A novel procedure for diagnosing multiple faults in rotating machinery

Zhijian Wang, Zhennan Han, Fengshou Gu, James Xi Gu, Shaohui Ning

Research output: Contribution to journalArticlepeer-review

58 Citations (Scopus)

Abstract

In analyzing signals from a wind turbine gearbox this paper suggests a new signal processing procedure named as CMF-EEMD method which is formed by applying conventional EEMD to a new type of combined mode function (CMF). This CMF consists of a low frequency CMF, denoted as CL, and a high frequency CMF, denoted as Ch. Then it optimizes the amplitude of the added noise in decomposing Ch and CL using EEMD. Finally, it calculates cyclic autocorrelation function (CAF) for every characteristic IMF from EEMD. The proposed procedure is applied to analyze the multi-faults of a wind turbine gearbox and the results confirm better performances in resolving different signal components by the proposed method than that from the cyclic autocorrelation function (CAF) of a direct EEMD analysis.

Original languageEnglish
Pages (from-to)208-218
Number of pages11
JournalISA Transactions
Volume55
Early online date11 Nov 2014
DOIs
Publication statusPublished - 1 Mar 2015

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