Ballastless track foundation bed surface layer hidden defect detection method and system

Abstract

The invention relates to the technical field of high-speed railway ballastless tracks, in particular to a ballastless track subgrade bed surface layer hidden defect detection method and system, and the method comprises the steps: obtaining the section size and form of a ballastless track subgrade; establishing a ballastless track-defect roadbed simulation model by adopting a discrete element-finite difference coupling method; balancing ground stress; adding foundation bed surface layer defect characteristics; applying a train load; fitting formulas of the roadbed dynamic displacement, the roadbed acceleration and the roadbed dynamic stress to the fine particle mass loss ratio are established through a numerical simulation method; the roadbed dynamic displacement, the roadbed acceleration and the roadbed dynamic stress are obtained in real time by using a sensor, and the mass loss ratio of the target fine particles is calculated to reflect the roadbed void degree. According to the invention, the void degree of the roadbed is reflected through the mass loss ratio of the target fine particles, the roadbed surface graded broken stone frost-pumping damage can be effectively detected, and the stability and safety of train operation are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of high-speed railway ballastless track, and in particular to a method and system for detecting hidden defects on the surface of a ballastless track subgrade. Background Art

[0002] As an important component of high-speed railways, the structural integrity and stability of ballastless track are directly related to the safe operation of trains. The roadbed under the track structure, as the key area for transferring train loads from the track to the roadbed, is constructed of graded crushed stone. However, there are significant differences in continuity and stiffness between graded crushed stone and ballastless track, which leads to various disasters under the influence of long-term train loads and environmental factors. These hidden defects not only affect the geometric dimensions and stability of the track, but may also cause serious safety accidents. Existing methods and technologies for detecting hidden defects have many shortcomings. Manual inspections require a lot of time and human resources. Track inspection vehicles have low detection accuracy, cannot fully cover all defect types, and cannot accurately simulate the defect-causing and disaster-causing evolution mechanism.

[0003] Among them, the most prominent problem is the mud and slurry of graded gravel on the surface of the base bed. The existing technology is unable to simulate the loss of fine particles of graded gravel, resulting in an unclear understanding of the mechanism of mud and slurry of graded gravel and an inability to detect the mud and slurry problems in high-speed railways in a timely manner. Its continued development will reduce the bearing capacity of the base bed and cause uneven settlement of the track, affecting the stability and safety of train operation. Summary of the Invention

[0004] To this end, the technical problem to be solved by the present invention is to overcome the problem that the existing technology cannot simulate the loss of fine particles of graded crushed stone, cannot timely detect the disease of mud and mud in high-speed railways, and affects the stability and safety of train operation.

[0005] To solve the above technical problems, the present invention provides a method for detecting hidden defects on the surface of a ballastless track subgrade, comprising:

[0006] Obtain the cross-sectional dimensions and form of the ballastless track subgrade;

[0007] According to the cross-sectional size and form of the ballastless track subgrade, the discrete element-finite difference coupling method is used to establish a ballastless track-defective subgrade simulation model, including:

[0008] Finite difference method was used to establish entity unit models of the foundation, subgrade bottom layer, and part of the subgrade surface layer except graded crushed stone from bottom to top. Discrete element method was used to construct a three-layer graded crushed stone model within the subgrade surface layer entity unit. Finite difference method was used to establish the track structure on the three-layer graded crushed stone model.

[0009] In the three-layer graded gravel model, fine particles are removed based on contact force to simulate the voiding phenomenon of graded gravel. The fine particle contact force ratio is used as the particle loss threshold. When the fine particle contact force is less than the average contact force, the fine particles are lost. The fine particle mass loss ratio is used as an evaluation index for the degree of subgrade voiding.

[0010] Train loads were applied to a ballastless track-defective subgrade simulation model. Numerical simulation methods were used to obtain the subgrade dynamic displacement, subgrade acceleration, and subgrade dynamic stress corresponding to different fine particle mass loss ratios. Fitting formulas for the subgrade dynamic displacement, subgrade acceleration, and subgrade dynamic stress to the fine particle mass loss ratio were established.

[0011] Sensors are used to obtain the roadbed dynamic displacement, roadbed acceleration and roadbed dynamic stress in real time. Three initial fine particle mass loss ratios are calculated according to the fitting formula. The weighted average of the three initial fine particle mass loss ratios is used as the target fine particle mass loss ratio to reflect the degree of roadbed voiding.

