Railway track wear analysis method and system based on moving peak-to-peak value and moving overrun rate

Abstract

The present application relates to the technical field of railway track corrugation detection, and discloses a track corrugation analysis method and system based on a moving peak-to-peak value and a moving overrun rate, which comprises a track corrugation parameter acquisition module, a track corrugation analysis module and a track corrugation processing module; according to the peak-to-valley value of the track corrugation detection measurement point, combined with numerical analysis and different types of track corrugation standard peak-to-valley value intervals set by the standard, the type of the target track corrugation detection measurement point position is accurately analyzed, the type of the track corrugation fault is scientifically monitored based on the moving peak-to-peak value, the type of the track corrugation is comprehensively judged according to the track corrugation type weight parameter combined with numerical analysis and the track corrugation type judgment weight safety threshold stored scientifically in the target track corrugation detection, the type of the track corrugation is scientifically evaluated based on the moving overrun rate, the dynamic and fine track corrugation detection is realized, and the quality of the track corrugation detection is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of railway track wear detection, in particular to a track wear analysis method and system based on moving peak-to-peak value and moving overrun rate. BACKGROUND

[0002] Railway track wear is a phenomenon of regular undulation of the top surface of the track. Track wear is divided into two types: corrugated wear and wavy wear. Corrugated wear has a wavelength range of 50-100mm and an amplitude of 0.1-0.4mm, and is characterized by high-frequency small-amplitude vibration. Wavy wear has a wavelength greater than 100mm but not more than 300mm and an amplitude of up to 2mm, and is characterized by low-frequency large-amplitude vibration. Corrugated wear is characterized by dense periodic undulation and is commonly found in metro small-radius curve sections. Wavy wear is commonly found in heavy-load railway straight lines or large-radius curve sections and is related to wheel-rail dynamic force distribution. Existing track wear detection processes cannot achieve fine detection of track wear state and intelligent evaluation of track wear treatment scheme.

[0003] Chinese patent CN105608312B discloses a wave wear evaluation method for guiding track wear maintenance. The wavelength influence value L of the wave wear section, the wave depth influence value D of the wave wear section, the vibration effective value influence value G of the wave wear section, and the kilometer marker length K of the wave wear section are calculated based on the track detection parameters of the wave wear section. The N segments are divided into segments with a length of k according to the calculation formula N=int(K / k)+1. The wheel-rail force influence value AN of each segment is calculated. The maintenance decision value W of each wave wear section of the track is calculated by a track wave wear comprehensive maintenance decision function. It is decided whether to maintain according to the W value of each section. The priority is determined according to the size order of the W value of each section to guide the track wear maintenance. The above technical solution cannot achieve accurate measurement and analysis of the track wear state. SUMMARY

[0004] (I) Technical problem to be solved

[0005] To solve the problem that the existing track wear detection process cannot achieve fine detection of track wear state and intelligent evaluation of track wear treatment scheme, the present application aims to achieve accurate measurement of track wear measurement point peak-to-valley value parameters, scientific analysis of track wear measurement point wear type, comprehensive evaluation of track wear type, and scientific formulation of track wear treatment scheme.

[0006] (II) Technical solution

[0007] The present application is implemented by the following technical solution: a track wear analysis method based on moving peak-to-peak value and moving overrun rate, comprising the following steps:

[0008] S1, collect track wear detection entity model data;

[0009] S2, based on the track wear detection entity model data, the measurement point division processing of the target track wear detection is carried out, and track wear detection measurement point coordinate data is generated;

[0010] S3, according to the track wear detection measurement point coordinate data, the wear peak and valley value measurement processing of the target track wear detection measurement point position is carried out, and the track wear detection measurement point peak and valley value is generated;

[0011] S4, according to the track wear detection measurement point peak and valley value and the different type track wear standard peak and valley value interval, the wear type analysis processing of the target track wear detection measurement point position is carried out, and the track wear detection measurement point wear type analysis data is generated;

[0012] S5, according to the track wear detection measurement point wear type analysis data, the wear type weight measurement processing of the target track wear detection is carried out, and the track wear type weight data is generated;

[0013] S6, according to the track wear type weight data and the track wear type judgment weight safety threshold, the wear type comprehensive judgment processing of the target track wear detection is carried out, and the track wear type judgment data is generated;

[0014] S7, according to the track wear type judgment data and the different track wear type maintenance strategy data, the maintenance scheme evaluation processing of the target track wear fault is carried out, and the track wear maintenance evaluation data is generated.

[0015] Preferably, the operation steps of collecting track wear detection entity model data are as follows:

[0016] S11, the track space three-dimensional entity along the length direction of the target railway track is modeled by the unmanned aerial vehicle carrying three-dimensional laser scanner online, and the track wear detection entity model data is generated .

[0017] Preferably, based on the track wear detection entity model data, the operation steps of the measurement point division processing of the target track wear detection are as follows:

[0018] S21, the track wear detection entity model data is imported into the three-dimensional modeling platform, and the measurement point linear division processing of the track wear detection is carried out along the track length direction according to equal interval , and the spherical coordinate system is established with the earth sphere as the matrix, the spatial position parameters of the track wear detection measurement point are measured, and the track wear detection measurement point coordinate data set is generated , ;in Indicates the number of collections The coordinate data of the track corrugation detection measurement points corresponding to each measurement point. The total number of measurement points is indicated. The coordinate data of the track corrugation detection measurement points include the longitude, latitude, and altitude of the track corrugation measurement point locations. The 3D modeling platform includes any one of DSmax, Rhino, Cinema4D, ZBrush, and Poser.

