西南交通大学学报2026，Vol.61Issue(2)：341-350,362,11.DOI:10.3969/j.issn.0258-2724.20240134
车轮非圆化信号平滑处理方法及对多边形磨耗预测的影响
Smoothing Methods of Wheel Out-of-Roundness Signals and Their Effects on Polygonal Wear Prediction
摘要
Abstract
As defects such as pitting usually occur on the wheel tread,the measured wheel out-of-roundness(OOR)signals often contain high-frequency noise interference,and sometimes the signals are discontinuous at the start and end points due to objective factors.Wheel OOR is an important wheel-rail interface excitation in the vehicle-track coupled dynamics model,exerting significant effects on the simulation of dynamic wheel-rail interaction and wheel OOR wear prediction.Selecting the suitable smoothing method is key to ensuring the accuracy of the simulation results.The smoothing effects of four commonly adopted methods based on the EN 15610 standard,Fourier series,moving average,and morphological filtering on processing wheel OOR signals were investigated,and the applicability of the four methods in predicting polygonal wear was discussed.The results indicate that the two methods of Fourier series and moving average can achieve signal smoothing and de-noising effect,preserve the waveform characteristics of original signals,and ensure continuity and differentiability at the start and end points of wheel OOR data when processing measured wheel OOR signals.Additionally,the two methods are also suitable for application in polygonal wear prediction.When the two methods are employed,the order of the Fourier series should be greater than 60 and the smoothing window length of moving average should be about 17 mm.关键词
车轮/非圆化/数据平滑/傅里叶级数/移动平均/形态学滤波/多边形磨耗预测Key words
wheel/out-of-roundness/data smoothing/Fourier series/moving average/morphological filtering/polygonal wear prediction分类
交通工程引用本文复制引用
杨晓璇,陶功权,温泽峰..车轮非圆化信号平滑处理方法及对多边形磨耗预测的影响[J].西南交通大学学报,2026,61(2):341-350,362,11.基金项目
国家自然科学基金项目(52002342,U21A20167) （52002342,U21A20167）
中国博士后科学基金面上项目(2020M673281)牵引动力国家重点实验室自主课题(2020TPL-T03)资助. （2020M673281）