[0012] Preferably, a three-layer graded crushed stone model is constructed by layered compaction, comprising:

[0013] For each layer of graded gravel, first add graded gravel and then add loading plates; apply compaction load on the loading plates to press the graded gravel layer to 0.15 meters; when the displacement of the graded gravel layer reaches stability, remove the loading plates and add the next layer of graded gravel.

[0014] Preferably, the track structure comprises, from bottom to top, a sealing layer, a base plate, self-compacting concrete, a slab, sleepers and a rail track.

[0015] Preferably, after establishing the ballastless track-defective roadbed simulation model, the method further includes: performing ground stress balance on the ballastless track-defective roadbed simulation model, including:

[0016] The initial boundary conditions of the ballastless track-defective roadbed simulation model are set, and gravity is applied to the model to simulate the gravity stress state of the rock and soil in its natural state.

[0017] Preferably, the formula for the fine particle contact force ratio is expressed as:

[0018]

[0019] Among them, f p represents the fine particle contact force ratio, F i represents the ith contact force of the fine particle, m is the number of contacts of the fine particles, C is the total number of contacts, and f j represents the jth contact force.

[0020] Preferably, the formula for the fine particle mass loss ratio is expressed as:

[0021]

[0022] Among them, l p represents the mass loss ratio of fine particles, m l represents the mass of fine particles lost, and m represents the total mass of particles.

[0023] Preferably, a three-level Fourier series is used to represent the train load, and the formula is:

[0024]

[0025] Where F(t) represents the train load, t represents the loading time, A0 represents the axle load, and A n and B n Both represent the third-order Fourier coefficients, f represents the loading frequency, and T represents the loading period.

[0026] Preferably, the fitting formula of the roadbed dynamic displacement and the fine particle mass loss ratio is expressed as:

[0027]

[0028] Among them, y1 represents the dynamic displacement of the roadbed, l p represents the fine particle mass loss ratio, A 10 、A 11 、A 12 and A 13 represents the fitting parameters;

[0029] The fitting formula of roadbed acceleration and fine particle mass loss ratio is expressed as:

[0030]

[0031] Among them, y2 represents the roadbed acceleration, A 20 、A 21 、A 22 、A 23 and A 24 represents the fitting parameters;

[0032] The fitting formula of roadbed dynamic stress and fine particle mass loss ratio is expressed as:

[0033]

[0034] Among them, y3 represents the dynamic stress of the roadbed, A 30 、A 31 、A 32 、A 33 、A 34 and A 35 represents the fitting parameters.

[0035] Preferably, three microscopic indicators, namely coordination number, force chain and anisotropy, are used as evaluation indicators for the ballastless track-defective roadbed simulation model.

[0036] The present invention also provides a ballastless track subgrade surface hidden defect detection system, comprising:

[0037] Roadbed acquisition module, used to obtain the cross-sectional size and form of ballastless track roadbed;

[0038] The model building module is used to build a ballastless track-defective roadbed simulation model using the discrete element-finite difference coupling method, including:

[0039] Finite difference method was used to establish entity unit models of the foundation, subgrade bottom layer, and part of the subgrade surface layer except graded crushed stone from bottom to top. Discrete element method was used to construct a three-layer graded crushed stone model within the subgrade surface layer entity unit. Finite difference method was used to establish the track structure on the three-layer graded crushed stone model.

[0040] The simulation module is used to remove fine particles based on contact force in a three-layer graded gravel model to simulate the voiding phenomenon of graded gravel. The fine particle contact force ratio is used as the particle loss threshold. When the fine particle contact force is less than the average contact force, the fine particles are lost. The fine particle mass loss ratio is used as an evaluation indicator for the degree of roadbed voiding.

[0041] A fitting module is used to apply train loads to the ballastless track-defective roadbed simulation model. Through numerical simulation methods, the subgrade dynamic displacement, subgrade acceleration, and subgrade dynamic stress corresponding to different fine particle mass loss ratios are obtained, and fitting formulas for subgrade dynamic displacement, subgrade acceleration, and subgrade dynamic stress to fine particle mass loss ratio are established respectively.

[0042] The detection module is used to use sensors to obtain the roadbed dynamic displacement, roadbed acceleration and roadbed dynamic stress in real time, and to calculate the three initial fine particle mass loss ratios according to the fitting formula. The weighted average of the three initial fine particle mass loss ratios is used as the target fine particle mass loss ratio to reflect the degree of roadbed voiding.

