Air-rail cooperative railway line bridge eccentricity detection method

Abstract

The invention discloses an air-rail cooperative railway line bridge eccentricity detection method. The method comprises the steps that S1, a line control network composed of a plane control network and an elevation control network is established; s2, measuring the relative position of a track at the cross section of the bridge and an on-line structure; s3, measuring the relative position of the beam edge at the cross section of the bridge and the on-line structure; and S4, performing time-space synchronization and fusion on the data obtained in S2 and S3 to obtain a line bridge eccentricity measurement result. The method is high in detection efficiency, accurate in detection, high in safety and low in labor cost.

Description

Technical Field

[0001] This invention relates to the field of railway engineering technology, and in particular to a method for detecting eccentricity of railway line bridges using a combination of air and rail systems. Background Technology

[0002] Railway line-bridge eccentricity refers to the horizontal deviation between the actual centerline of the railway line and the designed centerline of the bridge structure at the junction of the railway line and the bridge (line-bridge system) under the influence of factors such as train dynamic load, temperature changes, and foundation settlement. Line-bridge eccentricity is the result of the combined effects of multiple factors, including improper design pre-eccentricity settings, inappropriate construction techniques, inadequate maintenance methods during operation, degradation of bridge material performance, and the influence of geological conditions.

[0003] Railway line-bridge eccentricity can lead to poor wheel-rail coordination when trains run on the bridge, causing instability, affecting train speed, and even increasing the risk of derailment, posing a potential threat to passenger safety. Simultaneously, eccentricity causes the bridge to bear greater uneven loads; long-term uneven loading can lead to fatigue damage and further deterioration, threatening transportation safety and increasing the workload of bridge repair and maintenance. Therefore, the detection and remediation of railway line-bridge eccentricity is a crucial task during railway operation and maintenance.

[0004] Only through accurate and rapid detection of railway line and bridge eccentricity can effective remediation be ensured. Currently, there are three methods for detecting railway line and bridge eccentricity: total station measurement, laser rangefinder method, and photogrammetry.

[0005] 1. Total station measurement method: Set up a total station at key points of bridges and lines to simultaneously measure horizontal distance and elevation difference, and calculate the eccentricity value in combination with design drawings. Its advantage is high accuracy (up to millimeter level), and it is suitable for complex terrain or scenarios that require multi-angle measurement, such as curved bridges or slope sections. The disadvantage is that it requires manual point collection, which is not only inefficient but also has a large workload.

[0006] 2. Laser ranging method: This method uses a laser rangefinder to directly acquire the distance data between measuring points, and then quickly calculates the eccentricity value by combining it with positioning markers. This method is highly efficient, especially suitable for long-span bridges or situations requiring minimal human intervention. However, it has high requirements for ambient light intensity; strong light or fog may affect accuracy. Additionally, because the track and beam edges are not in the same field of view, they cannot be observed simultaneously, resulting in lower accuracy.

[0007] 3. Photogrammetry: This method involves capturing images of the bridge and railway line using a high-resolution camera, extracting spatial coordinates using 3D modeling software, and analyzing axis deviation. It generates visual reports for easy archiving and remote verification, and is commonly used for periodic monitoring or historical data comparison. However, photogrammetry is generally used to detect relative changes in bridge-line eccentricity. The amount of data processing is very large, requiring highly skilled surveyors and advanced equipment, leading to excessive costs. Summary of the Invention

[0008] To address the problems existing in the prior art, one objective of this invention is to provide a method for detecting railway line-bridge eccentricity using a combined air-rail system, which can achieve accurate, efficient, and low-cost detection of line-bridge eccentricity.

[0009] Another objective of this invention is to provide a precise method for detecting ballast thickness.

[0010] Therefore, the present invention adopts the following technical solution:

[0011] A method for detecting eccentricity of railway bridges using a combination of air and rail systems includes the following steps:

[0012] S1, Establish a line control network consisting of a plane control network and an elevation control network;

[0013] S2, using the aforementioned line control network as a reference, measure the track geometric parameters, and combine the calibration values ​​of the inertial navigation center and the lidar center to calculate the trajectory data of the lidar center in different sampling time series; perform a moving three-dimensional scan of the railway bridge's online structure, and fuse the obtained laser scan data with the trajectory data to form a three-dimensional point cloud of the railway bridge's online structure; convert the track center coordinates into track mileage; select the location of the bridge cross section, extract the cross section at that location from the three-dimensional point cloud data, and measure the relative position of the beam edge at the cross section with the online structure;

[0014] S3. Design the UAV flight path based on the orbital geometry parameters obtained in S2; use the line control network as the control reference to collect UAV flight path data and laser data on both sides of the bridge; unify the mileage system of UAV measurement data; extract the cross-section of the three-dimensional point cloud on the outside of the bridge according to the method in S2, and measure the relative position of the beam edge and the structure on the line at the cross-section.

[0015] S4 combines the measurement results from S2 and S3 to obtain the measurement results of the bridge eccentricity.

[0016] In step S2 above, the laser scanning data includes time-synchronized ranging values. and scanning angle ( The global coordinates of each point in the three-dimensional point cloud. Calculated using Euler transformation:

[0017] ;

[0018] in, The rotation matrix is ​​formed by the Euler angles in the trajectory. (yaw), (Looking up and down) (Scroll) Press The sequential construction is shown in the following formula:

[0019] ;

[0020] Translation vector ; The coordinates of the point in the local coordinate system of the laser scanner on the track inspection instrument are determined by the distance measurement value. and scanning angle calculate:

[0021] ;

[0022] in, It is a horizontal angle; It is a vertical angle.

[0023] In step S2 above, the track geometric parameters include track size parameters, shape geometric parameters, and the three-dimensional coordinates of the track centerline. , , The method for converting track center coordinates into track mileage includes the following steps: (and the deviations of the left and right rails in plane and elevation relative to the design alignment);

[0024] S231, orbital alignment fitting, including:

[0025] (1) Line segment fitting: Let the equation of the line be The solution using the least squares method is shown in the following equation:

[0026] ,

[0027] ;

[0028] (2) Circular curve fitting: Let the center of the circular curve be... , radius is The minimum sum of squared residuals is shown in the following equation:

[0029] ;

[0030] (3) Transition curve fitting: A cubic parabola model was adopted. The radius of the circular curve is... To represent the total length of the transition curve, then:

[0031] ;

[0032] S232, Establish a linear reference system, and realize the mutual conversion between track center coordinates and track mileage through forward and inverse calculations of mileage point coordinates. The specific steps are as follows:

[0033] 1) Convert mileage to coordinates:

[0034] For a line segment, the conversion formula is:

[0035] ,

[0036] ;

[0037] in The coordinates of the starting point of the line segment; It is the azimuth angle; For mileage;

[0038] For circular curve segments, the conversion formula is:

[0039] ,

[0040] ;

[0041] in Let r be the center of the circular curve segment; r is the radius of the circular curve segment. This is the starting mileage of the circular curve segment; The initial tangent angle;

[0042] For the transition curve segment, the conversion formula is:

[0043] ,

[0044] ;

[0045] in The total length of the transition curve; l is the integration variable, representing the variable in the process of finding the curve length; The starting mileage for easing the curve segment;

[0046] 2) Convert the coordinates to mileage, which is then calculated iteratively using the following formula:

[0047] ,

[0048] ,

[0049] in This is a positive calculation formula. Its derivative; ≥0.

