Quantitative method and device for railway track surface oblique crack

Abstract

The application discloses a railway rail surface oblique crack quantification method and device, wherein the method comprises the following steps: obtaining a calibration line with multiple groups of preset depth artificial damage prepared on the surface of a steel rail; obtaining the magnetic flux leakage signal amplitude of artificial damage with different preset depths, fitting to generate a first relationship curve of artificial damage depth and magnetic flux leakage signal amplitude; performing step-by-step polishing on the natural oblique crack of the rail surface, obtaining the measured residual depth after each polishing and obtaining the corresponding magnetic flux leakage signal amplitude, fitting to generate a second relationship curve of natural damage depth and magnetic flux leakage signal amplitude; matching the depth values under the same magnetic flux leakage signal amplitude of the first relationship curve and the second relationship curve, establishing the mapping relationship between the artificial damage depth and the natural damage depth; detecting the magnetic flux leakage signal amplitude of the to-be-measured oblique crack, and outputting the quantification depth value corresponding to the magnetic flux leakage signal amplitude based on the mapping relationship. The application is used to improve the oblique crack depth evaluation accuracy and eliminate the repeated detection cost caused by equipment differences.

Description

Technical Field

[0001] This invention relates to the field of railway inspection technology, and in particular to a method and apparatus for quantifying oblique cracks on railway rail surfaces. Background Technology

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

[0003] Rails bear the complex alternating loads of hundreds of tons of trains over long periods, leading to fatigue damage evolution on the rail surface. The typical damage path manifests as microstructural deterioration, surface crack initiation, and the propagation of diagonal cracks to macroscopic failure. Diagonal cracks, in particular, exhibit asymmetric propagation and subsurface development, making them highly concealed and rapidly expanding. Their numbers increase significantly when the total mass of the track exceeds 300 million tons, becoming a major threat to high-speed rail safety. While existing magnetic flux leakage detection technology can capture the leakage magnetic field of damage using magnetic sensors for in-depth assessment, related research focuses on quantitative models of artificial damage, such as analyzing depth through magnetic field spatial integration or AC signal time-domain characteristics. Because natural diagonal cracks differ significantly in morphology and size from standard artificial damage, existing models have poor practical application results.

[0004] Current magnetic flux leakage (MFL) detection technologies rely on assessment models built upon artificially created damage, which cannot accurately quantify the true depth of naturally occurring oblique cracks. Artificial damage has a uniform and regular shape, while naturally occurring oblique cracks are characterized by irregular morphology, discrete dimensions, and subsurface propagation, leading to significant errors in the fitting models based on artificial damage in practical applications. Furthermore, differences in manufacturing processes among different MFL detection devices result in inconsistent signal amplitudes for the same damage, further reducing assessment reliability. The concealed nature and rapid propagation of naturally occurring oblique cracks make them difficult to track using conventional methods, and current technologies lack depth quantification methods for their dynamic development stages, failing to meet the safety requirements for accurate oblique crack assessment in high-speed rail operations. Summary of the Invention

[0005] This invention provides a method for quantifying oblique cracks on railway rail surfaces, which improves the accuracy of oblique crack depth assessment on high-speed railway rail surfaces, eliminates the cost of repeated testing caused by equipment differences, and enhances the universality and reliability of oblique crack detection in high-speed railway operation and maintenance. The method includes:

[0006] Obtain calibration lines pre-prepared on the rail surface containing multiple sets of artificially created damage at preset depths;

[0007] Based on the scanning results of the calibration line by the magnetic flux leakage detection device under preset detection conditions, the magnetic flux leakage signal amplitude of artificial damage at different preset depths is obtained, and a first relationship curve between the depth of artificial damage and the amplitude of magnetic flux leakage signal is generated by fitting.

[0008] By performing stepped grinding on the natural oblique cracks on the rail surface, the remaining depth after each grinding is obtained; the leakage magnetic field detection device is used to obtain the leakage magnetic field signal amplitude corresponding to different remaining depths, and a second relationship curve between the natural damage depth and the leakage magnetic field signal amplitude is generated by fitting.

[0009] The depth values ​​of artificial damage and natural damage are matched by the first relationship curve and the second relationship curve under the same leakage magnetic signal amplitude to establish a mapping relationship between the depth of artificial damage and the depth of natural damage.

[0010] The amplitude of the leakage magnetic field signal of the oblique crack under test is detected, and a quantized depth value corresponding to the amplitude of the leakage magnetic field signal is output based on the mapping relationship.

[0011] This invention also provides a device for quantifying oblique cracks on railway tracks, used to improve the accuracy of oblique crack depth assessment on high-speed railway tracks, eliminate the cost of repeated testing caused by equipment differences, and improve the universality and reliability of oblique crack detection in high-speed railway operation and maintenance. The device includes:

[0012] The calibration line acquisition module is used to acquire calibration lines pre-prepared on the rail surface containing multiple sets of artificial damage at preset depths;

[0013] The first relationship curve establishment module is used to obtain the amplitude of the magnetic flux leakage signal of artificial damage at different preset depths based on the scanning results of the calibration line by the magnetic flux leakage detection device under preset detection conditions, and to fit and generate the first relationship curve between the depth of artificial damage and the amplitude of the magnetic flux leakage signal.

[0014] The second relationship curve establishment module is used to obtain the measured remaining depth after each grinding by performing stepped grinding on the natural oblique crack of the rail surface; and to obtain the leakage magnetic signal amplitude corresponding to different measured remaining depths by the leakage magnetic detection device, and to fit and generate a second relationship curve between the natural damage depth and the leakage magnetic signal amplitude.

[0015] The mapping relationship establishment module is used to match the depth values ​​of the first relationship curve and the second relationship curve under the same leakage magnetic signal amplitude to establish a mapping relationship between the depth of artificial damage and the depth of natural damage.

[0016] The quantization depth output module is used to detect the amplitude of the leakage magnetic signal of the oblique crack under test, and outputs the quantization depth value corresponding to the amplitude of the leakage magnetic signal based on the mapping relationship.

[0017] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described method for quantifying oblique cracks on railway track surfaces.

[0018] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for quantifying oblique cracks on railway track surfaces.

[0019] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for quantifying oblique cracks on railway track surfaces.

[0020] In this embodiment of the invention, a calibration line containing multiple sets of artificially created damage at preset depths is pre-prepared on the rail surface; based on the scanning results of the calibration line by a magnetic flux leakage detection device under preset detection conditions, the magnetic flux leakage signal amplitude of artificially created damage at different preset depths is obtained, and a first relationship curve between the artificial damage depth and the magnetic flux leakage signal amplitude is fitted and generated; by performing step-by-step grinding on the natural oblique crack of the rail surface, the remaining depth after each grinding is obtained; the magnetic flux leakage signal amplitude corresponding to different remaining depths is obtained by the magnetic flux leakage detection device, and a second relationship curve between the natural damage depth and the magnetic flux leakage signal amplitude is fitted and generated; the depth values ​​under the same magnetic flux leakage signal amplitude are matched between the first relationship curve and the second relationship curve to establish a mapping relationship between the artificial damage depth and the natural damage depth; the magnetic flux leakage signal amplitude of the oblique crack to be tested is detected, and a quantized depth value corresponding to the magnetic flux leakage signal amplitude is output based on the mapping relationship. This invention establishes a mapping relationship between the depth of artificial damage and the depth of natural damage. By using a second relationship curve established through stepped grinding of real natural cracks, it accurately reflects the characteristics of irregular cracks and overcomes the difference between the regularity of artificial damage morphology and the dispersion of natural damage. The mapping relationship uses the calibration line as a device-independent reference. When different devices scan the same calibration line, a unified natural damage depth value is output through depth matching, eliminating the evaluation deviation caused by device differences, reducing the cost of repeated testing caused by device differences, and improving the universality and reliability of oblique crack detection in high-speed rail operation and maintenance. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0022] Figure 1 This is a specific example diagram illustrating a theory for the formation of a leakage magnetic field in an embodiment of the present invention;

[0023] Figure 2 This is a specific example diagram illustrating a magnetic flux leakage detection principle in an embodiment of the present invention;

[0024] Figure 3 This is a specific example diagram illustrating the calibration steps of a magnetic flux leakage detection device in an embodiment of the present invention;

[0025] Figure 4 This is a specific schematic diagram illustrating the fitting of the correspondence between calibration line damage depth and signal amplitude in an embodiment of the present invention;

[0026] Figure 5 This is a specific example diagram illustrating the fitting of the correspondence between natural injury depth and signal amplitude in an embodiment of the present invention;

[0027] Figure 6 This is a specific example diagram illustrating the comparison between the calibration line and the amplitude-depth fitting of natural damage in an embodiment of the present invention;

[0028] Figure 7 This is a flowchart illustrating a method for quantifying oblique cracks on railway track surfaces according to an embodiment of the present invention.