[0043] The above technical solution of the present invention has the following beneficial effects compared with the prior art:

[0044] The present invention discloses a method for detecting hidden defects in the surface layer of a ballastless track subgrade. A ballastless track-defect subgrade simulation model is established using a discrete element method coupled with a finite difference method. A three-layer graded gravel model is constructed within the simulation model to simulate graded gravel. When a load is applied to the simulation model, contact forces are generated between fine particles in the three-layer graded gravel model. The fine particle contact force ratio is used as the particle loss threshold, and the fine particle mass loss ratio is used as an evaluation index for the degree of subgrade voiding. Numerical simulation is used to establish a fitting relationship between the subgrade dynamic displacement, acceleration, and dynamic stress, and the fine particle mass loss ratio. Sensors are used to obtain the subgrade dynamic displacement, acceleration, and dynamic stress in real time. The fitting relationship obtained from the simulation model is used to calculate the target fine particle mass loss ratio, providing an effective indicator for the degree of subgrade voiding. The present invention uses the target fine particle mass loss ratio to reflect the degree of subgrade voiding. This method can effectively detect mud and slurrying problems in the graded gravel surface layer of the subgrade, providing a theoretical basis for addressing the voiding hazards of graded gravel, enhancing the smoothness and safety of train operation, and contributing to the maintenance of routine high-speed railway operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments of the present invention in conjunction with the accompanying drawings, wherein:

[0046] Figure 1 This is a flow chart of a method for detecting hidden defects on the surface of a ballastless track subgrade of the present invention;

[0047] Figure 2 It is a schematic diagram of constructing a ballastless track-defective roadbed simulation model, where Figure 2 (1) is a schematic diagram of the ballastless track-defective roadbed simulation model established by the discrete element-finite difference coupling method. Figure 2 (2) is a schematic diagram of ground stress balance. Figure 2 (3) is a schematic diagram of train load application;

[0048] Figure 3 is a schematic diagram of the fine particle loss mechanism;

[0049] Figure 4 is a schematic diagram of the relationship between the fine particle loss mass ratio and the fine particle contact force ratio;

[0050] Figure 5 This is a schematic diagram of the change in dynamic deformation of the surface layer of the base bed in the present invention;

[0051] Figure 6 Schematic diagram of the relationship between the fine particle mass loss ratio and the dynamic deformation of the bed surface layer of the present invention;

[0052] Figure 7 It is a schematic diagram of the change of acceleration of the surface layer of the base bed in the present invention;

[0053] Figure 8 Schematic diagram of the relationship between the fine particle mass loss ratio and the acceleration of the bed surface layer according to the present invention;

[0054] Figure 9 Schematic diagram of the change of dynamic stress on the surface of the subgrade in the present invention;

[0055] Figure 10 Schematic diagram of the relationship between the fine particle mass loss ratio and the dynamic stress of the base bed surface layer of the present invention;

[0056] Figure 11 Schematic diagram of the change of coordination number of the present invention;

[0057] Figure 12 Schematic diagram of the relationship between the mass loss ratio of fine particles and the coordination number of the present invention;

[0058] Figure 13 It is a schematic diagram of the change of the strong chain in the present invention;

[0059] Figure 14 Schematic diagram of the relationship between the mass loss ratio of fine particles and the strong chain of the present invention;

[0060] Figure 15 is a schematic diagram of the anisotropy of normal contact force. DETAILED DESCRIPTION

[0061] The present invention will be further described below with reference to the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it. However, the embodiments are not intended to limit the present invention.

[0062] Example 1

[0063] Reference Figure 1 As shown, the present invention provides a method for detecting hidden defects on the surface of a ballastless track subgrade, comprising:

[0064] S1: Obtain the cross-sectional dimensions and form of the ballastless track subgrade.

[0065] In this embodiment, the cross-sectional dimensions and form are determined according to the "High-Speed Railway Design Specifications" or the actual roadbed. For specific cross-sectional dimensions, refer to Table 1.

[0066] Table 1. Roadbed cross-section dimensions

[0067]

[0068] S2: Based on the cross-sectional size and form of the ballastless track subgrade, a discrete element-finite difference coupling method is used to establish a ballastless track-defective subgrade simulation model, including:

[0069] S201: Determine the discrete element contact parameters of the graded gravel in the surface layer of the subgrade.

[0070] S202: Using the finite difference method, solid unit models of the foundation, subgrade bottom layer, and part of the subgrade surface layer except for the graded crushed stone are established from bottom to top.

[0071] S203: A three-layer graded gravel model is constructed in the solid unit of the subgrade surface layer using the discrete element method to simulate mud bubbling.

