Rail adjustment amount calculation method and system based on railcar dynamic measurement

Abstract

This invention discloses a method and system for calculating track adjustment based on dynamic measurement by a track vehicle, relating to the field of track adjustment technology. The system includes a track vehicle, a data acquisition module, a computation module, and a packaging module. The acquired effective values ​​of three-axis angular velocity, three-axis acceleration, raw distance increment, and three-dimensional geographic coordinates are input into the computation module. Subsequently, the optimal state estimation sequence of the track vehicle in three-dimensional space is output through a state estimation recursive formula. A three-dimensional trajectory point cloud is obtained based on this optimal state estimation sequence, thereby eliminating trajectory distortion caused by single-point measurement noise and intermittent jumps. The data acquisition module collects pulse signals output from the odometer and converts them into raw distance increments based on the track vehicle wheel diameter calibration value. The module also collects three-dimensional geographic coordinates output from the BeiDou positioning module. During the calculation of the optimal state estimation value, the raw distance increment and geographic coordinates are switched and used continuously.

Description

Technical Field

[0001] This invention relates to the field of track adjustment technology, and in particular to a method and system for calculating track adjustment based on dynamic measurements from a track vehicle. Background Technology

[0002] The continuous expansion of the railway network, while promoting economic development and facilitating people's travel, has also significantly increased the pressure on railway track maintenance. As the foundation of railway transportation, the condition of the track directly affects the safety and smoothness of train operation, making railway track maintenance crucial. Therefore, it is necessary to equip conventional track vehicles with various surveying tools to measure the track and identify points requiring maintenance.

[0003] The existing methods for calculating track adjustment often have the following problems: (1) Existing technologies often only collect data and detect deviations, without constructing a complete three-dimensional trajectory point cloud, and cannot eliminate the problem of trajectory distortion caused by single-point measurement noise and intermittent jump points; (2) In existing technologies, when conducting data observation, only a single odometer or Beidou positioning module is generally used for observation. When the odometer or Beidou positioning module fails or malfunctions, it will lead to the interruption of detection, or even cause serious deviations in the overall data; (3) In existing technologies, it is generally not considered that the three-dimensional line shape will be divided into corresponding planar line shape and elevation line shape, and it is even more impossible to judge the shape segmentation and segmented fitting of the planar line shape. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for calculating track adjustment based on dynamic measurement of a track vehicle, aiming to solve existing technical problems such as how to eliminate single-point measurement noise, trajectory distortion caused by intermittent jump points, how to solve the failure of a single odometer or Beidou positioning module, and how to realize the splitting and segmented fitting of three-dimensional line shapes.

[0005] To address the aforementioned technical problems, the present invention adopts the following technical solution: a method for calculating track adjustment based on dynamic measurement by a track vehicle, comprising the following steps: Step S1: When the railcar is stationary, the acquisition module collects six reference data output by the inertial navigation module. The six reference data are three-axis reference angular velocity data and three-axis reference acceleration data. Then, the arithmetic mean of each reference data is taken as the reference value of each reference data. Step S2: The track vehicle travels along the test line, and the acquisition module collects six kinds of raw data output by the inertial navigation module. The six kinds of raw data are the raw values ​​of the three-axis angular velocity and the raw values ​​of the three-axis acceleration. The reference values ​​of the six reference data in step S1 are subtracted from the six kinds of raw data one by one to obtain the effective values ​​of the three-axis angular velocity and the effective values ​​of the three-axis acceleration. Step S3: The acquisition module acquires the pulse signal output by the odometer and converts the pulse signal into the original distance increment based on the track wheel diameter calibration value. The acquisition module will then collect the three-dimensional geographic coordinates output by the BeiDou positioning module. Simultaneously, the acquisition module also acquires the track gauge value between the left and right rails output by the track gauge measurement module. ; Step S4: Obtain the effective values ​​of the three-axis angular velocity, the effective values ​​of the three-axis acceleration, and the original distance increment. and three-dimensional geographic coordinates The data is input into the computation module, and then the optimal state estimation sequence of the track vehicle in three-dimensional space is output through the state estimation recursive formula. The three-dimensional trajectory point cloud is obtained based on the optimal state estimation sequence in three-dimensional space. Step S5: Extract the lateral plane coordinates of each point in the 3D trajectory point cloud. and the corresponding cumulative mileage Then, the rate of change of heading angle was calculated point by point. and the rate of change of heading angle Perform sliding window filtering, based on the rate of change of the filtered heading angle. This is used to identify straight sections, circular curve sections, and transition curve sections in a planar alignment. Step S6: Then, perform different polynomial least squares fitting on the straight line segment, circular curve segment and transition curve segment in the plane alignment to obtain the plane baseline alignment. Then, perform quadratic polynomial least squares fitting on the entire elevation alignment segment to obtain the elevation baseline alignment. Step S7: Extract the lateral plane coordinates of each point in the 3D trajectory point cloud. and vertical elevation coordinates Then extract the reference plane coordinates of each point in the plane reference line. Reference elevation coordinates of each point in the elevation datum line Then the horizontal plane coordinates coordinates with reference plane Compare the results, and then convert the vertical elevation coordinates. and benchmark elevation coordinates By comparing the results, it can be determined whether the rails need to be corrected.