[0029] Figure 8 This is a schematic diagram of a computer device used for quantifying oblique cracks on railway track surfaces in an embodiment of the present invention;

[0030] Figure 9 This is a schematic diagram of the structure of a railway track surface oblique crack quantification device according to an embodiment of the present invention. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0032] In this document, the term "and / or" merely describes a relationship, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0033] In the description of this specification, the terms "comprising," "including," "having," and "containing" are open-ended terms, meaning that they include but are not limited to. The terms "an embodiment," "a specific embodiment," "some embodiments," and "for example," etc., refer to specific features, structures, or characteristics described in connection with that embodiment or example that are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. The order of steps involved in the various embodiments is used to illustrate the implementation of this application, and the order of steps is not limited and can be adjusted appropriately as needed.

[0034] The acquisition, storage, use, and processing of data in this application comply with relevant regulations. The information collected in this application is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with relevant standards, necessary confidentiality measures have been taken, and they do not violate public order and good morals. Corresponding operation interfaces are provided for users to choose to authorize or refuse.

[0035] It should be noted that in the embodiments of this application, certain existing solutions in the industry, such as software, components, and models, may be mentioned. For example, some existing software tools, components, algorithm models, or solutions well-known in other technical fields may be cited. These should be considered exemplary, and their purpose is only to illustrate the feasibility of implementing the technical solution of this application. These mentions should be understood as typical examples, and their core purpose is to illustrate and verify the rationality and feasibility of implementing the technical solution proposed in this application. However, this does not mean that the applicant has already used or necessarily used the solution. Such citations do not imply that the applicant has actually adopted these existing solutions, or that it will necessarily adopt these methods in its technical implementation process in the future. In other words, these mentions are only illustrative in nature, helping to understand the connection and transcendence of the innovation points of this application with the prior art, and do not constitute an endorsement or reliance statement on a specific prior art product.

[0036] The following terms are used in the embodiments of this invention and are explained below:

[0037] As a critical load-bearing component of the railway system, rails operate under complex conditions for extended periods. The narrow wheel-rail contact surface bears the complex alternating loads of hundreds of tons of trains, leading to material fatigue accumulation and multi-mode damage evolution. The typical damage path is: microstructure deterioration → surface crack initiation → diagonal crack propagation → macroscopic failure (nuclear damage / sparging). Among these, with the increasing operational years of high-speed railways, some lines have experienced a significant increase in rail surface fatigue damage, primarily characterized by diagonal cracks, after traversing a total mass exceeding 300 million tons.

[0038] Diagonal cracks, characterized by asymmetric propagation and a tendency to spread to the subsurface, are highly concealed, propagate rapidly, and are difficult to detect and assess, making them one of the main hidden dangers threatening the operational safety of high-speed railways. Furthermore, due to significant differences between high-speed and conventional railways in terms of train speed, axle load, rail material, and track structure, diagonal crack damage in high-speed railway rails exhibits new characteristics in its causes and development. Therefore, there is an urgent need to deepen our understanding of this type of damage, conduct regular inspections, and curb its progression. However, accurate quantitative assessment methods for detection are still lacking.

[0039] Magnetic leakage detection technology is based on the leakage magnetic field effect caused by the change in magnetic permeability at the damaged area after magnetization of ferromagnetic materials. By capturing the distribution characteristics of the leakage magnetic field through a magnetic sensor, the depth of damage can be assessed. The detection depth can reach 20mm. It has the advantages of not requiring coupling agent, simple operation, and high sensitivity, and is suitable for quantitative assessment of rail tread damage.

[0040] Currently, there is considerable research on the quantification of damage depth using magnetic flux leakage technology. For example, ultra-high-definition magnetic flux leakage crack detection technology based on the magnetic field spatial integration method achieves quantitative analysis of artificial crack depth and width through magnetic field integration and iterative analysis at different lift-off distances; a damage quantification method based on the time-domain characteristics of AC magnetic flux leakage signals decouples width and depth by analyzing signal differences and nonlinear characteristics, and its effectiveness is verified through artificial damage experiments. However, these studies primarily focus on artificial damage. Compared to relatively standardized artificial damage, natural damage often exhibits significant differences in morphology and size structure. Therefore, establishing evaluation models solely for artificial damage is insufficient to improve practical application effectiveness.

[0041] The following is the formation mechanism of oblique cracks: Oblique cracks on the rail surface are a type of rolling contact fatigue damage. When the wheel-rail contact surface is the rail head tread and side surface, the contact fatigue cracks formed at the gauge angle are fish-scale shaped, called fish-scale peeling cracks (abbreviated as: fish-scale cracks); when the wheel-rail contact surface is only on the rail head tread, the contact fatigue cracks are oblique, called oblique peeling cracks (abbreviated as: oblique cracks), but oblique cracks are more likely to propagate inward, forming core damage or even causing fracture.

[0042] The causes of oblique cracks in rails are multi-source, and can be mainly divided into two categories according to the inducing factors.

[0043] Category 1: Rail contact fatigue-induced (RCF-related Squats). This mainly includes rolling contact fatigue and corrugation, etc. Oblique cracks of this type are prone to occur at curves and welded joints.

[0044] The second category: WEL-related studs. These mainly include: rail surface abrasions, dents, and poor wear marks. These types of diagonal cracks are prone to occur in the entry and exit sections of hub stations and in the emergency braking test sections of EMU trains.

[0045] Rail surface diagonal cracks are characterized by being difficult to detect in their early stages, developing rapidly in the middle stages, and being difficult to eliminate by grinding or milling in the later stages. They are highly concealed and pose a significant hazard.

[0046] After the formation of oblique cracks in rails, the apparent characteristics of oblique crack damage mainly include "V"-shaped cracks, "black spots", rail surface depressions, and spalling, depending on the different development stages. Its development generally goes through the following main stages: rail surface oblique cracks → rail surface V-shaped cracks → rail surface double V-shaped cracks → rail surface spalling or rail head core damage.

[0047] The formation of leakage magnetic fields at damaged sites in magnetic materials mainly involves three steps: magnetic refraction, magnetic diffusion, and magnetic compression, such as... Figure 1 As shown, Figure 1 This is a specific example diagram illustrating a theory for the formation of a leakage magnetic field in an embodiment of the present invention. This is because the magnetic permeability of ferromagnetic materials is much higher than that of air. After being magnetized, a very high density of magnetic induction field accumulates inside the material. When the ferromagnetic material is damaged, i.e., the interface with the air is discontinuous, the magnetic boundary conditions lead to magnetic refraction. The magnetic field in the material is refracted and deflected into the air near the damaged area, forming magnetic diffusion in the air. However, due to the background magnetic field in the air, there is a reverse repulsive effect on the diffused magnetic field lines at the damaged area, causing the diffused magnetic field lines to be squeezed and deformed, which is the magnetic compression effect.

[0048] Ultimately, a leakage magnetic field Bmfl is formed at the damaged site, where Bmfl = Br + Bd - Bc, where Br is the magnetic flux density under magnetic refraction, Bd is the magnetic flux density caused by magnetic diffusion, and Bc is the magnetic flux density generated by magnetic compression. Br and Bd enhance the leakage magnetic field, while Bc weakens it.