[0072] Preferably, a three-layer graded gravel model is constructed by layered compaction, including: for each layer of graded gravel, first adding graded gravel and then adding a loading plate; applying a compaction load on the loading plate to press the graded gravel layer to 0.15 meters; when the displacement of the graded gravel layer reaches stability, removing the loading plate and adding the next layer of graded gravel.

[0073] The parameter settings of the three-layer graded gravel model are shown in Table 2.

[0074] Table 2. Parameter calibration results of graded gravel in the three-layer graded gravel model

[0075]

[0076] S204: The track structure is established on the three-layer graded gravel model using the finite difference method. From bottom to top, it includes: sealing layer, base plate, self-compacting concrete, slab, sleepers, and rails. The parameter settings are shown in Table 3.

[0077] Table 3. Parameter values in track structure

[0078]

[0079] S205: Obtain the dynamic response of the roadbed through acceleration sensors and displacement sensors installed on the roadbed surface, and determine the accuracy of the model by comparing the model with actual measurements.

[0080] The simulation parameters of the ballastless track-defective roadbed simulation model constructed in this embodiment are determined based on the parameter calibration method in the second step and existing research literature. In addition, to ensure the reliability of the hybrid model, it is necessary to verify the accuracy of the simulation parameters through field tests.

[0081] The dynamic response of the roadbed was captured using accelerometers and displacement sensors installed on the roadbed surface. The accelerometers had a sensitivity of 500 pC / g and a range of 150 g; the displacement sensors had a sensitivity of 1 mV / μm and a range of 3 mm. It is important to note that the test train had an axle weight of 14 tons, a fixed wheelbase of 2.5 meters, and a total train length of 201.4 meters. Furthermore, to minimize environmental impact on the test results during the field tests, multiple tests were conducted at different speeds. Linear functions were used to fit the upper and lower limits of the measured roadbed dynamic deformation and acceleration. It can be observed that the DEM-FDM coupled simulation results were all within the measurement range.

[0082] Figure 2 It is a schematic diagram of constructing a ballastless track-defective roadbed simulation model, where Figure 2 (1) is a schematic diagram of the ballastless track-defective roadbed simulation model established by the discrete element-finite difference coupling method. Figure 2 (2) is a schematic diagram of ground stress balance. Figure 2 (3) in the figure is a schematic diagram of applying train load.

[0083] S3: Conduct ground stress balance on the ballastless track-defective roadbed simulation model, including:

[0084] The initial boundary conditions of the ballastless track-defective roadbed simulation model are set, and gravity is applied to the model to simulate the gravity stress state of the rock and soil in its natural state.

[0085] S4: Add subgrade surface defect features to the ballastless track-defective subgrade simulation model.

[0086] In the three-layer graded crushed stone model, the removal of fine particles based on contact force is used to simulate the voiding phenomenon of graded crushed stone.

[0087] In this embodiment, the fine particle contact force ratio is used as the particle loss threshold. When the fine particle contact force is less than the average contact force, the fine particles are lost. The formula for the fine particle contact force ratio is:

[0088]

[0089] Among them, f p represents the fine particle contact force ratio, F i represents the ith contact force of the fine particle, m is the number of contacts of the fine particles, C is the total number of contacts, and f j represents the jth contact force.

[0090] The fine particle mass loss ratio is used as an evaluation index for the degree of subgrade voiding, and the formula is:

[0091]

[0092] Among them, l p represents the mass loss ratio of fine particles, m l represents the mass of fine particles lost, and m represents the total mass of particles.

[0093] The fine particle mass loss ratio l p To quantify the degree of particle loss, the fine particle loss mechanism is as follows Figure 3 The relationship between the fine particle loss mass ratio and the fine particle contact force ratio is shown in Figure 4 shown.

[0094] S5: Applying train loads to the ballastless track-defective roadbed simulation model.

[0095] The train load is expressed using a three-level Fourier series, and the formula is:

[0096]

[0097] Where F(t) represents the train load, t represents the loading time, A0 represents the axle load, and A n and B n Both represent the third-order Fourier coefficients, f represents the loading frequency, and T represents the loading period.

[0098] S6: Through numerical simulation methods, the subgrade dynamic displacement, subgrade acceleration and subgrade dynamic stress corresponding to different fine particle mass loss ratios are obtained, and fitting formulas for subgrade dynamic displacement, subgrade acceleration and subgrade dynamic stress and fine particle mass loss ratio are established respectively.

