamination rate evaluation result takes a long time, it is necessary to re-judge the contamination status of the target mileage, and the above steps S102 to S104 can be executed during the re-judgment.

[0063] The representative value of the dirtiness rate is selected from the dirtiness rate of the roadbed. The dirtiness rate of the roadbed corresponds to the target mileage. The target mileage is composed of multiple position points. The selected representative value of the dirtiness rate can be used to represent the dirtiness rate of the roadbed. It can be understood as: the dirtiness rate of the roadbed of the entire target mileage is represented by the representative value of the dirtiness rate corresponding to one or several position points in the target mileage.

[0064] According to the representative value of the dirtiness rate, its corresponding estimated dirtiness rate interval can be calculated. Assuming that the representative value of the dirtiness rate is A, the estimated dirtiness rate interval corresponding to A is calculated to be {M, N}. Considering that there may be errors in the calculation of the dirtiness rate of the roadbed, it is necessary to calculate the estimated dirtiness rate interval corresponding to the representative value of the dirtiness rate. Because the roadbed dirtiness rate corresponds to the target mileage, each position point on the target mileage corresponds to a value of the roadbed dirtiness rate. Assuming that the representative value of the dirtiness rate A selected from the roadbed dirtiness rate corresponds to the position point B in the target mileage, B can be identified as the representative value position point, and the actual dirtiness rate C corresponding to the representative value position point can be further determined, where the roadbed with the actual dirtiness rate of the target mileage corresponds to the dirtiness rate value of the actual representative value position point. If C belongs to the interval {M, N}, it means that the roadbed dirtiness rate is correct. The roadbed dirtiness rate of the target mileage is output to evaluate the dirtiness of the roadbed. If C does not belong to the interval {M, N}, it means that the roadbed dirtiness rate is incorrect and needs to be updated. The roadbed dirtiness rate of the updated target mileage is output to evaluate the dirtiness of the roadbed. The method in this paper improves the efficiency of roadbed dirtiness evaluation and reduces the waste of manpower and material costs.

[0065] Reference Figure 2 In the embodiment of this article, the step of determining the roadbed contamination rate corresponding to the roadbed of the target mileage according to the radar echo signal corresponding to the roadbed of the target mileage further includes:

[0066] S201: determining a characterization value sequence of a contamination state of the roadbed according to a radar echo signal corresponding to the roadbed of the target mileage;

[0067] S202: Determine, according to the characterization value sequence, a selected characterization value corresponding to the target mileage, wherein the selected characterization value is used to represent the characterization value sequence of the target mileage;

[0068] S203: Determine a selected position point corresponding to the selected characterization value in the target mileage, and an actual dirtiness rate corresponding to the selected position point;

[0069] S204: Associating the selected characterization value corresponding to the selected position point with the actual contamination rate to obtain a contamination model of the ballast bed;

[0070] S205: Determine the roadbed contamination rate corresponding to the roadbed of the target mileage according to the characterization value sequence of the roadbed contamination state and the roadbed contamination model.

[0071] According to the radar echo signal, the characterization value sequence of the roadbed contamination state can be determined, and then the contamination condition of the roadbed can be characterized by the characterization value sequence.

[0072] It should be noted that the characterization value sequence here only characterizes the changes in the roadbed contamination state in the target mileage. For example, at points A and B in the target mileage, the radar echo signal at point A is stronger than that at point B, and the roadbed contamination rate at point A is also higher than that at point B. That is, the characterization value sequence obtained from the radar echo signal can only relatively reflect the roadbed contamination state in the target mileage, but cannot absolutely determine the roadbed contamination rate.

[0073] Therefore, we can further select some representative selected characterization values ​​from the characterization value sequence, and determine the actual contamination rate of the selected characterization value at the selected position point in the target mileage. After associating the actual contamination rate with the selected characterization value, we can get the roadbed contamination model. Substituting the characterization value sequence into the roadbed contamination model, we can determine the roadbed contamination rate corresponding to the roadbed of the target mileage. The contamination rate means the proportion of the mass of dirty particles to the total mass. The total mass is the sum of the mass of dirty particles and the mass of non-dirty particles. The higher the roadbed contamination rate, the more serious the contamination of the roadbed. Therefore, we can determine the roadbed contamination state with high accuracy, and improve the decision-making accuracy during roadbed maintenance.

[0074] In the embodiment of this article, the step of obtaining the radar echo signal corresponding to the roadbed of the target mileage further includes:

[0075] The roadbed of the target mileage is sampled through the radar test system to obtain the radar echo signal corresponding to each position point in the target mileage;

[0076] Specifically, the radar test system includes a main control unit, a distance encoder and a radar antenna; wherein the main control unit is connected to the radar antenna, the main control unit sends a transmission instruction to the radar antenna and receives a radar echo signal sent by the radar antenna, and the radar antenna transmits a radar signal after receiving the transmission instruction, receives a radar echo signal, and sends the radar echo signal to the main control unit. In the embodiment of this article, the radar test system is pushed forward along the target mileage during the process of sampling the target mileage, and the radar test system collects once every time the distance encoder rotates a certain distance, and the distance encoder rotates multiple times along the target mileage, and the radar test system collects radar echo signals at multiple positions on the target mileage.

[0077] Furthermore, in order to more accurately determine the contamination of the roadbed, it is necessary to ensure 1. Environmental conditions: To minimize the impact of water content on the sampling results, the last rainfall should be at least 10 days away from the sampling day. 2. Line conditions: To ensure the consistency of the source of roadbed contamination, the lines to be tested should have the same type of cargo and relatively similar environmental conditions (rainfall, wind and sand, subgrade, etc.); double-track railways should include up and down lines, and the overall target mileage should not be less than 10km; the target mileage should include line structures such as bridges, culverts, and tunnels.

[0078] Reference Figure 3 The radar test system is installed on a connecting fixture that can move along the target mileage, keeping the radar antenna at the end of the pillow outside the rail, such as Figure 3 You can choose any one of the two antenna positions shown in the figure, so that the distance between the bottom of the radar antenna and the top of the rail is the set distance, and ensure that the antenna is within the railway vehicle limit when the connecting tooling is moved. The set distance can be set according to the actual working conditions and can be 190mm. The railway vehicle limit refers to the outline dimension line that cannot be crossed between buildings, equipment and locomotives and vehicles on the line to ensure transportation safety.

[0079] Reference Figure 4 The step of determining the characterization value sequence of the roadbed contamination state according to the radar echo signal corresponding to the roadbed of the target mileage further includes:

[0080] S301: determining a signal time domain scanning area of ​​the radar echo signal at a set ballast depth at each position point according to the radar echo signal corresponding to each position point in the target mileage;

[0081] S302: taking the signal time domain scanning area of ​​the radar echo signal at the ballast depth at each position point as the corresponding characterization value at the position point;

[0082] S303: Integrate the representation values ​​corresponding to all the position points in the target mileage to obtain a representation value sequence corresponding to the target mileage.

