Railway infrastructure deformation simulation method, device, equipment and medium

Abstract

The invention provides a railway infrastructure deformation simulation method and device, equipment and a medium, and relates to the technical field of safety monitoring, and the method comprises the steps: obtaining historical load parameters and a historical space-time development curve of a target facility; obtaining an initial space-time development curve; adjusting the line model, and taking the corresponding basic deformation simulation model as a target deformation simulation model; a sample set is formed based on all the working condition data and the corresponding deformation; training a preset neural network model based on the sample set to obtain a target deformation prediction model; and inputting the target working condition data into the target deformation prediction model to obtain the deformation of the target facility. According to the method, the line model is constructed and the load is applied through the similarity theory, and the change rule of the line model under various load working conditions is acquired by adopting the non-basic deformation monitoring device, so that the control of the whole deformation process is relatively simple, the basic deformation of various lines can be simulated, the cost is relatively low, and the simulation result is relatively accurate.

Description

Technical Field

[0001] The present invention relates to the field of safety monitoring technology, and in particular to a simulation method, device, equipment and medium for railway infrastructure deformation. Background Art

[0002] The railway line is an ultra-long strip structure with a complex and changeable geological environment underneath. Foundation deformation will cause changes in the stress state of the structure, thereby affecting the smoothness of the structure. The existing technology can only simulate the longitudinal settlement deformation in the railway foundation deformation simulation, which is quite different from the objective reality. In terms of deformation data collection, the existing technical methods mostly collect deformation data through strain gauges, which is complicated and easily affected by the external environment. Summary of the invention

[0003] The purpose of the present invention is to provide a method, device, equipment and medium for simulating deformation of railway infrastructure to improve the above problems. In order to achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0004] In a first aspect, the present application provides a method for simulating deformation of railway infrastructure, comprising:

[0005] Acquire historical load parameters and historical spatiotemporal development curves of target facilities, wherein the historical spatiotemporal development curves are used to characterize spatiotemporal deformation characteristics of the target facilities;

[0006] Bringing the historical load parameters into a pre-built basic deformation simulation model to obtain an initial time-space development curve, wherein the basic deformation simulation model at least includes a line model and a deformation model, wherein the line model is a reduced-size model corresponding to the target facility built based on geometric similarity theory, and the deformation model is used to apply load to the line model;

[0007] Adjusting the line model until the overall similarity between the initial space-time development curve and the historical space-time development curve is greater than a first set threshold, and using the corresponding basic deformation simulation model as a target deformation simulation model;

[0008] Bringing different working condition data into the target deformation simulation model to obtain corresponding deformation amounts, and forming a sample set based on all working condition data and corresponding deformation amounts, wherein the working condition data includes lateral load, longitudinal load and shear load;

[0009] Training a preset neural network model based on the sample set, and when the preset model index meets the set conditions, stopping the training to obtain a target deformation prediction model;

[0010] The target operating condition data is input into the target deformation prediction model to obtain the deformation amount of the target facility.

[0011] In a second aspect, the present application also provides a simulation device for railway infrastructure deformation, comprising:

[0012] A first acquisition unit is used to acquire historical load parameters and historical spatiotemporal development curves of target facilities, wherein the historical spatiotemporal development curves are used to characterize spatiotemporal deformation characteristics of the target facilities;

[0013] A first input unit is used to input the historical load parameters into a pre-built basic deformation simulation model to obtain an initial time-space development curve, wherein the basic deformation simulation model at least includes a line model and a deformation model, wherein the line model is a reduced-size model corresponding to the target facility built based on geometric similarity theory, and the deformation model is used to apply load to the line model;

[0014] an adjusting unit, configured to adjust the line model until the overall similarity between the initial spatiotemporal development curve and the historical spatiotemporal development curve is greater than a first set threshold, and use the corresponding basic deformation simulation model as a target deformation simulation model;

[0015] A second input unit is used to input different working condition data into the target deformation simulation model to obtain corresponding deformation amounts, and to form a sample set based on all working condition data and corresponding deformation amounts, wherein the working condition data includes lateral load, longitudinal load and shear load;

[0016] A training unit, used to train a preset neural network model based on the sample set, and when the preset model index meets the set conditions, stop the training to obtain a target deformation prediction model;

[0017] The input unit is used to input the target operating condition data into the target deformation prediction model to obtain the deformation amount of the target facility.