[0019] Preferably, the steps for measuring and processing the peak and valley values ​​of the target track corrugation detection point based on the coordinate data of the track corrugation detection measurement point to generate the peak and valley values ​​of the track corrugation detection measurement point are as follows:

[0020] S31. Using a 3D modeling platform and a distance measurement module, based on the coordinate data set of the track corrugation detection measurement points. The coordinate data of the track corrugation detection measurement points described in the article The system then measures the vertical distance between the crests and troughs of the track corrugation at all measurement points according to their numbers, and generates a set of peak and trough values ​​for each measurement point. ,in Indicates the first Peak and valley values ​​of track corrugation detection measurement points corresponding to each measurement point. The unit is millimeters;

[0021] Preferably, the steps for performing a warping type analysis of the target track warping detection and measurement point location based on the peak and valley values ​​of the track warping detection and measurement point and the standard peak and valley value ranges for different types of track warping, and generating track warping type analysis data, are as follows:

[0022] S41. Establish a set of standard peak-valley value intervals for different types of track corrugations. ,in This indicates the standard peak-valley value range for different types of track corrugation, corresponding to the corrugated shape. ,in and These represent the standard peak-valley value ranges for the different types of track corrugation. Minimum and maximum standard peak-valley values ​​for corrugated track wear. and The units are all millimeters; This indicates the standard peak-valley value range for different types of track corrugation, corresponding to the wavy shape. ,in and These represent the standard peak-valley value ranges for the different types of track corrugation. Minimum and maximum peak-valley values ​​for standard wavy track corrugation. and The units are all millimeters;

[0023] S42. Set the coordinate data of the track corrugation detection and measurement points. The coordinate data of the track corrugation detection measurement points described in the article The measurement points are ordered according to the set of standard peak and valley value intervals for different types of track corrugation. The internal peak-valley value ranges of different types of track corrugation standards The minimum peak and valley values ​​of the corrugated track corrugation standard and the maximum peak-valley value of the corrugated track corrugation standard and the standard peak-valley value ranges for different types of track corrugation. The minimum peak and valley values ​​of the standard for wavy track corrugation mentioned in the text and the maximum peak-valley value of the standard for the wavy track corrugation Peak and valley values ​​were compared separately, and a data set for analyzing the wear type of track wear detection measurement points was generated based on the comparison results. ,in Indicates the first The track corrugation detection measurement point corrugation type analysis data corresponding to each measurement point includes corrugated corrugation and wavy corrugation.

[0024] when ∈ When, it indicates the first If the track wear type at each measurement point is corrugated, then output the track wear detection measurement point wear type analysis data. It is a corrugated pattern;

[0025] when ∈ When, it indicates the first If the track corrugation type at each measurement point is wavy, then output the track corrugation detection measurement point corrugation type analysis data. It is a wavy wave pattern.

[0026] Preferably, the steps for generating track wear type weight data by performing wear type weighting processing on the wear type analysis data of the track wear detection measurement points are as follows:

[0027] S51. The Rabin-Karp search algorithm is used to analyze the data set of the track wear detection measurement points for wear type analysis. Analysis data on the type of track wear at the measurement points described in the article Perform a keyword search for track corrugation types, retrieve the summary data of the number of measurement points corresponding to different track corrugation types, and generate a set of track corrugation type counts. ,in This indicates the number of track corrugation types corresponding to the corrugated shape in the track corrugation type analysis results. This indicates the number of track corrugation types corresponding to wavy patterns in the track corrugation type analysis results. , The units are all individuals;

[0028] S52, Set the number of track corrugation types Number of track corrugation types described in the text to Each with the total number of measurement points Numerical quotient measurement processing is performed, and a weighted dataset of track corrugation types is generated. ,in The analysis results of track corrugation type are represented by the weight data of the track corrugation type corresponding to the corrugation shape. This indicates the weight data of the track corrugation type corresponding to the wavy shape in the track corrugation type analysis result; , The values ​​are all Random numbers within the interval, and .

[0029] Preferably, the steps for generating track corrugation type judgment data by comprehensively judging the corrugation type of the target track corrugation detection based on the track corrugation type weight data and the track corrugation type judgment weight safety threshold are as follows:

[0030] S61. Establish a weighted safety threshold for determining track corrugation type. , where 0.5 < <1, the track corrugation type judgment weight safety threshold represents the minimum weight value set for judging the specific corrugation type of the target track as a whole;

[0031] S62, Set the weighted data set of track corrugation type The weighted data of track corrugation type described in the text to The weighted safety threshold is determined by comparing it with the track wear type. Perform a weighted comparison of track wear types, and generate track wear type judgment data based on the comparison results. ;

[0032] when > and < When the target track corrugation weight value is the largest, the track corrugation type judgment data is output. It is wavy;

[0033] when > and < When the target track wavy texture weight value is at its maximum, the track wavy texture type judgment data is output. It is wavy.

[0034] Preferably, the steps for evaluating maintenance plans for the target track corrugation fault based on the track corrugation type judgment data and maintenance strategy data for different track corrugation types to generate track corrugation maintenance evaluation data are as follows:

[0035] S71. Establish a data set of maintenance strategies for different track corrugation types. ,in This indicates maintenance strategy data for different track corrugation types corresponding to the corrugated shape. This indicates maintenance strategy data for different track corrugation types corresponding to the wavy type of track corrugation; the maintenance strategy data for different track corrugation types includes track grinding and repair maintenance plan information, track stiffness adjustment maintenance plan information, and track fastener replacement maintenance plan information.

