Traffic safety detection device and evaluation method when high-speed rail passes through shield construction tunnel

Abstract

The invention relates to the technical field of rail traffic safety, in particular to a driving safety detection device and evaluation method when a high-speed rail passes through a shield construction tunnel, and the device comprises a point cloud collection module, a laser indication module and a processing module. The laser indication module can measure the center coordinate of a target plate on the point cloud acquisition module, and the processing module is electrically connected with the point cloud acquisition module and the laser indication module so as to receive point cloud model data and center coordinate data of the target plate and process the data to obtain the high-speed rail driving reliability. In this way, real-time detection of the high-speed rail traveling reliability is achieved, the point cloud collection module at least comprises four point cloud collection assemblies evenly distributed on the two sides of the traveling track, and the accuracy of the detection result is effectively guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of rail transit safety technology, and in particular to a driving safety detection device and an evaluation method when a high-speed railway passes through a shield construction tunnel. Background Art

[0002] As a high-speed rail transit system, high-speed rail has extremely high requirements for line stability and safety. In cities or complex geological environments, shield construction tunnels often need to cross or approach high-speed rail lines (such as high-speed rail bridges, tunnels or roadbeds) at close range. This may cause stratum disturbance, track deformation, and settlement risks, and even affect the safety of high-speed rail operation. Therefore, how to evaluate and control the impact of shield construction on high-speed rail driving safety has become an important research issue in the fields of civil engineering, rail transit and intelligent monitoring.

[0003] Traditional technology mainly uses the three-dimensional finite element method to establish the interaction model of shield construction-stratum-high-speed rail track. Analyze the influence of different construction stages (such as excavation, segment assembly, soil loss) on track settlement and stress distribution. Or use the Peck formula, Loganathan method, and Knothe method to estimate the influence of shield construction on the settlement of high-speed rail track.

[0004] The commonly used Peck formula, Loganathan method, Knothe formula, etc. are mainly based on statistical experience and are suitable for uniform soil layers and simple construction conditions, but have low accuracy in complex geological environments (such as soft soil, water-rich sand layers) or special construction conditions (such as deep excavation, asymmetric loading). These methods usually assume that the formation deformation mode is fixed and cannot adapt to the dynamically changing construction environment, resulting in large prediction errors.

[0005] Finite element analysis is a commonly used refined analysis method, but the calculation process is complicated, requires high-quality geological data and construction parameters, and takes a long time to calculate. However, finite element simulation is very sensitive to soil parameters, shield construction parameters, and initial conditions. A slight deviation may lead to distortion of the calculation results. Due to the high timeliness requirements of shield construction, FEM calculations usually take hours or even days to obtain evaluation results, which cannot meet the real-time monitoring needs of high-speed rail driving safety.

[0006] At present, the GNSS, total station, laser rangefinder, fiber Bragg grating and other equipment commonly used for high-speed rail track and shield construction monitoring have the following problems: monitoring data usually needs to be processed manually, the data update frequency is low, and it is impossible to achieve a second-level response. The sensor installation is complicated and the cost is high, making it difficult to promote on a large scale. Monitoring data is mostly discrete point data, making it difficult to build a complete three-dimensional track settlement evolution model, resulting in insufficient precision in track deformation analysis. Summary of the invention

[0007] The purpose of the present invention is to provide a driving safety detection device and evaluation method for high-speed railways passing through shield tunnels, which can accurately and efficiently perform reliability detection. The specific technical scheme is as follows: The present invention provides a driving safety detection device for a high-speed railway passing through a shield tunnel, which is used to detect the driving reliability of a shield tunnel passing through a high-speed railway subgrade section, and comprises a point cloud acquisition module, a laser indication module and a processing module. The point cloud acquisition module comprises at least four point cloud acquisition components evenly arranged on both sides of the driving track, and target plates are arranged on both sides of the point cloud acquisition component. The point cloud acquisition component is used to scan and obtain a point cloud model of the high-speed railway subgrade area to be detected; The laser indicator module includes two laser indicator assemblies arranged diagonally, the two laser indicator assemblies are arranged in the long-term non-deformation areas on both sides of the driving track, and the laser indicator assembly includes at least four laser indicators, the laser indicators are arranged in one-to-one correspondence with the target plate, and the laser indicators are used to measure the center coordinates of the corresponding target plate; The processing module is electrically connected to the point cloud acquisition component and the laser indicator respectively, and is used to process the point cloud model acquired by the point cloud acquisition component and the center coordinates of the target plate measured by the laser indicator to obtain the high-speed rail driving reliability.

[0008] Optionally, the point cloud acquisition component includes a support pole and a laser radar, the support pole is vertically arranged on the ground, and the target plates are arranged on both sides of the support pole; the laser radar is arranged on the support pole, and the point cloud model accumulated by each laser radar covers at least 100 meters of the driving track length.

