A high-speed polishing trolley body posture detection method based on rail section information

Abstract

The application discloses a high-speed polishing trolley body posture detection method based on rail section information and relates to the technical field of railway maintenance equipment. The technical scheme points of the application are as follows: the following steps are included: obtaining profile data after preprocessing; establishing a track reference coordinate system, a sensor coordinate system and a trolley body coordinate system, converting the profile data after preprocessing from the sensor coordinate system to the track reference coordinate system to obtain profile data under the track reference coordinate system; calculating trolley body posture parameters; calculating a trolley body translation vector; polishing unit coordinate calculation and trolley body posture inversion. Two-dimensional laser sensors are used to collect rail section information, and an algorithm model is combined to realize high-precision posture detection without a gyroscope.

Description

Technical Field

[0001] This invention relates to the field of railway maintenance equipment technology, and more specifically, to a method for detecting the body posture of a high-speed grinding trolley based on rail cross-section information. Background Technology

[0002] In railway track maintenance, high-speed grinding trolleys are key equipment for repairing rail surface defects and improving track smoothness. Real-time, high-precision detection of the trolley's posture is a crucial prerequisite for ensuring the quality of grinding operations. If the trolley exhibits roll, pitch, or yaw deviations, the contact pressure between the grinding unit and the rail surface, as well as the grinding angle, will deviate from preset values, resulting in over-grinding or incomplete grinding of the rails, affecting track lifespan and train safety. Currently, the attitude detection of high-speed grinding carriages mainly relies on gyroscope sensors. Traditional methods involve mounting gyroscopes on the carriage body to directly measure the angular motion parameters of the vehicle, thereby obtaining attitude information. However, this method has significant drawbacks: firstly, high-precision gyroscopes are expensive, significantly increasing the manufacturing cost of the equipment; secondly, the high-speed grinding carriage generates severe vibrations during operation, and these vibrations can cause a decrease in the measurement accuracy of the gyroscopes, leading to sensor drift and poor stability after long-term use; furthermore, gyroscopes can only directly measure angular parameters and cannot be correlated with the actual working position of the grinding unit, requiring additional data fusion with other sensors, increasing system complexity and the risk of failure. To address the aforementioned issues, the industry urgently needs a technical solution for high-precision and high-stability vehicle body attitude detection that does not rely on gyroscopes. The detection approach based on rail cross-section information has potential advantages: the contour features of the rail cross-section are fixed and unique, serving as a natural coordinate reference. By collecting rail cross-section information and establishing a correlation model with the vehicle body attitude, accurate attitude inversion is expected to be achieved. Therefore, developing a method for high-speed grinding vehicle body attitude detection based on rail cross-section information has become a pressing technical problem in this field. Summary of the Invention

[0003] The purpose of this invention is to provide a method for detecting the body posture of a high-speed grinding trolley based on rail cross-section information, which achieves high-precision and high-stability body posture detection without a gyroscope.

[0004] The above-mentioned technical objective of the present invention is achieved through the following technical solution: The first aspect of this invention provides a method for detecting the body posture of a high-speed grinding trolley based on rail cross-section information, comprising the following steps: Obtain preprocessed profile data, which includes rail section feature points; Establish the track reference coordinate system, sensor coordinate system and vehicle body coordinate system, and transform the preprocessed profile data from the sensor coordinate system to the track reference coordinate system to obtain the profile data in the track reference coordinate system. The vehicle body attitude parameters are calculated using the preprocessed profile data and the profile data under the track reference coordinate system. The vehicle body translation vector is calculated using the origin of the vehicle body coordinate system as a reference, based on the coordinates of the feature points of the rail section under the track reference coordinate system and the vehicle body geometric parameters. Based on the vehicle body posture parameters, establish the transformation matrix and translation vector from the vehicle body coordinate system to the track reference coordinate system; obtain the coordinates of the grinding plate in the vehicle body coordinate system, and transform them to the track reference coordinate system through the transformation matrix and translation vector to obtain the actual coordinates of the grinding plate in the track reference coordinate system; by comparing the actual coordinates of the grinding plate with the preset target grinding coordinates, the deviation of the vehicle body from the ideal posture is obtained, and the vehicle body posture detection is completed.