[0036] S72, The track corrugation type determination data The maintenance strategy data set for different track corrugation types The maintenance strategy data for different track corrugation types described in the text are used to perform track corrugation type keyword matching to search for track corrugation type judgment data. The corresponding maintenance strategy data for different track corrugation types are used, and track corrugation maintenance assessment data is generated after data identification. The process generates the track wear maintenance assessment data. The specific operating steps are as follows:

[0037] S721, Propagation: Data sets of maintenance strategies for different track corrugation types. The data synchronization of maintenance strategies for different track corrugation types described herein is set as water waves. Each water wave of the maintenance strategy for different track corrugation types is an independent entity. Therefore, each water wave of the maintenance strategy for different track corrugation types will have three attributes: position, wavelength, and so on. and wave height ;

[0038] In each iteration, the water ripples of each of the different track corrugation type maintenance strategy data sets will propagate through the different track corrugation type maintenance strategy data sets. The search space is used to search for maintenance strategy data for different track erosion types, and the wave height of the water waves in the maintenance strategy data for different track erosion types is also analyzed. It will decrease by 1, and its position update formula is as follows: ,in Indicating the first stage of the transmission process Water waves after the second iteration The maintenance strategy data set for different track corrugation types Search space location; Indicating the first stage of the transmission process Water waves before the next iteration The maintenance strategy data set for different track corrugation types Search for locations in the search space; , The maintenance strategy data sets for different track corrugation types are respectively. Upper and lower bounds in the search space It is a constant. Indicates the value A random function;

[0039] S722, Refraction: After the water waves representing the different track wave type maintenance strategy data propagate, the water waves representing the different track wave type maintenance strategy data propagate are refracted and the data set representing the different track wave type maintenance strategy data is refracted. The different track wave type maintenance strategy data in the search space are identified, and the wave height of the water waves in the different track wave type maintenance strategy data is determined with each propagation. It will decrease by 1 when When the wave size decreases to 0, it will refract, and its wave height and wavelength will change. The refracted position will be normally distributed at a position with the midpoint between the current wave and the optimal wave as the mean and the distance between the current wave and the optimal wave as the variance. After refraction, the wave height will be reinitialized to its maximum height. After refraction, the wavelength of the water wave is recalculated. ;

[0040] S723, Broken Waves: The water waves in the different track corrugation type maintenance strategy data set are described in the different track corrugation type maintenance strategy data set. After propagating in the search space, it reaches a position better than the current optimal water wave, and then maintains the data set of different orbital wave types. The search space retrieved data matching the track wear type. If the location matches the maintenance strategy data for different track wave types, the water wave will break up and propagate the current optimal water wave to the location where the breakup occurs, outputting the track wave type judgment data. The best matching wave fragmentation location for the maintenance strategy data of different track corrugation types is determined by the following formula: ,in Indicates the first stage of the wave-breaking phase. The maintenance strategies for different track corrugation types mentioned in the previous iteration are based on water wave data. The maintenance strategy data set for different track corrugation types Search for locations in the space. Indicates the value random function, to This indicates that each wave randomly selects a spatial dimension number. This indicates the specific spatial dimension that each wave breaker actually randomly selects. to The specific spatial dimension parameters randomly selected for each wave break. It is a constant;

[0041] S724, Output the data related to the track corrugation type determination in step S723. The most suitable maintenance strategy data for different track corrugation types;

[0042] S725. The maintenance strategy data for different track corrugation types output in step S724 are processed through data identification to generate track corrugation maintenance evaluation data. The track corrugation maintenance assessment data represents the optimal track corrugation maintenance scheme information matched to the target track corrugation fault type.

[0043] A track wear analysis system based on moving peak-to-peak value and moving over-limit rate is used to implement the track wear analysis method based on moving peak-to-peak value and moving over-limit rate. The system includes a track wear parameter acquisition module, a track wear analysis module, and a track wear processing module.

[0044] The track corrugation parameter acquisition module includes a track corrugation solid model acquisition unit, a track corrugation measurement point division unit, and a track corrugation measurement point peak and valley value measurement unit.

[0045] The track corrugation entity model acquisition unit acquires track corrugation detection entity model data using a drone equipped with a 3D laser scanner; the track corrugation measurement point division unit divides the target track corrugation detection measurement points based on the track corrugation detection entity model data and a 3D modeling platform, generating track corrugation detection measurement point coordinate data; the track corrugation measurement point peak and valley value measurement unit measures the corrugation peak and valley values ​​of the target track corrugation detection measurement point positions based on the track corrugation detection measurement point coordinate data and a distance measurement module in the 3D modeling platform, generating track corrugation detection measurement point peak and valley values.

[0046] The track corrugation analysis module includes a standard peak-valley value interval storage unit for different types of track corrugation, a track corrugation measurement point corrugation type analysis unit, a track corrugation type weight measurement unit, a track corrugation type judgment weight safety threshold storage unit, and a track corrugation type judgment unit.

[0047] The storage unit for standard peak-valley value intervals of different types of track corrugation is used to store standard peak-valley value intervals of different types of track corrugation; the track corrugation measurement point corrugation type analysis unit performs corrugation type analysis processing on the target track corrugation detection measurement point location based on the peak-valley values ​​of the track corrugation detection measurement point and the standard peak-valley value intervals of different types of track corrugation, generating track corrugation type analysis data; the track corrugation type weight measurement unit performs corrugation type weight measurement processing on the target track corrugation detection based on the track corrugation detection measurement point corrugation type analysis data, generating track corrugation type weight data; the storage unit for track corrugation type judgment weight safety threshold is used to store track corrugation type judgment weight safety threshold; the track corrugation type judgment unit performs comprehensive judgment processing on the target track corrugation detection corrugation type based on the track corrugation type weight data and the track corrugation type judgment weight safety threshold, generating track corrugation type judgment data.