[0006] Preferably, the triaxial reference angular velocity data includes the X-axis reference angular velocity. Y-axis reference angular velocity Z-axis reference angular velocity ; , , The unit is degrees per second; triaxial reference acceleration data includes X-axis reference acceleration. Y-axis reference acceleration Z-axis reference acceleration ; , , The unit is meters per second squared; the raw values ​​of the three-axis angular velocities include the raw values ​​of the X-axis angular velocity. Y-axis angular velocity original value Z-axis angular velocity original value ; , , The unit is degrees per second; the raw values ​​of triaxial acceleration include the raw values ​​of X-axis acceleration. Y-axis acceleration raw value Z-axis acceleration raw value ; , , The unit is meters per second squared; the effective values ​​of the three-axis angular velocities include the effective value of the X-axis angular velocity. Effective value of Y-axis angular velocity Z-axis angular velocity effective value ; , , The unit is degrees per second; the effective value of triaxial acceleration includes the effective value of X-axis acceleration. Effective value of Y-axis acceleration Z-axis acceleration effective value ; , , The unit is meters per second squared.

[0007] Preferably, the original distance increment The unit is meters; three-dimensional geographic coordinates The unit is meters; the track gauge between the left and right rails. The unit is meters.

[0008] Preferably, the sequence of optimal state estimates in three-dimensional space includes three-dimensional position coordinates. Three-axis velocity estimates and attitude angles; the three-axis velocity estimates include the X-axis velocity estimate. Y-axis velocity estimate Z-axis velocity estimate ; , , The unit is meters per second; attitude angles include roll angle. Pitch angle Heading angle ; , , The unit is radians; three-dimensional position coordinates The unit is meters.

[0009] Preferably, let vector Composed of a sequence of optimal state estimates, a vector The expression is as follows: ; In the formula: Indicates the k-th sampling time; , , Represent the three-dimensional position coordinates at the k-th sampling time. The coordinate values ​​in the three directions; , , These represent the estimated triaxial velocities in the three directions at the k-th sampling time; , , These represent the attitude angles in the three directions at the k-th sampling time; The recursive formula for state estimation is shown below: ; In the formula: This indicates the prediction of time k based on time k-1. The predicted value; Represents the state transition matrix; Represents the control input matrix; Represents the control input vector; Represents the (k-1)th time. The optimal state estimate; Indicates the k-th time. The optimal state estimate; Let represent the gain matrix at time k; Let represent the observation vector at time k; Represents the observation matrix; This represents the error covariance matrix predicted based on the (k-1)th time. Let represent the error covariance matrix at time k-1; Represents the observation noise covariance matrix. It is a 3×3 diagonal matrix. When using odometer observations, The diagonal elements are 1.0000. When using the BeiDou positioning module for observation, The diagonal element has a value of 0.0025; Represents the noise covariance matrix; The expression is as follows: ; In the formula: , , These represent the effective values ​​of the triaxial acceleration in the three directions at the k-th sampling time; , , These represent the effective values ​​of the triaxial angular velocities in the three directions at the k-th sampling time.

[0010] Preferably, The expression is as follows: ; In the formula: It is a third-order identity matrix; It is a third-order zero matrix; The time interval between two adjacent discrete sampling moments. The value range is from 0.001 seconds to 0.01 seconds; The expression is as follows: ; When using odometer observation expressions and The expression is as follows: ; In the formula: Represents the original distance increment at the k-th sampling time. ; , , This represents the estimated triaxial velocities in three directions at time k, predicted based on time k-1. When using a BeiDou positioning module for observation... expressions and The expression is as follows: ; In the formula: , , Represent the three-dimensional geographic coordinates at the k-th sampling time. The coordinate values ​​in the three directions; The expression is as follows: ; In the formula: This represents the standard deviation of accelerometer noise, expressed in meters per second squared, with a range of 0.01 to 0.1. This represents the standard deviation of gyroscope noise, expressed in radians per second, ranging from 0.001 to 0.01.