[0099] The ballastless track-defective roadbed simulation model is calculated in the gravity field until the maximum unbalanced force ratio is less than 10 -5 .

[0100] The fitting formula of roadbed dynamic displacement and fine particle mass loss ratio is expressed as:

[0101]

[0102] Among them, y1 represents the dynamic displacement of the roadbed, l p represents the fine particle mass loss ratio, A 10 、A 11 、A 12 and A 13 represents the fitting parameters.

[0103] According to the Technical Specifications for Dynamic Acceptance of High-Speed Railway Projects, the dynamic deformation of the ballastless track subgrade must be less than the specified limit of 0.22mm. Figure 5 This is a schematic diagram of the change in dynamic deformation of the surface layer of the base bed in the present invention; Figure 6 This is a schematic diagram of the relationship between the fine particle mass loss ratio and the dynamic deformation of the base bed surface. Figure 5 As shown, when l p When ≤3%, the surface of the subgrade mainly shows elastic deformation, and the dynamic deformation is consistent with the applied load, showing an "M" shape. p When the deformation rate is greater than 3%, the graded crushed stone mainly shows plastic deformation, and the dynamic deformation gradually increases with the increase of loading time. Figure 6 As shown, with l p As l increases, the dynamic deformation shows a trend of increasing slowly at first and then rapidly. p When ≤3%, the dynamic deformation is less than the limit of 0.22mm. p When the content is >3%, the skeleton structure of the graded crushed stone changes, the particles are rearranged, and the graded crushed stone undergoes significant plastic deformation, which leads to the hollowing of the roadbed and reduces the service performance of the high-speed railway roadbed.

[0104] The fitting formula of roadbed acceleration and fine particle mass loss ratio is expressed as:

[0105]

[0106] Among them, y2 represents the roadbed acceleration, A 20 、A 21 、A 22 、A 23 and A 24 represents the fitting parameters.

[0107] According to the Technical Specifications for Dynamic Acceptance of High-Speed Railway Projects, the acceleration of ballastless track subgrade must be less than 10m / s 2 . Figure 7 It is a schematic diagram of the change of acceleration of the surface layer of the base bed in the present invention; Figure 8 This is a schematic diagram of the relationship between the fine particle mass loss ratio and the acceleration of the bed surface. Figure 7 As shown, when l p =11%, the acceleration of the second train bogie is zero when it passes, which indicates that there is complete separation between the graded crushed stone and the base plate. Figure 8 As shown, with l p With the increase of the roadbed acceleration, the roadbed acceleration increases slowly at first, then decreases rapidly, and p =9% reaches its peak value. Therefore, it can be seen that when l p When ≤3%, the acceleration is less than 10m / s 2 Moreover, when l p When the value is greater than 3%, the degree of voiding on the surface of the subgrade gradually increases, and the relative coordination deformation between the subgrade bottom surface and the base plate becomes more significant. p When it is >9%, there is complete separation between the graded crushed stone and the base plate, causing the acceleration to approach zero.

[0108] The fitting formula of roadbed dynamic stress and fine particle mass loss ratio is expressed as:

[0109]

[0110] Among them, y3 represents the dynamic stress of the roadbed, A 30 、A 31 、A 32 、A 33 、A 34 and A 35 represents the fitting parameters.

[0111] According to the Technical Specifications for Dynamic Acceptance of High-Speed Railway Projects, the dynamic stress of the subgrade surface must be less than 100kPa. Figure 9 Schematic diagram of the change of dynamic stress on the surface of the subgrade in the present invention; Figure 10 This is a schematic diagram of the relationship between the fine particle mass loss ratio and the dynamic stress of the base bed surface. Figure 9 As shown, when l p When ≤3%, the dynamic stress of the roadbed is distributed in an "M" shape, and when l p When the dynamic stress is greater than 3%, it gradually decreases with the increase of loading time. Figure 10 As shown, the dynamic stress increases with l p The increase first rises rapidly, then decreases slowly, and p =3%. Therefore, it can be seen that the dynamic stress of the subgrade at different voiding levels is less than the limit of 100 kPa, making it difficult to evaluate the performance of the high-speed railway subgrade based on dynamic stress.

[0112] S7: Three microscopic indices, namely coordination number, force chain and anisotropy, are used as evaluation indicators for the ballastless track-defective roadbed simulation model.

[0113] Based on the evolution characteristics of the coordination number, the influence of the voids in graded crushed stone on the dynamic performance of the roadbed is studied. The calculation formula is as follows:

[0114]

[0115] where Z represents the coordination number, N represents the total number of particles, and N0 and N1 are the numbers of particles with zero contact and one contact, respectively.

