Rolling bearing diagnosing method based on Empirical Mode Decomposition of machine vibration signal

被引:177
作者
Dybala, Jacek [1 ]
Zimroz, Radoslaw [2 ]
机构
[1] Warsaw Univ Technol, Inst Vehicles, PL-02524 Warsaw, Poland
[2] Wroclaw Univ Technol, Diagnost & Vibroacoust Sci Lab, PL-50051 Wroclaw, Poland
关键词
Rolling element bearings; Bearing diagnostics; Condition monitoring; Empirical Mode Decomposition (EMD); Intrinsic Mode Function (IMF); Combined Mode Function (CMF); FAULT-DIAGNOSIS; ELEMENT BEARINGS; HILBERT SPECTRUM; DAMAGE DETECTION; TIME-SERIES; EMD; ALGORITHM; FILTER;
D O I
10.1016/j.apacoust.2013.09.001
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Rolling bearing faults are one of the major reasons for breakdown of industrial machinery and bearing diagnosing is one of the most important topics in machine condition monitoring. The main problem in industrial application of bearing vibration diagnostics is the masking of informative bearing signal by machine noise. The vibration signal of the rolling bearing is often covered or concealed by other structural vibrations sources, such as gears. Although a number of vibration diagnostic techniques have been developed over the last several years, in many cases these methods are quite complicated in use or only effective at later stages of damage development. This paper presents an EMD-based rolling bearing diagnosing method that shows potential for bearing damage detection at a much earlier stage of damage development. By using EMD a raw vibration signal is decomposed into a number of Intrinsic Mode Functions (IMFs). Then, a new method of IMFs aggregation into three Combined Mode Functions (CMFs) is applied and finally the vibration signal is divided into three parts of signal: noise-only part, signal-only part and trend-only part. To further bearing fault-related feature extraction from resultant signals, the spectral analysis of the empirically determined local amplitude is used. To validate the proposed method, raw vibration signals generated by complex mechanical systems employed in the industry (driving units of belt conveyors), including normal and fault bearing vibration data, are used in two case studies. The results show that the proposed rolling bearing diagnosing method can identify bearing faults at early stages of their development. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:195 / 203
页数:9
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