[0083] Reference Figure 5 Specifically, in the embodiment of this article, the step of determining the signal time domain scanning area of ​​the radar echo signal at each position point to set the ballast depth at each position point according to the radar echo signal corresponding to each position point in the target mileage further includes:

[0084] S401: determining, according to the radar echo signal corresponding to each position point in the target mileage, a sampling point sequence for setting the ballast depth of the radar echo signal at each position point, and a time difference between two adjacent sampling points in the sampling point sequence;

[0085] S402: Calculating a signal time domain scanning area of ​​each sampling point according to the radar echo signal amplitude corresponding to each sampling point in the sampling point sequence and the time difference;

[0086] S403: Integrate the signal time domain scanning area of ​​each sampling point in the sampling point sequence to obtain the signal time domain scanning area of ​​the set track bed depth at the position point corresponding to the sampling point sequence.

[0087] Reference Figure 6 After collecting the radar echo signals corresponding to each position point in the target mileage, these radar echo signals form a matrix of n rows and m columns, where n is the number of sampling points of the radar test system, and the value of n is generally 512 or 1024, such as Figure 6 The value of n is shown as 512; m is the number of acquisition tracks, the distance between adjacent acquisition tracks is Δd, generally speaking, the value range of Δd is 5 to 20 cm, and mΔd is the target mileage. It can be understood that: for the target mileage, a radar signal is emitted once at each position point and the radar echo signal of the position point is collected. By rotating the distance encoder, a radar signal is emitted once at the next position point and the radar echo signal of the position point is collected, where the distance between two adjacent position points is Δd, and each position point corresponds to a collection track. There are m collection tracks in the entire target mileage. For a certain position point, a radar signal is emitted at the position point through a radar antenna. The radar signal goes through: air-sleeper-inside the ballast bed, and the radar echo signal is generated after being reflected by the gravel inside the ballast bed. The radar echo signal goes through: inside the ballast bed-sleeper-air, and then is received by the radar antenna. The radar echo signal received in the time window is divided according to the number of sampling points to obtain the radar echo signal along the depth direction of the roadbed at the position point, where a certain sampling point represents a certain depth at the position point. The time window is generally 15 to 25ns. After the radar signal is transmitted, the radar echo signal is received, and a total of 15 to 25ns of radar echo signals are received.

[0088] According to the actual working conditions, it is only necessary to determine the radar echo signal corresponding to the set track bed depth in the track bed depth. For example, it is only necessary to collect the echo signal segment within 30 cm below the bottom surface of the sleeper. It is necessary to determine the echo signal segment of the set track bed depth in the received radar echo signal, that is, the sampling point data within 30 cm.

[0089] The specific method is: comprehensively consider the distance between the radar antenna and the sleeper (the signal propagates in the air) a , sleeper thickness l s 、Propagation distance in the track bed l b = 30 cm, as well as the radar transmission frequency and the propagation speed v in the air, sleepers and ballast bed a 、v s 、v b . Reference Figure 6 As shown in the figure, the radar sampling point sequence corresponding to the set track bed depth is s t ~s b :

[0090]

[0091]

[0092] △t is the time difference between two adjacent sampling points, △t = T / [2×(n-1)], where n is the number of sampling points. n sampling points divide the radar echo signal into n-1 segments, and T is the time window. Since the time window T corresponds to the time from transmitting the radar signal to receiving the radar echo signal, it is the round-trip time of the signal. T needs to be divided by 2 to obtain the propagation time of the radar echo signal, and then a sampling point sequence consisting of a series of sampling points corresponding to the set roadbed depth is obtained.

[0093] The signal time domain scanning area of ​​a certain sampling point in the sampling point sequence is the area enclosed by the radar echo signal of the sampling point and the time axis. Specifically, the time can be used as the horizontal coordinate and the signal amplitude as the vertical coordinate. The radar echo signal amplitude of the sampling point is multiplied by the time difference to obtain the signal time domain scanning area of ​​the sampling point. The signal time domain scanning area of ​​each sampling point in the sampling point sequence is integrated to obtain the signal time domain scanning area of ​​the set track bed depth at the corresponding position point. This paper integrates the signal time domain scanning areas of multiple sampling points, and uses the sum of the areas enclosed by the radar echo signals of all sampling points in the sampling point sequence at each position point and the time axis to approximate the signal time domain scanning area of ​​the set track bed depth at the position point, so that the calculation accuracy is higher. The signal time domain scanning area at a certain position point is used as the corresponding characterization value at the position point, and the corresponding characterization values ​​of all position points in the target mileage are integrated to obtain the characterization value sequence corresponding to the target mileage.

[0094] Reference Figure 7 After obtaining the characterization value sequence corresponding to the target mileage, the characterization value sequence can also be calibrated. Specifically:

[0095] S501: Acquire the detection value of the standard antenna and the detection value of the antenna to be calibrated in the same environment;

[0096] S502: Obtaining a calibration coefficient according to the detection value of the standard antenna and the detection value of the antenna to be calibrated;

[0097] S503: Calibrate the characterization value sequence of the antenna to be calibrated using the calibration coefficient.

[0098] Among them, the standard antenna is an antenna whose performance and indicators all meet the standards. Specifically, the standard antenna can be selected according to the selection standard of "Highway Section Flaw Detection and Structural Layer Thickness Ground Penetrating Radar" JJG (Traffic) 124-2015.

[0099] The detection value of the standard antenna is: the peak-to-valley difference of the echo signal or the time-domain scanning area of ​​the echo signal obtained after the standard antenna transmits the radar signal;

[0100] The detection value of the antenna to be calibrated is: the peak-to-valley difference of the echo signal or the time-domain scanning area of ​​the echo signal obtained after the antenna to be calibrated transmits the radar signal.

[0101] The detection value refers to the peak-to-valley difference of the echo signal or the time-domain scanning area of ​​the echo signal obtained after the radar antenna transmits the radar signal. The specific time-domain scanning area of ​​the echo signal can be calculated and solved by referring to the signal time-domain scanning area of ​​the sampling point mentioned above. The peak-to-valley difference of the echo signal is the difference between the peak and the trough of the echo signal.

[0102] Under the same environment, the peak-to-valley difference of the echo signal of a certain metal plate is detected by the standard antenna and the antenna to be calibrated respectively, and the detection value of the standard antenna and the detection value of the antenna to be calibrated are obtained. Alternatively, under the same environment, the time domain scanning area of ​​the echo signal of a certain standard ballast model is detected by the standard antenna and the antenna to be calibrated respectively, and the detection value of the standard antenna and the detection value of the antenna to be calibrated are obtained.