[0049] Common magnetic flux leakage detection equipment uses magnetic sensors to convert the leaking magnetic field into an electrical signal, and then uses signal processing techniques such as signal rectification, acquisition, and digital filtering to extract damage information from the signal.

[0050] In this invention, magnetic flux leakage detection targets the electromagnetic field generated on a rail under external DC excitation, which magnetizes the rail. When magnetic lines of force pass through a damaged area, due to the discontinuity of magnetic permeability caused by the damage, magnetic refraction occurs at the interface between the air and the rail. Through magnetic diffusion and magnetic compression effects, some magnetic lines of force leak out of the rail, forming a magnetic leakage field. Therefore, a magnetically sensitive probe is used to detect the magnetic leakage signal near the rail surface, converting it into a voltage signal. After signal conditioning and acquisition, the signal is finally processed and displayed by the host computer software. The principle of magnetic flux leakage detection and common magnetic flux leakage detection equipment are as follows: Figure 2 As shown, Figure 2 This is a specific example diagram illustrating a magnetic flux leakage detection principle in an embodiment of the present invention.

[0051] In contrast to the common problem that magnetic flux leakage detection and evaluation methods based on artificial damage are poorly applied to natural damage, this invention proposes a magnetic flux leakage detection device that simultaneously considers both artificial and natural damage to evaluate the oblique cracks on the rail surface of high-speed railway rails. This method establishes a connection between artificial and natural damage by grinding and analyzing the natural damage. By artificially preparing rails with standard depth cut damage (hereinafter referred to as: calibration lines), a correspondence is formed between calibration lines, signal amplitude, and the depth of natural damage.

[0052] Based on this correspondence, the calibration line manufactured under the same standard is first used for testing to obtain the signal amplitude of the corresponding damage. By finding the corresponding natural damage value through the correspondence, the assessment of the natural damage can be completed.

[0053] Since the magnetic flux leakage detection equipment is only an intermediate medium for establishing this relationship, the corresponding relationship obtained by using different detection equipment is consistent. Therefore, the core of this evaluation method is that the detection calibration line should be standard, which is easy to achieve. At the same time, it eliminates the difference in detection amplitude caused by different detection equipment, directly establishes a corresponding relationship between artificial injuries and natural injuries, and improves the accuracy of the evaluation.

[0054] This invention provides a method for quantifying oblique cracks on railway rail surfaces, which improves the accuracy of oblique crack depth assessment on high-speed railway rail surfaces, eliminates the cost of repeated testing caused by equipment differences, and enhances the universality and reliability of oblique crack detection in high-speed railway operation and maintenance. (See also...) Figure 7 , Figure 7 This is a flowchart illustrating a method for quantifying oblique cracks on railway rail surfaces according to an embodiment of the present invention. The method may include:

[0055] Step 701: Obtain calibration lines pre-prepared on the rail surface containing multiple sets of artificial damage at preset depths;

[0056] Step 702: Based on the scanning results of the calibration line by the magnetic flux leakage detection device under preset detection conditions, obtain the magnetic flux leakage signal amplitude of artificial damage at different preset depths, and fit and generate a first relationship curve between the depth of artificial damage and the amplitude of magnetic flux leakage signal.

[0057] Step 703: Perform step-by-step grinding on the natural oblique cracks on the rail surface to obtain the measured remaining depth after each grinding; obtain the leakage magnetic signal amplitude corresponding to different measured remaining depths through the leakage magnetic detection device, and fit to generate a second relationship curve between the natural damage depth and the leakage magnetic signal amplitude;

[0058] Step 704: Match the depth values ​​of the first relationship curve and the second relationship curve under the same leakage magnetic signal amplitude to establish a mapping relationship between the depth of artificial damage and the depth of natural damage;

[0059] Step 705: Detect the amplitude of the leakage magnetic signal of the oblique crack to be tested, and output the quantized depth value corresponding to the amplitude of the leakage magnetic signal based on the mapping relationship.

[0060] In this embodiment of the invention, a calibration line containing multiple sets of artificially created damage at preset depths is pre-prepared on the rail surface; based on the scanning results of the calibration line by a magnetic flux leakage detection device under preset detection conditions, the magnetic flux leakage signal amplitude of artificially created damage at different preset depths is obtained, and a first relationship curve between the artificial damage depth and the magnetic flux leakage signal amplitude is fitted and generated; by performing step-by-step grinding on the natural oblique crack of the rail surface, the remaining depth after each grinding is obtained; the magnetic flux leakage signal amplitude corresponding to different remaining depths is obtained by the magnetic flux leakage detection device, and a second relationship curve between the natural damage depth and the magnetic flux leakage signal amplitude is fitted and generated; the depth values ​​under the same magnetic flux leakage signal amplitude are matched between the first relationship curve and the second relationship curve to establish a mapping relationship between the artificial damage depth and the natural damage depth; the magnetic flux leakage signal amplitude of the oblique crack to be tested is detected, and a quantized depth value corresponding to the magnetic flux leakage signal amplitude is output based on the mapping relationship. This invention establishes a mapping relationship between the depth of artificial damage and the depth of natural damage. By using a second relationship curve established through stepped grinding of real natural cracks, it accurately reflects the characteristics of irregular cracks and overcomes the difference between the regularity of artificial damage morphology and the dispersion of natural damage. The mapping relationship uses the calibration line as a device-independent reference. When different devices scan the same calibration line, a unified natural damage depth value is output through depth matching, eliminating the evaluation deviation caused by device differences, reducing the cost of repeated testing caused by device differences, and improving the universality and reliability of oblique crack detection in high-speed rail operation and maintenance.

[0061] In specific implementation, the first step is step 701: obtaining calibration lines containing multiple sets of pre-prepared artificial damage at preset depths on the surface of the rail.

[0062] In this embodiment, when preparing calibration lines containing multiple sets of pre-set artificial damage depths on the rail surface, the first step is to select rail material consistent with the actual operating rail material, heat treatment process, and mechanical properties as the substrate. The artificial damage is prepared through precision machining, specifically using a diamond cutting tool to make perpendicular cuts along the longitudinal axis of the rail to the rail head tread. The cutting direction is parallel to the rail axis, and the cutting width is controlled within the range of 0.2 mm to 0.5 mm to simulate real crack characteristics. The pre-set depth sets cover typical damage ranges from shallow to deep, including ten gradient depth values: 0.35 mm, 0.5 mm, 1.0 mm, 1.5 mm, 2.0 mm, 2.7 mm, 3.5 mm, 4.0 mm, 6.0 mm, and 8.0 mm. This calibration line serves as a reference specimen, and the depth values ​​of its artificial damage are certified by a metrology institution and recorded as standardized data.

[0063] In specific implementation, after step 701: obtaining the calibration line containing multiple sets of artificial damage at preset depths pre-prepared on the rail surface, step 702: based on the scanning results of the calibration line by the magnetic flux leakage detection equipment under preset detection conditions, obtaining the magnetic flux leakage signal amplitude of artificial damage at different preset depths, and fitting to generate a first relationship curve between the depth of artificial damage and the amplitude of the magnetic flux leakage signal.

[0064] In one embodiment, based on the scanning results of the calibration line by the magnetic flux leakage detection device under preset detection conditions, the amplitude of the magnetic flux leakage signal for artificial damage at different preset depths is obtained, including:

[0065] The calibration line is repeatedly scanned multiple times at different moving speeds;

[0066] Extract the maximum amplitude of the leakage magnetic field signal after each scan;

[0067] Calculate the average signal amplitude from multiple scans of the same artificial injury;

[0068] Based on the preset depth of each artificial injury and the corresponding average signal amplitude, the first relationship curve is generated through curve fitting.