[0011] Preferably, the rate of change of heading angle For heading angle Regarding cumulative mileage The instantaneous rate of change; based on the filtered rate of change of heading angle. When identifying straight sections, circular curve sections, and transition curve sections in a horizontal alignment, the specific criterion is: when the rate of change of the heading angle... A section with a change in heading angle less than 0.002 radians per meter within a continuous 200m range is considered a straight section; when the rate of change of heading angle... A section of circular curve is defined as one where the constant value remains within a continuous range of 100m and is greater than 0.002 radians per meter; when the rate of change of heading angle... It exhibits a linear increasing or decreasing change, and the rate of change of heading angle When the absolute value of the rate of change is between 0.0001 radians per square meter and 0.01 radians per square meter, it is determined to be a transition curve segment; for straight segments, least squares fitting is performed using a first-order polynomial; for circular curve segments, least squares fitting is performed using a second-order polynomial; and for transition curve segments, least squares fitting is performed using a third-order polynomial. The storage module is used for parameter storage and encryption. In step S7, when determining whether the rail needs correction, the gauge value between the left and right rails also needs to be determined simultaneously. Whether it is within the acceptable range; then the determined elevation and plane baselines are distributed to large tamping machines to achieve mechanized and digitalized precise tamping maintenance of the line.

[0012] This invention also provides a track adjustment calculation system based on dynamic measurement by a track vehicle, including a track vehicle, a data acquisition module, a calculation module, and a storage module; the track vehicle is unidirectionally connected to the data acquisition module; the data acquisition module is unidirectionally connected to the calculation module; the calculation module is unidirectionally connected to the storage module; a detection beam is installed on the track vehicle; an inertial navigation module, an odometer, a track gauge measurement module, and a BeiDou positioning module are installed on the detection beam of the track vehicle; the inertial navigation module, odometer, track gauge measurement module, and BeiDou positioning module are all unidirectionally connected to the data acquisition module; the track vehicle has a weight of 44 to 46 tons; the running speed of the track vehicle ranges from 0 to 80 kilometers per hour; the positioning accuracy of the BeiDou positioning module is better than ±0.05 meters, and the sampling frequency is not less than 1 Hz.

[0013] The beneficial effects of this invention compared with the prior art are: (1) the obtained effective values ​​of triaxial angular velocity, triaxial acceleration, and original distance increment. and three-dimensional geographic coordinates The input is fed into the calculation module, and then the optimal state estimation value sequence of the track vehicle in three-dimensional space is output through the state estimation recursive formula. The three-dimensional trajectory point cloud is obtained based on the optimal state estimation value sequence in three-dimensional space, thereby eliminating the trajectory distortion problem caused by single-point measurement noise and intermittent jump points. (2) The acquisition module acquires the pulse signal output by the odometer and converts the pulse signal into the original distance increment according to the track wheel diameter calibration value. The acquisition module will then collect the three-dimensional geographic coordinates output by the BeiDou positioning module. Subsequently, during the calculation of the optimal state estimate, the original distance increment is continuously updated. and geographic coordinates (3) Extract the lateral plane coordinates of each point in the three-dimensional trajectory point cloud. and the corresponding cumulative mileage Then, the rate of change of heading angle was calculated point by point. and the rate of change of heading angle Perform sliding window filtering, based on the rate of change of the filtered heading angle. This method identifies straight sections, circular curve sections, and transition curve sections in the planar alignment. Then, different polynomial least squares fittings are performed on the straight sections, circular curve sections, and transition curve sections in the planar alignment to obtain the planar baseline. Finally, quadratic polynomial least squares fitting is performed on the entire elevation alignment to obtain the elevation baseline, further improving the accuracy of the baseline. Attached Figure Description

[0014] Figure 1 This is a flowchart of the method for calculating track adjustment based on dynamic measurement by a track vehicle according to the present invention.

[0015] Figure 2 This is a schematic diagram of the track adjustment calculation system based on dynamic measurement by a track vehicle, according to the present invention.