[0103] The obtaining of the detection value of the standard antenna and the detection value of the antenna to be calibrated under the same environment further includes:

[0104] Under the same environment, the standard antenna and the antenna to be calibrated are respectively tested by a first test device to obtain a peak-to-valley difference value of an echo signal of the standard antenna and a peak-to-valley difference value of an echo signal of the antenna to be calibrated;

[0105] Alternatively, the standard antenna and the antenna to be calibrated are tested respectively by a second test device under the same environment to obtain the time domain scanning area of ​​the echo signal of the standard antenna and the time domain scanning area of ​​the echo signal of the antenna to be calibrated.

[0106] Reference Fig.21 Specifically, the first test equipment includes two first brackets 1, a metal plate 2, a first connecting rod 3, a first antenna 4, a first connecting member 5, a first distance encoder (not shown in the figure) and a first main control unit (not shown in the figure).

[0107] The metal plate 2 is placed between the two first brackets 1 and laid flat on the hard and flat ground. The two ends of the first connecting rod 3 are respectively connected to the two first brackets 1. The first antenna 4 is set on the first connecting rod 3 through the first connecting member 5, so that the center of the first antenna 4 and the center of the metal plate 2 are kept horizontally without deviation, and a first set distance is maintained between the first antenna 4 and the metal plate 2; wherein the first connecting member 5 can be a connecting rod, a connecting block or other structures with a connecting function. The first set distance is set according to the actual working conditions. In this article, the first set distance can be 300mm.

[0108] The first antenna 4 is used to receive the instruction of the first main control unit to transmit the radar signal, and after receiving the echo signal, send the echo signal to the first main control unit.

[0109] The first antenna 4 is a standard antenna or an antenna to be calibrated. The environment for testing the standard antenna or the antenna to be calibrated is the same, including the same connection method of the cable between the first antenna 4 and the first main control unit. The cable is kept flat and must not be knotted or coiled.

[0110] When conducting the test, the following settings need to be set: sampling point 512, time window 15ns, channel spacing 5cm, pulse frequency 800k, distance trigger, no gain, and the test system is preheated for 5min. Turn the first distance encoder to continuously receive multiple echo signals.

[0111] Specifically, after the transmitting end of the first antenna 4 transmits a radar signal, the receiving end receives the echo signal within 15ns reflected by the metal plate 2, divides the echo signal, and obtains the echo signal values ​​corresponding to the 512 sampling points. Then the first distance encoder can be rotated 5cm. It should be noted that in the embodiment of this article, the first distance encoder is rotated but the actual first antenna 4 does not move and remains in the initial position. Then the radar signal is transmitted again, and the above steps are repeated multiple times to obtain multiple echo signals.

[0112] Reference Fig. 22 The second test equipment includes two second brackets 6, a standard ballast model box 7, a second connecting rod 8, a second antenna 9, a second connecting member 10, a second distance encoder (not shown in the figure) and a second main control unit (not shown in the figure).

[0113] The standard ballast model box 7 is placed between the two second brackets 6. The length and width of the standard ballast model box 7 are not less than twice the corresponding size of the second antenna 9. The ballast thickness is not less than 100 cm. The box body shall not be made of metal material. The ballast model box should be kept in a dry and vibration-free environment for a long time. The two ends of the second connecting rod 8 are respectively connected to the two second brackets 6. The second antenna 9 is set on the second connecting rod 8 through the second connecting member 10 to keep the center of the second antenna 9 and the center of the metal plate 2 horizontally without deviation. The second antenna 9 and the standard ballast model box 7 are maintained at a second set distance; wherein the second connecting member 10 can be a connecting rod, a connecting block or other structures with a connecting function. The second set distance is set according to the actual working conditions. In this article, the second set distance can be 300 mm.

[0114] The second antenna 9 is used to receive the instruction of the second main control unit to transmit the radar signal, and receive the echo signal and send it to the second main control unit.

[0115] The second antenna 9 is a standard antenna or an antenna to be calibrated. The environment for testing the standard antenna or the antenna to be calibrated is the same, including the same connection method of the cable between the second antenna 9 and the second main control unit. The cable is kept flat and must not be knotted or coiled.

[0116] When conducting the test, the following settings need to be set: sampling point 512, time window 15ns, channel spacing 5cm, pulse frequency 800k, distance trigger, no gain, and the test system is preheated for 5min. Turn the second distance encoder to continuously receive multiple echo signals.

[0117] The obtaining of the calibration coefficient according to the detection value of the standard antenna and the detection value of the antenna to be calibrated further comprises:

[0118] Obtaining a first calibration coefficient according to a correlation between a peak-to-valley difference value of an echo signal of the standard antenna and a peak-to-valley difference value of an echo signal of the antenna to be calibrated;

[0119] Or, the second calibration coefficient is obtained according to the correlation between the time-domain scanning area of ​​the echo signal of the standard antenna and the time-domain scanning area of ​​the echo signal of the antenna to be calibrated.

[0120] The first calibration coefficient is calculated by the following formula:

[0121]

[0122] in, is the first calibration coefficient, V R0 is the peak-to-valley difference of the echo signal of the standard antenna, V R is the peak-to-valley difference of the echo signal of the antenna to be calibrated.

[0123] The second calibration coefficient is calculated by the following formula:

[0124] μ = StAb0 / StAb;

[0125] Wherein, μ is the second calibration coefficient, StAb0 is the time domain scanning area of ​​the echo signal of the standard antenna, and StAb is the time domain scanning area of ​​the echo signal of the antenna to be calibrated.

[0126] The calibrating the characterization value sequence of the antenna to be calibrated by using the calibration coefficient further includes:

[0127] The calibration coefficient is multiplied by the characterization value sequence of the antenna to be calibrated to obtain a calibrated characterization value sequence.

[0128] The calibration coefficient is obtained by dividing the detection value of the standard antenna by the detection value of the calibration antenna. The calibrated characterization value sequence can be obtained by multiplying the characterization value sequence by the calibration coefficient. The calibrated characterization value sequence has higher accuracy.

[0129] Reference Figure 8 In the embodiment of this invention, the selected characterization value corresponding to the target mileage is determined according to the characterization value sequence, wherein the selected characterization value is used to represent the characterization value sequence of the target mileage further includes:

[0130] S601: sorting the characterization value sequence from small to large and dividing it into multiple levels of characterization intervals;

[0131] S602: Selecting a plurality of selected characterization values ​​from each level of the multi-level characterization interval to obtain a selected characterization value corresponding to the target mileage.