[0018] In a third aspect, the present application also provides a simulation device for railway infrastructure deformation, including:

[0019] Memory for storing computer programs;

[0020] A processor is used to implement the steps of the method for simulating the deformation of railway infrastructure when executing the computer program.

[0021] In a fourth aspect, the present application further provides a readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned simulation method based on railway infrastructure deformation are implemented.

[0022] The beneficial effects of the present invention are:

[0023] The present invention constructs a line model and applies loads through similarity theory, and adopts a non-foundation deformation monitoring device to collect the changing rules of the line model under various load conditions, so that the control of the entire deformation process is relatively simple, and the foundation deformation of various lines can be simulated, the cost is low, and the simulation results are relatively accurate.

[0024] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by implementing the embodiments of the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 It is a schematic flow chart of a method for simulating railway infrastructure deformation according to an embodiment of the present invention;

[0027] Figure 2 It is a schematic diagram of the structure of the basic deformation simulation model described in an embodiment of the present invention;

[0028] Figure 3 It is a schematic structural diagram of the longitudinal lifting device described in an embodiment of the present invention;

[0029] Figure 4 It is a schematic structural diagram of the lateral displacement device described in an embodiment of the present invention;

[0030] Figure 5 It is a schematic diagram of the structure of a simulation device for railway infrastructure deformation described in an embodiment of the present invention;

[0031] Figure 6 It is a schematic diagram of the structure of the simulation device for railway infrastructure deformation described in an embodiment of the present invention.

[0032] Markings in the figure:

[0033] 1. Monitoring device; 2. Longitudinal lifting device; 3. Lateral displacement device; 4. Line model; 5. Triangular reaction wall; 6. First lifting rod; 7. Support plate; 8. Ball twisting platform; 9. Flexible thin plate; 10. Second lifting rod; 11. Lateral displacement rod; 100. First acquisition unit; 200. First input unit; 300. Adjustment unit; 400. Second input unit; 500. Training unit; 600. Input unit; 800. Railway infrastructure deformation simulation device; 801. Processor; 802. Memory; 803. Multimedia component; 804. I / O interface; 805. Communication component. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0035] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0036] Embodiment 1:

[0037] This embodiment provides a method for simulating deformation of railway infrastructure.

[0038] See also Figure 1 , the figure shows that the method includes step S10, step S20, step S30, step S40, step S50 and step S60.

[0039] Step S10. Obtaining historical load parameters and historical spatiotemporal development curves of the target facility, where the historical spatiotemporal development curves are used to characterize the spatiotemporal deformation characteristics of the target facility;

[0040] Specifically, step S10 specifically includes step S11, step S12, step S13 and step S14:

[0041] Step S11. Acquire the stratum lithology, ground stress distribution and sensor deformation data of the area where the target facility is located;

[0042] Specifically, the target facility is located in the target area, data on the stratum lithology and ground stress distribution in the target area are collected, and sensors are buried in the target area to monitor the deformation data of the corresponding position of the target facility.

[0043] Step S12: Determine the historical deformation characteristics of the area where the target facility is located based on the stratum lithology and the distribution of ground stress;

[0044] Specifically, we sorted out the literature data such as experiments and model simulations related to deformation in the target area to clarify the historical deformation characteristics of the target strata in the target area.

[0045] Step S13. Drawing a lateral deformation curve and a longitudinal deformation curve based on the sensor deformation data;

[0046] Specifically, mathematical statistics methods are used to analyze the deformation data of the sensor and draw vertical and horizontal deformation curves of the target strata in the target area.