[0009] Optionally, the laser indicator includes a mounting base, a rotating servo, a pitch servo, a laser ranging element and an IMU element, wherein the mounting base is arranged on the ground in a long-term deformation-free area; the rotating servo is horizontally arranged on the mounting base; the pitch servo is connected to the output shaft of the rotating servo, and the rotating servo can drive the pitch servo to rotate in a horizontal plane; the laser ranging element is connected to the output shaft of the pitch servo, and the pitch servo can drive the laser ranging element to rotate in a vertical plane, the laser ranging element is used to measure the distance between the laser emission point and the target plate, and the laser ranging element is provided with a laser indicator light for lighting; the IMU element is arranged on the laser ranging element, and the IMU element is used to measure the azimuth and pitch angle of the laser ranging element.

[0010] Optionally, the laser pointer also includes a control element, which is arranged on the mounting base, and includes a single-chip microcomputer chip, a data transmission unit and a control unit. The single-chip microcomputer chip is electrically connected to the rotation servo and the pitch servo, and the data transmission unit is electrically connected to the laser ranging element, the IMU element and the processing module respectively, and is used to transmit the measurement data of the laser ranging element and the IMU element to the control unit; the control unit can calculate the center coordinates of the target plate according to the measurement data of the laser ranging element and the IMU element, and transmit them to the processing module.

[0011] The present invention also provides a method for evaluating the driving safety of a high-speed railway passing through a shield tunnel, using the above-mentioned driving safety detection device for a high-speed railway passing through a shield tunnel, comprising the following steps: S1. When the shield tunnel has not yet affected the high-speed railway subgrade section, the driving safety detection device for the high-speed railway passing through the shield construction tunnel is arranged in the high-speed railway subgrade area to be detected; S2. Establish a high-speed rail track recognition model, specifically: create a track label point cloud data set based on the N point cloud models obtained by scanning the shield tunnel under the high-speed rail subgrade section N times by the point cloud acquisition module, and establish a high-speed rail track recognition model using the RandLA-Net model, where: N is the set threshold; S3, using the high-speed rail track recognition model to identify the surface point cloud data on the top of the track; S4. The track deformation is calculated by using the KD tree nearest neighbor search algorithm and the Euclidean distance algorithm based on the difference in the surface point cloud data before and after the shield tunnel affects the high-speed railway subgrade section; S5. A high-speed rail operation state prediction model is established by using a train operation aerodynamic simulation model, a train-track dynamics model and a PSO-XGBoost prediction model, and the current operation speed of the high-speed rail, the current driving condition and the track deformation in S4 are input into the high-speed rail operation state prediction model, and the vertical acceleration, derailment coefficient and wheel load reduction rate of the high-speed rail when it is running in the high-speed rail subgrade area to be detected are output, wherein: the current driving condition refers to single-car driving or double-car crossing driving; S6. Input the vertical acceleration, derailment coefficient and wheel load reduction rate in S5 into the existing reliability model to obtain the reliability of the high-speed rail when it travels in the lower shield construction area. If the reliability is less than zero, the high-speed rail has a risk of overturning when passing through the area at the current speed and state; otherwise, repeat S3 to S6 every M minutes, where: M is the set threshold.

[0012] Optionally, the S1 includes: When the shield tunnel construction does not affect the high-speed railway subgrade section, at least four point cloud acquisition components are arranged at a distance of 10m to 15m from the center line of the subgrade. The four point cloud acquisition components are evenly arranged on both sides of the driving track in the high-speed railway subgrade area to be inspected, wherein: the scanning ranges of the two point cloud acquisition components on the same side of the driving track overlap; A laser indication assembly is arranged respectively at an area 100m to 150m away from the center line of the roadbed on both sides of the driving track and where the ground surface has no deformation for a long time, and the laser indication assemblies on both sides of the driving track are arranged diagonally.

[0013] Optionally, the S3 includes: S3.1. Calculate the coordinates of each laser radar according to the center coordinates of the target plate measured by the laser indication module, and use each laser radar to scan the high-speed railway subgrade surface at time t to obtain the point cloud coordinate data of the high-speed railway subgrade surface; S3.2, according to the coordinates of each laser radar, the point cloud coordinate data of the high-speed railway subgrade surface obtained by scanning by each laser radar is converted into the same coordinate system by using Euclidean transformation to obtain the point cloud model of the high-speed railway subgrade at time t; S3.3. Use the high-speed rail track recognition model to identify the track point cloud data in the high-speed rail base point cloud model to obtain the track point cloud data model, and use the regional growing algorithm to extract the surface point cloud data of the top of the track in the track point cloud data model.