[0050] In step S2, the method for extracting cross-sections from 3D point cloud data includes:

[0051] S241, Calculation of bridge cross-section location:

[0052] Calculate based on the fitting results of the design documents or the track centerline. The three-dimensional coordinates of the track center on the cross section at the mileage point Tangent azimuth and slope ;

[0053] S242, Construction of bridge cross-section equations:

[0054] The cross-section of the bridge is perpendicular to the centerline of the track, and its plane equation is expressed as:

[0055] ,

[0056] in, , , , ;

[0057] S243, Point Cloud Extraction:

[0058] Using the equations in S242, point cloud data within the cross-sectional area of ​​the bridge is extracted from the 3D point cloud to form a bridge cross-sectional point set. :

[0059] ,

[0060] in, Let N be the i-th point in the cross-sectional point set of the bridge, and N be the total number of points in the point set.

[0061] In step S2, the steps for measuring the relative position of the beam edge and the structure on the line at the cross-section are as follows:

[0062] S251, Point Cloud Denoising: Remove outlier noise points in 2D point clouds using statistical filtering or radius filtering;

[0063] S252, Point Cloud Classification: Using the design distance and height difference between the guardrail and the track as spatial thresholds, the left and right guardrail point clouds are separated through segmentation operations; using the design values ​​of line spacing and adjacent line height difference as spatial thresholds, the left and right rail point clouds of the left line and the right line are separated through segmentation operations.

[0064] S253, Cluster Analysis: DBSCAN clustering is performed on the guardrail point cloud to further extract the point clouds of the guardrail and rail.

[0065] S254, Point cloud fitting at the top of the guardrail: Perform line fitting on the point cloud at the top of the guardrail to obtain the coordinates of the top of the left guardrail. Coordinates of the top of the right guardrail ;

[0066] S255, Calculation of the relative position from the track center to the guardrail: The center point coordinates of the track rails are extracted using either the geometric feature method or the template matching method, and the relative position from the track center to the guardrail is calculated. Specifically, when calculating the relative position from the track center to the guardrail:

[0067] For single-line bridges, first extract the mileage. Center point of the left rail of the track at the cross section Center point of the right rail of the line Next, calculate the distance from the center of the left and right rails to the guardrail. and elevation difference , The formula is as follows:

[0068]

[0069]

[0070]

[0071]

[0072] Among them, X L Y L X R Y R , which are the x and y coordinates of the top of the left and right guardrails, respectively;

[0073] For a two-line bridge, first extract... Center point of the left rail on the left line at the cross section Center point of the left and right rails Center point of the left rail on the right line Center point of the right rail on the right line Next, measure the distance from the center of the left and right tracks to the guardrail. and and elevation difference and The formula is as follows:

[0074]

[0075]

[0076]

[0077]

[0078] In step S3 above, the steps for designing the drone flight path are as follows:

[0079] S311, Calculate the outward parallel path:

[0080] The normal vector direction of each centerline node is calculated based on the track geometry parameters measured in S2, and then parallel paths are generated by expanding outwards by 10 meters to both sides. The mathematical expression is as follows:

[0081] ;

[0082] in This represents the coordinate difference between adjacent 1m midline nodes. The coordinates of the midline node;

[0083] For railway curve sections, adjust the outward expansion direction in conjunction with the radius of curvature to avoid path intersections or abrupt changes;

[0084] S312, Altitude Control:

[0085] Drone flight altitude Should be compared with the rail surface elevation Low , For a distance of 3-5 meters, there are:

[0086] ;

[0087] If the flight path passes over an obstacle during flight, the altitude or lateral deviation should be dynamically adjusted to ensure a safe distance.

[0088] S313, optimizes flight routes;

[0089] The steps for measuring the relative position of the beam edge and the structure along the line at the cross-section are as follows:

[0090] S351, Point Cloud Denoising: Removes outlier noise points in 2D point clouds using statistical filtering or radius filtering;

[0091] S352, Point Cloud Classification: Based on the coordinates of the top of the left and right guardrails measured in S2, select an appropriate threshold and separate the point clouds of the left and right guardrails through a segmentation operation; based on the design value of the height difference between the rail and the beam, select an appropriate threshold and separate the point clouds of the left and right beam edges through a segmentation operation.

[0092] S353, Cluster Analysis: Cluster the point cloud of the guardrail to further extract the point cloud of the guardrail and beam edges;

[0093] S354, Point cloud fitting at the top of the guardrail: Perform line fitting on the point cloud at the top of the guardrail to obtain the coordinates of the top of the left guardrail. Coordinates of the top of the right guardrail The top corner point of the beam edge was extracted using a linear fitting method, and the coordinates of the top corner point of the left beam edge were obtained. Coordinates of the top corner point of the right beam edge ;

[0094] S355, Calculate the relative position of the top corner point of the beam edge to the guardrail: Extract mileage. The horizontal distance between the top of the left guardrail and the edge of the left beam in the cross section and elevation difference The horizontal distance between the top of the right guardrail and the edge of the right beam and elevation difference The distance between the left and right edges of the bridge beams :

[0095]

[0096]

[0097]

[0098]

[0099] .

[0100] In step S3, the flight path data includes the position (X, Y, Z) and attitude data during flight; the laser data includes time-synchronized ranging values ​​and scanning angles; based on the flight path data of the UAV, the calibration values ​​of the lidar and POS system, and the laser data, the global coordinates of each point in the three-dimensional point cloud are calculated, and finally the three-dimensional point cloud of the outer side of the bridge is generated.

[0101] In step S4, the measured eccentricity value of the cable bridge is achieved by fusing data from the relative positions of the track and the on-line structure at the cross-section obtained in S2 and the relative positions of the beam edge and the on-line structure at the cross-section obtained in S3, thereby realizing high-precision relative measurement of the cable bridge eccentricity. The measured eccentricity value of the cable bridge includes the following cases:

[0102] (1) For a straight section of a single-track bridge, the eccentricity P of the bridge is as follows:

[0103] ;

[0104] in, and These are the distances from the center of the left and right rails to the guardrail, measured in S255 respectively. This refers to the distance between the top of the left guardrail and the edge of the left beam, measured in S355. This refers to the distance between the top of the right guardrail and the edge of the right beam, as measured in S355.