[0005] In conjunction with the first aspect, the present invention is further configured such that: the method for obtaining preprocessed profile data includes the following steps: installing sensors on a high-speed grinding trolley to collect the original profile data of the rail cross section, and preprocessing the original profile data.

[0006] In conjunction with the first aspect, the present invention is further configured such that: the preprocessing includes noise filtering, data completion and feature point extraction, and the preprocessed profile data also includes two circular profile feature points and railhead edge feature points.

[0007] In conjunction with the first aspect, the present invention is further configured such that: the vehicle body posture parameters include the yaw angle ( ), nodding corner ( ) and roll angle ( ).

[0008] In conjunction with the first aspect, the present invention is further configured such that the method for calculating the vehicle body attitude parameters is as follows: Two circular profiles at the bottom of the rail are selected as references. Let the coordinates of the centers of the two circular profiles at the bottom of the standard rail in the rail reference coordinate system be respectively... , , its in The distance in the direction is , The distance in the direction is The coordinates of the centers of the two circular profiles at the bottom of the actual rail, measured by a two-dimensional laser sensor, are as follows: , , its in The distance in the direction is , The distance in the direction is According to geometric relationships, we can obtain Roll angle ( Calculation: Using the cross-sectional information of the left and right rails collected by the sensors at the front and rear ends of the grinding trolley, let the coordinates of the center of the left rail base measured by the front sensor be... The coordinates of the center of the right rail base circle are: The rear sensor measured the coordinates of the center of the left rail base as follows: The coordinates of the center of the right rail base circle are: Calculate the slope of the line connecting the centers of the bottom circles of the front and rear rails (slope of the front end line). Slope of the back end connection ), roll angle , in For front-end and back-end sensors Distance along the axial direction.

[0009] In conjunction with the first aspect, the present invention is further configured such that: the vehicle body translation vector includes the vehicle body in... Lateral displacement in the axial direction , Lifting or lowering in the axial direction , Axial expansion / contraction , in, This is the initial lateral displacement reference value for the vehicle body. This is the initial reference value for vehicle body lifting. This is the initial extension / retraction reference value for the vehicle body.

[0010] A second aspect of the present invention also provides a device / equipment / system for high-speed grinding trolley body posture detection based on rail cross-section information, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0011] A third aspect of the present invention also provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implement the steps of the above-described method.

[0012] A fourth aspect of the present invention also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described method.

[0013] In summary, the present invention has the following beneficial effects: 1. No gyroscope required, reducing costs: This method collects rail cross-section information using a two-dimensional laser sensor and combines it with an algorithm model to invert the vehicle's attitude. It does not rely on a high-precision gyroscope at all, which significantly reduces the manufacturing and maintenance costs of the equipment. At the same time, it avoids the decrease in accuracy caused by vibration interference and drift of the gyroscope.

[0014] 2. High-precision detection and strong stability: High detection accuracy: By extracting stable feature points such as the circular profile of the rail base as a benchmark, and combining multi-sensor data fusion and error compensation algorithms, high-precision measurement of vehicle body posture parameters is achieved, meeting the high-precision operation requirements of high-speed grinding trolleys. Moreover, no parameter drift will occur during long-term use, demonstrating strong stability.

[0015] 3. Simplified grinding vehicle structure: This invention does not rely on mechanical lateral positioning devices. By using a parallel mechanism that detects the vehicle body posture in real time and feeds it back to the grinding unit, the grinding position can be dynamically adjusted, which effectively simplifies the mechanical structure of the grinding vehicle and reduces equipment complexity and failure risk. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the installation position of the two-dimensional laser sensor in Embodiment 1 of the present invention (where 1, 2, 3 and 4 are the installation positions of the two-dimensional laser sensor). Figure 2 This is a schematic diagram of coordinate establishment in Embodiment 1 of the present invention; Figure 3 This is a schematic diagram of the vehicle body's pitch angle, yaw angle, and roll angle in Embodiment 1 of the present invention; Figure 4 This is a flowchart of the high-speed grinding trolley body posture detection method based on rail cross-section information in Embodiment 1 of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1: The installation location of the two-dimensional laser sensor is as follows Figure 1As shown, they are located at points 1, 2, 3, and 4 marked on the high-speed grinding carriage in the diagram.