[0014] Optionally, in S3.1, the steps for calculating the laser radar coordinates are as follows: ①. Adjust the high-precision laser pointer so that its laser point falls on the center of the target plate; ②. Use the total station to measure the three-dimensional geodetic coordinates of the laser ranging element ; and use the laser distance measuring element to measure the distance between the laser emission point and the center of the target plate The attached IMU module determines the azimuth of the laser ranging element and pitch angle ; ③. According to the three-dimensional geodetic coordinates of the laser ranging element, the distance between the laser emission point and the center of the target plate, the azimuth and pitch angle, the coordinates of the laser points on the two target plates in the point cloud acquisition component are calculated, that is, the center coordinates of the target plate , the specific calculation formula is as follows: ; in: is the azimuth of the geodetic coordinate system in the x-axis direction of the area where the laser ranging element is located; ④. Calculate the laser radar coordinates based on the center coordinates of the two target plates, specifically: When the shield tunnel construction does not affect the high-speed railway subgrade section, the corresponding coordinates of the laser radar corresponding to the center coordinates of the two target plates are calculated respectively, and the average of the corresponding coordinates of the two laser radars is used as the laser radar coordinates; When the shield tunnel construction affects the high-speed railway subgrade section, repeat ① to ③ to obtain the center coordinates of the two target plates in the point cloud acquisition component after the shield tunnel affects the high-speed railway subgrade section, and calculate the laser radar coordinates based on the average value of the center coordinate deformation of the target plates before and after the shield tunnel affects the high-speed railway subgrade section.

[0015] In the technical solution of the present invention, the point cloud acquisition module can adopt the point cloud model of the high-speed railway subgrade area to be detected, the laser indication module can measure the center coordinates of the target plate on the point cloud acquisition module, and the processing module is electrically connected to the point cloud acquisition module and the laser indication module respectively to receive the point cloud model data and the center coordinate data of the target plate and process them to obtain the high-speed railway driving reliability, thereby realizing real-time detection of the high-speed railway driving reliability, and the point cloud acquisition module includes at least four point cloud acquisition components evenly distributed on both sides of the driving track, which effectively ensures the accuracy of the detection results.

[0016] In addition to the above-described purposes, features and advantages, the present invention has other purposes, features and advantages. The present invention will be further described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings constituting a part of this application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings: Figure 1 It is a structural schematic diagram of a driving safety detection device when a high-speed railway passes through a shield tunnel in an embodiment of the present invention; Figure 2 is a structural schematic diagram of a point cloud acquisition module in an embodiment of the present invention; Figure 3 Schematic diagram of the structure of the laser pointer in the embodiment of the present invention.

[0018] Description of Figure Numbers: 1 Track, 1.1 Track surface, 2 Point cloud acquisition component, 2.1 Support rod, 2.2 LiDAR, 2.3 Target plate, 3 Laser designation component, 3.1 Laser designator, 3.1.1 Mounting base, 3.1.2 Rotation servo, 3.1.3 Pitch servo, 3.1.4 Laser ranging element, 3.1.5 IMU element, 3.1.6 Control element. DETAILED DESCRIPTION

[0019] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings. Several embodiments of the present invention are shown in the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein.

[0020] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. The terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features.

[0021] In the present invention, unless otherwise clearly specified and limited, the first feature being "above" or "below" the second feature may include the first and second features being in direct contact, or may include the first and second features being in contact not directly but through another feature between them. Moreover, the first feature being "above", "above" and "above" the second feature includes the first feature being directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. The first feature being "below", "below" and "below" the second feature includes the first feature being directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature. The terms "vertical", "horizontal", "left", "right", "above", "below" and similar expressions are for illustrative purposes only, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention.

[0022] The embodiments of the present invention are described in detail below with reference to the accompanying drawings, but the present invention can be implemented in many different ways as defined and covered by the claims. Example 1

[0023] See also Figures 1 to 3The present embodiment provides a driving safety detection device for a high-speed railway passing through a shield tunnel, which is used to detect the driving reliability of a shield tunnel passing through a high-speed railway subgrade section, and includes a point cloud acquisition module, a laser indication module and a processing module. The point cloud acquisition module includes at least four point cloud acquisition components 2 evenly arranged on both sides of a driving track 1, and target plates 2.3 are arranged on both sides of the point cloud acquisition component 2. The point cloud acquisition component 2 is used to scan and obtain a point cloud model of a high-speed railway subgrade area to be detected; the laser indication module includes two laser indication components 3 arranged diagonally, and the two laser indication components 3 are arranged diagonally. The optical indication component 3 is arranged in the long-term deformation-free areas on both sides of the driving track 1, and the laser indication component 3 includes at least four laser indicators 3.1, and the laser indicators 3.1 are arranged one by one corresponding to the target plate 2.3, and the laser indicators 3.1 are used to measure the center coordinates of the corresponding target plate 2.3; the processing module is electrically connected to the point cloud acquisition component 2 and the laser indicator 3.1 respectively, and the processing module is used to process the point cloud model acquired by the point cloud acquisition component 2 and the center coordinates of the target plate 2.3 measured by the laser indicator 3.1 to obtain the high-speed rail driving reliability. In actual operation, the point cloud acquisition module can adopt the point cloud model of the high-speed railway subgrade area to be detected, the laser indication module can measure the center coordinates of the target plate 2.3 on the point cloud acquisition module, and the processing module is electrically connected to the point cloud acquisition module and the laser indication module respectively to receive the point cloud model data and the center coordinate data of the target plate 2.3 and process them to obtain the high-speed railway driving reliability, thereby realizing real-time detection of the high-speed railway driving reliability, and the point cloud acquisition module includes at least four point cloud acquisition components 2 evenly distributed on both sides of the driving track 1, which effectively ensures the accuracy of the detection results.