[0105] (2) For single-track bridge curved sections, the influence of initial eccentricity needs to be considered; since the bridge plane is a broken line, the design centerline of the line does not coincide with the design centerline of the beam span, thus generating initial eccentricity; for each beam span, the initial eccentricity occurs at the midpoint and both ends of the beam span; according to the design drawings, "the planar arrangement of beams on curves is based on the principle that the chord length (equal to the distance between the center of the piers or the distance from the breast wall of the abutment to the center of the pier) is the midpoint (i.e., F=f / 2) of the bisector of the bridge centerline", then the eccentricity P of the line bridge is as follows:

[0106] ;

[0107] in, and These are the distances from the center of the left and right rails to the guardrail, measured in S255 respectively. This refers to the distance between the top of the left guardrail and the edge of the left beam, measured in S355. This refers to the distance between the top of the right guardrail and the edge of the right beam, as measured in S355. For track gauge, The superelevation is measured using the internal geometric parameters of the track in S21; L is the distance between the center of the pier or the distance from the breast wall of the abutment to the center of the pier, which can be approximated by the beam length; R is the curve radius, which can be obtained from the design data.

[0108] (3) For the straight sections of the double-track bridge, the design center lines of the left and right tracks coincide with the design center lines of the left and right beam spans (the left track is the track facing the large mileage). The actual distance from the track center line to the edge of the beam is measured and compared with the distance from the design center line of the beam span to the edge of the beam. The eccentricity values ​​of the track and bridge for the left and right tracks are calculated respectively. and As shown in the following formula:

[0109] ;

[0110] ;

[0111] in, and These are the distances from the center of the left and right rails to the guardrail, measured in S255 respectively. This refers to the distance between the top of the left guardrail and the edge of the left beam, measured in S355. This refers to the distance between the top of the right guardrail and the edge of the right beam, as measured in S355. The track gauge can be obtained by measuring the internal geometric parameters of the track in S21. This is the design distance from the center of the left track to the edge of the left beam. This is the design distance from the center of the right track to the edge of the right beam, which can be obtained from the design data;

[0112] (4) For the double-track bridge curve segment, considering the influence of the initial eccentricity, calculate the eccentricity values ​​of the left and right tracks respectively. and As shown in the following formula:

[0113] ;

[0114]

[0115] In step S1: The plane control network is established by deploying GNSS reference stations in the form of continuously operating GNSS reference stations or temporary GNSS stations, with an interval of 15-25 km between the GNSS reference stations; for GNSS reference stations with an interval of more than 18 km, a GNSS densification point is set up at the middle position, and the plane coordinates of the densification point are calculated by connecting it to the plane control network; the elevation control network is set up according to the fourth-order leveling measurement standard, and it is as close as possible to the GNSS points of the plane control network, wherein the spacing between elevation points along the entire line is controlled at about 4 km; for sections with a spacing greater than 4 km, elevation densification control points are set up; the elevation control points along the entire line and the elevation densification control points are all measured using the fourth-order leveling measurement standard and connected to the high-level control points with known elevations along the line.

[0116] This invention proposes a method for measuring railway line-bridge eccentricity and ballast thickness using cutting-edge technologies such as mobile 3D scanning, inertial measurement, and UAV LiDAR. The method first obtains the relative positions of the track and railway line structures using a "GNSS + inertial measurement + 3D scanning" precision surveying technique. Then, it uses UAV LiDAR to acquire 3D point clouds of beam edges and bridge railings offline, and measures the relative positions of these two locations. Through coordinate unification and data fusion, the relative positions of the line center and beam edges are accurately measured.

[0117] Compared with the prior art, the present invention has the following beneficial effects:

[0118] 1. High inspection efficiency and low labor cost. The inspection method of this invention enables rapid detection of the relative positions of the track and railway line structures, and the relative positions of beam edges and railway line structures (such as bridge railings, sound barriers, and catenary columns). Using a precision track measurement technology combining GNSS, inertial measurement, and 3D scanning, the online measurement speed can reach 5 km / h; the offline measurement speed using UAV lidar can reach 10 km / h. Data fusion of these two methods enables rapid measurement of the relative positions of the track and beam edges, ultimately allowing for the calculation of track and bridge eccentricity and ballast thickness. The overall efficiency of this method is greater than 5 km / h, more than five times that of the total station measurement method. Due to the high inspection efficiency, fewer track windows are required, significantly reducing labor costs and saving track window resources.

[0119] 2. Precise Detection. The detection method of this invention adopts a relative measurement method, eliminating the systematic errors of different measurement modes and achieving millimeter-level measurement accuracy. First, based on a unified track control network, the mileage system of track inspection instrument and UAV measurement data is unified, achieving a mileage positioning accuracy of better than 2cm for both track inspection instruments and UAVs. This ensures the consistency of the cross-section extracted from the 3D point cloud by the track inspection instrument and UAV, eliminating the error caused by mismatch in the measured cross-sections due to mileage mismatch. Through the measurement and data fusion of key dimensions of the measured cross-sections by the track inspection instrument and UAV, high-precision measurement of track and bridge eccentricity is achieved. The method can achieve a measurement accuracy of 1mm for the relative position of the track and the structure on the railway line, and a measurement accuracy of 2mm for the relative position of the beam edge and the structure on the railway line. According to the error propagation law, the measurement error of railway line and bridge eccentricity is less than 3mm, meeting the measurement accuracy requirements of the specifications; the measurement error of ballast thickness is less than 1cm, meeting the measurement accuracy requirements of the specifications.

[0120] 3. High safety. In the detection method of this invention, on-line measurement is only required when measuring the relative positions of the centerline of the line and the structures on the railway line (such as bridge railings, sound barriers, catenary columns, etc.) using the "GNSS + inertial measurement + three-dimensional scanning" line precision measurement technology. Only one measurement person is needed to operate on-line, which greatly reduces the safety risks of on-line operation. The drone flies on both sides of the bridge and below the bridge surface, which ensures high safety. Attached Figure Description

[0121] Figure 1 This is a schematic diagram of the railway line bridge eccentricity detection method of the present invention;

[0122] Figure 2 This is a flowchart of the railway line bridge eccentricity detection method of the present invention;

[0123] Figure 3 This is a schematic diagram of a three-dimensional point cloud scanned on a single-line bridge in an embodiment of the present invention;

[0124] Figure 4 This is a schematic diagram of a three-dimensional point cloud scanned on a double-line bridge line in an embodiment of the present invention;

[0125] Figure 5 This is a schematic diagram of the cross-sectional point cloud extracted from a single-line bridge in an embodiment of the present invention;

[0126] Figure 6 This is a schematic diagram of the cross-sectional point cloud extracted from the double-line bridge line in an embodiment of the present invention;

[0127] Figure 7 This is a schematic diagram of the extraction points of key locations on a single line in an embodiment of the present invention;

[0128] Figure 8This is a schematic diagram of the key location extraction points of the double line in an embodiment of the present invention.

