安徽大学学报（自然科学版）2024，Vol.48Issue(4)：50-56,7.DOI:10.3969/j.issn.1000-2162.2024.04.008
基于小波阈值降噪算法的滚动轴承故障诊断
Rolling bearing fault diagnosis based on the wavelet threshold denoising algorithm
摘要
Abstract
Rolling bearings are widely used in industrial production due to their smooth operation,and their safe and stable operation is of great significance to industrial production.Aiming at the fault diagnosis of rolling bearings,a wavelet threshold denoising(WTD)algorithm was proposed.The results showed that compared with the other three algorithms,WTD algorithm had strong fault diagnosis ability.Therefore,WTD algorithm had effectiveness.关键词
滚动轴承/故障诊断/小波阈值降噪算法/调幅调频模型/北方苍鹰优化算法/支持向量机Key words
rolling bearings/fault diagnosis/wavelet threshold denoising algorithm/amplitude modulated and frequency modulated model/northern goshawk optimization algorithm/support vector machine分类
机械制造引用本文复制引用
竺德,李鑫,高清维,卢一相,孙冬..基于小波阈值降噪算法的滚动轴承故障诊断[J].安徽大学学报（自然科学版）,2024,48(4):50-56,7.基金项目
国家自然科学基金资助项目(62071001) （62071001）
安徽省自然科学基金资助项目(2208085QF206,2308085QF224,2008085MF183) （2208085QF206,2308085QF224,2008085MF183）
安徽省高校自然科学重点科研项目(KJ2021A0013) （KJ2021A0013）