[0024] The point cloud acquisition component 2 includes a support pole 2.1 and a laser radar 2.2. The support pole 2.1 is vertically arranged on the ground, and target plates 2.3 are arranged on both sides of the support pole 2.1. The laser radar 2.2 is arranged on the support pole 2.1, and the point cloud model accumulated by each laser radar 2.2 covers at least 100 meters of the driving track 1. The laser radar 2.2 can be 360° circumferential and positive and negative 90° pitched to ensure that a track area of ​​at least 100m can be scanned. The scanning accuracy can reach the mm level, and the distance between neighboring points is 1mm. The point cloud model scanned by the laser radar 2.2 is a point with coordinates in a coordinate system with the position of the laser radar 2.2 as the reference point. The laser radar 2.2 is arranged on the top of the pole, and two target plates 2.3 arranged back to back are installed in the middle. The target plate 2.3 is a plastic white board with a grid, and the size is about 0.5m. 0.5m 0.01m, the target plate 2.3 is fixedly mounted on the straight rod; the bottom of the straight rod is fixed on the ground around the track, and when the ground settles, the straight rod settles as a whole. The laser radars 2.2 in the four point cloud acquisition components 2 cooperate to scan to ensure scanning accuracy, which is conducive to accurately detecting the deformation of the track surface 1.1. In this embodiment, the laser radar 2.2 is configured with a control module for processing point cloud data.

[0025] The laser indicator 3.1 includes a mounting base 3.1.1, a rotating servo 3.1.2, a pitching servo 3.1.3, a laser ranging element 3.1.4 and an IMU element 3.1.5. The mounting base 3.1.1 is arranged on the ground in a long-term non-deformation area; the rotating servo 3.1.2 is horizontally arranged on the mounting base 3.1.1; the pitching servo 3.1.3 is connected to the output shaft of the rotating servo 3.1.2, and the rotating servo 3.1.2 can drive the pitching servo 3.1.3 to rotate in a horizontal plane; the laser ranging element 3.1.4 is connected to the output shaft of the pitch servo 3.1.3, and the pitch servo 3.1.3 can drive the laser ranging element 3.1.4 to rotate in the vertical plane. The laser ranging element 3.1.4 is used to measure the distance between the laser emission point and the target plate 2.3, and a laser indicator light for lighting is provided on the laser ranging element 3.1.4; the IMU element 3.1.5 is arranged on the laser ranging element 3.1.4, and the IMU element 3.1.5 is used to measure the azimuth and pitch angle of the laser ranging element 3.1.4. A laser indicator light is provided to facilitate the staff to determine whether the area where the laser ranging is located is the target plate 2.3 area; the azimuth and pitch angles of the laser ranging element 3.1.4 are adjusted by rotating the servo 3.1.2 and the pitch servo 3.1.3 so that the laser landing point of the laser ranging element 3.1.4 coincides with the center point of the target plate 2.3, thereby obtaining the center coordinates of the target plate 2.3. The laser indicator 3.1 can measure the center coordinates of the target plate 2.3 in real time before and after the shield tunnel affects the high-speed railway subgrade section, so as to obtain the track deformation through the difference in the center coordinates of the target plate 2.3.

[0026] The laser pointer 3.1 also includes a control element 3.1.6, which is arranged on the mounting base 3.1.1. The control element 3.1.6 includes a single-chip microcomputer chip, a data transmission unit and a control unit. The single-chip microcomputer chip is electrically connected to the rotary servo 3.1.2 and the pitch servo 3.1.3. The data transmission unit is electrically connected to the laser ranging element 3.1.4, the IMU element 3.1.5 and the processing module respectively, and is used to transmit the measurement data of the laser ranging element 3.1.4 and the IMU element 3.1.5 to the control unit; the control unit can calculate the center coordinates of the target plate 2.3 according to the measurement data of the laser ranging element 3.1.4 and the IMU element 3.1.5, and transmit it to the processing module. The control element 3.1.6 is used to realize the automatic control of each component without human participation, which is conducive to saving labor costs and improving work efficiency. Example 2