[0019] Rail cross-section information acquisition and preprocessing: A two-dimensional laser sensor acquires the original profile data of the rail cross-section at a preset sampling frequency (not less than 50Hz). The original profile data includes the coordinate information of each feature point of the rail cross-section in the sensor coordinate system. The original profile data is preprocessed, including noise filtering (using Gaussian filtering algorithm to remove noise caused by ambient light, vibration and other interference), data completion (for sensor measurement blind spots or missing data areas, linear interpolation algorithm is used to complete the data based on adjacent valid data), and feature point extraction (extracting two circular profile feature points at the bottom of the rail and feature points at the edge of the rail head as reference points for subsequent attitude calculation).

[0020] 3. Coordinate system establishment and transformation: like Figure 2 As shown, establish the orbital reference coordinate system. The origin is the center of the bottom of the left rail. The direction perpendicular to the track extension direction within the plane of the track base is Axis (horizontal), vertical direction is The axis (vertical) extends along the direction of the track. Axis (longitudinal direction); Establish sensor coordinate system The origin is the optical center of the two-dimensional laser sensor. The sensor's optical axis direction is Axis, in the laser scanning plane and The horizontal direction perpendicular to the axis is The axis, vertical direction is axis; Establish vehicle body coordinate system Taking the geometric center of the car body as the origin. The length of the vehicle body is Axis (with respect to the orbital reference coordinate system) (axis parallel), vehicle width direction is Axis (with respect to the orbital reference coordinate system) (axis parallel), vehicle height direction is Axis (with respect to the orbital reference coordinate system) (axis parallel) Coordinate system transformation: Based on the calibration parameters (intrinsic parameter matrix) of a two-dimensional laser sensor extrinsic parameter matrix ,in Includes rotation matrix With translation matrix The preprocessed profile data (rail section feature points) is transformed from the sensor coordinate system to the track reference coordinate system to obtain the profile data in the track reference coordinate system, and the coordinates of the feature points in the track reference coordinate system are obtained. .

[0021] 4. Calculation of vehicle body attitude parameters: The vehicle body attitude parameters are calculated using the preprocessed profile data and the profile data in the track reference coordinate system; like Figure 3 As shown, the head-shaking angle ( ) and nodding corner ( Calculation: Select two circular profiles at the bottom of the rail as references. Let the coordinates of the centers of the two circular profiles at the bottom of the standard rail in the rail reference coordinate system be respectively... , , its in The distance in the direction is , The distance in the direction is The coordinates of the centers of the two circular profiles at the bottom of the actual rail, measured by a two-dimensional laser sensor, are as follows: , , its in The distance in the direction is , The distance in the direction is According to geometric relationships, we can obtain Roll angle ( Calculation: Using the cross-sectional information of the left and right rails collected by the sensors at the front and rear ends of the grinding trolley, let the coordinates of the center of the left rail base measured by the front sensor be... The coordinates of the center of the right rail base circle are: The rear sensor measured the coordinates of the center of the left rail base as follows: The coordinates of the center of the right rail base circle are: Calculate the slope of the line connecting the centers of the bottom circles of the front and rear rails (slope of the front end line). Slope of the back end connection ), roll angle , in For front-end and back-end sensors Distance along the axial direction.

[0022] Vehicle body translation calculation: based on the origin of the vehicle body coordinate system For reference, based on the coordinates of the rail cross-section feature points measured by the front and rear end sensors in the track reference coordinate system, combined with the vehicle body geometric parameters (length) ,width ,high ), calculate the vehicle body in Lateral displacement in the axial direction , Lifting or lowering in the axial direction , Axial expansion / contraction , in, This is the initial lateral displacement reference value for the vehicle body. This is the initial reference value for vehicle body lifting. This is the initial extension / retraction reference value for the vehicle body.