[0116] Figure 11 Schematic diagram of the change of coordination number of the present invention; Figure 12 Schematic diagram of the relationship between the mass loss ratio of fine particles and the coordination number of the present invention. Figure 11 As shown, with l p As the number of coordination decreases, it gradually decreases and remains stable when the second bogie passes through, especially when l p >9%. This indicates that when l pWhen the percentage is greater than 9%, the graded crushed stone gradually separates from the base plate, resulting in a gradual reduction in the train load transferred from the track structure to the base surface. Figure 12 As shown, the coordination number increases with l p This indicates that the density of the internal surface layer of the base bed decreases and the degree of voids increases.

[0117] The force chain is closely related to the ability of coarse-grained soil to withstand external loads and is usually defined by two indicators: the average contact force F a and contact direction δ, the formula is expressed as:

[0118]

[0119] Among them, F represents the strong chain, F s is the force chain, F a is the average force chain, and δ is the angle between the force chain and the horizontal plane.

[0120] Figure 13 It is a schematic diagram of the change of the strong chain in the present invention; Figure 14 Schematic diagram of the relationship between the mass loss ratio of fine particles and the strength chain of the present invention. Figure 13 As shown, when l p <11%, the strength chain presents an "M" shape consistent with the train load, and when l p = 11%, the force chain approaches zero when the second bogie passes. This indicates that when l p =11%, the gap between the graded crushed stone and the base plate is completely empty, which prevents the train load from being transferred to the surface of the base bed and makes the internal contact of the graded crushed stone tend to be stable. Figure 14 As shown in Figure 2, the force chain shows a trend of first increasing slowly and then decreasing rapidly. p When l is less than 3% and the internal skeleton structure of graded crushed stone remains unchanged, the loss of fine particles strengthens the contact interaction between coarse particles, resulting in an increase in strong chains. p The increase in the fine particles leads to a decrease in the contact interaction between the subgrade surface and the base plate, which reduces the impact of the train load on the force chain. p =11%, the strength chain approaches zero. In short, the strength chain is the most sensitive microstructural index to characterize the degree of voids in graded crushed stone.

[0121] In the two-dimensional model, the contact anisotropy of graded crushed stone is quantified to further reveal the degassing mechanism of the subgrade surface layer. The formula is expressed as:

[0122]

[0123] Where E(θ) represents the contact anisotropy, a nA parameter that defines the degree of anisotropy in the contact direction, θ n This defines the direction of anisotropy.

[0124] Figure 15 is a schematic diagram of the anisotropy of normal contact force. Figure 15 As shown, when v = 400km / h, A l =13.5t, the anisotropy of the normal contact force of the roadbed at different stages (t = 0.02s, t = 0.11s and t = 0.18s) was quantified. It can be observed that when the fine particle mass loss ratio is l p = 0%, the main direction of the contact force anisotropy shows a vertical-horizontal-vertical pattern over time; and l p >0%, the main axis direction always remains vertical. In addition, as l p As the contact anisotropy increases, the degree of contact anisotropy gradually decreases, and the main direction of the contact force gradually deviates from the vertical direction. This indicates that due to the loss of fine particles, the spatial structure inside the graded gravel has changed, causing the particles to rearrange in the vertical direction, thereby reducing the ability of the subgrade surface to withstand vertical loads.

[0125] S8: Use sensors to obtain the roadbed dynamic displacement, roadbed acceleration and roadbed dynamic stress in real time, and calculate the three initial fine particle mass loss ratios according to the fitting formula. The weighted average of the three initial fine particle mass loss ratios is used as the target fine particle mass loss ratio to reflect the degree of roadbed voiding.

[0126] In summary, the method for detecting hidden defects in the surface layer of a ballastless track subgrade described in the present invention adopts a discrete element-finite difference coupling method to establish a ballastless track-defective roadbed simulation model, and constructs a three-layer graded gravel model in the simulation model to simulate the graded gravel; after a load is applied to the simulation model, contact force is generated between fine particles in the three-layer graded gravel model, and the fine particle contact force ratio is used as the particle loss threshold, and the fine particle mass loss ratio is used as an evaluation index for the degree of roadbed voiding. Numerical simulation is used to establish a fitting relationship between the roadbed dynamic displacement, roadbed acceleration, and roadbed dynamic stress and the fine particle mass loss ratio; the roadbed dynamic displacement, roadbed acceleration, and roadbed dynamic stress are acquired in real time by sensors, and the target fine particle mass loss ratio is calculated using the fitting relationship obtained by the simulation model, thereby providing an effective indicator for the degree of roadbed voiding. The present invention reflects the degree of roadbed voiding through the target fine particle mass loss ratio, can effectively detect the mud and slurry disease of graded crushed stone on the surface of the subgrade, provides a theoretical basis for solving the disaster of graded crushed stone voiding, enhances the stability and safety of train operation, and helps maintain the daily operation of high-speed railways.