[0027] This embodiment provides a method for evaluating the driving safety of a high-speed railway passing through a shield tunnel, using the above-mentioned driving safety detection device for a high-speed railway passing through a shield tunnel, including the following steps: S1. When the shield tunnel has not yet affected the high-speed railway subgrade section, the driving safety detection device for the high-speed railway passing through the shield construction tunnel is arranged in the high-speed railway subgrade area to be detected; S1 includes: When the shield tunnel construction does not affect the high-speed railway subgrade section, at least four point cloud acquisition components 2 are arranged at a distance of 10m to 15m from the center line of the subgrade. The four point cloud acquisition components 2 are evenly arranged on both sides of the driving track 1 in the high-speed railway subgrade area to be detected, wherein: the scanning ranges of the two point cloud acquisition components 2 located on the same side of the driving track 1 overlap; Figure 1 The dotted line in is the scanning range of the point cloud acquisition component 2.

[0028] A laser pointing assembly 3 is arranged at both sides of the driving track 1 at a distance of 100m to 150m from the center line of the roadbed and in an area where the ground surface has no deformation for a long time, and the laser pointing assemblies 3 at both sides of the driving track 1 are arranged diagonally.

[0029] S2. Establish a high-speed rail track recognition model, specifically: create a track label point cloud data set based on N point cloud models obtained by scanning the shield tunnel under the high-speed rail subgrade section N times by the point cloud acquisition module, and establish a high-speed rail track recognition model using the RandLA-Net model, where: N is the set threshold; the establishment process of the high-speed rail track recognition model in this embodiment can refer to the article "Railway Bridge Point Cloud Component-Level Segmentation Method Based on Improved RandLA-Net".

[0030] S3, using the high-speed rail track recognition model to identify the surface point cloud data on the top of the track; S3 includes: S3.1, calculating the coordinates of each laser radar 2.2 according to the center coordinates of the target plate 2.3 measured by the laser indication module, and using each laser radar 2.2 to scan the high-speed railway subgrade surface at time t to obtain point cloud coordinate data of the high-speed railway subgrade surface; In S3.1, the calculation steps of the laser radar 2.2 coordinates are as follows: ①. Adjust the high-precision laser pointer so that its laser point falls on the center point of the target plate 2.3; ②. Use the total station to measure the three-dimensional geodetic coordinates of the laser ranging element 3.1.4 ; and use the laser distance measuring element 3.1.4 to measure the distance between the laser emission point and the center of the target plate 2.3 The associated IMU module determines the azimuth of the laser ranging element 3.1.4 and pitch angle ; ③. According to the three-dimensional geodetic coordinates of the laser ranging element 3.1.4, the distance between the laser emission point and the center of the target plate 2.3, the azimuth angle and the pitch angle, the coordinates of the laser points on the two target plates 2.3 in the point cloud acquisition component 2 are calculated, that is, the center coordinates of the target plate 2.3. , the specific calculation formula is as follows: ; in: is the azimuth of the geodetic coordinate system in the x-axis direction of the area where the laser ranging element 3.1.4 is located; ④. Calculate the coordinates of the laser radar 2.2 according to the center coordinates of the two target plates 2.3, specifically: When the shield tunnel construction does not affect the high-speed railway subgrade section, the corresponding coordinates of the laser radar 2.2 corresponding to the center coordinates of the two target plates 2.3 are calculated respectively. The average of the corresponding coordinates of the two laser radars 2.2 is taken as the coordinate of the laser radar 2.2; When the shield tunnel construction affects the high-speed railway subgrade section, repeat ① to ③ to obtain the center coordinates of the two target plates 2.3 in the point cloud acquisition component 2 after the shield tunnel affects the high-speed railway subgrade section, and calculate the laser radar 2.2 coordinates based on the average value of the center coordinate deformation of the target plates 2.3 before and after the shield tunnel affects the high-speed railway subgrade section, specifically: When settlement and deformation occur in the high-speed railway subgrade section, the driving safety detection device will also deform as a whole when the high-speed railway passes through the shield construction tunnel. However, since each module is fixedly installed, the deformation of each part of the driving safety detection device is synchronous and the same when the high-speed railway passes through the shield construction tunnel. Therefore, when the laser ranging element 3.1.4 is deformed, it can calculate the coordinates of the new laser landing point on the target plate 2.3, that is, the center coordinates of the deformed target plate 2.3. The coordinate difference between the center coordinates of the target plate 2.3 before and after the deformation is the deformation of the corresponding point cloud acquisition component 2. According to the deformation calculated from the landing points of the target plates 2.3 on both sides, the corresponding deformation mean can be obtained. , the deformation mean can be considered as the movement of the coordinates of the laser radar 2.2 device, and thus the coordinates of the laser radar 2.2 can be adjusted to: ; After the deformation amount is adjusted, the coordinates of the laser radar 2.2 are used to rescan the high-speed railway subgrade section to ensure that the corresponding point cloud coordinates are also in the same coordinate system as the initial point cloud coordinates.