[0132] Accordingly, determining the selected position point of the selected characterization value in the target mileage and the actual dirtiness rate corresponding to the selected position point further includes:

[0133] Determine a selected position point in the target mileage for each selected characterization value in each level of the multi-level characterization interval, and an actual dirtiness rate corresponding to the selected position point.

[0134] Specifically, to ensure that the selected characterization value is representative, the multi-level characterization interval is at least a three-level characterization interval.

[0135] Reference Fig. 9 In addition to the above-mentioned multi-level division method, in the embodiment of this article, the step of sorting the characterization value sequence from small to large and then dividing it into multi-level characterization intervals further includes:

[0136] S701: Determine the interval length according to the characterization value sequence and the number of levels of the multi-level characterization interval;

[0137] S702: Divide the representation values ​​in the representation value sequence into intervals of equal length from small to large to obtain multi-level representation intervals.

[0138] Specifically, if it is a three-level characterization interval, its level is three, and if it is a five-level characterization interval, its level is five. The total number of characterization values ​​in the characterization value sequence is divided by the level, and the quotient obtained is the interval length. The meaning of the interval length is the number of characterization values ​​included in any first-level characterization interval. After sorting the characterization values ​​in the characterization value sequence from small to large, multiple levels of characterization intervals are taken from small to large, and the number of characterization values ​​in any first-level characterization interval is the interval length. Of course, it should be noted that since the total number of characterization values ​​may not be divided evenly when divided by the level, and this article only uses the quotient as the interval length, it is very likely that there is a part of the characterization values ​​that are sorted later and the number is less than the interval length and cannot form one of the first-level characterization intervals. For the above situation, this article can use the size of the number of this part of the characterization values ​​to determine whether to determine this part of the characterization values ​​as one of the first-level characterization intervals. If the number of this part of the characterization values ​​is greater than the set length, then the part of the characterization values ​​is determined as one of the first-level characterization intervals, and vice versa. The set length here can be determined according to the actual situation, for example, it can be half of the interval length.

[0139] Reference Fig.10 In the embodiment of this article, the selecting of a plurality of selected characterization values ​​from each level of the multi-level characterization interval to obtain the selected characterization value corresponding to the target mileage further includes:

[0140] S801: Selecting a first selected characterization value from each level of the multi-level characterization interval;

[0141] S802: Determine the characterization value corresponding to the position point adjacent to the first selected characterization value as the second selected characterization value, and determine the first selected characterization value and the second selected characterization value as the selected characterization values ​​corresponding to the characterization interval of this level.

[0142] Reference Fig.11 , taking the three-level representation interval as an example, specifically, each representation value in the representation value sequence of the target mileage has its corresponding level, and a first selected representation value is randomly selected from each level, such as Fig.11 The circled position points shown are the first selected characterization values ​​corresponding to the first level, the second level and the third level respectively; then the characterization value corresponding to the position point adjacent to the first characterization value is determined as the second selected characterization value. It should be noted that the above-mentioned adjacent position points do not only refer to the adjacent ones. The position points within a set number before and after the first selected characterization value can be centered on the first selected characterization value as the adjacent position points of the first selected characterization value. For example, the 20 position points before and after the first selected characterization value are all adjacent position points of the first selected characterization value, and the second selected characterization value is selected from these 40 position points before and after.

[0143] The specific second selected characterization value may be one or more. In order to improve the accuracy of the calculation and ensure the efficiency of the calculation, two second selected characterization values ​​may be selected. The two second selected characterization values ​​may be selected one before and one after the first selected characterization value, which is more representative. Each level has one first selected characterization value and two second selected characterization values, and there are three levels and nine selected characterization values ​​in total.

[0144] On this basis, in order to avoid the abnormal situation of sudden increase or decrease of the characterization value, when randomly selecting a first selected characterization value in each level, the sudden increase or decrease value happens to be selected, resulting in inaccurate final calculation results, refer to Fig.12 , a first selected characterization value can be selected in each level by the following method:

[0145] S901: Selecting a continuous representation value segment within a certain level of representation interval in the representation value sequence;

[0146] S902: Randomly select a first selected characterization value from the characterization value segment.

[0147] Taking the first-level characterization interval as an example, in the characterization value sequence, being continuously in the first-level characterization interval means that multiple consecutive characterization values ​​in the characterization value sequence belong to the first level. The specific number of consecutive characterization values ​​can be determined according to the actual working conditions. If multiple consecutive characterization values ​​belong to the first level, it means that the characterization value segment does not contain a sudden increase or decrease value, and a first selected characterization value can be randomly selected from the characterization value segment. If there are multiple characterization value segments in the first-level characterization interval, any one of the characterization value segments can be randomly selected, so that the final calculation result can be guaranteed to be more accurate.

[0148] In the embodiment of this article, taking the three-level representation interval as an example, the selected representation value corresponding to the target mileage is obtained by selecting multiple selected representation values ​​from each level of the three-level representation interval. It can also be: randomly selecting multiple selected representation values ​​from each level. In order to ensure the calculation efficiency while taking into account the calculation accuracy, three selected representation values ​​can be selected at each level, and there are a total of nine selected representation values ​​in three levels.

[0149] Reference Fig.13 In the embodiment of this article, associating the selected characterization value corresponding to the selected position point with the actual contamination rate to obtain the roadbed contamination model further includes:

[0150] S1001: Establishing a functional relationship between the actual dirtiness rate and the characterization value sequence;

[0151] S1002: Substituting the actual contamination rate corresponding to the selected position point and the selected characterization value into the functional relationship to obtain a contamination model of the ballast bed.

[0152] Taking the three-level representation interval as an example, after establishing the functional relationship between the actual dirtiness rate and the representation value sequence, it is necessary to further determine the actual dirtiness rate corresponding to the selected representation value at the selected location point. Specifically, there are three levels and nine selected representation values. According to the selected location point of each selected representation value in the target mileage, the selected location point is sampled: refer to Fig.14 First, a sampling hole is dug at the selected location. The depth of the sampling hole is the set ballast depth, for example, 30 cm. When digging the sampling hole, a temporary steel chisel should be used to protect it to prevent the ballast from collapsing. Then, the wet weight of the n samples dug is weighed, and then the dry weight M of the samples is weighed after drying. t . Finally, screening is performed to obtain the mass M of dirty particles below the specified particle size distribution in each sample, where the specified particle size distribution is the apparent diameter of the sample particles, which can be 25mm, 16mm, 10mm, 5mm, or 0.075mm according to the working conditions. In the ballast gravel, particles below the specified particle size distribution are identified as dirty particles, so the above-mentioned sampling and screening work is required. Calculate the actual dirtiness rate FI(i) of the i-th excavation test point (for n excavation test points, 1≤i≤n).