[0129] in:

[0130] 1. Laser scanner, 2. Left side railing of bridge, 3. Left rail, 4. Right rail, 5. Right side railing of bridge, 6. Left rail of left line, 7. Right rail of left line, 8. Left rail of right line, 9. Right rail of right line. Detailed Implementation

[0131] The detection method of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0132] See Figure 1 and Figure 2 The air-rail coordinated railway bridge eccentricity detection method of the present invention includes the following steps:

[0133] S1, Establish the line control network:

[0134] The line control network is established according to the principle of hierarchical layout, consisting of two parts: the horizontal control network and the vertical control network. The horizontal control network and the vertical control network share as many points as possible.

[0135] In one embodiment of the present invention, the plane control network adopts an engineering independent coordinate system based on the 2000 National Geodetic Coordinate System (CGCS2000), and the independent coordinate system is designed before the network is built to ensure that the projected length deformation value on the line design elevation surface is not greater than 25mm / km; the elevation control network is established using the 1985 National Elevation Datum.

[0136] The planar control network is constructed using GNSS reference stations in the form of Continuously Operating Reference Stations (CORS) or temporary GNSS stations, with an interval of 15-25 km between the reference stations. Depending on the route conditions, for GNSS reference stations with an interval of more than 18 km, an additional GNSS densification point is deployed between them. The GNSS densification point is connected to the planar control network, and its planar coordinates are calculated.

[0137] The elevation control network is established according to the fourth-order leveling measurement standard, and it shares points with the GNSS of the plane control network as much as possible. The spacing between elevation control points along the entire line is controlled to be approximately 4 km. For sections with a spacing greater than 4 km, additional elevation control points are set up. In one embodiment of the invention, both the overall elevation control points and the additional elevation control points are measured using the fourth-order leveling measurement standard, and are connected to high-level control points with known elevations along the line.

[0138] S2, Measuring the relative position of the track and the on-line structure at the bridge cross-section includes: using the track control network as a reference, measuring the track geometric parameters; combining the calibration values ​​of the inertial navigation center and the lidar center, calculating the trajectory data of the lidar center at different sampling time series; performing a moving three-dimensional scan of the railway bridge's on-line structure, fusing the obtained laser scan data with the trajectory data to form a three-dimensional point cloud of the railway bridge's on-line structure; converting the track center coordinates into track mileage; selecting the location of the bridge cross-section, extracting the cross-section at that location from the three-dimensional point cloud data, and measuring the relative position of the beam edge and the on-line structure at the cross-section. The specific steps are as follows:

[0139] S21, Measure the orbital geometry parameters to obtain the trajectory data of the lidar center at different sampling time series:

[0140] Based on the track control network, a precise track measurement technique based on "GNSS + inertial measurement + 3D scanning" is employed, using relevant instruments and equipment (such as inertial navigation track inspection instruments integrating lidar) to measure track geometric parameters. These track geometric parameters include internal and external geometric parameters. Internal geometric parameters include: track gauge (d), superelevation (h), levelness, alignment, elevation, versine, torsion (triangular crater), and gauge change rate, among other track dimensional and shape geometric parameters. External geometric parameters include: the three-dimensional coordinates of the track centerline (…). , , The track position geometric parameters include the deviations of the left and right rails from the design alignment in the plane (lateral) and elevation (vertical).

[0141] Based on the measurement results of the internal and external geometric parameters of the track, and combined with the calibration values ​​of the inertial navigation center and the lidar center, the trajectory data of the lidar center in different sampling time series are calculated. , , , , , , ),in , , These are the translation parameters in three spatial directions; (yaw), (Looking up and down) (Roll) refers to the Euler angle in the trajectory line; is the scale factor.

[0142] S22, Online structural 3D scanning:

[0143] Based on the "GNSS + inertial measurement + 3D scanning" precision surveying technology, while implementing S21, a moving 3D scan of the railway bridge's online structure (such as bridge railings, sound barriers, and catenary columns) is performed to obtain laser scan data of the online structure. The laser scan data includes time-synchronized distance measurements. and scanning angle ( The laser scanning data is fused with the trajectory line data obtained in S21 to form a three-dimensional point cloud of the railway bridge structure. The global coordinates of each point in the three-dimensional point cloud are... Calculated using Euler transformation:

[0144] ,

[0145] in:

[0146] The rotation matrix is ​​formed by the Euler angles in the trajectory. (yaw), (Looking up and down) (Scroll) Press The sequential construction is shown in the following formula:

[0147] ,

[0148] Translation vector ;

[0149] The coordinates of the point in the local coordinate system of the laser scanner on the inertial navigation track inspection instrument are obtained through the distance measurement value. and scanning angle The calculation yielded:

[0150] ,

[0151] in, It is a horizontal angle; It is a vertical angle.

[0152] In one embodiment of the present invention, the fused three-dimensional point cloud of the railway line structure is as follows: Figure 3 and Figure 4 As shown, 2 is the left side railing of the bridge, 3 is the left rail, 4 is the right rail, 5 is the right side railing of the bridge, 6 is the left rail of the left line, 7 is the right rail of the left line, 8 is the left rail of the right line, and 9 is the right rail of the right line.

[0153] S23, Unified Mileage System: Based on the three-dimensional coordinates of the track centerline in the external geometric parameters measured in S21 ( , , The process involves orbital alignment fitting, calculation of orbital curve parameters, and the establishment of a linear reference system to convert orbital center coordinates to orbital mileage. The specific steps are as follows:

[0154] S231, Track alignment fitting: The track is decomposed into straight lines, circular curves, and transition curves, and piecewise fitting is performed. Parameters are then calculated using the least squares method, as detailed below:

[0155] (1) Line segment fitting: Let the equation of the line be The solution using the least squares method is shown in the following equation:

[0156] ,

[0157] ,

[0158] (2) Circular curve fitting: Let the center of the circular curve be... , radius is The minimum sum of squared residuals is shown in the following equation:

[0159] ,

[0160] (3) Transition curve fitting: A cubic parabola model was adopted. The radius of the circular curve is... To represent the total length of the transition curve, then:

[0161] .