[0047] Step S14. Based on the historical deformation characteristics, the lateral deformation curve and the longitudinal deformation curve, determine the historical load parameters and the historical time-space development curve;

[0048] Specifically, by combining the historical deformation characteristics with the on-site monitoring data, the spatiotemporal development laws of the vertical and horizontal deformation of the target strata in the target area are obtained, and the historical spatiotemporal development curve of the foundation deformation is obtained.

[0049] Step S20. Bring the historical load parameters into the pre-built basic deformation simulation model to obtain the initial time-space development curve. The basic deformation simulation model at least includes a line model and a deformation model. The line model is a scaled-down model corresponding to the target facility built based on the geometric similarity theory. The deformation model is used to apply load to the line model.

[0050] Specifically, the geometric similarity theory states that if two buildings have similar shapes, proportions, and structures, then their performance behaviors at the same scale are also similar. This theory can be used to derive the corresponding test results of the large model from the test results of the small model. The formula is:

[0051]

[0052] Among them, a1 and b1 are the original line sizes, a , 1 and b , 1 is the line model size, C is the similarity constant;

[0053] Time similarity theory refers to the similarity principle that structures or systems with similar dynamic responses at different time scales must satisfy. According to the time similarity theory, if a system has similar dynamic response behaviors at different time scales, then the system is time similar. This theory can be used to predict how the results obtained at the laboratory scale are applicable to large-scale systems in actual engineering. The basic formula of the time similarity theory can be expressed as:

[0054]

[0055] Among them, t1 and t2 are time; L1 and L2 are deformation scales;

[0056] like Figure 2 As shown in FIG. 1 , a basic deformation simulation model is shown. The basic deformation simulation device includes a plurality of longitudinal lifting devices 2 and lateral displacement devices 3. Figure 3 As shown, the longitudinal lifting device 2 includes a support plate 7 and a first lifting rod 6. The four corner points of the lower surface of the support plate 7 are connected to the first lifting rod 6 through a ball joint. The ball joint platform 8 slides laterally with the movement of the support plate 7. The four corner points of the upper surface of the support plate 7 are fixedly connected to a flexible thin plate 9. The flexible thin plate 9 is a whole and is fixedly connected to multiple support plates 7 at the same time. The first lifting rod 6 is uniformly controlled by the control center, and the control of displacement and application rate can be realized; as shown in FIG. Figure 4 As shown, the lateral displacement device 3 is composed of a second lifting rod 10 and a lateral displacement rod 11. The second lifting rod 10 can longitudinally adjust the position of applying the lateral displacement. The lateral displacement device 3 is connected to the triangular reaction wall 5. The retention and lateral deformation simulation are achieved by adjusting the second lifting rod 10. The lifting amplitude and rate are uniformly controlled by the control center.

[0057] Step S30: Adjust the line model until the overall similarity between the initial space-time development curve and the historical space-time development curve is greater than a first set threshold, and use the corresponding basic deformation simulation model as the target deformation simulation model;

[0058] Specifically, the geometric similarity theory is used to reduce the line of the target facility to a line model, the deformation model is used to apply historical loads, and the deformation time-space development curve under the historical load is obtained. When the overall similarity between the deformation time-space development curve and the historical time-space development curve is high, it is considered that the line model can accurately reflect the deformation state of the actual line.

[0059] Specifically, step S30 specifically includes step S31, step S32, step S33 and step S34:

[0060] Step S31. Based on the spatiotemporal characteristics, the initial spatiotemporal development curve and the historical spatiotemporal development curve are respectively split into a plurality of first units and a plurality of second units, and a plurality of unit sample pairs are obtained in one-to-one correspondence;

[0061] Step S32. Calculate the first distance between the velocity feature vectors of the first unit and the second unit in each unit sample pair and the second distance between the acceleration feature vectors based on the dynamic time warping algorithm;

[0062] Step S33. Determine a local distance based on the first distance and the second distance;

[0063] Step S34. Sum the local similarities to obtain the overall similarity;

[0064] Specifically, the two space-time development curves used to compare the overall similarity are divided into multiple segments. Considering that the space-time development curve uses time as the horizontal coordinate and the deformation as the vertical coordinate, the time warping algorithm can be used to calculate the local similarity of each segment respectively, and then integrate to obtain the overall similarity, so as to determine whether the two space-time development curves are similar. When the overall similarity does not reach the set threshold, it is necessary to adjust the line model construction parameters until the overall similarity of the two lines reaches the set threshold.