[0031] S3.2, according to the coordinates of each laser radar 2.2, the point cloud coordinate data of the high-speed railway foundation surface scanned by each laser radar 2.2 is converted into the same coordinate system by using Euclidean transformation to obtain a point cloud model of the high-speed railway foundation at time t; S3.3. Use the high-speed rail track recognition model to identify the track point cloud data in the high-speed rail base point cloud model to obtain the track point cloud data model, and use the regional growing algorithm to extract the surface point cloud data of the top of the track in the track point cloud data model.

[0032] S4. The track deformation is calculated by using the KD tree nearest neighbor search algorithm and the Euclidean distance algorithm based on the difference in the surface point cloud data before and after the shield tunnel affects the high-speed railway subgrade section; S5. A high-speed rail operation state prediction model is established by using a train operation aerodynamic simulation model, a train-track dynamics model and a PSO-XGBoost prediction model, and the current operation speed of the high-speed rail, the current driving condition and the track deformation in S4 are input into the high-speed rail operation state prediction model, and the vertical acceleration, derailment coefficient and wheel load reduction rate of the high-speed rail when it is running in the high-speed rail subgrade area to be detected are output, wherein: the current driving condition refers to single-car driving or double-car crossing driving; The above model has been established and implemented in the relevant paper "Safety of crossing existing high-speed railways under shield tunneling conditions considering random fields" and does not require additional description.

[0033] The specific process of establishing the high-speed rail operation status prediction model is as follows: first, the existing train operation aerodynamic simulation model and train-track dynamics model are used to simulate the train operation status according to different track deformations, driving conditions and driving speeds to obtain at least K groups of simulation data; then, the simulation data includes the corresponding train vertical acceleration, derailment coefficient and wheel weight reduction rate; finally, the PSO-XGBoost prediction model is used to learn the expanded simulation data to establish a high-speed rail operation status prediction model; in this embodiment, the Kriging proxy model is used to expand the simulation data, and the amount of data after expansion is at least 1000 groups of data, and then the PSO-XGBoost prediction model is used to learn the data, and the prediction models of high-speed rail vertical acceleration, derailment coefficient and wheel weight reduction rate are established respectively, where: K is 300.

[0034] S6. Input the vertical acceleration, derailment coefficient and wheel load reduction rate in S5 into the existing reliability model to obtain the reliability of the high-speed rail when it is running in the lower shield construction area. If the reliability is less than zero, the high-speed rail has a risk of overturning when passing through the area at the current speed and state; otherwise, repeat S3 to S6 every M minutes, where M is the set threshold. In this embodiment, M=30min, and the establishment of the reliability model can refer to the "Random Reliability Assessment Method for High-speed Railway Driving Safety when the Shield is Passing Under".

[0035] The driving safety evaluation method for high-speed railways passing through shield tunnels in this embodiment combines laser point cloud acquisition, track surface 1.1 identification, settlement calculation, PSO-XGBoost prediction model and reliability calculation model, and has the following significant technical advantages in the rapid evaluation of driving safety when high-speed railways pass through shield tunnels: the point cloud acquisition module and laser indication module can provide high-resolution track settlement data, accurately identify track surface 1.1 deformation, and based on the PSO-XGBoost model, can quickly predict key indicators such as high-speed railway vertical acceleration and derailment coefficient; through the reliability calculation model, comprehensive analysis of various factors, and provide accurate driving safety reliability evaluation. Compared with traditional finite element analysis, this method can achieve low-cost and efficient safety evaluation, can be applied in different geological and construction environments, and support long-term dynamic monitoring and evaluation. At the same time, it has the ability of automated evaluation and real-time early warning, providing data-driven decision support for high-speed railway operation safety. In general, this method greatly improves the accuracy, real-time and intelligence level of high-speed rail driving safety assessment by integrating laser point cloud technology, machine learning and reliability calculation models, and provides a more scientific and efficient solution for the driving safety of high-speed rail when passing through shield construction tunnels.

[0036] This embodiment also includes a readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, the above-mentioned method for evaluating driving safety when a high-speed railway passes through a shield construction tunnel is implemented.

[0037] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0038] This embodiment also includes an electronic device, including: at least one processor, at least one memory, and computer program instructions stored in the memory. When the computer program instructions are executed by the processor, the driving safety evaluation method for a high-speed railway passing through a shield construction tunnel as described above is implemented.

[0039] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the electronic device.

[0040] The electronic device may be a computing device such as a mobile phone, a desktop computer, a notebook, a PDA, a cloud server, etc. The electronic device may include, but is not limited to, a processor and a memory. For example, the electronic device may also include an input / output device, a network access device, a bus, etc.