[0048] The track corrugation processing module includes a storage unit for different types of track corrugation maintenance strategies and a track corrugation maintenance strategy evaluation unit.

[0049] The storage unit for different types of track corrugation maintenance strategies is used to store maintenance strategy data for different types of track corrugation; the track corrugation maintenance strategy evaluation unit evaluates the maintenance scheme for the target track corrugation fault based on the track corrugation type judgment data and the maintenance strategy data for different types of track corrugation, and generates track corrugation maintenance evaluation data.

[0050] (III) Beneficial Effects

[0051] This invention provides a method and system for analyzing track wear based on moving peak-to-peak value and moving over-limit rate. It has the following beneficial effects:

[0052] 1. By using a drone equipped with a 3D laser scanner to dynamically and accurately acquire information from the physical model of the track corrugation detection, the system achieves efficient remote acquisition of the target track's true 3D structural information across all regions. Based on the track corrugation detection physical model data and a 3D modeling platform, the system digitally establishes measurement points for target track corrugation detection, enabling the establishment of measurement points based on big data science and improving the accuracy of track corrugation detection. Furthermore, based on the coordinate information of the track corrugation detection measurement points and the distance measurement module in the 3D modeling platform, the system digitally measures the corrugation peak and valley values ​​at the target track corrugation detection measurement points, further enhancing the precision of track corrugation detection.

[0053] Second, based on the peak and valley values ​​of track corrugation detection measurement points, combined with numerical analysis and standard-set peak and valley value intervals for different types of track corrugation, a precise analysis of the corrugation type at the target track corrugation detection measurement point location is performed, enabling scientific monitoring of track corrugation fault types based on moving peak-to-peak values. Efficient statistical analysis of weight parameters for different corrugation types in target track corrugation detection is conducted based on the corrugation type analysis parameters of the track corrugation detection measurement points, enabling digital analysis of the proportion of different track corrugation types. Furthermore, based on the track corrugation type weight parameters, combined with numerical analysis and scientifically stored track corrugation type judgment weight safety thresholds, a comprehensive judgment of the corrugation type in target track corrugation detection is performed, enabling scientific evaluation of track corrugation types based on moving over-limit rates, achieving dynamic and refined track corrugation detection, and improving the quality of track corrugation detection.

[0054] Third, by combining parameters based on track corrugation type with artificial intelligence recognition algorithms and standard-stored maintenance strategy data for different track corrugation types, intelligent evaluation and processing of maintenance plans for target track corrugation faults are performed. This enables scientific and intelligent analysis of maintenance plans for target track corrugation faults, improves the efficiency and workload of track corrugation detection, and enhances track service life and safety. Attached Figure Description

[0055] Fig. 1 A schematic diagram of the module of the track wear analysis system based on moving peak-to-peak value and moving over-limit rate provided by the present invention;

[0056] Fig. 2 The flowchart shows the track wear analysis method based on moving peak-to-peak value and moving over-limit rate provided by the present invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] An embodiment of the track wear analysis method and system based on moving peak-to-peak value and moving over-limit rate is as follows:

[0059] Example 1:

[0060] Please see Figs. 1-2 A method for analyzing track wear based on moving peak-to-peak value and moving exceedance rate, comprising the following steps:

[0061] S1. Collect data from the physical model of track corrugation detection;

[0062] S2. Based on the track wear detection entity model data, perform target track wear detection measurement point division processing to generate track wear detection measurement point coordinate data;

[0063] S3. Based on the coordinate data of the track corrugation detection measurement point, perform corrugation peak and valley value measurement and processing at the target track corrugation detection measurement point location to generate the track corrugation detection measurement point peak and valley value;

[0064] S4. Based on the peak and valley values ​​of the track corrugation detection measurement points and the standard peak and valley value ranges of different types of track corrugation, perform corrugation type analysis processing of the target track corrugation detection measurement point location to generate track corrugation detection measurement point corrugation type analysis data;

[0065] S5. Based on the analysis data of the track corrugation detection measurement points, perform corrugation type weighting processing for the target track corrugation detection to generate track corrugation type weight data;

[0066] S6. Based on the track wear type weight data and the track wear type judgment weight safety threshold, perform comprehensive judgment processing on the wear type of the target track wear detection to generate track wear type judgment data;

[0067] S7. Based on the track corrugation type judgment data and the maintenance strategy data for different track corrugation types, evaluate and process the maintenance plan for the target track corrugation fault to generate track corrugation maintenance evaluation data.

[0068] For further details, please refer to Figs. 1-2 The steps for collecting data from the physical model of track corrugation detection are as follows:

[0069] S11. Using a drone equipped with a 3D laser scanner, the target railway track is modeled online along its length to create a 3D solid model, generating track corrugation detection entity model data. .

[0070] The steps for dividing the target track wear detection measurement points and generating the coordinate data of the track wear detection measurement points based on the track wear detection entity model data are as follows:

[0071] S21. Transfer the track corrugation detection solid model data. Importing into a 3D modeling platform at equal intervals along the track length direction The measurement points for track wear detection are linearly divided, and a spherical coordinate system is established with the Earth as the base. The spatial position parameters of the track wear detection measurement points are measured, and a set of coordinate data for the track wear detection measurement points is generated. , ;in Indicates the number of collections The coordinate data of the track corrugation detection measurement points corresponding to each measurement point. This indicates the total number of measurement points. The coordinate data of the track corrugation detection measurement points include the longitude, latitude, and altitude of the track corrugation measurement point locations. The 3D modeling platform includes any one of DSmax, Rhino, Cinema4D, ZBrush, and Poser.