[0023] 5. Grinding unit coordinate calculation and vehicle body attitude inversion: Given grinding units (4 in total, namely unit...) , , , The relative positional relationship between the grinding plates of the four grinding units and the vehicle body coordinate system is as follows: In the vehicle body coordinate system, the coordinates of the grinding plates of the four grinding units are respectively... , , , And satisfy , , , (Nominal dimensional symmetry relationship); Based on the vehicle attitude parameters calculated in step 4 Establish the transformation matrix from the vehicle coordinate system to the track reference coordinate system. (Obtained by multiplying the rotation matrices corresponding to the head-shaking angle, head-nodding angle, and roll angle) and the translation vector ; The coordinates of the grinding unit's pressure plate in the vehicle coordinate system are transformed using a matrix. With translation vector Transform to the track reference coordinate system to obtain the actual coordinates of the grinding plate in the track reference coordinate system. , , , ; By comparing the actual coordinates of the grinding plate with the preset target grinding coordinates (determined based on the standard rail section), the deviation of the vehicle body from the ideal posture is obtained, thus completing the vehicle body posture detection.

[0024] Example 2: A method for detecting the body posture of a high-speed grinding trolley based on rail cross-section information includes the following steps: Obtain the preprocessed profile data, which includes the feature points of the rail section; Establish the track reference coordinate system, sensor coordinate system and vehicle body coordinate system, and transform the preprocessed profile data from the sensor coordinate system to the track reference coordinate system to obtain the profile data in the track reference coordinate system. The vehicle body attitude parameters are calculated using the preprocessed profile data and the profile data under the track reference coordinate system. The vehicle body translation vector is calculated using the origin of the vehicle body coordinate system as a reference, based on the coordinates of the feature points of the rail section under the track reference coordinate system and the vehicle body geometric parameters. Based on the vehicle body posture parameters, establish the transformation matrix and translation vector from the vehicle body coordinate system to the track reference coordinate system; obtain the coordinates of the grinding plate in the vehicle body coordinate system, and transform them to the track reference coordinate system through the transformation matrix and translation vector to obtain the actual coordinates of the grinding plate in the track reference coordinate system; by comparing the actual coordinates of the grinding plate with the preset target grinding coordinates, the deviation of the vehicle body from the ideal posture is obtained, and the vehicle body posture detection is completed.

[0025] In this embodiment, the method for obtaining preprocessed profile data includes the following steps: installing sensors on a high-speed grinding trolley to collect the original profile data of the rail cross section, and preprocessing the original profile data.

[0026] In this embodiment, the preprocessing includes noise filtering, data completion, and feature point extraction. The preprocessed profile data also includes two circular profile feature points and railhead edge feature points.

[0027] In this embodiment, the vehicle body attitude parameters include the pitch angle ( ) and nodding corner ( ).

[0028] In this embodiment, the method for calculating the vehicle body attitude parameters is as follows: Two circular profiles at the bottom of the rail are selected as references. Let the coordinates of the centers of the two circular profiles at the bottom of the standard rail in the rail reference coordinate system be respectively... , , its in The distance in the direction is , The distance in the direction is The coordinates of the centers of the two circular profiles at the bottom of the actual rail, measured by a two-dimensional laser sensor, are as follows: , , its in The distance in the direction is , The distance in the direction is According to geometric relationships, we can obtain Roll angle ( Calculation: Using the cross-sectional information of the left and right rails collected by the sensors at the front and rear ends of the grinding trolley, let the coordinates of the center of the left rail base measured by the front sensor be... The coordinates of the center of the right rail base circle are: The rear sensor measured the coordinates of the center of the left rail base as follows: The coordinates of the center of the right rail base circle are: Calculate the slope of the line connecting the centers of the bottom circles of the front and rear rails (slope of the front end line). Slope of the back end connection ), roll angle , in For front-end and back-end sensors Distance along the axial direction.

