电机与控制应用2023，Vol.50Issue(12)：1-9,9.DOI:10.12177/emca.2023.156
基于多传感信号融合处理的滚动轴承故障定位诊断方法
Rolling Bearing Fault Diagnosis and Localization Based on Multi-Sensor Signal Fusion Processing
摘要
Abstract
In traditional rolling bearing dynamic models,the contact profile of rolling elements is often neglected.Based on the comprehensive analysis of a rolling ball entering and leaving a defect,an equivalent profile quantitative characterization function for localized defects is established,integrating the geometric-motion principles of rolling bearings.From this,an enhanced dynamic model for system failures in rolling bearings is constructed.Using theoretical analysis and numerical simulations based on the dynamic model,the mapping relationship between the location dimensions of outer raceway defect for rolling element bearings and the characteristics of vibration signals is explored,offering a mechanistic foundation for the construction and extraction of quantitative diagnostic indicators.To address the challenge presented by noise interference affecting the diagnostic accuracy of location formulas in real signals,a new algorithm for adaptively decomposing multi-channel time series is used in this paper.In analyses of both simulated and experimental signals,it is shown that the subtle fault quantification features hidden within the original multi-channel signals are more effectively extracted using tensor singular spectrum decomposition.关键词
滚动轴承/量化诊断/张量分解/动力学模型Key words
rolling bearing/quantitative diagnosis/tensor decomposition/dynamic model分类
机械制造引用本文复制引用
高瑞斌,张飞斌..基于多传感信号融合处理的滚动轴承故障定位诊断方法[J].电机与控制应用,2023,50(12):1-9,9.基金项目
国家自然科学基金(52105109)The National Natural Science Foundation of China(52105109) （52105109）