[0069] In the above embodiment, when obtaining the amplitude of the artificial damage magnetic flux leakage signal based on the scanning results of the calibration line by the magnetic flux leakage detection equipment, a DC-excited magnetization unit applies a constant intensity magnetic field to the rail, with the magnetization direction parallel to the longitudinal axis of the rail. The magnetic sensor array moves uniformly along the calibration line at a fixed lift-off distance, and high-sensitivity magnetic induction elements are selected as the sensor type, with a sampling frequency meeting the requirements of high-speed detection.

[0070] The scanning process involves multiple sets of repeated detections at different moving speeds, covering the train operating speed range under typical operating conditions. Each scan simultaneously acquires multi-channel detection signals, and for each preset depth of artificial damage, the global maximum value of the leakage magnetic field signal amplitude in all channels is extracted as the feature value for that scan.

[0071] After multiple scans, the feature values ​​of the same artificial injury acquired at different speeds were arithmetically averaged to eliminate signal deviations caused by speed fluctuations. This resulted in multiple sets of data corresponding to preset depths and average signal amplitudes. Based on this dataset, a polynomial function was fitted using the least squares method, with the function order determined according to the data distribution characteristics. This first relationship curve fully characterizes the nonlinear mapping between the depth of the artificial injury and the amplitude of the leakage magnetic signal. The curve shape shows that the amplitude increase is gradual in shallow injury areas, while the amplitude change rate is significantly increased in deep injury areas, consistent with the physical characteristics caused by the magnetic saturation effect of ferromagnetic materials. The fitting results were verified by residual analysis and coefficient of determination to ensure that the curve accuracy meets engineering application standards.

[0072] In specific implementation, after step 702: obtaining the magnetic flux leakage signal amplitude of artificial damage at different preset depths based on the scanning results of the calibration line by the magnetic flux leakage detection device under preset detection conditions, and fitting to generate a first relationship curve between the depth of artificial damage and the amplitude of the magnetic flux leakage signal, step 703: obtaining the measured remaining depth after each grinding by performing stepped grinding on the natural oblique crack of the rail surface; obtaining the magnetic flux leakage signal amplitude corresponding to different measured remaining depths by the magnetic flux leakage detection device, and fitting to generate a second relationship curve between the depth of natural damage and the amplitude of the magnetic flux leakage signal.

[0073] In one embodiment, the remaining depth after each grinding step is measured by performing stepped grinding on the natural oblique cracks on the rail surface, including:

[0074] Each step of the polishing process removes a preset thickness until the natural damage marks disappear.

[0075] Obtain the remaining depth after each polishing.

[0076] In one embodiment, the magnetic flux leakage detection device acquires the amplitude of the magnetic flux leakage signal corresponding to different remaining measurement depths, and fits and generates a second relationship curve between the natural damage depth and the amplitude of the magnetic flux leakage signal, including:

[0077] After each polishing, the magnetic flux leakage detection device is used to perform multiple scans under the same detection conditions to extract the maximum amplitude of the magnetic flux leakage signal.

[0078] Calculate the average signal amplitude from multiple scans at the same remaining depth;

[0079] The second relationship curve is generated by curve fitting based on each remaining depth and the corresponding average signal amplitude.

[0080] In the above embodiment, when obtaining depth data by performing stepped grinding on natural oblique cracks on the rail surface, the damaged area of ​​the natural oblique crack existing in the actual track is first selected. This damaged area must contain complete oblique crack development characteristics. The grinding equipment adopts a CNC grinding wheel system, with a standard grinding head diameter, moderate grit size, and a stable spindle speed. The thickness removed by each grinding is precisely controlled to a preset fixed value, the grinding direction is strictly along the longitudinal direction of the rail, and the grinding width covers the damaged area and its surrounding extension range. The surface is cleaned immediately after each grinding, and a high-precision displacement sensor is used to measure the height difference between the lowest point of the damage and the rail surface reference as the remaining depth. This process is repeated until the damage marks completely disappear, and the remaining depth value after each grinding is recorded.

[0081] After each polishing process, the same magnetic flux leakage detection equipment was used for signal acquisition. The magnetization unit of the equipment applied the same DC excitation parameters as the calibration line detection, and the lift-off distance of the magnetic sensor remained constant. Multiple repeated scans were performed at each remaining depth, covering a speed range that would cover the actual testing conditions. Multi-channel magnetic flux leakage signals were recorded in real time during the scan, and the global maximum signal amplitude from all channels was extracted as a feature value for each scan. After multiple scans, the feature values ​​at the same remaining depth were arithmetically averaged to obtain the stable amplitude data corresponding to that depth.

[0082] Based on multiple sets of data corresponding to the remaining depth and average amplitude, a polynomial function was fitted using the least squares method. This function fully reflects the mapping relationship between the depth of the natural oblique crack and the leakage magnetic field signal. The curve shape conforms to the magnetic field attenuation characteristics caused by the subsurface expansion of natural damage, and the goodness of fit meets the predetermined standard. This second relationship curve serves as the benchmark for assessing the depth of natural damage.

[0083] In specific implementation, after step 703: performing stepped grinding on the natural oblique cracks on the rail surface to obtain the measured remaining depth after each grinding; obtaining the leakage magnetic signal amplitude corresponding to different measured remaining depths through the leakage magnetic detection device, and fitting to generate a second relationship curve between the natural damage depth and the leakage magnetic signal amplitude, step 704: matching the depth values ​​of the first relationship curve and the second relationship curve under the same leakage magnetic signal amplitude to establish a mapping relationship between artificial damage depth and natural damage depth.

[0084] In one embodiment, the depth values ​​of the first and second relationship curves under the same leakage magnetic signal amplitude are matched to establish a mapping relationship between the depth of artificial injury and the depth of natural injury, including:

[0085] Select multiple signal amplitude points on the first relationship curve;

[0086] Find the corresponding amplitude point on the second relationship curve that is the same as the signal amplitude point;

[0087] Record the correspondence between artificial injury depth values ​​and natural injury depth values ​​under the same signal amplitude;

[0088] Based on the aforementioned correspondence, a mapping dataset between artificial injury depth and natural injury depth is established.

[0089] In the above embodiments, when matching the depth values ​​of the first and second relationship curves under the same leakage magnetic field amplitude, multiple signal amplitude points covering the entire range of artificial damage are first selected on the first relationship curve. The selection process must ensure that the amplitude points are evenly distributed, covering key feature points from the low-amplitude region of shallow damage to the high-amplitude region of deep damage. Subsequently, an amplitude matching operation is performed on the second relationship curve, precisely finding corresponding points that are exactly the same as the amplitude points selected on the first relationship curve through function interpolation or data traversal. A double-precision floating-point comparison algorithm is used during the matching process to ensure that the amplitude difference is controlled within the instrument measurement error range.

[0090] After amplitude point matching is completed, the system automatically records the correspondence between artificial damage depth values ​​and natural damage depth values ​​under the same signal amplitude. The record format is structured data pairs, with each data set containing three core fields: matched signal amplitude, artificial damage depth, and natural damage depth. A depth mapping dataset is generated based on all matching points, and this dataset is arranged in ascending order of signal amplitude to form a query index table. During the mapping data verification phase, the maximum depth deviation is confirmed to not exceed a preset threshold by comparing the known depth of the calibration line with the natural damage depth output by the mapping. The final mapping dataset contains a complete depth correspondence from shallow to deep damage, serving as a device-independent evaluation benchmark.

[0091] In specific implementation, after performing step 704: matching the depth values ​​of the first relationship curve and the second relationship curve under the same leakage magnetic signal amplitude to establish a mapping relationship between artificial damage depth and natural damage depth, step 705: detecting the leakage magnetic signal amplitude of the oblique crack to be tested, and outputting a quantized depth value corresponding to the leakage magnetic signal amplitude based on the mapping relationship.

[0092] In one embodiment, detecting the amplitude of the magnetic flux leakage signal of the oblique crack under test and outputting a quantized depth value corresponding to the amplitude of the magnetic flux leakage signal based on the mapping relationship includes:

[0093] The magnetic flux leakage detection device is used to scan the oblique crack under test and obtain its magnetic flux leakage signal amplitude.