[0072] The steps for measuring and processing the peak and valley values ​​of the target track corrugation detection point based on the coordinate data of the track corrugation detection measurement point, and generating the peak and valley values ​​of the track corrugation detection measurement point, are as follows:

[0073] S31. Using a 3D modeling platform and a distance measurement module based on the coordinate data set of track corrugation detection measurement points. Coordinate data of measurement points for track corrugation detection The system then measures the vertical distance between the crests and troughs of the track corrugation at all measurement points according to their numbers, and generates a set of peak and trough values ​​for each measurement point. ,in Indicates the first Peak and valley values ​​of track corrugation detection measurement points corresponding to each measurement point. The unit is millimeters;

[0074] The track corrugation entity model acquisition unit utilizes a drone equipped with a 3D laser scanner to dynamically and accurately acquire track corrugation detection entity model information, achieving efficient remote acquisition of the target track's true 3D structural information across all regions. The track corrugation measurement point division unit, based on the track corrugation detection entity model data and a 3D modeling platform, digitally and scientifically establishes measurement points for target track corrugation detection, achieving big data-driven scientific establishment of measurement points and improving the accuracy of track corrugation detection. The track corrugation measurement point peak-valley value measurement unit, based on the coordinate information of the track corrugation detection measurement points and the distance measurement module of the 3D modeling platform, digitally measures the corrugation peak-valley values ​​at the target track corrugation detection measurement points, improving the precision of track corrugation detection.

[0075] For further details, please refer to Figs. 1-2The steps for generating track corrugation type analysis data for track corrugation detection points are as follows: Based on the peak and valley values ​​of track corrugation detection measurement points and the standard peak and valley value ranges for different types of track corrugation, the corrugation type analysis of the target track corrugation detection measurement point locations is performed:

[0076] S41. Establish a set of standard peak-valley value intervals for different types of track corrugations. ,in This indicates the standard peak-valley value range for different types of track corrugation, corresponding to the corrugated shape. ,in and These represent the standard peak and valley value ranges for different types of track corrugation. Minimum and maximum standard peak-valley values ​​for corrugated track wear. and The units are all millimeters; This indicates the standard peak-valley value range for different types of track corrugation, corresponding to the wavy shape. ,in and These represent the standard peak and valley value ranges for different types of track corrugation. Minimum and maximum peak-valley values ​​for standard wavy track corrugation. and The units are all millimeters;

[0077] S42. Set up the coordinate data of the track corrugation detection measurement points. Coordinate data of measurement points for track corrugation detection The measurement points are ordered according to their numbers, and the set of standard peak and valley value intervals for different types of track corrugation is used. Different types of internal track corrugation standard peak and valley value ranges Minimum peak and valley values ​​of the standard for corrugated track wear and the maximum peak and valley values ​​of the standard for corrugated track milling and the standard peak-valley value range for different types of track corrugation. Minimum peak and valley values ​​of the standard for wavy track corrugation and the maximum value of the standard peak and valley of the wavy track corrugation Peak and valley values ​​were compared separately, and a data set for analyzing the wear type of track wear detection measurement points was generated based on the comparison results. ,in Indicates the first The track corrugation detection measurement point corrugation type analysis data corresponding to each measurement point includes corrugated corrugation and wavy corrugation.

[0078] when ∈ When, it indicates the first If the track wear type at each measurement point is corrugated, then the output track wear detection measurement point wear type analysis data will be provided. It is a corrugated pattern;

[0079] when ∈ When, it indicates the first If the track corrugation type at each measurement point is wavy, then the output data will be the track corrugation detection measurement point corrugation type analysis data. It is a wavy wave pattern.

[0080] The steps for generating track wear type weight data by performing wear type weighting processing on the wear type analysis data of the track wear detection measurement points are as follows:

[0081] S51. The Rabin-Karp search algorithm is used to analyze the data set of track wear detection measurement points for wear type analysis. Analysis data on the type of corrugation at the measurement points of the track corrugation detection. Perform a keyword search for track corrugation types, retrieve the summary data of the number of measurement points corresponding to different track corrugation types, and generate a set of track corrugation type counts. ,in This indicates the number of track corrugation types corresponding to the corrugated shape in the track corrugation type analysis results. This indicates the number of track corrugation types corresponding to wavy patterns in the track corrugation type analysis results. , The units are all individuals;

[0082] S52, Set the number of track corrugation types Number of types of medium track corrugated mill to Respectively compared with the total number of measurement points Numerical quotient measurement processing is performed, and a weighted dataset of track corrugation types is generated. ,in The analysis results of track corrugation type are represented by the weight data of the track corrugation type corresponding to the corrugation shape. This indicates the weight data of the track corrugation type corresponding to the wavy shape in the track corrugation type analysis result; , The values ​​are all Random numbers within the interval, and .