[0127] Example 2

[0128] Based on the method for detecting hidden defects on the surface of a ballastless track subgrade described in Example 1, this embodiment provides a system for detecting hidden defects on the surface of a ballastless track subgrade, comprising:

[0129] Roadbed acquisition module, used to obtain the cross-sectional size and form of ballastless track roadbed;

[0130] The model building module is used to build a ballastless track-defective roadbed simulation model using the discrete element-finite difference coupling method, including:

[0131] Finite difference method was used to establish entity unit models of the foundation, subgrade bottom layer, and part of the subgrade surface layer except graded crushed stone from bottom to top. Discrete element method was used to construct a three-layer graded crushed stone model within the subgrade surface layer entity unit. Finite difference method was used to establish the track structure on the three-layer graded crushed stone model.

[0132] The simulation module is used to remove fine particles based on contact force in a three-layer graded gravel model to simulate the voiding phenomenon of graded gravel. The fine particle contact force ratio is used as the particle loss threshold. When the fine particle contact force is less than the average contact force, the fine particles are lost. The fine particle mass loss ratio is used as an evaluation indicator for the degree of roadbed voiding.

[0133] A fitting module is used to apply train loads to the ballastless track-defective roadbed simulation model. Through numerical simulation methods, the subgrade dynamic displacement, subgrade acceleration, and subgrade dynamic stress corresponding to different fine particle mass loss ratios are obtained, and fitting formulas for subgrade dynamic displacement, subgrade acceleration, and subgrade dynamic stress to fine particle mass loss ratio are established respectively.

[0134] The detection module is used to use sensors to obtain the roadbed dynamic displacement, roadbed acceleration and roadbed dynamic stress in real time, and to calculate the three initial fine particle mass loss ratios according to the fitting formula. The weighted average of the three initial fine particle mass loss ratios is used as the target fine particle mass loss ratio to reflect the degree of roadbed voiding.

[0135] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0136] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0137] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0138] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0139] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will appreciate that other variations or modifications can be made based on the above description. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. A method for detecting hidden defects on the surface of a ballastless track subgrade, characterized in that: include: Obtain the cross-sectional dimensions and form of the ballastless track subgrade; According to the cross-sectional size and form of the ballastless track subgrade, the discrete element-finite difference coupling method is used to establish a ballastless track-defective subgrade simulation model, including: Finite difference method was used to establish entity unit models of the foundation, subgrade bottom layer, and part of the subgrade surface layer except graded crushed stone from bottom to top. Discrete element method was used to construct a three-layer graded crushed stone model within the subgrade surface layer entity unit. Finite difference method was used to establish the track structure on the three-layer graded crushed stone model. In the three-layer graded gravel model, fine particles are removed based on contact force to simulate the voiding phenomenon of graded gravel. The fine particle contact force ratio is used as the particle loss threshold. When the fine particle contact force is less than the average contact force, the fine particles are lost. The fine particle mass loss ratio is used as an evaluation index for the degree of subgrade voiding. Train loads were applied to a ballastless track-defective subgrade simulation model. Numerical simulation methods were used to obtain the subgrade dynamic displacement, subgrade acceleration, and subgrade dynamic stress corresponding to different fine particle mass loss ratios. Fitting formulas for the subgrade dynamic displacement, subgrade acceleration, and subgrade dynamic stress to the fine particle mass loss ratio were established. Sensors are used to obtain the roadbed dynamic displacement, roadbed acceleration and roadbed dynamic stress in real time. Three initial fine particle mass loss ratios are calculated according to the fitting formula. The weighted average of the three initial fine particle mass loss ratios is used as the target fine particle mass loss ratio to reflect the degree of roadbed voiding.

2. A method for detecting hidden defects on the surface of a ballastless track subgrade according to claim 1, characterized in that: A three-layer graded gravel model was constructed through layered compaction, including: For each layer of graded gravel, first add graded gravel and then add loading plates; apply compaction load on the loading plates to press the graded gravel layer to 0.15 meters; when the displacement of the graded gravel layer reaches stability, remove the loading plates and add the next layer of graded gravel.