[0094] In the mapping relationship, match the artificial injury depth value that has the same amplitude as the acquired signal;

[0095] Based on the correspondence between artificial injury depth values ​​and natural injury depths in the mapping relationship, the corresponding natural injury depth value is output as a quantitative evaluation result.

[0096] In the above embodiment, when detecting the oblique crack under test and outputting the quantized depth value, the test area is first scanned using the same magnetic flux leakage detection equipment as the calibration line detection. The equipment's magnetization unit applies standard DC excitation parameters, and the magnetic sensor array moves longitudinally along the rail at a constant lift-off distance. During the scanning process, multi-channel magnetic flux leakage signals are acquired in real time, and the global maximum signal amplitude from all channels is extracted as the characteristic amplitude of the crack under test. This characteristic amplitude is then input into the data processing system after environmental noise interference is eliminated by the signal conditioning module.

[0097] The data processing system calls the pre-stored mapping dataset and performs feature amplitude matching in the artificial injury depth index column. The matching process uses the nearest neighbor interpolation algorithm. When the difference between the feature amplitude and the amplitude corresponding to a certain artificial injury depth in the mapping dataset is less than a preset threshold, it is considered a successful match. The system automatically reads the artificial injury depth value and, based on the corresponding natural injury depth in the mapping relationship, outputs the corresponding natural injury depth value as the final quantization result.

[0098] The following is a specific embodiment to illustrate the specific application of the method of the present invention.

[0099] In this embodiment, a calibration line containing multiple sets of pre-set artificial damage depths is first prepared on the rail surface, with the artificial damage depths covering typical damage ranges. A magnetic flux leakage detection device is used to scan this calibration line under pre-set detection conditions. The device's magnetization unit applies a DC excitation magnetic field, and the magnetic sensor array moves at a constant lift-off distance. The scanning process includes multiple repeated detections at different moving speeds. After each scan, the maximum amplitude of the multi-channel magnetic flux leakage signal is extracted as a feature value. The arithmetic mean of multiple feature values ​​for the same artificial damage is calculated to obtain stable amplitude data corresponding to each pre-set depth. Based on the corresponding dataset of pre-set depths and average amplitudes, a first relationship curve between the artificial damage depth and the magnetic flux leakage signal amplitude is generated by fitting using the least squares method.

[0100] A stepped grinding process was performed on natural oblique cracks in the actual circuit. A fixed thickness of material was removed each time, and the surface was immediately cleaned and the remaining depth measured after each grinding. This process was repeated until the damage disappeared, and the remaining depth value was recorded after each grinding. After each grinding, the same magnetic flux leakage (MFL) detection equipment was used to scan under the same detection conditions, acquiring multi-channel MFL signals and extracting the maximum amplitude. The average amplitude was calculated from multiple scans of the same remaining depth, forming a dataset corresponding to the natural damage depth and the average amplitude. Based on this dataset, a second relationship curve between the natural damage depth and the MFL signal amplitude was fitted and generated.

[0101] The depth values ​​of the first and second relationship curves under the same leakage magnetic signal amplitude are matched. Feature amplitude points are uniformly selected on the first curve, and the same amplitude points are found on the second curve using an interpolation algorithm. The corresponding artificial injury depth and natural injury depth data pairs are recorded. A mapping dataset of artificial injury depth and natural injury depth is constructed based on all matching points, and the data is arranged in ascending order of amplitude to form an index table.

[0102] When detecting oblique cracks, the same magnetic flux leakage detection equipment is used to scan the target area. Multi-channel magnetic flux leakage signals are acquired in real time, and the global maximum amplitude is extracted as the feature amplitude. The artificial damage depth value closest to this feature amplitude is matched in the mapping dataset and converted into the corresponding natural damage depth value according to the mapping relationship, outputting the quantized result. When the feature amplitude exceeds the mapping range, a boundary extrapolation algorithm is activated, and an accuracy warning is generated. The output includes the detection location coordinates, signal feature values, and quantized depth values.

[0103] Specifically, the artificial damage data of the calibration line established in this embodiment is shown in Table 1, which is a table of artificial damage to the calibration line.

[0104] The magnetic flux leakage detection equipment was used to detect artificial damage cut on the calibration line, and the maximum amplitude among the multiple detection channels was selected as the detection signal amplitude of the corresponding damage.

[0105] Table 1

[0106] Standard damage 1# 2# 3# 4# 5# 6# 7# 8# 9# 10# Cutting depth (unit: mm) 0.35 0.5 1.0 1.5 2.0 2.7 3.5 4.0 6.0 8.0

[0107] To ensure the reliability of the detection signal, data was collected 10 times at different speeds for artificial damage to the calibration line, and the average was taken. A fitting curve was established using the collected data, and the correlation coefficient R was calculated. 2 The closer the values ​​of artificial injury are, the larger the correlation coefficient of the fitted curve, and the more accurate the established correspondence.

[0108] The same magnetic flux leakage detection equipment was used to detect natural damage, and 1 mm of polishing was performed after each detection. The correspondence between natural damage and detection amplitude was established, and a fitting curve was built.

[0109] By combining the calibration line signal amplitude-damage depth fitting curve (i.e., the first relationship curve mentioned above) and the natural damage signal amplitude-damage depth fitting curve (i.e., the second relationship curve mentioned above), the corresponding relationship under the same leakage flux detection equipment's detection signal amplitude can be obtained. The specific calibration process is as follows: Figure 3 As shown, Figure 3 This is a specific example diagram illustrating the calibration steps of a magnetic flux leakage detection device in an embodiment of the present invention.

[0110] Table 2 shows the corresponding data of artificial injury depth and signal amplitude at the calibration line. Using the artificial injuries in Table 1 as the calibration line, the signal amplitude of the artificial injury was measured, as shown in Table 2. The relationship between the calibration line injury depth and signal amplitude fitted to Table 2 conforms to a polynomial:

[0111] y = -0.1051x 3 +1.3242x 2 -1.5659x+1.095 (1)

[0112] Table 2

[0113]

[0114]

[0115] Among them, R 2 =0.9778. The result is as follows: Figure 4 As shown, Figure 4 This is a schematic diagram illustrating the fitting of the correspondence between calibration line damage depth and signal amplitude in an embodiment of the present invention.

[0116] To accurately assess the depth of natural damage, the shallow surface of the rail was ground every 1.0 mm, and the corresponding magnetic flux leakage signal amplitude was recorded. A total of 5 grinding operations were performed. The grinding confirmed that the deepest natural damage was approximately 4.75 mm, with no trace of damage remaining after the 5th grinding. Similar to the calibration rail procedure, after each grinding, a magnetic flux leakage detection device was used to detect the damage 10 times at different speeds. The average of the recorded signal amplitudes was taken, as shown in Table 3. Table 3 presents the data corresponding to the depth of natural damage and the signal amplitude.

[0117] Table 3

[0118]

[0119] Table 4 shows the correspondence between the depth of calibration lines with the same amplitude and the depth of natural damage. Fitting the data in Table 4, we can find that the correspondence between the depth of natural damage and the signal amplitude conforms to a polynomial:

[0120] y = -0.0317x 3 +0.3534x 2 +1.3453x+0.3657 (2)

[0121] Among them, R 2 =0.9887, the result is as follows Figure 5 As shown, Figure 5 This is a specific example diagram illustrating the fitting of the correspondence between natural damage depth and signal amplitude in an embodiment of the present invention.

[0122] By combining the calibration line signal amplitude-damage depth fitting curve and the natural damage signal amplitude-damage depth fitting curve, the corresponding relationship under the same magnetic flux leakage detection equipment signal amplitude is obtained. Points in the fitting results that have the same signal amplitude as the calibration line (10 artificial damage sites) are selected for comparison. Figure 6 As shown, Figure 6 This is a specific example diagram comparing the amplitude-depth fitting of a calibration line with natural damage in an embodiment of the present invention. Table 4 shows the corresponding data for the calibration line depth and natural damage depth at the same amplitude.