[0016] Figure 3 This is a schematic diagram of the track adjustment calculation system based on dynamic measurement by a track vehicle, according to the present invention.

[0017] In the diagram: 1-Rail vehicle; 2-Acquisition module; 3-Computation module; 4-Storage module; 11-Inertial navigation module; 12-Odometer; 13-Track gauge measurement module; 14-BeiDou positioning module. Detailed Implementation

[0018] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0019] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0020] Figures 1 to 3 This is a preferred embodiment of the present invention.

[0021] Figure 1 A flowchart of the track adjustment calculation method based on dynamic measurement by a track vehicle according to the present invention is provided, including the following steps: Step S1: When the railcar 1 is stationary, the acquisition module 2 acquires six types of reference data output by the inertial navigation module 11. The six types of reference data are three-axis reference angular velocity data and three-axis reference acceleration data. Then, the arithmetic mean of each type of reference data is taken as the reference value of each type of reference data. Step S2: The track vehicle 1 travels along the test line, and the acquisition module 2 acquires six kinds of raw data output by the inertial navigation module. The six kinds of raw data are the raw values ​​of the three-axis angular velocity and the raw values ​​of the three-axis acceleration. The reference values ​​of the six reference data in step S1 are subtracted from the six kinds of raw data one by one to obtain the effective values ​​of the three-axis angular velocity and the effective values ​​of the three-axis acceleration. Step S3: Acquisition module 2 acquires the pulse signal output by odometer 12, and converts the pulse signal into the original distance increment based on the wheel diameter calibration value of track vehicle 1. Subsequently, acquisition module 2 will also acquire the three-dimensional geographic coordinates output by Beidou positioning module 14. Simultaneously, the acquisition module 2 also acquires the track gauge value between the left and right rails output by the track gauge measurement module 13. ; Step S4: Obtain the effective values ​​of the three-axis angular velocity, the effective values ​​of the three-axis acceleration, and the original distance increment. and three-dimensional geographic coordinates The data is input into the calculation module 3, and then the optimal state estimation value sequence of the track vehicle 1 in three-dimensional space is output through the state estimation recursive formula. The three-dimensional trajectory point cloud is obtained based on the optimal state estimation value sequence in three-dimensional space. Step S5: Extract the lateral plane coordinates of each point in the 3D trajectory point cloud. and the corresponding cumulative mileage Then, the rate of change of heading angle was calculated point by point. and the rate of change of heading angle Perform sliding window filtering, based on the rate of change of the filtered heading angle. This is used to identify straight sections, circular curve sections, and transition curve sections in a planar alignment. Step S6: Then, perform different polynomial least squares fitting on the straight line segment, circular curve segment and transition curve segment in the plane alignment to obtain the plane baseline alignment. Then, perform quadratic polynomial least squares fitting on the entire elevation alignment segment to obtain the elevation baseline alignment. Step S7: Extract the lateral plane coordinates of each point in the 3D trajectory point cloud. and vertical elevation coordinates Then extract the reference plane coordinates of each point in the plane reference line. Reference elevation coordinates of each point in the elevation datum line Then the horizontal plane coordinates coordinates with reference plane Compare the results, and then convert the vertical elevation coordinates. and benchmark elevation coordinates By comparing the results, it can be determined whether the rails need to be corrected.

