A novel procedure for diagnosing multiple faults in rotating machinery. (March 2015)

• Record Type: Journal Article
• Authors: Wang, Zhijian; Han, Zhennan; Gu, Fengshou; Gu, James Xi; Ning, Shaohui
• Is Part Of: ISA transactions. Volume 55(2015:Mar.)
• Page Start: 208
• Page End: 218
• Publication Date: 2015-03
• Subjects: CMF -- EEMD -- CAF -- Fault diagnosis; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2014.09.006
• Languages: English
• ISSNs: 0019-0578

Abstract

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 C L, and a high frequency CMF, denoted as Ch . Then it optimizes the amplitude of the added noise in decomposing Ch and C L 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. Highlights: A new signal processing procedure named as CMF-EEMD method has been proposed. CMF-EEMD optimizes the amplitude of added noise in decomposing C h and C L using EEMD. It calculates cyclic autocorrelation function (CAF) for every characteristic IMF from EEMD. The method is compared with the CAF of a direct EEMD, showing its superiority. CMF-EEMD is applied to analyze the multi-fault of a wind turbine gearbox. The results provide references for improving the layout of the wind turbine gearbox test system.