CN-122021181-A - Wheel abrasion simulation optimization method, device, equipment and medium

CN122021181ACN 122021181 ACN122021181 ACN 122021181ACN-122021181-A

Abstract

The application discloses a wheel abrasion simulation optimization method, a device, equipment and a medium, which relate to the technical field of computers and comprise the steps of determining corresponding abrasion depth statistic values based on abrasion depths of target grid nodes output by a preset abrasion model, judging whether the abrasion depth statistic values reach a preset abrasion depth threshold value according to the abrasion depth statistic values, and determining node intervals of steel rail section profiles related to the statistic values if the abrasion depth statistic values reach the preset abrasion depth threshold value, wherein the node intervals are used as steel rail profile simulation parameters, and the steel rail section profiles consist of a plurality of discrete nodes. And triggering morphological reconstruction of the initial grid unit, so that the target displacement of each target grid node along the normal direction in the tread of the wheel is consistent with the abrasion depth, and obtaining the target grid unit. And finally, carrying out wheel abrasion simulation by combining the target grid unit and the rail profile simulation parameters through a preset abrasion model to generate a corresponding simulation result. The application can realize the simulation calculation convergence of the full abrasion depth range.

Inventors

ZHANG JINYU
LIN JUN
QU WENQIANG
WANG CHANGLONG
ZHAO MENGHUA

Assignees

中车青岛四方机车车辆股份有限公司

Dates

Publication Date: 20260512
Application Date: 20260311

Claims (11)

1. A wheel wear simulation optimization method, comprising: Determining a corresponding abrasion depth statistic value based on the abrasion depth of a target grid node output by a preset abrasion model, wherein the preset abrasion model is a wheel-steel rail abrasion model which is built in advance, the target grid node is a grid node on each initial grid unit of a target area in the preset abrasion model, the target area comprises a contact area of a wheel and a steel rail and a target nearby area, and the target nearby area is an area corresponding to a preset nearby area range of the contact area; Judging whether the abrasion depth statistic is smaller than a preset abrasion depth threshold value or not; If the abrasion depth statistic value is not smaller than a preset abrasion depth threshold value, determining node intervals of the steel rail section profiles associated with the abrasion depth statistic value to obtain steel rail profile simulation parameters, wherein in the preset abrasion model, the steel rail section profiles are obtained through a plurality of discrete nodes; Triggering morphological reconstruction operation aiming at the initial grid unit to control a target displacement amount to be consistent with the corresponding abrasion depth to obtain a target grid unit, wherein the target displacement amount is the displacement amount of each target grid node on the initial grid unit along the inner normal direction of the tread of the wheel; and carrying out wheel abrasion simulation operation according to the target grid unit through the preset abrasion model and based on the steel rail profile simulation parameters so as to generate a corresponding wheel abrasion simulation result.
2. The wheel wear simulation optimization method according to claim 1, wherein determining the corresponding wear depth statistic based on the wear depth of the target grid node output by the preset wear model comprises: taking the maximum value of the abrasion depths of all the target grid nodes output by the preset abrasion model as a corresponding abrasion depth statistic value; or, taking the average value of the abrasion depths of all the target grid nodes output by the preset abrasion model as a corresponding abrasion depth statistic value; Or, taking the median of the abrasion depths of all the target grid nodes output by the preset abrasion model as the corresponding abrasion depth statistic value.
3. The method of wheel wear simulation optimization of claim 1, wherein before determining the node spacing of the rail cross-sectional profile associated with the wear depth statistic to obtain the rail profile simulation parameters, further comprising: Presetting at least two continuous abrasion depth intervals, wherein the lower limit critical value of the first abrasion depth interval in the two continuous abrasion depth intervals is not smaller than the preset abrasion depth threshold value, and each abrasion depth interval corresponds to a node interval of a steel rail section profile.
4. A wheel wear simulation optimization method according to claim 3, wherein the larger the wear depth of the wear depth zone, the larger the node interval for different wear depth zones.
5. The wheel wear simulation optimization method according to claim 1, wherein in the process of controlling the target displacement amount to coincide with the corresponding wear depth to obtain the target grid cell, further comprising: the cell width of the target grid cell is controlled to be not less than a first cell width threshold and not greater than a second cell width threshold.
6. The method for optimizing wheel wear simulation according to claim 1, wherein before determining the corresponding wear depth statistic based on the wear depth of the target grid node output by the preset wear model, further comprises: Reading the contact pressure stress of each target grid node on the initial grid unit and the sliding distance of each target grid node relative to a steel rail through a user subroutine of the preset abrasion model; And calculating the abrasion depth of each target grid node according to the contact pressure stress of each target grid node and the sliding distance of each target grid node relative to the steel rail.
7. The wheel wear simulation optimization method according to claim 6, wherein the calculating the wear depth of each target mesh node based on the contact compressive stress of each target mesh node and the sliding distance of each target mesh node with respect to a rail comprises: For each target grid node, carrying out product operation processing on the contact pressure stress of the target grid node, the sliding distance of the target grid node relative to the steel rail and a preset abrasion coefficient to obtain an operation result corresponding to the target grid node; and determining the operation result as the abrasion depth of the target grid node.
8. The wheel wear simulation optimization method according to claim 7, further comprising: If the contact pressure stress of any target grid node is larger than a preset pressure stress threshold value in a continuous first number of periods or the sliding distance of any target grid node relative to the steel rail is smaller than a preset sliding threshold value in a continuous second number of periods, judging that the corresponding target grid node is an abnormal node; Determining a plurality of grid nodes adjacent to the abnormal node; determining contact pressure stress average values of the adjacent grid nodes and sliding distance average values of the adjacent grid nodes relative to the steel rail; And calculating the abrasion depth of the abnormal node according to the contact pressure stress average value and the sliding distance average value.
9. A wheel wear simulation optimizing apparatus, comprising: The abrasion depth determining module is used for determining a corresponding abrasion depth statistic value based on the abrasion depth of a target grid node output by a preset abrasion model, wherein the preset abrasion model is a wheel-steel rail abrasion model which is built in advance, the target grid node is a grid node on each initial grid unit of a target area in the preset abrasion model, the target area comprises a contact area of a wheel and a steel rail and a target nearby area, and the target nearby area is an area corresponding to a preset nearby area range of the contact area; The abrasion depth comparison module is used for judging whether the abrasion depth statistic value is smaller than a preset abrasion depth threshold value or not; The node interval determining module is used for determining the node interval of the steel rail section profile associated with the abrasion depth statistic value to obtain the steel rail profile simulation parameter if the abrasion depth statistic value is not smaller than a preset abrasion depth threshold value, wherein in the preset abrasion model, the steel rail section profile is obtained through a plurality of discrete nodes; the grid cell reconstruction module is used for triggering morphological reconstruction operation aiming at the initial grid cell so as to control the target displacement to be consistent with the corresponding abrasion depth to obtain a target grid cell, wherein the target displacement is the displacement of each target grid node on the initial grid cell along the inner normal direction of the tread of the wheel; and the wheel abrasion simulation module is used for performing wheel abrasion simulation operation according to the target grid unit through the preset abrasion model and based on the rail profile simulation parameters so as to generate corresponding wheel abrasion simulation results.
10. An electronic device, comprising: A memory for storing a computer program; A processor for executing the computer program to implement the wheel wear simulation optimization method according to any one of claims 1 to 8.
11. A computer readable storage medium for storing a computer program, wherein the computer program when executed by a processor implements the wheel wear simulation optimization method according to any one of claims 1 to 8.