[0162] S232. Establish a linear reference system and realize the mutual conversion between track center coordinates and track mileage through forward and inverse calculation formulas for mileage point coordinates. The specific steps are as follows:

[0163] 1) Convert mileage to coordinates (forward calculation):

[0164] The calculation is based on the line segmentation type, as follows:

[0165] ① Straight line segment:

[0166] ,

[0167] ,

[0168] in The coordinates of the starting point of the line segment; It is the azimuth angle; For mileage;

[0169] ② Circular curve segment:

[0170] ,

[0171] ,

[0172] in Let r be the center of the circular curve segment; r is the radius of the circular curve segment. This is the starting mileage of the circular curve segment; The initial tangent angle;

[0173] ③ Transition curve segment:

[0174] ,

[0175] ,

[0176] in The total length of the transition curve; l is the integration variable, representing the variable in the process of finding the curve length; The starting mileage for easing the curve segment;

[0177] 2) Convert coordinates to mileage (inverse calculation). Mileage is calculated iteratively using the following formula:

[0178] ,

[0179] ,

[0180] in This is a positive calculation formula. Its derivative; ≥0.

[0181] S24, Select the location of the bridge cross-section and extract the cross-section at that location from the 3D point cloud data:

[0182] First, on-site measurements are conducted using railway ledgers or inertial navigation track inspection instruments to obtain the mileage of each beam joint on the bridge. Then, according to different types of bridges, corresponding selection strategies are adopted to obtain the bridge cross sections. For simply supported beam bridges with a length of 32 meters or less, three cross sections are selected: the beam start point, the beam midpoint, and the beam end point. For continuous beam bridges with a length greater than 32 meters, the beam start point and the beam end point are selected, and starting from the beam start point, a beam midpoint cross section is taken every 30 meters.

[0183] Based on the three-dimensional coordinates of the orbital center obtained in S21 ( , , The 3D point cloud of the railway bridge structure obtained in S22 is used to determine the 3D coordinates of the track center corresponding to the target mileage by using the conversion relationship between track center coordinates and track mileage. Then, the cross-section at that location is extracted from the 3D point cloud data. The specific steps are as follows:

[0184] S241, Calculation of bridge cross-section position: Based on the design documents or the fitting results of the track centerline, calculate... The three-dimensional coordinates of the track center on the cross section at the mileage point Tangent azimuth and slope ;

[0185] S242, Construction of bridge cross-section equations:

[0186] The cross-section of the bridge is perpendicular to the centerline of the track, and its plane equation can be expressed as:

[0187] ,

[0188] in, , , , ;

[0189] S243, Point Cloud Extraction: Using the equations in S242, extract point cloud data within the bridge cross-section area from the 3D point cloud to form a bridge cross-section point set. :

[0190] ,

[0191] in, Let N be the i-th point in the cross-sectional point set of the bridge, and N be the total number of points in the point set.

[0192] The fixed mileage extracted in the embodiments of the present invention The point clouds of the bridge cross section are as follows: Figure 5 and Figure 6 As shown, 2 is the left side railing of the bridge, 3 is the left rail, 4 is the right rail, 5 is the right side railing of the bridge, 6 is the left rail of the left line, 7 is the right rail of the left line, 8 is the left rail of the right line, and 9 is the right rail of the right line.

[0193] S25, Measurement of the relative position of the track and the structure on the line at the bridge cross-section: for fixed mileage At the cross-section, the relative positions of the track and the bridge railing are measured. The specific steps are as follows:

[0194] S251, Point Cloud Denoising: Remove outlier noise points in 2D point clouds using statistical filtering or radius filtering;

[0195] S252, Point Cloud Classification: Using the design distance and height difference between the guardrail and the track as spatial thresholds, the left and right guardrail point clouds are separated through segmentation operations; using the design values ​​of line spacing and adjacent line height difference as spatial thresholds, the left and right rail point clouds of the left line and the right line are separated through segmentation operations.

[0196] S253, Cluster Analysis: DBSCAN clustering is performed on the guardrail point cloud to further extract the point clouds of the guardrail and rail.

[0197] S254, Point cloud fitting at the top of the guardrail: Perform line fitting on the point cloud at the top of the guardrail to obtain the coordinates of the top of the left and right guardrails. , ;

[0198] S255, Calculation of the relative position from the track center to the guardrail: The coordinates of the center point of the track rail are extracted by geometric feature method or template matching method, and the relative position from the track center to the guardrail is calculated.

[0199] In one embodiment of the present invention, such as Figure 7 As shown, for a single-line bridge, a certain mileage is first extracted. Center point of the left rail on the cross section of the track Center point of the right rail of the line Next, measure the distance from the center of the left and right rails to the guardrail. and elevation difference , As shown in the following formula:

[0200] ,

[0201] ,

[0202] ,

[0203] ,

[0204] Among them, X L Y L X R Y R , , are the x and y coordinates of the top coordinates of the left and right guardrails, respectively.

[0205] In another embodiment of the invention, such as Figure 8 As shown, for a double-track bridge, a certain mileage is first extracted. Center point of the left rail on the cross section Center point of the left and right rails Center point of the left rail on the right line Center point of the right rail on the right line Next, measure the distance from the center of the left and right tracks to the guardrail. and and elevation difference and As shown in the following formula:

[0206] ,

[0207] ,

[0208] ,

[0209] .

[0210] S3, measuring the relative position of the beam edge and the structure on the line at the bridge cross-section, includes: designing the UAV flight path based on the orbital geometry parameters obtained in S2; collecting UAV flight path data and laser data from both sides of the bridge using the aforementioned line control network as the control reference; unifying the mileage system of the UAV measurement data; extracting the cross-section of the three-dimensional point cloud on the outer side of the bridge using the method in S2, and measuring the relative position of the beam edge and the structure on the line at the cross-section. The specific steps are as follows:

[0211] S31, designing drone flight paths:

[0212] Based on the three-dimensional coordinates of the track centerline measured in S21, the UAV flight path is designed to achieve safe UAV measurement of existing railway lines. The steps are as follows:

[0213] S311, Calculate the outward parallel path:

[0214] Based on the three-dimensional coordinates of the track centerline measured in S21 ( , , Calculate the normal vector direction (perpendicular to the tangent direction of the line) for each centerline node, then expand outwards by 10 meters to both sides to generate parallel paths. The mathematical expression is as follows:

[0215] ;

[0216] in This represents the coordinate difference between adjacent 1m midline nodes. The coordinates of the midline node;

[0217] For railway curve sections, the outward expansion direction needs to be adjusted according to the radius of curvature to avoid path intersections or abrupt changes;

[0218] S312, Altitude Control: Orbital Elevation Constraint: The UAV's flight altitude must be higher than the orbital elevation. Low Under normal circumstances Take 3-5 meters, as shown in the following formula:

[0219] ;

[0220] If the flight path passes over obstacles (such as bridges or mountains) during flight, the altitude or lateral deviation can be dynamically adjusted to ensure a safe distance.