3. The method for detecting hidden defects on the surface of ballastless track subgrade according to claim 1, characterized in that: The track structure includes from bottom to top: sealing layer, base plate, self-compacting concrete, slab, sleepers and rail tracks.

4. The method for detecting hidden defects on the surface of ballastless track subgrade according to claim 1, characterized in that: After establishing the ballastless track-defective roadbed simulation model, the following steps are also included: performing ground stress balance on the ballastless track-defective roadbed simulation model, including: The initial boundary conditions of the ballastless track-defective roadbed simulation model are set, and gravity is applied to the model to simulate the gravity stress state of the rock and soil in its natural state.

5. The method for detecting hidden defects on the surface of ballastless track subgrade according to claim 1, characterized in that: The formula for the fine particle contact force ratio is expressed as: Among them, f p represents the fine particle contact force ratio, F i represents the ith contact force of the fine particle, m is the number of contacts of the fine particles, C is the total number of contacts, and f j represents the jth contact force.

6. The method for detecting hidden defects on the surface of ballastless track subgrade according to claim 1, characterized in that: The formula for the fine particle mass loss ratio is: Among them, l p represents the mass loss ratio of fine particles, m l represents the mass of fine particles lost, and m represents the total mass of particles.

7. The method for detecting hidden defects on the surface of ballastless track subgrade according to claim 1, characterized in that: The train load is expressed using a three-level Fourier series, and the formula is: Where F(t) represents the train load, t represents the loading time, A0 represents the axle load, and A n and B n Both represent the third-order Fourier coefficients, f represents the loading frequency, and T represents the loading period.

8. The method for detecting hidden defects on the surface of ballastless track subgrade according to claim 1, characterized in that: The fitting formula of roadbed dynamic displacement and fine particle mass loss ratio is expressed as: Among them, y1 represents the dynamic displacement of the roadbed, l p represents the fine particle mass loss ratio, A 10 、A 11 、A 12 and A 13 represents the fitting parameters; The fitting formula of roadbed acceleration and fine particle mass loss ratio is expressed as: Among them, y2 represents the roadbed acceleration, A 20 、A 21 、A 22 、A 23 and A 24 represents the fitting parameters; The fitting formula of roadbed dynamic stress and fine particle mass loss ratio is expressed as: Among them, y3 represents the dynamic stress of the roadbed, A 30 、A 31 、A 32 、A 33 、A 34 and A 35 represents the fitting parameters.

9. The method for detecting hidden defects on the surface of ballastless track subgrade according to claim 1, characterized in that: Three microscopic indices, namely coordination number, force chain and anisotropy, are used as evaluation indicators for the ballastless track-defective roadbed simulation model.

10. A ballastless track subgrade surface hidden defect detection system, characterized in that: include: Roadbed acquisition module, used to obtain the cross-sectional size and form of ballastless track roadbed; The model building module is used to build a ballastless track-defective roadbed simulation model using the discrete element-finite difference coupling method, including: The finite difference method is used to establish solid unit models of the foundation, subgrade layer, and part of the subgrade surface layer excluding graded gravel from bottom to top. The discrete element method is used to construct a three-layer graded gravel model within the subgrade surface solid unit. The finite difference method is used to establish the track structure on the three-layer graded gravel model. The simulation module is used to remove fine particles based on contact force in the three-layer graded gravel model to simulate the degassing phenomenon of graded gravel. The fine particle contact force ratio is used as the particle loss threshold. When the fine particle contact force is less than the average contact force, the fine particles are lost. The fine particle mass loss ratio is used as an evaluation indicator of the degree of subgrade degassing. A fitting module is used to apply train loads to the ballastless track-defective roadbed simulation model. Through numerical simulation methods, the subgrade dynamic displacement, subgrade acceleration, and subgrade dynamic stress corresponding to different fine particle mass loss ratios are obtained, and fitting formulas for subgrade dynamic displacement, subgrade acceleration, and subgrade dynamic stress to fine particle mass loss ratio are established respectively. The detection module is used to use sensors to obtain the roadbed dynamic displacement, roadbed acceleration and roadbed dynamic stress in real time, and to calculate the three initial fine particle mass loss ratios according to the fitting formula. The weighted average of the three initial fine particle mass loss ratios is used as the target fine particle mass loss ratio to reflect the degree of roadbed voiding.

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