[0022] The working principle of this invention is as follows: Figure 1 As shown, in step S1: When the track vehicle 1 is stationary, the acquisition module 2 acquires six types of reference data output by the inertial navigation module 11. The six types of reference data are triaxial reference angular velocity data and triaxial reference acceleration data. Then, the arithmetic mean of each type of reference data is taken as the reference value of each type of reference data. The track vehicle 1 travels along the measured line, and the acquisition module 2 acquires six types of raw data output by the inertial navigation module. The six types of raw data are raw values ​​of triaxial angular velocity and raw values ​​of triaxial acceleration. The reference values ​​of the six types of reference data in step S1 are subtracted from each of the six types of raw data to obtain the effective values ​​of triaxial angular velocity and triaxial acceleration. The acquisition module 2 acquires the pulse signal output by the odometer 12 and converts the pulse signal into the raw distance increment according to the wheel diameter calibration value of the track vehicle 1. Subsequently, acquisition module 2 will also acquire the three-dimensional geographic coordinates output by Beidou positioning module 14. Simultaneously, the acquisition module 2 also acquires the track gauge value between the left and right rails output by the track gauge measurement module 13. The obtained effective values ​​of triaxial angular velocity, effective values ​​of triaxial acceleration, and original distance increment will be used to... and three-dimensional geographic coordinates The data is input into the computation module 3, which then outputs the optimal state estimation sequence of the track vehicle 1 in three-dimensional space through the state estimation recursive formula. A three-dimensional trajectory point cloud is obtained based on this optimal state estimation sequence. Subsequently, the computation module 3 extracts the lateral plane coordinates of each point in the three-dimensional trajectory point cloud. and the corresponding cumulative mileage Then, the rate of change of heading angle was calculated point by point. and the rate of change of heading angle Perform sliding window filtering, based on the rate of change of the filtered heading angle. The system identifies straight sections, circular curve sections, and transition curve sections in the planar alignment. Then, the computation module 3 performs different polynomial least squares fittings on the straight sections, circular curve sections, and transition curve sections in the planar alignment to obtain the planar baseline alignment. Next, it performs quadratic polynomial least squares fitting on the entire elevation alignment to obtain the elevation baseline alignment. Finally, it extracts the lateral plane coordinates of each point in the 3D trajectory point cloud. and vertical elevation coordinates Then extract the reference plane coordinates of each point in the plane reference line. Reference elevation coordinates of each point in the elevation datum line Then the horizontal plane coordinates coordinates with reference plane Compare the results, and then convert the vertical elevation coordinates. and benchmark elevation coordinates By comparing the results, it can be determined whether the rails need to be corrected.

[0023] Furthermore, the three-axis reference angular velocity data includes the X-axis reference angular velocity. Y-axis reference angular velocity Z-axis reference angular velocity ; , , The unit is degrees per second; triaxial reference acceleration data includes X-axis reference acceleration. Y-axis reference acceleration Z-axis reference acceleration ; , , The unit is meters per second squared; the raw values ​​of the three-axis angular velocities include the raw values ​​of the X-axis angular velocity. Y-axis angular velocity original value Z-axis angular velocity original value ; , , The unit is degrees per second; the raw values ​​of triaxial acceleration include the raw values ​​of X-axis acceleration. Y-axis acceleration raw value Z-axis acceleration raw value ; , , The unit is meters per second squared; the effective values ​​of the three-axis angular velocities include the effective value of the X-axis angular velocity. Effective value of Y-axis angular velocity Z-axis angular velocity effective value ; , , The unit is degrees per second; the effective value of triaxial acceleration includes the effective value of X-axis acceleration. Effective value of Y-axis acceleration Z-axis acceleration effective value ; , , The unit is meters per second squared.

[0024] Furthermore, the original distance increment The unit is meters; three-dimensional geographic coordinates The unit is meters; the track gauge between the left and right rails. The unit is meters.

[0025] Furthermore, the optimal state estimate sequence in three-dimensional space includes three-dimensional position coordinates. Three-axis velocity estimates and attitude angles; the three-axis velocity estimates include the X-axis velocity estimate. Y-axis velocity estimate Z-axis velocity estimate ; , , The unit is meters per second; attitude angles include roll angle. Pitch angle Heading angle ; , , The unit is radians; three-dimensional position coordinates The unit is meters.

[0026] Furthermore, let vector Composed of a sequence of optimal state estimates, a vector The expression is as follows: ; In the formula: Indicates the k-th sampling time; , , Represent the three-dimensional position coordinates at the k-th sampling time. The coordinate values ​​in the three directions; , , These represent the estimated triaxial velocities in the three directions at the k-th sampling time; , , These represent the attitude angles in the three directions at the k-th sampling time; The recursive formula for state estimation is shown below: ; In the formula: This indicates the prediction of time k based on time k-1. The predicted value; Represents the state transition matrix; Represents the control input matrix; Represents the control input vector; Represents the (k-1)th time. The optimal state estimate; Indicates the k-th time. The optimal state estimate; Let represent the gain matrix at time k; Let represent the observation vector at time k; Represents the observation matrix; This represents the error covariance matrix predicted based on the (k-1)th time. Let represent the error covariance matrix at time k-1; Represents the observation noise covariance matrix. It is a 3×3 diagonal matrix. When using odometer 12 for observation, The diagonal element has a value of 1.0000. When using the BeiDou positioning module 14 for observation, The diagonal element has a value of 0.0025; Represents the noise covariance matrix; The expression is as follows: ; In the formula: , , These represent the effective values ​​of the triaxial acceleration in the three directions at the k-th sampling time; , , These represent the effective values ​​of the triaxial angular velocities in the three directions at the k-th sampling time.