[0083] The steps for generating track corrugation type judgment data are as follows: Based on the track corrugation type weight data and the track corrugation type judgment weight safety threshold, a comprehensive judgment of the corrugation type of the target track corrugation is performed:

[0084] S61. Establish a weighted safety threshold for determining track corrugation type. , where 0.5 < <1, the safety threshold for judging track corrugation type represents the minimum weight value set for judging the specific corrugation type of the target track as a whole;

[0085] S62, Set up the weighted data set of track corrugation type Weight data of medium track corrugation type to The weighted safety threshold is determined by the type of track wear. Perform a weighted comparison of track wear types, and generate track wear type judgment data based on the comparison results. ;

[0086] when > and < When the target track corrugation weight value is the largest, the track corrugation type judgment data is output. It is wavy;

[0087] when > and < When the target track wavy texture weight value is at its maximum, the track wavy texture type judgment data is output. It is wavy.

[0088] The track corrugation measurement point corrugation type analysis unit performs precise analysis of the corrugation type at the target track corrugation measurement point location based on the peak and valley values ​​of the track corrugation detection measurement point, combined with numerical analysis and standard-set peak and valley value ranges for different types of track corrugation. This enables scientific monitoring of track corrugation fault types based on moving peak-to-peak values. The track corrugation type weighting unit efficiently statistically analyzes the weight parameters of different corrugation types in the target track corrugation detection based on the corrugation type analysis parameters of the track corrugation detection measurement point, enabling digital analysis of the proportion of different track corrugation types. The track corrugation type judgment unit comprehensively judges the corrugation type in the target track corrugation detection based on the track corrugation type weight parameters, combined with numerical analysis and scientifically stored track corrugation type judgment weight safety thresholds. This enables scientific evaluation of track corrugation types based on moving over-limit rates, achieving dynamic and refined track corrugation detection and improving the quality of track corrugation detection.

[0089] For further details, please refer toFigs. 1-2 The steps for evaluating and processing maintenance plans for target track corrugation faults based on track corrugation type judgment data and maintenance strategy data for different track corrugation types to generate track corrugation maintenance evaluation data are as follows:

[0090] S71. Establish a data set of maintenance strategies for different track corrugation types. ,in This indicates maintenance strategy data for different track corrugation types corresponding to the corrugated shape. This indicates maintenance strategy data for different track corrugation types corresponding to the wavy type. The maintenance strategy data for different track corrugation types includes track grinding and repair maintenance plan information, track stiffness adjustment maintenance plan information, and track fastener replacement maintenance plan information.

[0091] S72, Obtain track wear type judgment data Data sets of maintenance strategies for different track corrugation types The maintenance strategy data for different track corrugation types in China was used to perform keyword matching for track corrugation type to retrieve track corrugation type judgment data. The corresponding maintenance strategy data for different track corrugation types are used to generate track corrugation maintenance assessment data after data identification. Generate track wear maintenance assessment data. The specific operating steps are as follows:

[0092] S721, Propagation: Data set of maintenance strategies for different track corrugation types The maintenance strategy data for different track corrugation types is synchronized as water waves. Each water wave of the maintenance strategy data for different track corrugation types is an independent entity. Therefore, each water wave of the maintenance strategy data for different track corrugation types will have three attributes: position, wavelength, and so on. and wave height ;

[0093] In each iteration, the water ripples of each different track corrugation type maintenance strategy data set will propagate through different track corrugation type maintenance strategy data sets. The search space was used to search for maintenance strategy data for different track ripple types, and the wave height of the water waves in the maintenance strategy data for different track ripple types was also analyzed. It will decrease by 1, and its position update formula is as follows: ,in Indicating the first stage of the transmission process Water waves after the second iteration Maintenance strategy data set for different track corrugation types Search space location; Indicating the first stage of the transmission process Water waves before the next iteration Maintenance strategy data set for different track corrugation types Search for locations in the search space; , Maintenance strategy data sets for different track corrugation types Upper and lower bounds in the search space It is a constant. Indicates the value A random function;

[0094] S722, Refraction: After water waves propagate through a maintenance strategy data set with different track wave types, the water waves undergo refraction, which affects the data set of the maintenance strategy data set with different track wave types. The search space was used to identify maintenance strategy data for different orbital wave types. For each propagation, the wave height of the water waves under different orbital wave type maintenance strategy data was determined. It will decrease by 1 when When the wave size decreases to 0, it will refract, and its wave height and wavelength will change. The refracted position will be normally distributed at a position with the midpoint between the current wave and the optimal wave as the mean and the distance between the current wave and the optimal wave as the variance. After refraction, the wave height will be reinitialized to its maximum height. After refraction, the wavelength of the water wave is recalculated. ;

[0095] S723, Broken Waves: Data on Maintenance Strategies for Different Track Wave Types (Data set of water wave maintenance strategies for different track wave types) After propagating through the search space, it reaches a position superior to the current optimal water wave, and maintains a strategy data set for different orbital wave types. Data related to track wear type was found in the search space. If the location of the maintenance strategy data for different track wave types is matched, the water wave will break up and propagate the current optimal water wave to the location where the breakup occurs, outputting data related to the track wave type judgment. The best matching wave fragmentation location for different track wave pattern maintenance strategies is determined by the following formula: ,in Indicates the first stage of the wave-breaking phase. Before the next iteration, maintenance strategies for different track corrugation types were implemented using water ripple data. Maintenance strategy data set for different track corrugation types Search for locations in the space. Indicates the value random function, to This indicates that each wave randomly selects a spatial dimension number. This indicates the specific spatial dimension that each wave breaker actually randomly selects. to The specific spatial dimension parameters randomly selected for each wave break. It is a constant;

[0096] S724, Output the data related to the track wear type determination in step S723. Data on the most suitable maintenance strategies for different track corrugation types;

[0097] S725. Generate track corrugation maintenance assessment data by processing the maintenance strategy data for different track corrugation types output in step S724 after data identification. The track corrugation maintenance assessment data represents the optimal track corrugation maintenance plan information matched to the target track corrugation fault type.