[0065] Step S40. Bring different working condition data into the target deformation simulation model to obtain corresponding deformations, and form a sample set based on all working condition data and corresponding deformations, the working condition data including lateral load, longitudinal load and shear load;

[0066] Specifically, in the present application, a non-contact deformation monitoring device is used for monitoring and collection, and the collection steps are simple and the collection accuracy is high.

[0067] Specifically, step S40 specifically includes step S41, step S42, step S43, step S44, step S45 and step S46:

[0068] Step S41. Acquire a first speckle image of the target deformation simulation model based on the monitoring device, where the first speckle image is a corresponding image before the working condition data is introduced;

[0069] Step S42. Acquire a second speckle image of the target deformation simulation model based on the monitoring device, where the second speckle image is a corresponding image after the working condition data is introduced;

[0070] Step S43: converting the first speckle image and the second speckle image into sub-pixel level images, and determining the target contour to obtain the first contour and the second contour, wherein the target contour is used to characterize the overall contour of the line model;

[0071] Specifically, the load combination working condition is determined according to the actual loading state of the line, so as to control the deformation rate of the lateral and longitudinal displacements of the deformation model over time. The load applied by the deformation model is the load after similarity transformation, which can be a single load type or an equivalent load after conversion of multiple load combinations.

[0072] The initial image of the line model and the image after the load is applied are collected by using a non-contact deformation monitoring device, and the initial contour position of the line model and the contour position after the load is applied are determined therefrom.

[0073] Step S44. Determine corresponding points on the first contour and the second contour based on a feature point matching algorithm to obtain a plurality of point pairs;

[0074] Specifically, in the present application, the deformation difference between the initial contour and the contour after load application is calculated by determining a plurality of corresponding points of the two contours, respectively calculating the position difference between the corresponding points, and thus obtaining the position difference of the contours.

[0075] Specifically, step S44 specifically includes step S441, step S442, step S443 and step S444:

[0076] Step S441. compress the second contour to obtain a third contour, where the degree of overlap between the third contour and the first contour is greater than a second set threshold;

[0077] Step S442. Mark the overlapping points of the first contour and the third contour to obtain multiple target points;

[0078] Step S443. Decompress the third contour to obtain a fourth contour carrying the target point;

[0079] Step S444. Use the corresponding target points in the first contour and the fourth contour as a point pair;

[0080] Specifically, the contour after the load is applied is compressed, usually by lateral compression and longitudinal compression, and the compressed contour is overlapped with the initial contour. There will be overlapping positions, and the overlapping positions are marked with points. It is believed that the marked points are the corresponding points between the two contours.

[0081] Step S45. Calculate the relative position difference between each point pair, determine multiple target displacements, and the target displacements carry corresponding point information;

[0082] Step S46. Determine the deformation amount based on multiple target displacement amounts;

[0083] Specifically, step S46 specifically includes step S461, step S462, step S463, step S464, step S465 and step S466:

[0084] Step S461. Divide the area where the target facility is located into multiple modules to obtain multiple grid units;

[0085] Step S462: Based on the point information carried by the target displacement, the target displacement is correspondingly set in the grid unit to obtain a first grid;

[0086] Step S463. Perform an iterative filling process on the blank grid cells in the first grid where no data exists, to obtain a second grid, wherein the iterative filling process is used to indicate that the blank grid cells are filled after iterative calculation based on the data in the grid cells adjacent to the blank grid cells;

[0087] Step S464. Determine the lateral displacement and the longitudinal displacement based on the second grid;