[0221] S313, Route Optimization:

[0222] The main methods for route optimization are as follows, but are not limited to:

[0223] Path smoothing: Use cubic spline interpolation or B-spline curves to process the outward path, ensuring that the flight trajectory is continuous and differentiable.

[0224] Collaborative planning: If multiple drones are working together, flight segments need to be allocated and conflicts avoided, for example, by using ant colony algorithms or genetic algorithms to optimize the path.

[0225] S32, UAV Data Acquisition: The UAV integrates an airborne POS system and a small lidar, using the line control network as the control reference, to collect flight path data and lidar data from both sides of the bridge.

[0226] The airborne POS system performs attitude determination and positioning of the UAV based on PPK mode, and acquires flight path data of the UAV, including the position during flight ( , , ) and attitude data ( (yaw), (Looking up and down) (roll));

[0227] The lidar performs a three-dimensional scan of both sides of the bridge to acquire laser data, which mainly includes time-synchronized ranging values. and scanning angle ( );

[0228] Based on the UAV flight path data, the calibration values ​​of the lidar and POS system, and the laser data, the global coordinates of each point in the 3D point cloud are calculated, ultimately generating a 3D point cloud of the outer side of the bridge. The method for calculating the global coordinates of each point in the 3D point cloud is the same as the method in S22.

[0229] S33, unified mileage system:

[0230] This step directly uses the linear reference system established in S23 to realize the conversion from the orbital center coordinates to the orbital mileage.

[0231] S34, Cross-section extraction based on the 3D point cloud of the outer side of the bridge:

[0232] This step uses the cross-section extraction method in S24 to extract the cross-section of the three-dimensional point cloud on the outer side of the bridge.

[0233] S35, Measurement of the relative position of the beam edge and the structure on the line at the bridge cross section:

[0234] Fixed mileage The relative position of the beam edge and the guardrail on the cross-section is measured using the following steps:

[0235] S351, Point Cloud Denoising: Removes outlier noise points in 2D point clouds using statistical filtering or radius filtering;

[0236] S352, Point Cloud Classification: Based on the coordinates of the top of the left and right guardrails measured in S25, select an appropriate threshold and separate the point clouds of the left and right guardrails through a segmentation operation; based on the design value of the height difference between the rail and the beam, select an appropriate threshold and separate the point clouds of the left and right beam edges through a segmentation operation.

[0237] S353, Cluster Analysis: Perform DBSCAN clustering on the guardrail point cloud to further extract the point cloud of the guardrail and beam edges;

[0238] S354, Point cloud fitting of the top of the guardrail:

[0239] Linear fitting was performed on the point cloud at the top of the guardrail to obtain the coordinates of the top of the left guardrail. Coordinates of the top of the right guardrail Note that the steps described in this section... , Measured in S254 , For two measurements at the same location, the accuracy of repeated measurements can be improved by using a point cloud fitting algorithm.

[0240] The top corner point of the beam edge is extracted using a linear fitting method, and then the coordinates of the top corner point of the left beam edge are obtained. Coordinates of the top corner point of the right beam edge .

[0241] S355, Calculation of the relative position of the top corner point of the beam edge to the guardrail:

[0242] like Figure 7 , Figure 8 As shown, extraction is performed for single-line and double-line bridges. The horizontal distance between the top of the left guardrail and the edge of the left beam on the cross section of the bridge. and elevation difference The horizontal distance between the top of the right guardrail and the edge of the right beam and elevation difference The distance between the left and right edges of the bridge beams As shown in the following formula:

[0243] ,

[0244] ,

[0245] ,

[0246] ,

[0247] .

[0248] S4, Measuring the eccentricity of the track bridge: The relative position data of the track and the structure on the line obtained in S2 and the relative position data of the beam edge and the structure on the line obtained in S3 are fused in a time-space synchronization to achieve high-precision relative measurement of the eccentricity of the track bridge.

[0249] Calculate fixed mileage The cable bridge is eccentric, including the following situations:

[0250] (1) For a straight section of a single-track bridge, the formula for calculating the eccentricity P of the bridge is as follows:

[0251] ,

[0252] in, and These are the distances from the center of the left and right rails to the guardrail, measured in S255 respectively. and These are the distances between the top of the left and right guardrails and the edges of the left and right beams, respectively, as measured in S355.

[0253] (2) For single-track bridge curved sections, the effect of initial eccentricity needs to be considered. Since the bridge plane is a broken line, the design centerline of the line does not coincide with the design centerline of the beam span, thus generating initial eccentricity. For each beam span, the initial eccentricity occurs at the midpoint and both ends of the beam span. According to the design drawings, "the planar arrangement of beams on curves is based on the principle that the chord length (equal to the distance between the center of the piers or the distance from the breast wall of the abutment to the center of the pier) is the midpoint (i.e., F=f / 2) of the bisector of the bridge centerline," the formula for calculating the eccentricity P of the single-track bridge is as follows:

[0254] ,

[0255] in, and These are the distances from the center of the left and right rails to the guardrail, measured in S255 respectively. and The distances between the top of the left and right guardrails and the edges of the left and right beams, respectively, as measured in S355; For track gauge, The superelevation is measured using the internal geometric parameters of the track in S21; L1 is the distance between the center of the pier or the distance from the breast wall of the abutment to the center of the pier, which can be approximated by the beam length. The radius of the curve can be obtained from the design data;

[0256] (3) For the straight sections of the double-track bridge, the design center lines of the left and right tracks coincide with the design center lines of the left and right beam spans (the left track is the track facing the large mileage). The actual distance from the track center line to the edge of the beam is measured and compared with the distance from the design center line of the beam span to the edge of the beam. The eccentricity values ​​of the track and bridge for the left and right tracks are calculated respectively. and As shown in the following formula:

[0257] ,

[0258] ,

[0259] in, and These are the distances from the center of the left and right rails to the guardrail, measured in S255 respectively. and These are the distances between the top of the left and right guardrails and the edges of the left and right beams, respectively, as measured in S355. The track gauge is obtained by measuring the internal geometric parameters of the track as measured by S21. This is the design distance from the center of the left track to the edge of the left beam. This is the design distance from the center of the right track to the edge of the right beam, which can be obtained from the design data;

[0260] (4) For the double-track bridge curve segment, considering the influence of the initial eccentricity, calculate the eccentricity values ​​of the left and right tracks respectively. and As shown in the following formula:

[0261] ,

[0262] .