[0027] Furthermore, The expression is as follows: ; In the formula: It is a third-order identity matrix; It is a third-order zero matrix; The time interval between two adjacent discrete sampling moments. The value range is from 0.001 seconds to 0.01 seconds; The expression is as follows: ; When using odometer 12 for observation expressions and The expression is as follows: ; In the formula: Represents the original distance increment at the k-th sampling time. ; , , This represents the estimated triaxial velocity values ​​in three directions at time k, predicted based on time k-1. When using the BeiDou positioning module 14 for observation... expressions and The expression is as follows: ; In the formula: , , Represent the three-dimensional geographic coordinates at the k-th sampling time. The coordinate values ​​in the three directions; The expression is as follows: ; In the formula: This represents the standard deviation of accelerometer noise, expressed in meters per second squared, with a range of 0.01 to 0.1. This represents the standard deviation of gyroscope noise, expressed in radians per second, ranging from 0.001 to 0.01.

[0028] Furthermore, the rate of change of heading angle For heading angle Regarding cumulative mileage The instantaneous rate of change; based on the filtered rate of change of heading angle. When identifying straight sections, circular curve sections, and transition curve sections in a horizontal alignment, the specific criterion is: when the rate of change of the heading angle... A section with a change in heading angle less than 0.002 radians per meter within a continuous 200m range is considered a straight section; when the rate of change of heading angle... A section of circular curve is defined as one where the constant value remains within a continuous range of 100m and is greater than 0.002 radians per meter; when the rate of change of heading angle... It exhibits a linear increasing or decreasing change, and the rate of change of heading angle When the absolute value of the rate of change is between 0.0001 radians per square meter and 0.01 radians per square meter, it is determined to be a transition curve segment; for straight segments, least squares fitting is performed using a first-order polynomial; for circular curve segments, least squares fitting is performed using a second-order polynomial; and for transition curve segments, least squares fitting is performed using a third-order polynomial. Storage module 4 is used for parameter storage and encryption. In step S7, when determining whether the rail needs correction, the gauge value between the left and right rails also needs to be determined simultaneously. Whether it is within the acceptable range; then the determined elevation and plane baselines are distributed to large tamping machines to achieve mechanized and digitalized precise tamping maintenance of the line.

[0029] For a track adjustment calculation system based on dynamic measurements from a track vehicle, such as Figure 2 and Figure 3 As shown, the track vehicle 1 is unidirectionally connected to the acquisition module 2; the acquisition module 2 is unidirectionally connected to the calculation module 3; the calculation module 3 is unidirectionally connected to the storage module 4; a detection beam is installed on the track vehicle 1; an inertial navigation module 11, an odometer 12, a track gauge measurement module 13, and a Beidou positioning module 14 are installed on the detection beam of the track vehicle 1; the inertial navigation module 11, the odometer 12, the track gauge measurement module 13, and the Beidou positioning module 14 are all unidirectionally connected to the acquisition module 2; the track vehicle 1 has a weight of 44 to 46 tons; the running speed of the track vehicle 1 ranges from 0 to 80 kilometers per hour; the positioning accuracy of the Beidou positioning module 14 is better than ±0.05 meters.

[0030] This invention is not limited to the specific embodiments described above. Any modifications made by those skilled in the art based on the above concept without creative effort are within the protection scope of this invention.