[0088] Step S465. Determine the lateral strain, longitudinal strain and longitudinal shear strain based on the lateral displacement and the longitudinal displacement;

[0089] Step S466. Determine the deformation amount based on the lateral strain, the longitudinal strain and the longitudinal shear strain;

[0090] Specifically, the area where the target facility is located is divided into a grid style, and the target displacement calculated based on the corresponding point is filled into the corresponding position of the grid. It is considered that the line model is a linear material. When deformation occurs, the deformation amount at the adjacent position also changes linearly. Therefore, the unfilled positions in the grid can be filled by iterative filling in four directions. The deformation amount at each position of the target facility is obtained based on the completely filled image.

[0091] Step S50: training the preset neural network model based on the sample set, and when the preset model index meets the set conditions, stopping the training to obtain the target deformation prediction model;

[0092] Step S60: input the target working condition data into the target deformation prediction model to obtain the deformation amount of the target facility;

[0093] Specifically, by inputting the target working condition data into the trained target deformation prediction model, a more accurate deformation prediction value can be obtained.

[0094] Embodiment 2:

[0095] like Figure 5 As shown, this embodiment provides a simulation device for railway infrastructure deformation, the device comprising:

[0096] The first acquisition unit 100 is used to acquire the historical load parameters and the historical space-time development curve of the target facility, where the historical space-time development curve is used to characterize the space-time deformation characteristics of the target facility;

[0097] The first input unit 200 is used to input the historical load parameters into the pre-built basic deformation simulation model to obtain the initial time-space development curve. The basic deformation simulation model at least includes a line model and a deformation model. The line model is a reduced version model corresponding to the target facility built based on the geometric similarity theory. The deformation model is used to apply load to the line model.

[0098] An adjustment unit 300 is used to adjust the line model until the overall similarity between the initial space-time development curve and the historical space-time development curve is greater than a first set threshold, and the corresponding basic deformation simulation model is used as a target deformation simulation model;

[0099] The second input unit 400 is used to input different working condition data into the target deformation simulation model to obtain corresponding deformation amounts, and to form a sample set based on all working condition data and corresponding deformation amounts, wherein the working condition data includes lateral load, longitudinal load and shear load;

[0100] The training unit 500 is used to train the preset neural network model based on the sample set, and when the preset model index meets the set conditions, the training is stopped to obtain the target deformation prediction model;

[0101] The input unit 600 is used to input the target operating condition data into the target deformation prediction model to obtain the deformation amount of the target facility.

[0102] In a specific implementation manner disclosed in the present application, the first acquisition unit 100 includes:

[0103] The second acquisition unit is used to acquire the formation lithology, ground stress distribution and sensor deformation data of the area where the target facility is located;

[0104] A first determination unit is used to determine the historical deformation characteristics of the area where the target facility is located based on the formation lithology and ground stress distribution;

[0105] A drawing unit, used for drawing a lateral deformation curve and a longitudinal deformation curve based on the sensor deformation data;

[0106] The second determination unit is used to determine the historical load parameters and the historical space-time development curve based on the historical deformation characteristics, the lateral deformation curve and the longitudinal deformation curve.

[0107] In a specific embodiment disclosed in the present application, the second bringing-in unit 400 includes:

[0108] A third acquisition unit is used to acquire a first speckle image of the target deformation simulation model based on the monitoring device, where the first speckle image is a corresponding image before the working condition data is introduced;

[0109] A fourth acquisition unit, configured to acquire a second speckle image of the target deformation simulation model based on the monitoring device, wherein the second speckle image is a corresponding image after the working condition data is brought in;

[0110] A conversion unit, used to convert the first speckle image and the second speckle image into a sub-pixel image, and determine a target contour to obtain a first contour and a second contour, wherein the target contour is used to characterize an overall contour of the line model;

[0111] A matching unit, used to determine corresponding points on the first contour and the second contour based on a feature point matching algorithm to obtain a plurality of point pairs;

[0112] A first calculation unit is used to calculate the relative position difference between each point pair and determine a plurality of target displacements, wherein the target displacements carry corresponding point information;

[0113] The third determining unit is used to determine the deformation amount based on the multiple target displacement amounts.