[0153]

[0154] The functional relationship between the actual dirtiness rate and the characterization value sequence is established as follows:

[0155] FI = k × StAb2 + b;

[0156] Where FI is the actual dirtiness rate, StAb2 is the characterization value sequence, b is the constant term of the function; k is the function coefficient, which is also the slope of the function.

[0157] Both k and b are calculated using the least squares method. For data with n samples, the calculation formula is as follows:

[0158]

[0159]

[0160] Among them, FI(i) is the actual dirtiness rate of the i-th selected position point, StAb2(i) is the selected characterization value of the i-th selected position point, and n is the number of selected position points.

[0161] After calculating the values ​​of k and b, substituting the values ​​of k and b into the above functional relationship, the functional relationship between the actual fouling rate and the characterization value sequence, that is, the ballast bed fouling model, can be obtained.

[0162] For the track bed contamination model, each characterization value in the characterization value sequence StAb2 has a corresponding actual contamination rate, that is, there is a corresponding actual contamination rate at each position point in the target mileage, so the actual contamination rate of the track bed of the target mileage can be obtained with high accuracy, which helps to improve the decision-making accuracy during track bed maintenance.

[0163] Reference Fig.15 In the embodiment of this article, the selecting of a representative value of the dirtiness rate from the dirtiness rate of the roadbed, and calculating the estimated dirtiness rate interval corresponding to the representative value of the dirtiness rate according to the representative value of the dirtiness rate further comprises:

[0164] S1101: sorting the roadbed contamination rates of all position points corresponding to the roadbed of the target mileage from small to large and dividing them into multiple levels of contamination intervals;

[0165] S1102: Select a dirtiness rate representative value from each level of the multi-level dirtiness intervals, and calculate an estimated dirtiness rate interval corresponding to each dirtiness rate representative value according to the dirtiness rate representative value.

[0166] Specifically, the multi-level dirty interval is at least a three-level dirty interval, and the number of levels of the multi-level dirty interval is equal to the number of levels of the multi-level characterization interval. The method for dividing the multi-level dirty interval can be divided by referring to the method for dividing the multi-level characterization interval described in steps S701-S702. Taking the three-level dirty interval as an example, the roadbed dirtiness rate of all position points of the target mileage is sorted from small to large and then divided into three levels. From small to large, the first 1 / 3 of the roadbed dirtiness rate is divided into the first level, the middle 1 / 3 of the roadbed dirtiness rate is divided into the second level, and the last 1 / 3 of the roadbed dirtiness rate is divided into the multi-level. In this way, the roadbed dirtiness rate of each position point has its corresponding level. These three levels divide the roadbed dirtiness rate into three-level dirty intervals, and each level of dirty interval has a corresponding 1 / 3 of the roadbed dirtiness rate. A representative value of the dirtiness rate is selected from each level of dirtiness interval. The representative value of the dirtiness rate can represent the dirtiness rate of the roadbed at all positions in the first-level dirtiness interval to which it belongs. The three representative values ​​of the dirtiness rate can represent the dirtiness rate of the roadbed of the target mileage.

[0167] In S1102, according to each of the representative values ​​of the soiling rate, the estimated soiling rate interval corresponding to the representative value of the soiling rate is calculated under the condition of significance level α (as the preferred value range of α: 0.05≤α≤0.1), and the confidence interval {FI1,FI2} of the representative value of the soiling rate FI(new_h) is calculated, and the confidence interval is determined as the estimated soiling rate interval corresponding to the representative value of the soiling rate. The confidence interval {FI1,FI2} is calculated by the following formula:

[0168]

[0169] Among them, σ 2is the variance of the random error term, StAb2(i) is the selected characterization value of the i-th selected position point; FI(new_h) is the representative value of the dirtiness rate; n is the number of selected position points; FI(i) is the actual dirtiness rate of the i-th selected position point; α is the significance level, 0.05≤α≤0.1, t represents t distribution, t distribution is used for confidence interval estimation and significance test, t α / 2 It represents the critical value under the t distribution with a significance level of α.

[0170] In this article, the three representative values ​​of dirtiness rate correspond to each other and there are estimated dirtiness rate ranges.

[0171] In the embodiment of this article, the determining whether the actual dirtiness rate belongs to the estimated dirtiness rate interval further includes:

[0172] It is determined whether the actual dirtiness rate of each of the representative value position points belongs to the estimated dirtiness rate interval corresponding to the corresponding dirtiness rate representative value.

[0173] The specific method for calculating the actual dirtiness rate can be as shown above, by taking samples and weighing them, and after calculating the actual dirtiness rate of each representative value position point, it is determined whether each actual dirtiness rate belongs to the corresponding estimated dirtiness rate range.

[0174] If the judgment results are all yes, it is proved that the roadbed contamination rate of the target mileage is correct, and the roadbed contamination rate corresponding to the roadbed of the target mileage is output;

[0175] If a judgment result is no, it proves that the roadbed contamination rate of the target mileage is incorrect. It is necessary to update the roadbed contamination rate corresponding to the roadbed of the target mileage according to the representative value position point and the actual contamination rate corresponding thereto, and output the updated roadbed contamination rate corresponding to the roadbed of the target mileage.

[0176] Reference Fig.16 In the embodiment of this article, the updating of the roadbed contamination rate corresponding to the roadbed of the target mileage according to the representative value position point and the actual contamination rate corresponding thereto further includes:

[0177] S1201: Determine, according to the characterization value sequence, a dirtiness rate characterization value corresponding to each representative value position point in each level of the multi-level dirtiness interval;

[0178] S1202: The dirtiness rate representation value and the actual dirtiness rate corresponding to each representative value position point in each level of the multi-level dirtiness interval are updated to replace the selected representation value and the actual dirtiness rate corresponding to a selected position point in the corresponding level of the multi-level representation interval, to obtain the selected representation value and the actual dirtiness rate corresponding to the updated selected position point;

[0179] S1203: Associating the selected characterization value corresponding to the updated selected position point with the actual contamination rate to obtain an updated roadbed contamination model;

[0180] S1204: updating the roadbed contamination rate corresponding to the roadbed of the target mileage according to the characterization value sequence of the roadbed contamination state and the updated roadbed contamination model.

[0181] In this article, it is necessary to distinguish that: as the position points in the target mileage change, the roadbed contamination rates corresponding to different position points are different, the representative value of the contamination rate is selected from the roadbed contamination rate to represent the roadbed contamination rate, and the position point of the representative value of the contamination rate in the target mileage is the representative value position point. As the position points in the target mileage change, different position points have different corresponding representation values ​​in the representation value sequence, and the corresponding representation values ​​at the representative value position points in the representation value sequence are different, and the representation value corresponding to the representative value position point is the contamination rate representation value.