[0123] Table 4

[0124]

[0125] By establishing a correspondence between artificial injury calibration lines and natural injuries through this relationship, the depth of natural injuries can be assessed by using calibration line injuries for different types of natural injuries through the relationship between the two.

[0126] To verify the reliability of the evaluation method, after calibrating the magnetic flux leakage detection equipment, 15 natural damages were selected for depth quantitative evaluation. The evaluated depth was compared with the actual depth obtained after grinding. The evaluation results are shown in Table 5.

[0127] Table 5

[0128]

[0129]

[0130] Experimental tests show that the calibrated magnetic flux leakage detection equipment has an error of less than 18%, which meets the requirements of practical applications.

[0131] The key technical point of this invention lies in establishing a mapping relationship between calibration lines, signal amplitude, and natural damage depth using a magnetic flux leakage (MFL) detection device. Since different MFL detection devices produce inconsistent signal amplitudes for the same damage due to differences in manufacturing processes, establishing this mapping relationship is a crucial prerequisite for ensuring the authenticity and validity of the detection results. Specifically, the implementation is as follows: First, a calibration line containing artificially created damage of a preset depth is prepared as a reference specimen. Simultaneously, depth profile data is obtained by performing stepped grinding on a real natural oblique crack. Then, the same MFL detection device is used to scan both the artificially created damage on the calibration line and the natural damage during the grinding process, simultaneously acquiring signal amplitudes. Based on the artificial damage depth-signal amplitude curve and the natural damage depth-signal amplitude curve, depth values ​​are matched under the same signal amplitude conditions to form a dataset showing the correspondence between the artificial damage depth and the natural damage depth on the calibration line.

[0132] The key innovation of this technology is its innovative solution to the evaluation bias caused by equipment differences. When switching between different magnetic flux leakage detection devices, only the same calibration line needs to be scanned to obtain the signal amplitude. A unified natural damage depth value can then be output through a mapping relationship, eliminating the need to rebuild the natural damage model. In this process, the stepped grinding operation of natural damage is the foundation for constructing the true depth-signal relationship, while the calibration line, as an equipment-independent conversion medium, enables the standardized output of detection results.

[0133] This invention focuses on a method for establishing a mapping relationship by combining natural damage grinding with magnetic flux leakage detection. The method comprises three essential steps: first, precisely grinding natural damage and measuring the remaining depth to construct a dataset of actual damage depth; second, using magnetic flux leakage detection equipment to simultaneously acquire signal amplitudes at each stage of grinding, forming a baseline curve of natural damage depth versus signal amplitude; and third, matching the signal amplitudes of the baseline curve of natural damage with the artificial damage curve of the calibration line, ultimately forming a conversion rule between artificial damage depth and natural damage depth. This method is applicable to any artificial damage calibration line conforming to rail material specifications. When the calibration line parameters change, reconstructing the mapping relationship through the same process still falls within the scope of this invention.

[0134] Of course, it is understood that there may be other variations of the above detailed process, and all such variations should fall within the protection scope of this invention.

[0135] In this embodiment of the invention, a calibration line containing multiple sets of artificially created damage at preset depths is pre-prepared on the rail surface; based on the scanning results of the calibration line by a magnetic flux leakage detection device under preset detection conditions, the magnetic flux leakage signal amplitude of artificially created damage at different preset depths is obtained, and a first relationship curve between the artificial damage depth and the magnetic flux leakage signal amplitude is fitted and generated; by performing step-by-step grinding on the natural oblique crack of the rail surface, the remaining depth after each grinding is obtained; the magnetic flux leakage signal amplitude corresponding to different remaining depths is obtained by the magnetic flux leakage detection device, and a second relationship curve between the natural damage depth and the magnetic flux leakage signal amplitude is fitted and generated; the depth values ​​under the same magnetic flux leakage signal amplitude are matched between the first relationship curve and the second relationship curve to establish a mapping relationship between the artificial damage depth and the natural damage depth; the magnetic flux leakage signal amplitude of the oblique crack to be tested is detected, and a quantized depth value corresponding to the magnetic flux leakage signal amplitude is output based on the mapping relationship. This invention establishes a mapping relationship between the depth of artificial damage and the depth of natural damage. By using a second relationship curve established through stepped grinding of real natural cracks, it accurately reflects the characteristics of irregular cracks and overcomes the difference between the regularity of artificial damage morphology and the dispersion of natural damage. The mapping relationship uses the calibration line as a device-independent reference. When different devices scan the same calibration line, a unified natural damage depth value is output through depth matching, eliminating the evaluation deviation caused by device differences, reducing the cost of repeated testing caused by device differences, and improving the universality and reliability of oblique crack detection in high-speed rail operation and maintenance.

[0136] As described above, this invention establishes a calibration line-signal amplitude-natural damage relationship based on different depths of cracks and natural damage under a calibration line using a magnetic flux leakage (MFL) detection device. Since different MFL detection devices, due to variations in manufacturing processes, may produce different signal amplitudes when detecting the same damage, proper calibration to establish the correspondence between the calibration line, signal amplitude, and natural damage depth is a prerequisite for ensuring the accuracy and effectiveness of MFL detection results. This relationship is established by polishing the natural damage. Through the correlation between the calibration line, signal amplitude, and natural damage, differences in detection results caused by different MFL detection devices are effectively avoided. In this embodiment, the artificial damage setting for the rail surface oblique crack calibration line is also applicable to this key point for different calibration lines. That is, when changing different artificial damage calibration lines, establishing the calibration line-signal amplitude-natural damage relationship using the method mentioned in the text is also covered by this invention.

[0137] This invention establishes a hyperbolic mapping mechanism of "artificial calibration line - natural damage," using the calibration line as an equipment-independent intermediate reference. By matching the depth of artificial / natural damage under the same signal amplitude, it converts easily detectable artificial damage signals into true natural damage depths. This retains the controllability advantage of artificial damage while incorporating the authenticity of natural damage data, fundamentally solving the problem of misjudging natural oblique cracks in high-speed railways using existing magnetic flux leakage detection technology.

[0138] This invention also provides a device for quantifying oblique cracks on railway rail surfaces, as described in the following embodiments. Since the principle by which this device solves the problem is similar to the method for quantifying oblique cracks on railway rail surfaces, the implementation of this device can refer to the implementation of the method for quantifying oblique cracks on railway rail surfaces; repeated details will not be elaborated further.

[0139] This invention also provides a device for quantifying oblique cracks on railway tracks, used to improve the accuracy of oblique crack depth assessment on high-speed railway tracks, eliminate the cost of repeated testing caused by equipment differences, and improve the universality and reliability of oblique crack detection in high-speed railway operation and maintenance. Figure 9 As shown, Figure 9 This is a schematic diagram of a railway track surface oblique crack quantification device according to an embodiment of the present invention. The device includes:

[0140] The calibration line acquisition module 901 is used to acquire calibration lines pre-prepared on the rail surface containing multiple sets of artificial damage at preset depths;

[0141] The first relationship curve establishment module 902 is used to obtain the amplitude of the magnetic flux leakage signal of artificial damage at different preset depths based on the scanning results of the calibration line by the magnetic flux leakage detection device under preset detection conditions, and to fit and generate a first relationship curve between the depth of artificial damage and the amplitude of the magnetic flux leakage signal.

[0142] The second relationship curve establishment module 903 is used to obtain the measured remaining depth after each grinding by performing step grinding on the natural oblique crack of the rail surface; and to obtain the leakage magnetic signal amplitude corresponding to different measured remaining depths by the leakage magnetic detection device, and to fit and generate a second relationship curve between the natural damage depth and the leakage magnetic signal amplitude.

[0143] The mapping relationship establishment module 904 is used to match the depth values ​​of the first relationship curve and the second relationship curve under the same leakage magnetic signal amplitude to establish a mapping relationship between the artificial damage depth and the natural damage depth.

