噪声与振动控制2018，Vol.38Issue(3)：152-156,5.DOI:10.3969/j.issn.1006-1355.2018.03.029
基于MS-EEMD的滚动轴承微弱故障提取研究
Weak Fault Signal Extraction of Rolling Bearings based on MS-EEMD
摘要
Abstract
In the practical case, early fault signals of bearings belong to weak signals compared with strong noise signals. It is a difficult problem to extract the early fault signals from the strong noise environment. In this paper, a method for extracting weak faults of rolling bearings based on mask signal (MS) method and ensemble empirical mode decomposition (EEMD) method is proposed. Because there exists the modal mixing in the IMF components decomposed from the noise background by using the EEMD method, it is difficult to distinguish whether the failure frequency is true or false. So, the MS method is introduced to deal with the decomposed IMF components, suppress spurious frequency and extract the real fault frequency. By combining the MS method with EEMD method, the fault signal with noise is processed and the fault signal is extracted.关键词
振动与波/强噪声/掩膜法/总体平均经验模态分解/故障诊断Key words
vibration and wave/strong noise/mask signal (MS) method/ensemble empirical mode decomposition (EEMD)/fault diagnosis分类
信息技术与安全科学引用本文复制引用
王志坚,吴文轩,张纪平,王日俊,寇彦飞..基于MS-EEMD的滚动轴承微弱故障提取研究[J].噪声与振动控制,2018,38(3):152-156,5.基金项目
山西省自然科学基金资助项目(2015011063) （2015011063）