[0182] Since the representative value of the dirtiness rate in each level of the multi-level dirtiness interval has been determined, the representative value position point corresponding to the representative value of the dirtiness rate in each level can be further determined. Based on the representative value position point in each level, the dirtiness rate representation value corresponding to the representative value position point in the representation value sequence can be determined, and the roadbed at the representative value position point can be excavated and sampled and then weighed and calculated to obtain the actual dirtiness rate of the representative value position point.

[0183] When calculating the roadbed contamination rate, the roadbed contamination model is established through the functional relationship between the actual contamination rate and the characterization value sequence. Therefore, when updating the roadbed contamination rate, the roadbed contamination model needs to be updated first. The original roadbed contamination model is obtained by substituting the selected characterization value and the actual contamination rate corresponding to the selected position point into the functional relationship. In order to update the roadbed contamination model, the selected characterization value and the actual contamination rate corresponding to the selected position point need to be updated.

[0184] Specifically, taking the three-level characterization interval and the three-level dirtiness interval as examples, there are multiple selected characterization values ​​at each level of the three-level characterization interval, and each selected characterization value has a selected position point and an actual dirtiness rate at the selected position point. The dirtiness rate characterization value and the actual dirtiness rate corresponding to the representative value position point of the first level in the three-level dirtiness interval can be updated to replace the selected characterization value and the actual dirtiness rate corresponding to one of the selected position points of the first level in the three-level characterization interval, and the second and third levels are updated and replaced in the same way as the first level.

[0185] Further execute the above S1001 to S1002.

[0186] For example, the original selected position points include the first level: 1, 2, 3; the second level: 4, 5, 6; the third level: 7, 8, 9, and the representative value position point 10 replaces 3 in the first level, 11 replaces 6 in the second level, and 12 replaces 9 in the third level, and the updated selected position points are 1, 2, 3, 10, 4, 5, 11, 7, 8, 12. The values ​​of k and b in the functional relationship between the actual fouling rate and the characterization value sequence are calculated through the updated selected position points, and the updated roadbed fouling model is obtained.

[0187] Furthermore, by substituting the characterization value sequence of the roadbed contamination state into the updated roadbed contamination model, the roadbed contamination rate corresponding to the roadbed of the target mileage can be updated, and the roadbed contamination rate corresponding to the roadbed of the updated target mileage can be output.

[0188] Reference Fig.17 In the embodiment of the present invention, the step of updating and replacing the soiling rate characterization value and the actual soiling rate corresponding to each representative value position point in each level of the multi-level soiling interval with the selected characterization value and the actual soiling rate corresponding to a selected position point in the corresponding level of the multi-level characterization interval further includes:

[0189] S1301: Determine the selected date corresponding to all selected position points in each level of the multi-level representation interval, wherein the selected date is the date corresponding to when the selected representation value corresponding to the selected position point is selected from the representation value sequence, or the date when the selected representation value is updated and replaced by the soiling rate representation value;

[0190] S1302: The soil rate representation value and actual soil rate corresponding to each representative value position point in each level of the multi-level soil interval are updated and replaced with the selected representation value and actual soil rate corresponding to the selected position point with the earliest selected date in the corresponding level of the multi-level representation interval.

[0191] Since there are multiple selected position points in each level of the multi-level characterization interval, when updating and replacing the representative value position points of each level in the multi-level dirty interval, in addition to randomly replacing one of the multiple selected position points, it is better to make certain selections. The purpose is that the ballast bed has undergone major repairs, screening, ballast replenishment, ballast replacement and other operations, or the evaluation results of the ballast bed dirtiness rate lasted for a long time, and the position point with the largest change after the above process among the multiple selected position points is selected and replaced.

[0192] In the above steps, the selected date of each selected location point is recorded respectively. The selected date can be the date on which the actual soiling rate corresponding to the selected location point is obtained. The earlier the selected date, the more changes the selected location point has experienced. The selected representation value and the actual soiling rate corresponding to the location point are replaced, but there is also a situation where the selected dates of multiple selected location points in each level are the same.

[0193] Reference Fig.18 , at this time, further selection can be performed through the following steps: the soiling rate representation value and the actual soiling rate corresponding to each representative value position point in each level of the multi-level soiling interval are updated to replace the selected representation value and the actual soiling rate corresponding to a selected position point in the corresponding level of the multi-level representation interval, further comprising:

[0194] S1401: determining the detection contamination rate corresponding to each selected position point in each level of the multi-level characterization interval according to the contamination rate of the roadbed corresponding to the target mileage;

[0195] S1402: Calculate a deviation value of each selected position point according to the actual dirtiness rate and the detected dirtiness rate corresponding to each selected position point in each level of the multi-level characterization interval; wherein the deviation value is used to characterize the deviation of the actual dirtiness rate corresponding to the selected position point from the detected dirtiness rate;

[0196] S1403: The dirtiness rate representation value and the actual dirtiness rate corresponding to each representative value position point in each level of the multi-level dirtiness interval are updated and replaced with the selected representation value and the actual dirtiness rate corresponding to the selected position point with the largest deviation value in the corresponding level of the multi-level representation interval.

[0197] The calculation accuracy of the roadbed dirtiness rate at each selected location point is determined by calculating the deviation value of each selected location point. The deviation value is used to reflect whether the calculation result of the roadbed dirtiness rate at the selected location point is accurate. The roadbed dirtiness rate corresponding to each selected location point is determined as the detection dirtiness rate. The detection dirtiness rate is the roadbed dirtiness rate of the selected location point calculated by the quantitative evaluation method shown in this article. In order to more accurately measure the calculation result of the roadbed dirtiness rate at the selected location point, the deviation value of the selected location point is calculated by the actual dirtiness rate and the detection dirtiness rate of the selected location point. The deviation value can be: |XY| / X; where X is the detection dirtiness rate and Y is the actual dirtiness rate. The absolute value of the difference between the detection dirtiness rate and the actual dirtiness rate of the selected location point is divided by the detection dirtiness rate to obtain the deviation value of the selected location point. The larger the deviation value, the lower the calculation accuracy of the roadbed dirtiness rate at the selected location point, and it needs to be updated and replaced.

[0198] In practical applications, the selected date of the selected location point in S1301 to S1302 can be used to determine the replacement of a selected location point. If the selected dates are the same, the selected location point can be replaced by the deviation value in S1401 to S1403. Of course, the selected location point can also be directly replaced by the deviation value in S1401 to S1403, and the specific application method is not limited in this article.