[0098] The track corrugation maintenance strategy evaluation unit intelligently evaluates and processes maintenance plans for target track corrugation faults based on track corrugation type judgment parameters, combined with artificial intelligence recognition algorithms and standard-stored maintenance strategy data for different track corrugation types. This enables scientific and intelligent analysis of maintenance plans for target track corrugation faults, improves the efficiency and workload of track corrugation detection, and enhances track service life and safety.

[0099] Example 2:

[0100] Please see Figs. 1-2 A track corrugation analysis system based on moving peak-to-peak value and moving over-limit rate is used to implement a track corrugation analysis method based on moving peak-to-peak value and moving over-limit rate. The system includes a track corrugation parameter acquisition module, a track corrugation analysis module, and a track corrugation processing module.

[0101] The track corrugation parameter acquisition module includes a track corrugation solid model acquisition unit, a track corrugation measurement point division unit, and a track corrugation measurement point peak and valley value measurement unit.

[0102] The track corrugation entity model acquisition unit uses a drone equipped with a 3D laser scanner to acquire track corrugation detection entity model data; the track corrugation measurement point division unit uses the track corrugation detection entity model data and a 3D modeling platform to divide the target track corrugation detection measurement points and generate track corrugation detection measurement point coordinate data; the track corrugation measurement point peak and valley value measurement unit uses the track corrugation detection measurement point coordinate data and the distance measurement module in the 3D modeling platform to measure the corrugation peak and valley values ​​of the target track corrugation detection measurement points and generate track corrugation detection measurement point peak and valley values.

[0103] The track corrugation analysis module includes a standard peak-valley value range storage unit for different types of track corrugation, a track corrugation measurement point corrugation type analysis unit, a track corrugation type weight measurement unit, a track corrugation type judgment weight safety threshold storage unit, and a track corrugation type judgment unit;

[0104] The system includes: a standard peak-valley value interval storage unit for different types of track corrugation, used to store standard peak-valley value intervals for different types of track corrugation; a track corrugation measurement point corrugation type analysis unit, which analyzes the corrugation type of the target track corrugation detection measurement point location based on the peak-valley values ​​of the track corrugation detection measurement point and the standard peak-valley value intervals for different types of track corrugation, generating track corrugation type analysis data; a track corrugation type weighting unit, which performs corrugation type weighting for the target track corrugation detection based on the track corrugation type analysis data, generating track corrugation type weighting data; a track corrugation type judgment weight safety threshold storage unit, used to store the track corrugation type judgment weight safety threshold; and a track corrugation type judgment unit, which performs comprehensive judgment processing on the corrugation type of the target track corrugation detection based on the track corrugation type weighting data and the track corrugation type judgment weight safety threshold, generating track corrugation type judgment data.

[0105] The track corrugation treatment module includes a storage unit for different types of track corrugation maintenance strategies and a track corrugation maintenance strategy evaluation unit.

[0106] The storage unit for different types of track corrugation maintenance strategies is used to store maintenance strategy data for different types of track corrugation; the track corrugation maintenance strategy evaluation unit evaluates the maintenance plan for the target track corrugation fault based on the track corrugation type judgment data and the maintenance strategy data for different types of track corrugation, and generates track corrugation maintenance evaluation data.

[0107] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for analyzing track wear based on moving peak-to-peak value and moving over-limit rate, characterized in that, The method includes the following steps: S1. Collect data from the physical model of track corrugation detection; S2. Based on the track wear detection entity model data, perform target track wear detection measurement point division processing to generate track wear detection measurement point coordinate data; S3. Based on the coordinate data of the track corrugation detection measurement point, perform corrugation peak and valley value measurement processing at the target track corrugation detection measurement point location to generate track corrugation detection measurement point peak and valley values; S4. Based on the peak and valley values ​​of the track corrugation detection measurement points and the standard peak and valley value ranges of different types of track corrugation, perform corrugation type analysis processing on the target track corrugation detection measurement point location to generate track corrugation detection measurement point corrugation type analysis data. S5. Based on the track corrugation detection measurement point corrugation type analysis data, perform corrugation type weighting processing for target track corrugation detection to generate track corrugation type weight data; S6. Based on the track corrugation type weight data and the track corrugation type judgment weight safety threshold, perform comprehensive judgment processing on the corrugation type of the target track corrugation detection to generate track corrugation type judgment data; S7. Based on the track corrugation type judgment data and the maintenance strategy data for different track corrugation types, evaluate the maintenance plan for the target track corrugation fault and generate track corrugation maintenance evaluation data. S2 includes the following steps: S21. Transfer the track corrugation detection solid model data. Importing into a 3D modeling platform at equal intervals along the track length direction The measurement points for track wear detection are linearly divided, and a spherical coordinate system is established with the Earth as the base. The spatial position parameters of the track wear detection measurement points are measured, and a set of coordinate data for the track wear detection measurement points is generated. , ;in Indicates the number of collections The coordinate data of the track corrugation detection measurement points corresponding to each measurement point Indicates the total number of measurement points; S3 includes the following steps: S31. Using the distance measurement module of the 3D modeling platform according to the above... The above The system then measures the vertical distance between the crests and troughs of the track corrugation at all measurement points according to their numbers, and generates a set of peak and trough values ​​for each measurement point. ,in Indicates the first Peak and valley values ​​of track corrugation detection measurement points corresponding to each measurement point. The unit is millimeters; S4 includes the following steps: S41. Establish a set of standard peak-valley value intervals for different types of track corrugations. ,in This indicates the standard peak-valley value range for different types of track corrugation, corresponding to the corrugated shape. ,in and Each represents the Minimum and maximum standard peak-valley values ​​for corrugated track wear. and The units are all millimeters; This indicates the standard peak-valley value range for different types of track corrugation, corresponding to the wavy shape. ,in and Each represents the Minimum and maximum peak-valley values ​​for standard wavy track corrugation. and The units are all millimeters; S42, the above The above According to the measurement point numbering, in order with the above The internal description The above and stated and the aforementioned The above and stated Peak and valley values ​​were compared separately, and a data set for analyzing the wear type of track wear detection measurement points was generated based on the comparison results. ,in Indicates the first Analysis data on the type of track corrugation detection measurement points corresponding to each measurement point; when ∈ When that happens, the output will be... It is a corrugated pattern; when ∈ When that happens, the output will be... It is a wavy wave pattern.