[0041] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the electronic device, and various interfaces and lines are used to connect various parts of the entire electronic device.

[0042] The memory can be used to store the computer program and / or module, and the processor implements the computer program by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0043] Wherein, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0044] 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.

Claims

1. A driving safety detection device for high-speed railways passing through shield tunnels, used to detect the driving reliability of shield tunnels passing through high-speed railway subgrade sections, characterized in that: The invention comprises a point cloud acquisition module, a laser indication module and a processing module, wherein the point cloud acquisition module comprises at least four point cloud acquisition components (2) evenly arranged on both sides of a running track (1), and target plates (2.3) are arranged on both sides of the point cloud acquisition component (2), and the point cloud acquisition component (2) is used to scan and obtain a point cloud model of a high-speed railway subgrade area to be detected; The laser pointing module comprises two laser pointing assemblies (3) arranged diagonally, the two laser pointing assemblies (3) being arranged in long-term non-deformation areas on both sides of the vehicle track (1), and the laser pointing assembly (3) comprising at least four laser pointers (3.1), the laser pointers (3.1) being arranged in one-to-one correspondence with the target plates (2.3), and the laser pointers (3.1) being used to measure the center coordinates corresponding to the target plates (2.3); The processing module is electrically connected to the point cloud acquisition component (2) and the laser indicator (3.1) respectively, and is used to process the point cloud model acquired by the point cloud acquisition component (2) and the center coordinates of the target plate (2.3) measured by the laser indicator (3.1) to obtain the high-speed rail driving reliability.

2. The driving safety detection device for high-speed railway passing through a shield tunnel according to claim 1 is characterized in that: The point cloud acquisition component (2) comprises a support rod (2.1) and a laser radar (2.2); the support rod (2.1) is vertically arranged on the ground, and the target plates (2.3) are arranged on both sides of the support rod (2.1); the laser radar (2.2) is arranged on the support rod (2.1), and the point cloud model accumulated by each of the laser radars (2.2) covers at least 100 meters of the length of the driving track (1).

3. The driving safety detection device for high-speed railway passing through a shield construction tunnel according to claim 2 is characterized in that the laser indicator (3.1) includes a mounting base (3.1.1), a rotary steering gear (3.1.2), a pitch steering gear (3.1.3), a laser ranging element (3.1.4) and an IMU element (3.1.5), wherein the mounting base (3.1.1) is arranged on the ground in a long-term non-deformation area; the rotary steering gear (3.1.2) is horizontally arranged on the mounting base (3.1.1); the pitch steering gear (3.1.3) is connected to the output shaft of the rotary steering gear (3.1.2), and the rotary steering gear (3.1.2) can drive the pitch steering gear (3.1.3) to rotate in a horizontal plane; the laser ranging element (3.1.4) is connected to the pitch steering gear ( The pitch servo (3.1.3) is connected to the output shaft of the laser ranging element (3.1.4), the pitch servo (3.1.3) can drive the laser ranging element (3.1.4) to rotate in the vertical plane, the laser ranging element (3.1.4) is used to measure the distance between the laser emission point and the target plate (2.3), and the laser ranging element (3.1.4) is provided with a laser indicator light for lighting; the IMU element (3.1.5) is arranged on the laser ranging element (3.1.4), and the IMU element (3.1.5) is used to measure the azimuth and pitch angle of the laser ranging element (3.1.4).

4. The driving safety detection device for high-speed railway passing through a shield tunnel according to claim 3 is characterized in that: The laser indicator (3.1) further comprises a control element (3.1.6), the control element (3.1.6) being arranged on the mounting base (3.1.1), the control element (3.1.6) comprising a single-chip microcomputer chip, a data transmission unit and a control unit, the single-chip microcomputer chip being connected to the rotary servo (3.1.2) and the pitch servo ( The data transmission unit is electrically connected to the laser ranging element (3.1.4), the IMU element (3.1.5) and the processing module respectively, and is used to transmit the measurement data of the laser ranging element (3.1.4) and the IMU element (3.1.5) to the control unit; the control unit can calculate the center coordinates of the target plate (2.3) according to the measurement data of the laser ranging element (3.1.4) and the IMU element (3.1.5), and transmit them to the processing module.

