机械科学与技术2025，Vol.44Issue(6)：921-928,8.DOI:10.13433/j.cnki.1003-8728.20230253
增强MOMEDA算法及在滚动轴承微弱故障诊断中的应用研究
Enhanced MOMEDA Algorithm and Application in Weak Fault Diagnosis of Rolling Bearings
摘要
Abstract
Aiming at the improvement of Multipoint optimal minimum entropy deconvolution adjusted(MOMEDA),an enhanced MOMEDA algorithm is proposed and applied to the weak fault diagnosis of rolling bearings.Firstly,a frequency domain index that can reflect the filtering effect is constructed.It is found that the filtering effect of MOMEDA depends on the fault period rather than the filtering length.Then,a method combining autocorrelation,envelope demodulation and multipoint kurtosis(MKurt)is proposed to determine the optimal fault period.The rolling bearing fault and normal data of the external casing measuring point are used for verification.The results show that the method can effectively overcome the problem that the traditional MOMEDA algorithm is difficult to select the fault period,and can adaptively extract the more significant fault period.Finally,compared with the MED-based collaborative diagnosis method,it is found that MOMEDA focuses on determining the fault cycle,while the MED-based collaborative diagnosis method focuses on selecting the filter length.After the fault cycle is correctly extracted,the MOMEDA filtering effect is better.关键词
滚动轴承/MOMEDA/MKurt/故障诊断/特征增强Key words
rolling bearings/MOMEDA/MKurt/fault diagnosis/feature enhancement分类
航空航天引用本文复制引用
盛嘉玖,陈果,刘曜宾,贺志远,王浩,尉询楷..增强MOMEDA算法及在滚动轴承微弱故障诊断中的应用研究[J].机械科学与技术,2025,44(6):921-928,8.基金项目
国家自然科学基金项目(52272436)、国家科技重大专项计划(J2019-IV-004-0071)及江苏省研究生科研与实践创新计划(KYCX200211) （52272436）