[0114] In a specific implementation disclosed in the present application, the matching unit includes:

[0115] A compression unit, used for compressing the second contour to obtain a third contour, wherein the overlap between the third contour and the first contour is greater than a second set threshold;

[0116] A marking unit, used for marking the coincident points of the first contour and the third contour to obtain a plurality of target points;

[0117] A decompression unit, used for decompressing the third contour to obtain a fourth contour carrying the target point;

[0118] As a unit, it is used to take the corresponding target points in the first contour and the fourth contour as a point pair.

[0119] In a specific implementation manner disclosed in the present application, the third determining unit includes:

[0120] A division unit is used to divide the area where the target facility is located into multiple modules to obtain multiple grid units;

[0121] A setting unit, used for setting the point information carried by the target displacement amount in a corresponding grid unit to obtain a first grid;

[0122] A filling unit, used for iteratively filling blank grid cells in the first grid without data to obtain a second grid, wherein the iterative filling process is used to indicate filling after iterative calculation based on data in grid cells adjacent to the blank grid cells;

[0123] a fourth determining unit, configured to determine a lateral displacement and a longitudinal displacement based on the second grid;

[0124] Determine the lateral strain, longitudinal strain and longitudinal shear strain based on the lateral displacement and the longitudinal displacement;

[0125] The fifth determining unit is used to determine the deformation amount based on the lateral strain, the longitudinal strain and the longitudinal shear strain.

[0126] In a specific implementation disclosed in the present application, the adjustment unit 300 includes:

[0127] A splitting unit is used to split the initial spatiotemporal development curve and the historical spatiotemporal development curve into a plurality of first units and a plurality of second units respectively based on the spatiotemporal characteristics, and obtain a plurality of unit sample pairs in one-to-one correspondence;

[0128] A second calculation unit, used for calculating a first distance between respective velocity feature vectors of a first unit and a second unit in each unit sample pair and a second distance between respective acceleration feature vectors based on a dynamic time warping algorithm;

[0129] a sixth determining unit, configured to determine a local distance based on the first distance and the second distance;

[0130] The third calculation unit is used to sum up the local similarities to obtain the overall similarity.

[0131] It should be noted that, regarding the device in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment of the method, and will not be elaborated here.

[0132] Embodiment 3:

[0133] Corresponding to the above method embodiment, this embodiment also provides a simulation device for railway infrastructure deformation. The simulation device for railway infrastructure deformation described below and the simulation method for railway infrastructure deformation described above can refer to each other.

[0134] Figure 6 FIG. 8 is a block diagram of a simulation device 800 for railway infrastructure deformation according to an exemplary embodiment. Figure 6 As shown, the simulation device 800 for railway infrastructure deformation may include: a processor 801 and a memory 802. The simulation device 800 for railway infrastructure deformation may also include one or more of a multimedia component 803, an I / O interface 804, and a communication component 805.

[0135] The processor 801 is used to control the overall operation of the railway infrastructure deformation simulation device 800 to complete all or part of the steps in the above-mentioned railway infrastructure deformation simulation method. The memory 802 is used to store various types of data to support the operation of the railway infrastructure deformation simulation device 800, and these data may include, for example, instructions for any application or method operating on the railway infrastructure deformation simulation device 800, and application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The memory 802 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, disk or optical disk. The multimedia component 803 can include a screen and an audio component. The screen can be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component can include a microphone, and the microphone is used to receive external audio signals. The received audio signal can be further stored in the memory 802 or sent through the communication component 805. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 804 provides an interface between the processor 801 and other interface modules, and the above-mentioned other interface modules can be keyboards, mice, buttons, etc. These buttons can be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the simulation device 800 for railway infrastructure deformation and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 805 can include: Wi-Fi module, Bluetooth module, NFC module.