[0144] The quantization depth output module 905 is used to detect the amplitude of the leakage magnetic signal of the oblique crack under test, and output the quantization depth value corresponding to the amplitude of the leakage magnetic signal based on the mapping relationship.

[0145] In one embodiment, based on the scanning results of the calibration line by the magnetic flux leakage detection device under preset detection conditions, the amplitude of the magnetic flux leakage signal for artificial damage at different preset depths is obtained, including:

[0146] The calibration line is repeatedly scanned multiple times at different moving speeds;

[0147] Extract the maximum amplitude of the leakage magnetic field signal after each scan;

[0148] Calculate the average signal amplitude from multiple scans of the same artificial injury;

[0149] Based on the preset depth of each artificial injury and the corresponding average signal amplitude, the first relationship curve is generated through curve fitting.

[0150] In one embodiment, the remaining depth after each grinding step is measured by performing stepped grinding on the natural oblique cracks on the rail surface, including:

[0151] Each step of the polishing process removes a preset thickness until the natural damage marks disappear.

[0152] Obtain the remaining depth after each polishing.

[0153] In one embodiment, the magnetic flux leakage detection device acquires the amplitude of the magnetic flux leakage signal corresponding to different remaining measurement depths, and fits and generates a second relationship curve between the natural damage depth and the amplitude of the magnetic flux leakage signal, including:

[0154] After each polishing, the magnetic flux leakage detection device is used to perform multiple scans under the same detection conditions to extract the maximum amplitude of the magnetic flux leakage signal.

[0155] Calculate the average signal amplitude from multiple scans at the same remaining depth;

[0156] The second relationship curve is generated by curve fitting based on each remaining depth and the corresponding average signal amplitude.

[0157] In one embodiment, the depth values ​​of the first and second relationship curves under the same leakage magnetic signal amplitude are matched to establish a mapping relationship between the depth of artificial injury and the depth of natural injury, including:

[0158] Select multiple signal amplitude points on the first relationship curve;

[0159] Find the corresponding amplitude point on the second relationship curve that is the same as the signal amplitude point;

[0160] Record the correspondence between artificial injury depth values ​​and natural injury depth values ​​under the same signal amplitude;

[0161] Based on the aforementioned correspondence, a mapping dataset between artificial injury depth and natural injury depth is established.

[0162] In one embodiment, detecting the amplitude of the magnetic flux leakage signal of the oblique crack under test and outputting a quantized depth value corresponding to the amplitude of the magnetic flux leakage signal based on the mapping relationship includes:

[0163] The magnetic flux leakage detection device is used to scan the oblique crack under test and obtain its magnetic flux leakage signal amplitude.

[0164] In the mapping relationship, match the artificial injury depth value that has the same amplitude as the acquired signal;

[0165] Based on the correspondence between artificial injury depth values ​​and natural injury depths in the mapping relationship, the corresponding natural injury depth value is output as a quantitative evaluation result.

[0166] This invention provides an embodiment of a computer device for implementing all or part of the above-described method for quantifying oblique cracks on railway rail surfaces. The computer device specifically includes the following components:

[0167] The computer device comprises a processor, memory, a communications interface, and a bus; wherein the processor, memory, and communications interface communicate with each other via the bus; the communications interface is used to realize information transmission between related devices; the computer device can be a desktop computer, tablet computer, or mobile terminal, etc., and this embodiment is not limited to these. In this embodiment, the computer device can be implemented with reference to the embodiments for implementing the method for quantifying oblique cracks on railway rail surfaces and the embodiments for implementing the device for quantifying oblique cracks on railway rail surfaces, the contents of which are incorporated herein, and repeated details will not be described again.

[0168] Figure 8This is a schematic block diagram illustrating the system configuration of the computer device 1000 according to an embodiment of this application. Figure 8 As shown, the computer device 1000 may include a central processing unit 1001 and a memory 1002; the memory 1002 is coupled to the central processing unit 1001. It is worth noting that... Figure 8 This is an example; other types of structures can also be used to supplement or replace this structure to achieve telecommunications functions or other functions.

[0169] In one embodiment, the function for quantifying oblique cracks on the railway track surface can be integrated into the central processing unit 1001. The central processing unit 1001 can be configured to perform the following control:

[0170] Obtain calibration lines pre-prepared on the rail surface containing multiple sets of artificially created damage at preset depths;

[0171] Based on the scanning results of the calibration line by the magnetic flux leakage detection device under preset detection conditions, the magnetic flux leakage signal amplitude of artificial damage at different preset depths is obtained, and a first relationship curve between the depth of artificial damage and the amplitude of magnetic flux leakage signal is generated by fitting.

[0172] By performing stepped grinding on the natural oblique cracks on the rail surface, the remaining depth after each grinding is obtained; the leakage magnetic field detection device is used to obtain the leakage magnetic field signal amplitude corresponding to different remaining depths, and a second relationship curve between the natural damage depth and the leakage magnetic field signal amplitude is generated by fitting.

[0173] The depth values ​​of artificial damage and natural damage are matched by the first relationship curve and the second relationship curve under the same leakage magnetic signal amplitude to establish a mapping relationship between the depth of artificial damage and the depth of natural damage.

[0174] The amplitude of the leakage magnetic field signal of the oblique crack under test is detected, and a quantized depth value corresponding to the amplitude of the leakage magnetic field signal is output based on the mapping relationship.

[0175] In another embodiment, the railway track surface diagonal crack quantification device can be configured separately from the central processing unit 1001. For example, the railway track surface diagonal crack quantification device can be configured as a chip connected to the central processing unit 1001, and the railway track surface diagonal crack quantification function can be realized through the control of the central processing unit.

[0176] like Figure 8 As shown, the computer device 1000 may further include: a communication module 1003, an input unit 1004, an audio processor 1005, a display 1006, and a power supply 1007. It is worth noting that the computer device 1000 does not necessarily need to include... Figure 8 All components shown; in addition, the computer device 1000 may also include Figure 8 For components not shown, please refer to existing technology.

[0177] like Figure 8 As shown, the central processing unit 1001, sometimes also referred to as a controller or operation control, may include a microprocessor or other processor device and / or logic device. The central processing unit 1001 receives input and controls the operation of various components of the computer device 1000.

[0178] The memory 1002 may be, for example, one or more of a cache, flash memory, hard drive, removable medium, volatile memory, non-volatile memory, or other suitable device. It can store the aforementioned device-related information, and may also store programs for executing that information. The central processing unit 1001 can execute the program stored in the memory 1002 to perform information storage or processing, etc.

[0179] Input unit 1004 provides input to central processing unit 1001. This input unit 1004 may be, for example, a keypad or touch input device. Power supply 1007 provides power to computer device 1000. Display 1006 displays images, text, and other display objects. This display may be, for example, an LCD display, but is not limited to this.

[0180] The memory 1002 can be a solid-state memory, such as a read-only memory (ROM), random access memory (RAM), a SIM card, etc. It can also be a memory that retains information even when power is off, can be selectively erased, and contains more data; examples of this type of memory are sometimes referred to as EPROMs, etc. The memory 1002 can also be some other type of device. The memory 1002 includes a buffer memory 1021 (sometimes referred to as a buffer). The memory 1002 may include an application / function storage unit 1022 for storing application programs and function programs or processes for executing operations of the computer device 1000 via the central processing unit 1001.

[0181] The memory 1002 may also include a data storage unit 1023 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the computer device. The driver storage unit 1024 of the memory 1002 may include various drivers for the computer device for communication functions and / or for performing other functions of the computer device (such as messaging applications, address book applications, etc.).

[0182] The communication module 1003 is a transmitter / receiver that transmits and receives signals via the antenna 1008. The communication module (transmitter / receiver) 1003 is coupled to the central processing unit 1001 to provide input signals and receive output signals, which is the same as in a conventional mobile communication terminal.