[0263] The ballast thickness of railway bridges refers to the vertical height from the bottom surface of the sleeper to the top surface of the bridge beam support (ballast thickness). Insufficient ballast thickness increases the rigidity of the track bed, causing the impact force of trains to be directly transmitted to the beam, accelerating beam cracks and bearing defects. Therefore, periodic inspection is necessary. Currently, ground-penetrating radar is mainly used to measure the ballast thickness of bridges, but its accuracy is difficult to meet the requirements of major track maintenance. Using the eccentricity detection results of the track and bridge obtained by this invention, the accurate ballast thickness of the bridge can be obtained.

[0264] like Figure 7 Figure 8 As shown, the ballast thickness for both single-track and double-track bridges is the height difference between the rail surface and the beam surface. Let the ballast thickness be Q, then:

[0265] ,

[0266] in, The height difference between the top and bottom of the rail. The thickness of the sleeper can be obtained from the design data.

Claims

1. A method for detecting eccentricity of railway line bridges using a combination of air and rail systems, characterized in that, Includes the following steps: S1, Establish a line control network consisting of a plane control network and an elevation control network; S2, using the aforementioned line control network as a reference, measure the track geometric parameters, and combine the calibration values ​​of the inertial navigation center and the lidar center to calculate the trajectory data of the lidar center in different sampling time series; perform a moving three-dimensional scan of the railway bridge's online structure, and fuse the obtained laser scan data with the trajectory data to form a three-dimensional point cloud of the railway bridge's online structure; convert the track center coordinates into track mileage; select the location of the bridge cross section, extract the cross section at that location from the three-dimensional point cloud data, and measure the relative position of the beam edge at the cross section with the online structure; S3. Design the UAV flight path based on the orbital geometry parameters obtained in S2; use the line control network as the control reference to collect UAV flight path data and laser data on both sides of the bridge; unify the mileage system of UAV measurement data; extract the cross-section of the three-dimensional point cloud on the outside of the bridge according to the method in S2, and measure the relative position of the beam edge and the structure on the line at the cross-section. S4 combines the measurement results from S2 and S3 to obtain the measurement results of the bridge eccentricity.

2. The railway line bridge eccentricity detection method according to claim 1, characterized in that: The laser scanning data described in S2 includes time-synchronized ranging values. and scanning angle ( The global coordinates of each point in the three-dimensional point cloud. Calculated using Euler transformation: ； in, The rotation matrix is ​​formed by the Euler angles in the trajectory. (yaw), (Looking up and down) (Scroll) Press The sequential construction is shown in the following formula: ； Translation vector ; The coordinates of the point in the local coordinate system of the laser scanner on the track inspection instrument are determined by the distance measurement value. and scanning angle calculate: ； in, It is a horizontal angle; It is a vertical angle.

3. The method for detecting eccentricity of railway line bridges according to claim 1, characterized in that: The track geometric parameters mentioned in S2 include track size parameters, shape geometric parameters, and the three-dimensional coordinates of the track centerline. , , The method for converting track center coordinates into track mileage includes the following steps: (and the deviations of the left and right rails in plane and elevation relative to the design alignment); S231, orbital alignment fitting, including: (1) Line segment fitting: Let the equation of the line be The solution using the least squares method is shown in the following equation: ， ； (2) Circular curve fitting: Let the center of the circular curve be... , radius is The minimum sum of squared residuals is shown in the following equation: ； (3) Transition curve fitting: A cubic parabola model was adopted. The radius of the circular curve is... For the total length of the transition curve, then: ； S232, Establish a linear reference system, and realize the mutual conversion between track center coordinates and track mileage through forward and inverse calculations of mileage point coordinates. The specific steps are as follows: 1) Convert mileage to coordinates: For a line segment, the conversion formula is: ， ； in The coordinates of the starting point of the line segment; It is the azimuth angle; For mileage; For circular curve segments, the conversion formula is: ， ； in Let r be the center of the circular curve segment; r is the radius of the circular curve segment. This is the starting mileage of the circular curve segment; The initial tangent angle; For the transition curve segment, the conversion formula is: ， ； in The total length of the transition curve; l is the integration variable, representing the variable in the process of finding the curve length; The starting mileage for easing the curve segment; 2) Convert the coordinates to mileage, which is then calculated iteratively using the following formula: ， ， in This is a positive calculation formula. Its derivative; ≥0.

4. The railway line bridge eccentricity detection method according to claim 1, characterized in that, Methods for extracting cross sections from 3D point cloud data in S2 include: S241, Calculation of bridge cross-section location: Calculate based on the fitting results of the design documents or the track centerline. The three-dimensional coordinates of the track center on the cross section at the mileage point Tangent azimuth and slope ; S242, Construction of bridge cross-section equations: The cross-section of the bridge is perpendicular to the centerline of the track, and its plane equation is expressed as: ， in, , , , ; S243, Point Cloud Extraction: Using the equations in S242, point cloud data within the cross-sectional area of ​​the bridge is extracted from the 3D point cloud to form a bridge cross-sectional point set. : ， in, Let N be the i-th point in the cross-sectional point set of the bridge, and N be the total number of points in the point set.

5. The method for detecting eccentricity of railway line bridges according to claim 1, characterized in that, The steps for measuring the relative position of the beam edge and the structure along the line at the cross section in S2 are as follows: S251, Point Cloud Denoising: Remove outlier noise points in 2D point clouds using statistical filtering or radius filtering; S252, Point Cloud Classification: Using the design distance and height difference between the guardrail and the track as spatial thresholds, the left and right guardrail point clouds are separated through segmentation operations; using the design values ​​of line spacing and adjacent line height difference as spatial thresholds, the left and right rail point clouds of the left line and the right line are separated through segmentation operations. S253, Cluster Analysis: DBSCAN clustering is performed on the guardrail point cloud to further extract the point clouds of the guardrail and rail. S254, Point cloud fitting at the top of the guardrail: Perform line fitting on the point cloud at the top of the guardrail to obtain the coordinates of the top of the left guardrail. Coordinates of the top of the right guardrail ; S255, Calculation of the relative position from the track center to the guardrail: The coordinates of the center point of the track rail are extracted by geometric feature method or template matching method, and the relative position from the track center to the guardrail is calculated.