Claims

1. A method for calculating track adjustment based on dynamic measurement by a track vehicle, characterized in that, Includes the following steps: Step S1: When the track vehicle (1) is stationary, the acquisition module (2) acquires six reference data output by the inertial navigation module (11). The six reference data are three-axis reference angular velocity data and three-axis reference acceleration data. Then, the arithmetic mean of each reference data is taken as the reference value of each reference data. Step S2: The track vehicle (1) travels along the test line, and the acquisition module (2) acquires six kinds of raw data output by the inertial navigation module. The six kinds of raw data are the raw values ​​of the three-axis angular velocity and the raw values ​​of the three-axis acceleration. The reference values ​​of the six reference data in step S1 are subtracted from the six kinds of raw data one by one to obtain the effective values ​​of the three-axis angular velocity and the effective values ​​of the three-axis acceleration. Step S3: The acquisition module (2) acquires the pulse signal output by the odometer (12) and converts the pulse signal into the original distance increment based on the wheel diameter calibration value of the railcar (1). Subsequently, the acquisition module (2) will also acquire the three-dimensional geographic coordinates output by the Beidou positioning module (14). Simultaneously, the acquisition module (2) also acquires the track gauge value between the left and right rails output by the track gauge measurement module (13). ; Step S4: Obtain the effective values ​​of the three-axis angular velocity, the effective values ​​of the three-axis acceleration, and the original distance increment. and three-dimensional geographic coordinates The input is fed into the calculation module (3), and then the optimal state estimation value sequence of the track vehicle (1) in three-dimensional space is output through the state estimation recursive formula. The three-dimensional trajectory point cloud is obtained based on the optimal state estimation value sequence in three-dimensional space. Step S5: Extract the lateral plane coordinates of each point in the 3D trajectory point cloud. and the corresponding cumulative mileage Then, the rate of change of heading angle was calculated point by point. and the rate of change of heading angle Perform sliding window filtering, based on the rate of change of the filtered heading angle. This is used to identify straight sections, circular curve sections, and transition curve sections in a planar alignment. Step S6: Then, perform different polynomial least squares fitting on the straight line segment, circular curve segment and transition curve segment in the plane alignment to obtain the plane baseline alignment. Then, perform quadratic polynomial least squares fitting on the entire elevation alignment segment to obtain the elevation baseline alignment. Step S7: Extract the lateral plane coordinates of each point in the 3D trajectory point cloud. and vertical elevation coordinates Then extract the reference plane coordinates of each point in the plane reference line. and the reference elevation coordinates of each point in the elevation datum line. Then the horizontal plane coordinates coordinates with reference plane Compare the results, and then convert the vertical elevation coordinates. and benchmark elevation coordinates By comparing the results, it can be determined whether the rails need to be corrected.

2. The method for calculating track adjustment based on dynamic measurement by a track vehicle as described in claim 1, characterized in that: The three-axis reference angular velocity data includes the X-axis reference angular velocity. Y-axis reference angular velocity Z-axis reference angular velocity ; , , The unit is degrees per second; Triaxial reference acceleration data includes X-axis reference acceleration. Y-axis reference acceleration Z-axis reference acceleration ; , , The unit is meters per second squared; the raw values ​​of the three-axis angular velocities include the raw values ​​of the X-axis angular velocity. Y-axis angular velocity original value Z-axis angular velocity original value ; , , The unit is degrees per second; the raw values ​​of triaxial acceleration include the raw values ​​of X-axis acceleration. Y-axis acceleration raw value Z-axis acceleration raw value ; , , The unit is meters per second squared; the effective values ​​of the three-axis angular velocities include the effective value of the X-axis angular velocity. Effective value of Y-axis angular velocity Effective value of Z-axis angular velocity ; , , The unit is degrees per second; the effective value of triaxial acceleration includes the effective value of X-axis acceleration. Effective value of Y-axis acceleration Z-axis acceleration effective value ; , , The unit is meters per second squared.

3. The method for calculating track adjustment based on dynamic measurement by a track vehicle as described in claim 2, characterized in that: Original distance increment The unit is meters; three-dimensional geographic coordinates The unit is meters; the track gauge between the left and right rails. The unit is meters.

4. The method for calculating track adjustment based on dynamic measurement by a track vehicle as described in claim 3, characterized in that: The optimal state estimate sequence in three-dimensional space includes three-dimensional position coordinates. Three-axis velocity estimates and attitude angles; the three-axis velocity estimates include the X-axis velocity estimate. Y-axis velocity estimate Z-axis velocity estimate ; , , The unit is meters per second; attitude angles include roll angle. Pitch angle Heading angle ; , , The unit is radians; three-dimensional position coordinates The unit is meters.