5. A method for evaluating the driving safety of a high-speed railway passing through a shield tunnel, using the driving safety detection device for a high-speed railway passing through a shield tunnel as described in any one of claims 2 to 4, characterized in that: The steps include: S1. When the shield tunnel has not yet affected the high-speed railway subgrade section, the driving safety detection device for the high-speed railway passing through the shield construction tunnel is arranged in the high-speed railway subgrade area to be detected; S2. Establish a high-speed rail track recognition model, specifically: create a track label point cloud data set based on the N point cloud models obtained by scanning the shield tunnel under the high-speed rail subgrade section N times by the point cloud acquisition module, and establish a high-speed rail track recognition model using the RandLA-Net model, where: N is the set threshold; S3, using the high-speed rail track recognition model to identify the surface point cloud data on the top of the track; S4. The track deformation is calculated by using the KD tree nearest neighbor search algorithm and the Euclidean distance algorithm based on the difference in the surface point cloud data before and after the shield tunnel affects the high-speed railway subgrade section; S5. A high-speed rail operation state prediction model is established by using a train operation aerodynamic simulation model, a train-track dynamics model and a PSO-XGBoost prediction model, and the current operation speed of the high-speed rail, the current driving condition and the track deformation in S4 are input into the high-speed rail operation state prediction model, and the vertical acceleration, derailment coefficient and wheel load reduction rate of the high-speed rail when it is running in the high-speed rail subgrade area to be detected are output, wherein: the current driving condition refers to single-car driving or double-car crossing driving; S6. Input the vertical acceleration, derailment coefficient and wheel load reduction rate in S5 into the existing reliability model to obtain the reliability of the high-speed rail when it travels in the lower shield construction area. If the reliability is less than zero, the high-speed rail has a risk of overturning when passing through the area at the current speed and state; otherwise, repeat S3 to S6 every M minutes, where: M is the set threshold.

6. The method for evaluating driving safety of a high-speed railway when passing through a shield tunnel according to claim 5 is characterized in that: The S1 includes: When the shield tunnel construction does not affect the high-speed railway subgrade section, at least four point cloud acquisition components (2) are arranged at a distance of 10m to 15m from the center line of the subgrade, and the four point cloud acquisition components (2) are evenly arranged on both sides of the driving track (1) of the high-speed railway subgrade area to be inspected, wherein: the scanning ranges of the two point cloud acquisition components (2) located on the same side of the driving track (1) overlap; A laser indication assembly (3) is arranged respectively in an area 100m to 150m away from the roadbed centerline on both sides of the driving track (1) and where the ground surface has no deformation for a long time, and the laser indication assemblies (3) on both sides of the driving track (1) are arranged diagonally.

7. The method for evaluating driving safety of a high-speed railway passing through a shield tunnel according to claim 6, characterized in that: The S3 includes: S3.1, calculating the coordinates of each laser radar (2.2) according to the center coordinates of the target plate (2.3) measured by the laser indication module, and using each laser radar (2.2) to scan the high-speed railway subgrade surface at time t to obtain point cloud coordinate data of the high-speed railway subgrade surface; S3.2, according to the coordinates of each laser radar (2.2), the point cloud coordinate data of the high-speed railway foundation surface scanned by each laser radar (2.2) is converted into the same coordinate system by using Euclidean transformation to obtain a point cloud model of the high-speed railway foundation at time t; S3.

3. Use the high-speed rail track recognition model to identify the track point cloud data in the high-speed rail base point cloud model to obtain the track point cloud data model, and use the regional growing algorithm to extract the surface point cloud data of the top of the track in the track point cloud data model.

8. The method for evaluating driving safety of a high-speed railway passing through a shield tunnel according to claim 7, characterized in that: In S3.1, the steps for calculating the laser radar (2.2) coordinates are as follows: ①. Adjust the high-precision laser pointing device so that its laser point falls on the center point of the target plate (2.3); ② Use the total station to measure the three-dimensional geodetic coordinates of the laser ranging element (3.1.4) ; and use the laser distance measuring element (3.1.4) to measure the distance between the laser emission point and the center of the target plate (2.3) The associated IMU module determines the azimuth of the laser ranging element (3.1.4) and pitch angle ; ③. According to the three-dimensional geodetic coordinates of the laser ranging element (3.1.4), the distance between the laser emission point and the center of the target plate (2.3), the azimuth angle and the pitch angle, the coordinates of the laser points on the two target plates (2.3) in the point cloud acquisition component (2) are calculated, that is, the center coordinates of the target plate (2.3) , the specific calculation formula is as follows: ； in: is the azimuth of the geodetic coordinate system in the x-axis direction of the area where the laser ranging element (3.1.4) is located; ④. Calculate the laser radar (2.2) coordinates based on the center coordinates of the two target plates (2.3), specifically: When the shield tunnel construction does not affect the high-speed railway subgrade section, the corresponding coordinates of the laser radar (2.2) corresponding to the center coordinates of the two target plates (2.3) are calculated respectively, and the average of the corresponding coordinates of the two laser radars (2.2) is used as the coordinates of the laser radar (2.2); When the shield tunnel construction affects the high-speed railway subgrade section, repeat ① to ③ to obtain the center coordinates of the two target plates (2.3) in the point cloud acquisition component (2) after the shield tunnel affects the high-speed railway subgrade section, and calculate the laser radar (2.2) coordinates based on the average value of the center coordinate deformation of the target plates (2.3) before and after the shield tunnel affects the high-speed railway subgrade section.

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