Description

Wheel abrasion simulation optimization method, device, equipment and medium Technical Field The invention relates to the technical field of computers, in particular to a wheel abrasion simulation optimization method, device, equipment and medium. Background When the railway vehicle brakes, the wheel rail adhesion coefficient is reduced, the wheel is easy to cause wheel locking and sliding, then scratch flat is formed, and the size and the depth of the scratch flat are simulated, so that the method has important significance for vehicle safety evaluation. Abaqus (general commercial finite element software) can develop relevant simulation in combination with user subroutine, and grid division is the basic premise of finite element simulation. Specifically, the grid division is to adjust the density according to the stress-strain gradient, namely, for the region with high stress-strain value and large gradient, a fine grid is required to ensure the calculation accuracy, and for the region with low stress-strain value and small gradient, a coarsening grid is required to improve the calculation efficiency. The wheel-rail contact area is used as a highly concentrated stress-strain area in the wheel abrasion process, and a fine grid is required. The method can solve the problem of convergence of simulation calculation when the depth of the scratch flat is larger, but when the depth of the scratch flat is further increased, the hidden danger of non-convergence of calculation still exists, and the method needs to be further optimized to realize convergence of simulation calculation of a whole scene. Disclosure of Invention In view of the above, the present invention aims to provide a method, a device and a medium for optimizing wheel abrasion simulation, which can realize the convergence of simulation calculation of the full abrasion depth range. The specific scheme is as follows: In a first aspect, the application discloses a wheel abrasion simulation optimization method, comprising the following steps: Determining a corresponding abrasion depth statistic value based on the abrasion depth of a target grid node output by a preset abrasion model, wherein the preset abrasion model is a wheel-steel rail abrasion model which is built in advance, the target grid node is a grid node on each initial grid unit of a target area in the preset abrasion model, the target area comprises a contact area of a wheel and a steel rail and a target nearby area, and the target nearby area is an area corresponding to a preset nearby area range of the contact area; Judging whether the abrasion depth statistic is smaller than a preset abrasion depth threshold value or not; If the abrasion depth statistic value is not smaller than a preset abrasion depth threshold value, determining node intervals of the steel rail section profiles associated with the abrasion depth statistic value to obtain steel rail profile simulation parameters, wherein in the preset abrasion model, the steel rail section profiles are obtained through a plurality of discrete nodes; Triggering morphological reconstruction operation aiming at the initial grid unit to control a target displacement amount to be consistent with the corresponding abrasion depth to obtain a target grid unit, wherein the target displacement amount is the displacement amount of each target grid node on the initial grid unit along the inner normal direction of the tread of the wheel; and carrying out wheel abrasion simulation operation according to the target grid unit through the preset abrasion model and based on the steel rail profile simulation parameters so as to generate a corresponding wheel abrasion simulation result. Optionally, the determining the corresponding abrasion depth statistic value based on the abrasion depth of the target grid node output by the preset abrasion model includes: taking the maximum value of the abrasion depths of all the target grid nodes output by the preset abrasion model as a corresponding abrasion depth statistic value; or, taking the average value of the abrasion depths of all the target grid nodes output by the preset abrasion model as a corresponding abrasion depth statistic value; Or, taking the median of the abrasion depths of all the target grid nodes output by the preset abrasion model as the corresponding abrasion depth statistic value. Optionally, before determining the node interval of the rail section profile associated with the wear depth statistic to obtain the rail profile simulation parameter, the method further includes: Presetting at least two continuous abrasion depth intervals, wherein the lower limit critical value of the first abrasion depth interval in the two continuous abrasion depth intervals is not smaller than the preset abrasion depth threshold value, and each abrasion depth interval corresponds to a node interval of a steel rail section profile. Optionally, for different wear depth intervals, the greater the wear depth of the wea