6. The method for detecting eccentricity of railway line bridges according to claim 5, characterized in that, In step S255, when calculating the relative position from the center of the track to the guardrail: For single-line bridges, first extract the mileage. Center point of the left rail of the track at the cross section Center point of the right rail of the line Next, calculate the distance from the center of the left and right rails to the guardrail. and elevation difference , The formula is as follows: Among them, X L Y L X R Y R , which are the x and y coordinates of the top of the left and right guardrails, respectively; For a two-line bridge, first extract... Center point of the left rail on the left line at the cross section Center point of the left and right rails Center point of the left rail on the right line Center point of the right rail on the right line Next, measure the distance from the center of the left and right tracks to the guardrail. and and elevation difference and The formula is as follows:

7. The method for detecting eccentricity of railway line bridges according to claim 6, characterized in that: The steps for designing a drone flight path in S3 are as follows: S311, Calculate the outward parallel path: The normal vector direction of each centerline node is calculated based on the track geometry parameters measured in S2, and then parallel paths are generated by expanding outwards by 10 meters to both sides. The mathematical expression is as follows: ； in This represents the coordinate difference between adjacent 1m midline nodes. The coordinates of the midline node; For railway curve sections, adjust the outward expansion direction in conjunction with the radius of curvature to avoid path intersections or abrupt changes; S312, Altitude Control: Drone flight altitude Should be compared with the rail surface elevation Low , For a distance of 3-5 meters, there are: ； If the flight path passes over an obstacle during flight, the altitude or lateral deviation should be dynamically adjusted to ensure a safe distance. S313, optimizes flight routes; The steps for measuring the relative position of the beam edge and the structure along the line at the cross-section are as follows: S351, Point Cloud Denoising: Removes outlier noise points in 2D point clouds using statistical filtering or radius filtering; S352, Point Cloud Classification: Based on the coordinates of the top of the left and right guardrails measured in S2, select an appropriate threshold and separate the point clouds of the left and right guardrails through a segmentation operation; based on the design value of the height difference between the rail and the beam, select an appropriate threshold and separate the point clouds of the left and right beam edges through a segmentation operation. S353, Cluster Analysis: Cluster the point cloud of the guardrail to further extract the point cloud of the guardrail and beam edges; S354, Point cloud fitting at the top of the guardrail: Perform line fitting on the point cloud at the top of the guardrail to obtain the coordinates of the top of the left guardrail. Coordinates of the top of the right guardrail The top corner point of the beam edge was extracted using a linear fitting method, and the coordinates of the top corner point of the left beam edge were obtained. Coordinates of the top corner point of the right beam edge ; S355, Calculate the relative position of the top corner point of the beam edge to the guardrail: Extract mileage. The horizontal distance between the top of the left guardrail and the edge of the left beam in the cross section and elevation difference The horizontal distance between the top of the right guardrail and the edge of the right beam and elevation difference The distance between the left and right edges of the bridge beams : 。 8. The method for detecting eccentricity of railway line bridges according to claim 5, characterized in that, The track data mentioned in S3 includes the position (X, Y, Z) and attitude data during flight; the laser data includes time-synchronized ranging values ​​and scanning angles; Based on the flight path data of the UAV, the calibration values ​​of the lidar and POS system, and the laser data, the global coordinates of each point in the three-dimensional point cloud are calculated, and finally the three-dimensional point cloud of the outer side of the bridge is generated.

9. The method for detecting eccentricity of railway bridges according to claim 1, characterized in that, The measurement of the eccentricity of the bridge in S4 is achieved by fusing the data of the relative position between the track and the structure on the line at the cross section obtained in S2 and the data of the relative position between the beam edge and the structure on the line at the cross section obtained in S3, thereby realizing high-precision relative measurement of the eccentricity of the bridge. The measured bridge eccentricity value includes the following cases: (1) For a straight section of a single-track bridge, the eccentricity P of the bridge is as follows: ； in, and These are the distances from the center of the left and right rails to the guardrail, measured in S255 respectively. This refers to the distance between the top of the left guardrail and the edge of the left beam, measured in S355. This refers to the distance between the top of the right guardrail and the edge of the right beam, as measured in S355. (2) For single-track bridge curved sections, the influence of initial eccentricity needs to be considered; since the bridge plane is a broken line, the design centerline of the line does not coincide with the design centerline of the beam span, thus generating initial eccentricity; for each beam span, the initial eccentricity occurs at the midpoint and both ends of the beam span; according to the design drawings, "the planar arrangement of the beams on the curve is based on the principle that the chord length (equal to the distance between the center of the piers or the distance from the breast wall of the abutment to the center of the pier) is the midpoint (i.e., F=f / 2)," then the eccentricity P of the line-bridge is as follows: ； in, and These are the distances from the center of the left and right rails to the guardrail, measured in S255 respectively. This refers to the distance between the top of the left guardrail and the edge of the left beam, measured in S355. This refers to the distance between the top of the right guardrail and the edge of the right beam, as measured in S355. For track gauge, The superelevation is measured using the internal geometric parameters of the track in S21; L is the distance between the center of the pier or the distance from the breast wall of the abutment to the center of the pier, which can be approximated by the beam length; R is the curve radius, which can be obtained from the design data. (3) For the straight sections of the double-track bridge, the design center lines of the left and right tracks coincide with the design center lines of the left and right beam spans (the left track is the track facing the large mileage). The actual distance from the track center line to the edge of the beam is measured and compared with the distance from the design center line of the beam span to the edge of the beam. The eccentricity values ​​of the track and bridge for the left and right tracks are calculated respectively. and As shown in the following formula: ； ； in, and These are the distances from the center of the left and right rails to the guardrail, measured in S255 respectively. This refers to the distance between the top of the left guardrail and the edge of the left beam, measured in S355. This refers to the distance between the top of the right guardrail and the edge of the right beam, as measured in S355. The track gauge can be obtained by measuring the internal geometric parameters of the track in S21. This is the design distance from the center of the left track to the edge of the left beam. This is the design distance from the center of the right track to the edge of the right beam, which can be obtained from the design data; (4) For the double-track bridge curve segment, considering the influence of the initial eccentricity, calculate the eccentricity values ​​of the left and right tracks respectively. and As shown in the following formula: ； 10. The method for detecting eccentricity of railway line bridges according to any one of claims 1-9, characterized in that, In S1: The plane control network is constructed with GNSS reference stations in the form of GNSS continuously operating reference stations or GNSS temporary stations, with an interval of 15-25km between the GNSS reference stations; for GNSS reference stations with an interval of more than 18km, a GNSS densification point is deployed in the middle position, and the plane coordinates of the densification point are calculated by connecting the plane control network to the GNSS densification point. The elevation control network is established according to the fourth-order leveling measurement standard and shares points with the GNSS of the plane control network as much as possible. The spacing between elevation points along the entire line is controlled at about 4km. For sections with a spacing greater than 4km, additional elevation control points are set up. All elevation control points along the entire line and additional elevation control points are measured using the fourth-order leveling measurement standard and are connected to high-level control points with known elevations along the line.

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