[0029] In this embodiment, the vehicle translation vector includes the vehicle body in... Lateral displacement in the axial direction , Lifting or lowering in the axial direction , Axial expansion / contraction , in, This is the initial lateral displacement reference value for the vehicle body. This is the initial reference value for vehicle body lifting. This is the initial extension / retraction reference value for the vehicle body.

[0030] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for detecting the body posture of a high-speed grinding trolley based on rail cross-section information, characterized in that: Includes the following steps: Obtain preprocessed profile data, which includes rail section feature points; Establish the track reference coordinate system, sensor coordinate system and vehicle body coordinate system, and transform the preprocessed profile data from the sensor coordinate system to the track reference coordinate system to obtain the profile data in the track reference coordinate system. The vehicle body attitude parameters are calculated using the preprocessed profile data and the profile data in the track reference coordinate system. With the origin of the vehicle body coordinate system as a reference, the vehicle body translation vector is calculated based on the coordinates of the feature points of the rail section in the track reference coordinate system and the vehicle body geometric parameters. Based on the vehicle body posture parameters, establish the transformation matrix and translation vector from the vehicle body coordinate system to the track reference coordinate system; obtain the coordinates of the grinding plate in the vehicle body coordinate system, and transform them to the track reference coordinate system through the transformation matrix and translation vector to obtain the actual coordinates of the grinding plate in the track reference coordinate system; by comparing the actual coordinates of the grinding plate with the preset target grinding coordinates, the deviation of the vehicle body from the ideal posture is obtained, and the vehicle body posture detection is completed.

2. The method for detecting the body posture of a high-speed grinding trolley based on rail cross-section information according to claim 1, characterized in that: The method for obtaining preprocessed profile data includes the following steps: installing sensors on a high-speed grinding trolley to collect the original profile data of the rail cross section, and preprocessing the original profile data.

3. The method for detecting the body posture of a high-speed grinding trolley based on rail cross-section information according to any one of claims 1-2, characterized in that: The preprocessing includes noise filtering, data completion, and feature point extraction. The preprocessed profile data also includes two circular profile feature points and railhead edge feature points.

4. The method for detecting the body posture of a high-speed grinding trolley based on rail cross-section information according to claim 3, characterized in that: The vehicle attitude parameters include the head-up angle ( ) and nodding corner ( ).

5. The method for detecting the body posture of a high-speed grinding trolley based on rail cross-section information according to claim 4, characterized in that: The method for calculating the vehicle body attitude parameters is as follows: Two circular profiles at the bottom of the rail are selected as references. Let the coordinates of the centers of the two circular profiles at the bottom of the standard rail in the rail reference coordinate system be respectively... , , its in The distance in the direction is , The distance in the direction is The coordinates of the centers of the two circular profiles at the bottom of the actual rail, measured by a two-dimensional laser sensor, are as follows: , , its in The distance in the direction is , The distance in the direction is According to geometric relationships, we can obtain ； ； Roll angle ( Calculation: Using the cross-sectional information of the left and right rails collected by the sensors at the front and rear ends of the grinding trolley, let the coordinates of the center of the left rail base measured by the front sensor be... The coordinates of the center of the right rail base circle are: The rear sensor measured the coordinates of the center of the left rail base as follows: The coordinates of the center of the right rail base circle are: Calculate the slope of the line connecting the centers of the bottom circles of the front and rear rails (slope of the front end line). Slope of the back end connection ), roll angle , ； ； ； in, For front-end and back-end sensors Distance along the axial direction.

6. The method for detecting the body posture of a high-speed grinding trolley based on rail cross-section information according to claim 5, characterized in that: The vehicle translation vector includes the vehicle's position in the direction of the vehicle's translation. Lateral displacement in the axial direction , Lifting or lowering in the axial direction , Axial expansion / contraction , ； ； ； in, This is the initial lateral displacement reference value for the vehicle body. This is the initial reference value for vehicle body lifting. This is the initial extension / retraction reference value for the vehicle body.

7. A device / equipment / system for high-speed grinding trolley body posture detection based on rail cross-section information, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1-6.

8. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that... When the computer program / instruction is executed by the processor, it implements the steps of the method described in any one of claims 1-6.

9. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method described in any one of claims 1-6.

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