5. The method for calculating track adjustment based on dynamic measurement by a track vehicle as described in claim 4, characterized in that: Let vector Composed of a sequence of optimal state estimates, a vector The expression is as follows: U k = X W , k Y W , k Z W , k V X , k V Y , k V Z , k φ k θ k ψ k T ； In the formula: Indicates the k-th sampling time; , , Represent the three-dimensional position coordinates at the k-th sampling time. The coordinate values ​​in the three directions; , , These represent the estimated triaxial velocities in the three directions at the k-th sampling time; , , These represent the attitude angles in the three directions at the k-th sampling time; The recursive formula for state estimation is shown below: ； In the formula: This indicates the prediction of time k based on time k-1. The predicted value; Represents the state transition matrix; Represents the control input matrix; Represents the control input vector; Represents the (k-1)th time. The optimal state estimate; Indicates the k-th time. The optimal state estimate; Let represent the gain matrix at time k; Let represent the observation vector at time k; Represents the observation matrix; This represents the error covariance matrix predicted based on the (k-1)th time. Let represent the error covariance matrix at time k-1; Represents the observation noise covariance matrix. It is a 3×3 diagonal matrix. When using odometer (12) observation, The diagonal element takes a value of 1.0000. When using the Beidou positioning module (14) for observation, The diagonal element has a value of 0.0025; Represents the noise covariance matrix; The expression is as follows: M k = a X 2 , k a Y 2 , k a Z 2 , k ω X 2 , k ω Y 2 , k ω Z 2 , k T ； In the formula: , , These represent the effective values ​​of the triaxial acceleration in the three directions at the k-th sampling time; , , These represent the effective values ​​of the triaxial angular velocities in the three directions at the k-th sampling time.

6. The method for calculating track adjustment based on dynamic measurement by a track vehicle as described in claim 5, characterized in that: The expression is as follows: ； In the formula: It is a third-order identity matrix; It is a third-order zero matrix; The time interval between two adjacent discrete sampling moments. The value range is from 0.001 seconds to 0.01 seconds; The expression is as follows: ； When using an odometer (12) for observation, expressions and The expression is as follows: ； In the formula: Represents the original distance increment at the k-th sampling time. ; , , This represents the estimated triaxial velocity values ​​in three directions at time k, predicted based on time k-1; when observed using the BeiDou positioning module (14), expressions and The expression is as follows: ； In the formula: , , Represent the three-dimensional geographic coordinates at the k-th sampling time. The coordinate values ​​in the three directions; The expression is as follows: ； In the formula: This represents the standard deviation of accelerometer noise, expressed in meters per second squared, with a range of 0.01 to 0.

1. This represents the standard deviation of gyroscope noise, expressed in radians per second, ranging from 0.001 to 0.

01.

7. The method for calculating track adjustment based on dynamic measurement by a track vehicle as described in claim 6, characterized in that: Rate of change of heading angle For heading angle Regarding cumulative mileage The instantaneous rate of change; based on the filtered rate of change of heading angle. When identifying straight sections, circular curve sections, and transition curve sections in a horizontal alignment, the specific criterion is: when the rate of change of the heading angle... A section with a change in heading angle less than 0.002 radians per meter within a continuous 200m range is considered a straight section; when the rate of change of heading angle... A section of circular curve is defined as one where the constant value remains within a continuous range of 100m and is greater than 0.002 radians per meter; when the rate of change of heading angle... It exhibits a linear increasing or decreasing change, and the rate of change of heading angle When the absolute value of the rate of change is between 0.0001 radians per square meter and 0.01 radians per square meter, it is determined to be a transition curve segment; for straight segments, least squares fitting is performed using a first-order polynomial; for circular curve segments, least squares fitting is performed using a second-order polynomial; for transition curve segments, least squares fitting is performed using a third-order polynomial; the storage module (4) is used for storing and encrypting parameters; in step S7, when determining whether the rail needs to be corrected, the gauge value between the left and right rails also needs to be determined simultaneously. Whether it is within the acceptable range; then the determined elevation and plane baselines are distributed to large tamping machines to achieve mechanized and digitalized precise tamping maintenance of the line.

8. A system based on the track adjustment calculation method based on dynamic measurement of a track vehicle as described in claim 7, characterized in that: The system includes a track vehicle (1), a data acquisition module (2), a computing module (3), and a storage module (4). The track vehicle (1) is unidirectionally connected to the data acquisition module (2). The data acquisition module (2) is unidirectionally connected to the computing module (3). The computing module (3) is unidirectionally connected to the storage module (4). The track vehicle (1) is equipped with a detection beam. The detection beam of the track vehicle (1) is equipped with an inertial navigation module (11), an odometer (12), a track gauge measurement module (13), and a Beidou positioning module (14). The inertial navigation module (11), the odometer (12), the track gauge measurement module (13), and the Beidou positioning module (14) are all unidirectionally connected to the data acquisition module (2). The track vehicle (1) has a weight of 44 to 46 tons. The running speed of the track vehicle (1) ranges from 0 to 80 kilometers per hour. The positioning accuracy of the Beidou positioning module (14) is better than ±0.05 meters.

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