2. The track wear analysis method based on moving peak-to-peak value and moving over-limit rate according to claim 1, characterized in that: S1 includes the following steps: S11. Using a drone equipped with a 3D laser scanner, the target railway track is modeled online along its length to create a 3D solid model, generating track corrugation detection entity model data. .

3. The track wear analysis method based on moving peak-to-peak value and moving over-limit rate according to claim 1, characterized in that: S5 includes the following steps: S51. The Rabin-Karp search algorithm is used to search the... The above Perform a keyword search for track corrugation types, retrieve the summary data of the number of measurement points corresponding to different track corrugation types, and generate a set of track corrugation type counts. ,in This indicates the number of track corrugation types corresponding to the corrugated shape in the track corrugation type analysis results. This indicates the number of track corrugation types corresponding to wavy patterns in the track corrugation type analysis results. , The units are all individuals; S52, the above The above to Each with the above Numerical quotient measurement processing is performed, and a weighted dataset of track corrugation types is generated. ,in The analysis results of track corrugation type are represented by the weight data of the track corrugation type corresponding to the corrugation shape. This indicates the weight data of the track corrugation type corresponding to the wavy shape in the track corrugation type analysis result; , The values ​​are all Random numbers within the interval, and .

4. The track wear analysis method based on moving peak-to-peak value and moving over-limit rate according to claim 3, characterized in that: S6 includes the following steps: S61. Establish a weighted safety threshold for determining track corrugation type. , where 0.5 < <1; S62, the above The above to Each with the above Perform a weighted comparison of track wear types, and generate track wear type judgment data based on the comparison results. ; when > and < When that happens, the output will be... It is wavy; when > and < When that happens, the output will be... It is wavy.

5. The track wear analysis method based on moving peak-to-peak value and moving over-limit rate according to claim 4, characterized in that: S7 includes the following steps: S71. Establish a data set of maintenance strategies for different track corrugation types. ,in This indicates maintenance strategy data for different track corrugation types corresponding to the corrugated shape. This indicates maintenance strategy data for different track corrugation types corresponding to the wavy type. S72, the above With the The maintenance strategy data for different track corrugation types described in the text are used for track corrugation type keyword matching to search for the corresponding... The corresponding maintenance strategy data for different track corrugation types are used, and track corrugation maintenance assessment data is generated after data identification. The process generates the track wear maintenance assessment data. The specific operating steps are as follows: S721, Propagation: The aforementioned The data synchronization of maintenance strategies for different track corrugation types described herein is set as water waves. Each water wave of the maintenance strategy for different track corrugation types is an independent entity. Therefore, each water wave of the maintenance strategy for different track corrugation types will have three attributes: position, wavelength, and so on. and wave height ; In each iteration, the water ripples of each of the different track corrugation type maintenance strategy data sets will propagate through the different track corrugation type maintenance strategy data sets. The search space is used to search for maintenance strategy data for different track erosion types, and the wave height of the water waves in the maintenance strategy data for different track erosion types is also analyzed. It will decrease by 1; S722, Refraction: After the water waves of the different track wave type maintenance strategy propagate, the water waves of the different track wave type maintenance strategy are refracted and... The different track wave type maintenance strategy data in the search space are identified, and the wave height of the water waves in the different track wave type maintenance strategy data is determined with each propagation. It will decrease by 1 when When the wave size decreases to 0, it will refract, and its wave height and wavelength will change. The refracted position will be normally distributed at a position with the midpoint between the current wave and the optimal wave as the mean and the distance between the current wave and the optimal wave as the variance. After refraction, the wave height will be reinitialized to its maximum height. After refraction, the wavelength of the water wave is recalculated. ; S723, Broken Waves: The maintenance strategy data for different track wave mill types is described in the water wave section. After propagating in the search space, it reaches a position better than the current optimal water wave. The search space found results related to the above. If the location matches the position of the maintenance strategy data for different track wave types, the water wave will break up and propagate the current optimal water wave to the location where the breakup occurs, outputting the data. The location of the broken waves that best matches the maintenance strategy data for the different track wave types; In steps S724 and S723, the output is related to the above. The most suitable maintenance strategy data for different track corrugation types; S725. The maintenance strategy data for different track corrugation types output in step S724 are processed through data identification to generate track corrugation maintenance evaluation data. .

6. A track wear analysis system based on moving peak-to-peak value and moving exceedance rate, used to implement the track wear analysis method based on moving peak-to-peak value and moving exceedance rate as described in any one of claims 1-5, characterized in that: The system includes a track corrugation parameter acquisition module, a track corrugation analysis module, and a track corrugation processing module.

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