[0136] In an exemplary embodiment, the railway infrastructure deformation simulation device 800 can be implemented by one or more application-specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned railway infrastructure deformation simulation method.

[0137] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned simulation method for railway infrastructure deformation are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 802 including program instructions, and the above-mentioned program instructions can be executed by the processor 801 of the simulation device 800 for railway infrastructure deformation to complete the above-mentioned simulation method for railway infrastructure deformation.

[0138] Embodiment 4:

[0139] Corresponding to the above method embodiment, a readable storage medium is also provided in this embodiment. The readable storage medium described below and the simulation method for railway infrastructure deformation described above can refer to each other.

[0140] A readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for simulating railway infrastructure deformation in the above method embodiment.

[0141] The readable storage medium may specifically be a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or other readable storage medium that can store program codes.

[0142] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0143] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for simulating deformation of railway infrastructure, characterized in that: include: Acquire historical load parameters and historical spatiotemporal development curves of target facilities, wherein the historical spatiotemporal development curves are used to characterize spatiotemporal deformation characteristics of the target facilities; Bringing the historical load parameters into a pre-built basic deformation simulation model to obtain an initial time-space development curve, wherein the basic deformation simulation model at least includes a line model and a deformation model, wherein the line model is a reduced-size model corresponding to the target facility built based on geometric similarity theory, and the deformation model is used to apply load to the line model; Adjusting the line model until the overall similarity between the initial space-time development curve and the historical space-time development curve is greater than a first set threshold, and using the corresponding basic deformation simulation model as a target deformation simulation model; Bringing different working condition data into the target deformation simulation model to obtain corresponding deformation amounts, and forming a sample set based on all working condition data and corresponding deformation amounts, wherein the working condition data includes lateral load, longitudinal load and shear load; Training a preset neural network model based on the sample set, and when the preset model index meets the set conditions, stopping the training to obtain a target deformation prediction model; The target operating condition data is input into the target deformation prediction model to obtain the deformation amount of the target facility.

2. The method for simulating railway infrastructure deformation according to claim 1, characterized in that , obtaining the historical load parameters and historical spatiotemporal development curve of the target facility, the historical spatiotemporal development curve is used to characterize the spatiotemporal deformation characteristics of the target facility, including: Acquiring stratum lithology, ground stress distribution and sensor deformation data of the area where the target facility is located; Determining historical deformation characteristics of the area where the target facility is located based on the formation lithology and the ground stress distribution; Drawing a lateral deformation curve and a longitudinal deformation curve based on the sensing deformation data; Based on the historical deformation characteristics, the lateral deformation curve and the longitudinal deformation curve, the historical load parameters and the historical space-time development curve are determined.

3. The method for simulating railway infrastructure deformation according to claim 2, characterized in that , bringing different working condition data into the target deformation simulation model to obtain corresponding deformation amounts, and forming a sample set based on all working condition data and corresponding deformation amounts, the basic deformation simulation model also includes a monitoring device, which is used to measure the deformation amount of the line model, including: Acquire a first speckle image of the target deformation simulation model based on a monitoring device, where the first speckle image is a corresponding image before the working condition data is introduced; Acquire a second speckle image of the target deformation simulation model based on a monitoring device, where the second speckle image is a corresponding image after the working condition data is brought in; Converting the first speckle image and the second speckle image into sub-pixel images, and determining a target contour to obtain a first contour and a second contour, wherein the target contour is used to characterize an overall contour of a line model; Determine corresponding points on the first contour and the second contour based on a feature point matching algorithm to obtain a plurality of point pairs; Calculate the relative position difference between each point pair to determine multiple target displacements, where the target displacements carry corresponding point information; The deformation amount is determined based on a plurality of target displacement amounts.