[0199] Based on the above-mentioned quantitative evaluation method for the dirty state of the roadbed, the embodiments of this article also provide a quantitative evaluation device for the dirty state of the roadbed. The device may include a system (including a distributed system), software (application), module, component, server, client, etc. using the method described in the embodiments of this article and a device combined with necessary implementation hardware. Based on the same innovative concept, the device in one or more embodiments provided in the embodiments of this article is as described in the following embodiments. Since the implementation scheme and method of the device to solve the problem are similar, the implementation of the specific device in the embodiments of this article can refer to the implementation of the aforementioned method, and the repetitions will not be repeated. As used below, the term "unit" or "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0200] Specifically, Fig.19 This is a schematic diagram of the module structure of an embodiment of a quantitative evaluation device for the dirty state of a roadbed provided in an embodiment of this invention, referring to Fig.19 As shown, a quantitative evaluation device for the contamination state of a roadbed provided in an embodiment of the present invention includes: a roadbed contamination rate determination module 100, a calculation module 200, an actual contamination rate determination module 300, and a judgment module 400.

[0201] The roadbed contamination rate determination module 100 is used to determine the roadbed contamination rate corresponding to the roadbed of the target mileage according to the radar echo signal corresponding to the roadbed of the target mileage;

[0202] A calculation module 200, configured to select a representative value of the dirtiness rate from the dirtiness rate of the roadbed, and calculate an estimated dirtiness rate interval corresponding to the representative value of the dirtiness rate according to the representative value of the dirtiness rate;

[0203] The actual dirtiness rate determination module 300 is used to determine a representative value position point of the dirtiness rate representative value in the target mileage, and the actual dirtiness rate corresponding to the representative value position point;

[0204] A determination module 400 is used to determine whether the actual dirtiness rate falls within the estimated dirtiness rate range;

[0205] If yes, then output the roadbed contamination rate corresponding to the roadbed of the target mileage;

[0206] If not, the roadbed contamination rate corresponding to the roadbed of the target mileage is updated according to the representative value position point and the actual contamination rate corresponding thereto, and the updated roadbed contamination rate corresponding to the roadbed of the target mileage is output.

[0207] Reference Fig. 20As shown, based on the above-mentioned quantitative evaluation method for the dirty state of the track bed, a computer device 2002 is also provided in one embodiment of the present invention, wherein the above-mentioned method is run on the computer device 2002. The computer device 2002 may include one or more processors 2004, such as one or more central processing units (CPUs) or graphics processing units (GPUs), and each processing unit may implement one or more hardware threads. The computer device 2002 may also include any memory 2006, which is used to store any kind of information such as code, settings, data, etc. In a specific embodiment, the computer program on the memory 2006 and which can be run on the processor 2004, when the computer program is run by the processor 2004, can execute instructions according to the above-mentioned method. Non-limitingly, for example, the memory 2006 may include any one or more combinations of the following: any type of RAM, any type of ROM, flash memory device, hard disk, optical disk, etc. More generally, any memory may use any technology to store information. Further, any memory may provide volatile or non-volatile retention of information. Further, any memory may represent a fixed or removable component of the computer device 2002. In one embodiment, when the processor 2004 executes the associated instructions stored in any memory or combination of memories, the computer device 2002 can perform any operation of the associated instructions. The computer device 2002 also includes one or more drive mechanisms 2008 for interacting with any memory, such as a hard disk drive mechanism, an optical disk drive mechanism, etc.

[0208] Computer device 2002 may also include an input / output module 2010 (I / O) for receiving various inputs (via input device 2012) and for providing various outputs (via output device 2014). A specific output mechanism may include a rendering device 2016 and an associated graphical user interface 2018 (GUI). In other embodiments, input / output module 2010 (I / O), input device 2012, and output device 2014 may not be included, and only a computer device in a network may be used. Computer device 2002 may also include one or more network interfaces 2020 for exchanging data with other devices via one or more communication links 2022. One or more communication buses 2024 couple the components described above together.

[0209] The communication link 2022 may be implemented in any manner, for example, through a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. The communication link 2022 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc. governed by any protocol or combination of protocols.

[0210] Corresponds to Figure 1, Figure 2 , Figure 4 , Figure 5 , Figure 7 , Fig.10 , Fig.12 , Fig.13 , Figures 15 to 18 The method in this article also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are executed.

[0211] The embodiment of the present invention also provides a computer readable instruction, wherein when the processor executes the instruction, the program therein causes the processor to execute the following Figure 1 , Figure 2 , Figure 4 , Figure 5 , Figure 7 , Fig.10 , Fig.12 , Fig.13 , Figures 15 to 18 The method shown in .

[0212] It should be understood that in the various embodiments of this document, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this document.

[0213] It should also be understood that in the embodiments of this article, the term "and / or" is only a description of the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0214] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this article.

[0215] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0216] In the several embodiments provided herein, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or can be electrical, mechanical or other forms of connection.

[0217] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of this article.

[0218] In addition, each functional unit in each embodiment of this invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of software functional unit.

[0219] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this article is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of this article. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0220] Specific embodiments are used in this article to illustrate the principles and implementation methods of this article. The description of the above embodiments is only used to help understand the methods and core ideas of this article. At the same time, for general technicians in this field, according to the ideas of this article, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on this article.

Claims

1. A quantitative evaluation method for the contamination state of a roadbed, characterized in that: include: Determine a sequence of characterization values ​​of the dirty state of the roadbed according to the radar echo signal corresponding to the roadbed of the target mileage; Determine, according to the characterization value sequence, a selected characterization value corresponding to the target mileage, wherein the selected characterization value is used to represent the characterization value sequence of the target mileage, and the characterization value sequence is sorted from small to large and then divided into multiple levels of characterization intervals; Determining a selected location point corresponding to the selected characterization value in the target mileage, and an actual dirtiness rate corresponding to the selected location point; Associating the selected characterization value corresponding to the selected position point with the actual contamination rate to obtain a contamination model of the ballast bed; Determining the roadbed contamination rate corresponding to the roadbed of the target mileage according to the characterization value sequence of the roadbed contamination state and the roadbed contamination model; Selecting a representative value of the dirtiness rate from the dirtiness rate of the ballast, and calculating an estimated dirtiness rate interval corresponding to the representative value of the dirtiness rate according to the representative value of the dirtiness rate; Determine a representative value position point of the dirtiness rate representative value in the target mileage, and an actual dirtiness rate corresponding to the representative value position point; Determining whether the actual dirtiness rate of each of the representative value positions belongs to the estimated dirtiness rate interval corresponding to the corresponding dirtiness rate representative value; If yes, then output the roadbed contamination rate corresponding to the roadbed of the target mileage; If not, then Determine, according to the characterization value sequence, a dirtiness rate characterization value corresponding to each representative value position point in each level of the multi-level dirtiness interval; The dirtiness rate characterization value and the actual dirtiness rate corresponding to each representative value position point in each level of the multi-level dirtiness interval are updated to replace the selected characterization value and the actual dirtiness rate corresponding to a selected position point in the corresponding level of the multi-level characterization interval, to obtain the selected characterization value and the actual dirtiness rate corresponding to the updated selected position point; Associating the selected characterization value corresponding to the updated selected position point with the actual contamination rate to obtain an updated ballast contamination model; According to the characterization value sequence of the roadbed contamination state and the updated roadbed contamination model, the roadbed contamination rate corresponding to the roadbed of the target mileage is updated, and the updated roadbed contamination rate corresponding to the roadbed of the target mileage is output.

