CN-122015735-A - Wheel abrasion detection method and system

CN122015735ACN 122015735 ACN122015735 ACN 122015735ACN-122015735-A

Abstract

The invention provides a wheel abrasion detection method and a system, wherein the method comprises the steps of calculating measurement parameter values of wheel tread measurement data; determining control point coordinates and curve weight factors according to measured parameter values, constructing a tread curve after wheel abrasion according to the control point coordinates and the curve weight factors, calculating the difference area of a difference area between the tread curve after wheel abrasion and wheel tread measurement data, performing iterative optimization on the curve weight factors according to the difference area to obtain weight factor combinations, acquiring operation mileage of wheels of a train to be tested, and determining wheel abrasion values according to the operation mileage and the weight factor combinations. According to the embodiment of the invention, the weight factor combination is used as the abrasion characteristic parameter, and the quantitative mapping relation between the abrasion characteristic parameter and the wheel abrasion value is constructed, so that the corresponding wheel abrasion value can be automatically calculated after the operation mileage of the train wheel to be tested is obtained, and the specific condition of the wheel abrasion can be intuitively reflected.

Inventors

XIAO QIAN
CHENG YUQI
GAO XUESHAN
LIU HESHENG
SHI KAIZHI
CHEN YONGWEN
ZHAO JUNLONG
XIE RUIYUN

Assignees

华东交通大学

Dates

Publication Date: 20260512
Application Date: 20260128

Claims (10)

1. A method of wheel wear detection, the method comprising: acquiring wheel tread measurement data of a sample train, and calculating measurement parameter values of the wheel tread measurement data; Determining control point coordinates and curve weight factors according to the measurement parameter values, and constructing a tread curve after wheel abrasion according to the control point coordinates and the curve weight factors; calculating the difference area of a difference area between the tread curve after wheel abrasion and the wheel tread measurement data, and performing iterative optimization on the curve weight according to the difference area to obtain a weight combination; And acquiring the operation mileage of the train wheels to be tested, and determining a wheel abrasion value according to the operation mileage and the weight factor combination, wherein the wheel abrasion value comprises abrasion amount and/or abrasion depth.
2. The wheel wear detection method according to claim 1, wherein the formula adopted to calculate the measurement parameter value of the wheel tread measurement data includes: ; Wherein, the The value of the measurement parameter is represented by, Represents a sequential series of points in the tread surface measurement data, Representing the forward differential vector.
3. The wheel wear detection method according to claim 2, wherein the formula adopted to determine the control point coordinates and the curve weight from the measurement parameter values includes: ; Wherein, the The coordinates of the control point are represented, Representing the fitting of the target point, The curve weight corresponding to the control point is represented, Representing the B-spline basis function of degree k, Represents the j-th data point in the tread surface measurement data, and n represents the total number of data points of the tread surface measurement data.
4. The wheel wear detection method according to claim 1, wherein constructing a wheel wear rear tread curve from the control point coordinates and the curve weighting factor includes: Constructing a non-uniform rational B-spline curve according to the control point coordinates and the curve weight factors, and restraining the control point coordinates in the non-uniform rational B-spline curve according to control point restraint conditions to obtain a tread curve after the wheel is worn; the control point constraint condition is that coordinates of the control points adjacent left and right are collinear with corresponding control points at a curve connection point of the tread curve after the wheel is worn.
5. The wheel wear detection method according to claim 1, wherein the formula adopted to calculate the difference area of the difference region between the wheel wear rear tread curve and the wheel tread measurement data includes: ; Wherein, the Representing the difference area of the difference region, Represents the actual measured scatter points of the wheel tread abrasion section in the wheel tread measurement data, Representing the number of scatter points in the region of difference, Representing the abscissa of the ith vertex on the discrepancy zone, The abscissa representing the (i + 1) th vertex on the difference region, Representing the ordinate of the ith vertex on the discrepancy zone, Representing the ordinate of the (i + 1) th vertex on the difference region, Representing the first of the difference regions The abscissa of the individual vertices of the graph, Representing the first of the difference regions The ordinate of the individual vertices, The abscissa representing the 1 st vertex on the difference region, Representing the ordinate of the 1 st vertex on the difference region.
6. The wheel wear detection method according to claim 1, wherein iteratively optimizing the curve weights according to the difference areas to obtain a weight combination includes: and taking the curve weight factors as variables, taking the minimum value of the difference area as a target value, and adopting a genetic algorithm to carry out iterative optimization on the curve weight factors to obtain the weight factor combination, wherein the weight factor combination comprises at least one internal weight factor.
7. The wheel wear detection method as set forth in claim 6, wherein determining a wheel wear value from the combination of the operating mileage and the weight factor, the wheel wear value including a wear amount and/or a wear depth using a formula including: ; Wherein, the Indicating the amount of wear or the depth of wear, 、、 Represents the internal weight in the weight combination, The term of the error is represented as, 、、、、、、、、、 And representing the fitting coefficient corresponding to the operation mileage.
8. A wheel wear detection system, the system comprising: The parameterization module is used for acquiring wheel tread measurement data of the sample train and calculating measurement parameter values of the wheel tread measurement data; The tread curve construction module is used for determining control point coordinates and curve weight factors according to the measurement parameter values and constructing tread curves after wheel abrasion according to the control point coordinates and the curve weight factors; The weight factor optimization module is used for calculating the difference area of the difference area between the tread curve after the wheel is worn and the wheel tread measurement data, and carrying out iterative optimization on the curve weight factors according to the difference area to obtain weight factor combinations; And the abrasion output module is used for acquiring the operation mileage of the train wheels to be tested, determining the wheel abrasion value according to the operation mileage and the weight factor combination, wherein the wheel abrasion value comprises abrasion amount and/or abrasion depth.
9. The wheel wear detection system of claim 8, wherein the tread curve construction module is further configured to: Constructing a non-uniform rational B-spline curve according to the control point coordinates and the curve weight factors, and restraining the control point coordinates in the non-uniform rational B-spline curve according to control point restraint conditions to obtain a tread curve after the wheel is worn; the control point constraint condition is that coordinates of the control points adjacent left and right are collinear with corresponding control points at a curve connection point of the tread curve after the wheel is worn.
10. The wheel wear detection system of claim 8, wherein the weight optimization module is further configured to: and taking the curve weight factors as variables, taking the minimum value of the difference area as a target value, and adopting a genetic algorithm to carry out iterative optimization on the curve weight factors to obtain the weight factor combination, wherein the weight factor combination comprises at least one internal weight factor.