4. The method for simulating railway infrastructure deformation according to claim 3, characterized in that , based on the feature point matching algorithm, determine the corresponding points on the first contour and the second contour to obtain multiple point pairs, including: Compressing the second contour to obtain a third contour, wherein the overlap between the third contour and the first contour is greater than a second set threshold; Marking the overlapping points of the first contour and the third contour to obtain a plurality of target points; Performing a decompression process on the third contour to obtain a fourth contour carrying the target point; The corresponding target points in the first contour and the fourth contour are used as the point pair.

5. A simulation device for railway infrastructure deformation, characterized in that: include: A first acquisition unit is used to acquire historical load parameters and historical spatiotemporal development curves of target facilities, wherein the historical spatiotemporal development curves are used to characterize spatiotemporal deformation characteristics of the target facilities; A first input unit is used to input the historical load parameters into a pre-built basic deformation simulation model to obtain an initial time-space development curve, wherein the basic deformation simulation model at least includes a line model and a deformation model, wherein the line model is a reduced-size model corresponding to the target facility built based on geometric similarity theory, and the deformation model is used to apply load to the line model; an adjusting unit, configured to adjust the line model until the overall similarity between the initial spatiotemporal development curve and the historical spatiotemporal development curve is greater than a first set threshold, and use the corresponding basic deformation simulation model as a target deformation simulation model; A second input unit is used to input different working condition data into the target deformation simulation model to obtain corresponding deformation amounts, and to form a sample set based on all working condition data and corresponding deformation amounts, wherein the working condition data includes lateral load, longitudinal load and shear load; A training unit, used to train a preset neural network model based on the sample set, and when the preset model index meets the set conditions, stop the training to obtain a target deformation prediction model; The input unit is used to input the target operating condition data into the target deformation prediction model to obtain the deformation amount of the target facility.

6. The simulation device for railway infrastructure deformation according to claim 5, characterized in that: The first acquiring unit includes: A second acquisition unit is used to acquire the stratum lithology, ground stress distribution and sensor deformation data of the area where the target facility is located; A first determining unit is used to determine the historical deformation characteristics of the area where the target facility is located based on the formation lithology and the ground stress distribution; A drawing unit, used for drawing a lateral deformation curve and a longitudinal deformation curve based on the sensing deformation data; The second determination unit is used to determine the historical load parameter and the historical space-time development curve based on the historical deformation characteristics, the lateral deformation curve and the longitudinal deformation curve.

7. The simulation device for railway infrastructure deformation according to claim 6, characterized in that: The second bringing-in unit comprises: A third acquisition unit, configured to acquire a first speckle image of the target deformation simulation model based on a monitoring device, wherein the first speckle image is a corresponding image before the working condition data is introduced; a fourth acquisition unit, configured to acquire a second speckle image of the target deformation simulation model based on a monitoring device, wherein the second speckle image is a corresponding image after the working condition data is introduced; a conversion unit, configured to convert the first speckle image and the second speckle image into sub-pixel images, and determine a target contour to obtain a first contour and a second contour, wherein the target contour is used to characterize an overall contour of a line model; A matching unit, configured to determine corresponding points on the first contour and the second contour based on a feature point matching algorithm to obtain a plurality of point pairs; A first calculation unit is used to calculate the relative position difference between each point pair and determine a plurality of target displacements, wherein the target displacements carry corresponding point information; The third determining unit is used to determine the deformation amount based on multiple target displacement amounts.

8. The railway infrastructure deformation simulation device according to claim 7, characterized in that: The matching unit comprises: a compression unit, configured to compress the second contour to obtain a third contour, wherein the degree of overlap between the third contour and the first contour is greater than a second set threshold; A marking unit, used for marking the coincident points of the first contour and the third contour to obtain a plurality of target points; A decompression unit, used for decompressing the third contour to obtain a fourth contour carrying the target point; As a unit, it is used to take the corresponding target points in the first contour and the fourth contour as the point pair.

9. A simulation device for railway infrastructure deformation, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the method for simulating railway infrastructure deformation as claimed in any one of claims 1 to 4 when executing the computer program.

10. A readable storage medium, characterized in that: The readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for simulating railway infrastructure deformation as claimed in any one of claims 1 to 4.

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