[0183] Based on different communication technologies, multiple communication modules 1003 can be configured in the same computer device, such as cellular network modules, Bluetooth modules, and / or wireless LAN modules. The communication module (transmitter / receiver) 1003 is also coupled to a speaker 1009 and a microphone 1010 via an audio processor 1005 to provide audio output via the speaker 1009 and receive audio input from the microphone 1010, thereby realizing typical telecommunications functions. The audio processor 1005 may include any suitable buffer, decoder, amplifier, etc. Furthermore, the audio processor 1005 is also coupled to a central processing unit 1001, enabling on-device recording via the microphone 1010 and on-device playback of stored sound via the speaker 1009.

[0184] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for quantifying oblique cracks on railway track surfaces.

[0185] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for quantifying oblique cracks on railway track surfaces.

[0186] In this embodiment of the invention, a calibration line containing multiple sets of artificially created damage at preset depths is pre-prepared on the rail surface; based on the scanning results of the calibration line by a magnetic flux leakage detection device under preset detection conditions, the magnetic flux leakage signal amplitude of artificially created damage at different preset depths is obtained, and a first relationship curve between the artificial damage depth and the magnetic flux leakage signal amplitude is fitted and generated; by performing step-by-step grinding on the natural oblique crack of the rail surface, the remaining depth after each grinding is obtained; the magnetic flux leakage signal amplitude corresponding to different remaining depths is obtained by the magnetic flux leakage detection device, and a second relationship curve between the natural damage depth and the magnetic flux leakage signal amplitude is fitted and generated; the depth values ​​under the same magnetic flux leakage signal amplitude are matched between the first relationship curve and the second relationship curve to establish a mapping relationship between the artificial damage depth and the natural damage depth; the magnetic flux leakage signal amplitude of the oblique crack to be tested is detected, and a quantized depth value corresponding to the magnetic flux leakage signal amplitude is output based on the mapping relationship. This invention establishes a mapping relationship between the depth of artificial damage and the depth of natural damage. By using a second relationship curve established through stepped grinding of real natural cracks, it accurately reflects the characteristics of irregular cracks and overcomes the difference between the regularity of artificial damage morphology and the dispersion of natural damage. The mapping relationship uses the calibration line as a device-independent reference. When different devices scan the same calibration line, a unified natural damage depth value is output through depth matching, eliminating the evaluation deviation caused by device differences, reducing the cost of repeated testing caused by device differences, and improving the universality and reliability of oblique crack detection in high-speed rail operation and maintenance.

[0187] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0188] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0189] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0190] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0191] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for quantifying oblique cracks on railway rail surfaces, characterized in that, include: Obtain calibration lines pre-prepared on the rail surface containing multiple sets of artificially created damage at preset depths; Based on the scanning results of the calibration line by the magnetic flux leakage detection device under preset detection conditions, the magnetic flux leakage signal amplitude of artificial damage at different preset depths is obtained, and a first relationship curve between the depth of artificial damage and the amplitude of magnetic flux leakage signal is generated by fitting. By performing stepped grinding on the natural oblique cracks on the rail surface, the remaining depth after each grinding is obtained; the leakage magnetic field detection device is used to obtain the leakage magnetic field signal amplitude corresponding to different remaining depths, and a second relationship curve between the natural damage depth and the leakage magnetic field signal amplitude is generated by fitting. The depth values ​​of artificial damage and natural damage are matched by the first relationship curve and the second relationship curve under the same leakage magnetic signal amplitude to establish a mapping relationship between the depth of artificial damage and the depth of natural damage. The amplitude of the leakage magnetic field signal of the oblique crack under test is detected, and a quantized depth value corresponding to the amplitude of the leakage magnetic field signal is output based on the mapping relationship.

2. The method as described in claim 1, characterized in that, Based on the scanning results of the calibration line by the magnetic flux leakage detection equipment under preset detection conditions, the amplitude of the magnetic flux leakage signal for artificial damage at different preset depths is obtained, including: The calibration line is repeatedly scanned multiple times at different moving speeds; Extract the maximum amplitude of the leakage magnetic field signal after each scan; Calculate the average signal amplitude from multiple scans of the same artificial injury; Based on the preset depth of each artificial injury and the corresponding average signal amplitude, the first relationship curve is generated through curve fitting.

3. The method as described in claim 1, characterized in that, By performing stepped grinding on the natural oblique cracks on the rail surface, the remaining depth after each grinding step was measured, including: Each step of the polishing process removes a preset thickness until the natural damage marks disappear. Obtain the remaining depth after each polishing.

4. The method as described in claim 1, characterized in that, The magnetic flux leakage detection device acquires the amplitude of the magnetic flux leakage signal corresponding to different remaining measurement depths, and fits and generates a second relationship curve between the natural damage depth and the amplitude of the magnetic flux leakage signal, including: After each polishing, the magnetic flux leakage detection device is used to perform multiple scans under the same detection conditions to extract the maximum amplitude of the magnetic flux leakage signal. Calculate the average signal amplitude from multiple scans at the same remaining depth; The second relationship curve is generated by curve fitting based on each remaining depth and the corresponding average signal amplitude.

5. The method as described in claim 1, characterized in that, By matching the depth values ​​of the first and second relationship curves under the same leakage magnetic signal amplitude, a mapping relationship between the depth of artificial injury and the depth of natural injury is established, including: Select multiple signal amplitude points on the first relationship curve; Find the corresponding amplitude point on the second relationship curve that is the same as the signal amplitude point; Record the correspondence between artificial injury depth values ​​and natural injury depth values ​​under the same signal amplitude; Based on the aforementioned correspondence, a mapping dataset between artificial injury depth and natural injury depth is established.

6. The method as described in claim 1, characterized in that, The amplitude of the magnetic flux leakage signal of the oblique crack under test is detected, and a quantized depth value corresponding to the amplitude of the magnetic flux leakage signal is output based on the mapping relationship, including: The magnetic flux leakage detection device is used to scan the oblique crack under test and obtain its magnetic flux leakage signal amplitude. In the mapping relationship, match the artificial injury depth value that has the same amplitude as the acquired signal; Based on the correspondence between artificial injury depth values ​​and natural injury depths in the mapping relationship, the corresponding natural injury depth value is output as a quantitative evaluation result.

7. A device for quantifying oblique cracks on railway track surfaces, characterized in that, include: The calibration line acquisition module is used to acquire calibration lines pre-prepared on the rail surface containing multiple sets of artificial damage at preset depths; The first relationship curve establishment module is used to obtain the amplitude of the magnetic flux leakage signal of artificial damage at different preset depths based on the scanning results of the calibration line by the magnetic flux leakage detection device under preset detection conditions, and to fit and generate the first relationship curve between the depth of artificial damage and the amplitude of the magnetic flux leakage signal. The second relationship curve establishment module is used to obtain the measured remaining depth after each grinding by performing stepped grinding on the natural oblique crack of the rail surface; and to obtain the leakage magnetic signal amplitude corresponding to different measured remaining depths by the leakage magnetic detection device, and to fit and generate a second relationship curve between the natural damage depth and the leakage magnetic signal amplitude. The mapping relationship establishment module is used to match the depth values ​​of the first relationship curve and the second relationship curve under the same leakage magnetic signal amplitude to establish a mapping relationship between the depth of artificial damage and the depth of natural damage. The quantization depth output module is used to detect the amplitude of the leakage magnetic signal of the oblique crack under test, and outputs the quantization depth value corresponding to the amplitude of the leakage magnetic signal based on the mapping relationship.

8. The apparatus as claimed in claim 7, characterized in that, The first relationship curve establishment module is specifically used for: The calibration line is repeatedly scanned multiple times at different moving speeds; Extract the maximum amplitude of the leakage magnetic field signal after each scan; Calculate the average signal amplitude from multiple scans of the same artificial injury; Based on the preset depth of each artificial injury and the corresponding average signal amplitude, the first relationship curve is generated through curve fitting.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 6.

11. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 6.

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