Description

Wheel abrasion detection method and system Technical Field The invention relates to the technical field of wheel detection, in particular to a wheel abrasion detection method and system. Background The wheels are used as core bearing parts for the contact of the high-speed train and the rail, and the abrasion state of the wheels directly determines the running safety, stability and economy of the train. With the increase of the operation speed of the high-speed train, the accumulation of the operation mileage and the frequent crossing of complex line conditions (such as small radius curves and turnout areas), the dynamic interaction between wheel and rail is more and more intense, and the wheel abrasion presents complex characteristics of nonlinear and multi-factor coupling. The contact relation of the wheel and the rail can be changed by slight abrasion (a few tenths of a millimeter), so that critical speed is reduced, vibration is aggravated, and faults such as overrun of the thickness of the wheel rim, peeling of the tread and the like are caused when the critical speed is severe, so that the service life of the wheel is shortened (a normal turning and repairing period is usually 20-30 ten thousand kilometers), huge maintenance cost is also required, and even driving safety is threatened. In the existing train wheel detection process, a wheel set fault dynamic detection system is generally adopted for vehicle detection, but only the values of the thickness, the height, the diameter, the inner distance, the diameter difference of the coaxial wheels and the like of the wheel rims are measured, the specific abrasion depth and the abrasion quantity of the wheels cannot be reflected, and the specific situation of the abrasion of the wheels cannot be reflected. Disclosure of Invention The embodiment of the invention aims to provide a wheel abrasion detection method and system, which are used for solving the problem that the specific situation of wheel abrasion cannot be represented in the prior art. The embodiment of the invention is realized in such a way that a wheel abrasion detection method comprises the following steps: acquiring wheel tread measurement data of a sample train, and calculating measurement parameter values of the wheel tread measurement data; Determining control point coordinates and curve weight factors according to the measurement parameter values, and constructing a tread curve after wheel abrasion according to the control point coordinates and the curve weight factors; calculating the difference area of a difference area between the tread curve after wheel abrasion and the wheel tread measurement data, and performing iterative optimization on the curve weight according to the difference area to obtain a weight combination; And acquiring the operation mileage of the train wheels to be tested, and determining a wheel abrasion value according to the operation mileage and the weight factor combination, wherein the wheel abrasion value comprises abrasion amount and/or abrasion depth. Preferably, the formula for calculating the measurement parameter value of the wheel tread measurement data includes: Wherein, the The value of the measurement parameter is represented by,Represents a sequential series of points in the tread surface measurement data,Representing the forward differential vector. Preferably, the formula adopted for determining the control point coordinates and the curve weight according to the measured parameter value comprises: Wherein, the The coordinates of the control point are represented,Representing the fitting of the target point,The curve weight corresponding to the control point is represented,Representing the B-spline basis function of degree k,Represents the j-th data point in the tread surface measurement data, and n represents the total number of data points of the tread surface measurement data. Preferably, constructing a tread curve after wheel abrasion according to the control point coordinates and the curve weight factor, including: Constructing a non-uniform rational B-spline curve according to the control point coordinates and the curve weight factors, and restraining the control point coordinates in the non-uniform rational B-spline curve according to control point restraint conditions to obtain a tread curve after the wheel is worn; the control point constraint condition is that coordinates of the control points adjacent left and right are collinear with corresponding control points at a curve connection point of the tread curve after the wheel is worn. Preferably, the formula for calculating the difference area of the difference area between the wheel wear rear tread curve and the wheel tread measurement data includes: Wherein, the Representing the difference area of the difference region,Represents the actual measured scatter points of the wheel tread abrasion section in the wheel tread measurement data,Representing the number of scatter points in the re