NDLI: Enhancing the ability of Ensemble Empirical Mode Decomposition in machine fault diagnosis

Content Provider	IEEE Xplore Digital Library
Author	Wei Guo Tse, P.W.
Copyright Year	2010
Description	Author affiliation: Smart Engineering Asset Management (SEAM) Laboratory, Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, 83 Tat Chee Ave., Kowloon Tong, Hong Kong (Wei Guo; Tse, P.W.)
Abstract	Empirical Mode Decomposition (EMD) is an adaptive time-frequency analysis method that has been widely employing for machinery fault diagnosis. EMD is famous in revealing instantaneous change of frequency or time from non-linear sensory signal so that the occurrence of anomalous signal can be accurately detected. However, its shortcomings include mode mixing and end effects that often appear in its decomposed bands. These problems decrease the accuracy, particularly in vibration-based fault diagnosis. Recently, many researchers have proposed various improved methods, which include the famous Ensemble EMD (EEMD), to solve the problem of mode mixing. Its purpose is to introduce controlled amount of white noise to the original EMD. After adding known white noise into the raw signal, the signal in the band will have a uniformly distributed reference scale which forces the EEMD to exhaust all possible solutions in the sifting process for minimizing mode mixing effect. Even though EEMD becomes popular, the proper settings for the number of ensemble and the amplitude of white noise that should be added are still not formally prescribed. This paper discusses the influence of parameters setting on the results of reducing mode mixing problem. Tests were done using both simulated and real machine signals. Their results provide a guideline on setting the parameters properly so that the ability of EEMD on machine fault diagnosis can be significantly enhanced.
Starting Page	1
Ending Page	7
File Size	1771247
Page Count	7
File Format	PDF
ISBN	9781424447565
e-ISBN	9781424447589
DOI	10.1109/PHM.2010.5413421
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-01-12
Publisher Place	Macao
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis Electric breakdown Laboratories Signal processing Wavelet analysis Time frequency analysis Wavelet packets Manufacturing Asset management Signal analysis
Content Type	Text
Resource Type	Article

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