2. The quantitative evaluation method for the contamination state of the roadbed according to claim 1 is characterized in that: The selecting a representative value of the dirtiness rate from the dirtiness rate of the roadbed, and calculating the estimated dirtiness rate interval corresponding to the representative value of the dirtiness rate according to the representative value of the dirtiness rate further comprises: The roadbed contamination rates of all position points corresponding to the roadbed of the target mileage are sorted from small to large and then divided into multiple levels of contamination intervals; A soiling rate representative value is selected from each level of the multi-level soiling intervals, and based on each soiling rate representative value, an estimated soiling rate interval corresponding to the soiling rate representative value is calculated.

3. The quantitative evaluation method for the contamination state of the track bed according to claim 2 is characterized in that: The step of determining the selected characterizing value corresponding to the target mileage according to the characterizing value sequence, wherein the selected characterizing value is used to represent the characterizing value sequence of the target mileage further comprises: Sorting the characterization value sequence from small to large and dividing it into multiple levels of characterization intervals; Selecting a plurality of selected characterization values ​​from each level of the multi-level characterization interval to obtain a selected characterization value corresponding to the target mileage; The determining of the selected position point of the selected characterization value in the target mileage and the actual dirtiness rate corresponding to the selected position point further includes: Determine a selected position point in the target mileage for each selected characterization value in each level of the multi-level characterization interval, and an actual dirtiness rate corresponding to the selected position point.

4. The quantitative evaluation method for the contamination state of the roadbed according to claim 1 is characterized in that: The step of updating and replacing the soil rate characterization value and the actual soil rate corresponding to each representative value position point in each level of the multi-level soiling interval with the selected characterization value and the actual soil rate corresponding to a selected position point in the corresponding level of the multi-level characterization interval further comprises: Determine the selected date corresponding to all selected position points in each level of the multi-level characterization interval, wherein the selected date is the date corresponding to when the selected characterization value corresponding to the selected position point is selected from the characterization value sequence, or the date when the selected characterization value is updated and replaced by the dirtiness rate characterization value; The soil rate representation value and actual soil rate corresponding to each representative value position point in each level of the multi-level soil interval are updated to replace the selected representation value and actual soil rate corresponding to the selected position point with the earliest selected date in the corresponding level of the multi-level representation interval.

5. The quantitative evaluation method for the contamination state of the roadbed according to claim 1 is characterized in that: The step of updating and replacing the soil rate characterization value and the actual soil rate corresponding to each representative value position point in each level of the multi-level soiling interval with the selected characterization value and the actual soil rate corresponding to a selected position point in the corresponding level of the multi-level characterization interval further comprises: Determine the detection contamination rate corresponding to each selected position point in each level of the multi-level characterization interval according to the contamination rate of the roadbed corresponding to the target mileage; Calculate the deviation value of each selected position point according to the actual dirtiness rate and the detected dirtiness rate corresponding to each selected position point in each level of the multi-level characterization interval; wherein the deviation value is used to characterize the deviation of the actual dirtiness rate corresponding to the selected position point compared with the detected dirtiness rate; The dirtiness rate representation value and actual dirtiness rate corresponding to each representative value position point in each level of the multi-level dirtiness interval are updated to replace the selected representation value and actual dirtiness rate corresponding to the selected position point with the largest deviation value in the corresponding level of the multi-level representation interval.

6. A quantitative evaluation device for the dirty state of a roadbed, characterized in that: The device comprises: A module for determining the roadbed contamination rate is used to determine a sequence of characterization values ​​of the roadbed contamination state according to a radar echo signal corresponding to the roadbed of a target mileage; Determine, according to the characterization value sequence, a selected characterization value corresponding to the target mileage, wherein the selected characterization value is used to represent the characterization value sequence of the target mileage, and the characterization value sequence is sorted from small to large and then divided into multiple levels of characterization intervals; Determining a selected location point corresponding to the selected characterization value in the target mileage, and an actual dirtiness rate corresponding to the selected location point; Associating the selected characterization value corresponding to the selected position point with the actual contamination rate to obtain a contamination model of the ballast bed; Determining the roadbed contamination rate corresponding to the roadbed of the target mileage according to the characterization value sequence of the roadbed contamination state and the roadbed contamination model; A calculation module, used for selecting a representative value of the dirtiness rate from the dirtiness rate of the roadbed, and calculating an estimated dirtiness rate interval corresponding to the representative value of the dirtiness rate according to the representative value of the dirtiness rate; An actual dirtiness rate determination module, used to determine a representative value position point of the dirtiness rate representative value in the target mileage, and an actual dirtiness rate corresponding to the representative value position point; A judgment module, used to judge whether the actual dirtiness rate of each representative value position point belongs to the estimated dirtiness rate interval corresponding to the corresponding dirtiness rate representative value; If yes, then output the roadbed contamination rate corresponding to the roadbed of the target mileage; If not, then Determine, according to the characterization value sequence, a dirtiness rate characterization value corresponding to each representative value position point in each level of the multi-level dirtiness interval; The dirtiness rate characterization value and the actual dirtiness rate corresponding to each representative value position point in each level of the multi-level dirtiness interval are updated to replace the selected characterization value and the actual dirtiness rate corresponding to a selected position point in the corresponding level of the multi-level characterization interval, to obtain the selected characterization value and the actual dirtiness rate corresponding to the updated selected position point; Associating the selected characterization value corresponding to the updated selected position point with the actual contamination rate to obtain an updated ballast contamination model; According to the characterization value sequence of the roadbed contamination state and the updated roadbed contamination model, the roadbed contamination rate corresponding to the roadbed of the target mileage is updated, and the updated roadbed contamination rate corresponding to the roadbed of the target mileage is output.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that: When the computer program is executed by the processor, the computer program executes the instructions of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor of a computer device, the computer program executes the instructions of the method according to any one of claims 1 to 5.

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