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Gearbox fault diagnosis using ensemble empirical mode decomposition (EEMD) and residual signal

Published online by Cambridge University Press:  23 April 2012

Hafida Mahgoun ,
Rais Elhadi Bekka  and
Ahmed Felkaoui
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Abstract

This paper presents the application of new time frequency method, ensemble empirical mode decomposition (EEMD), in purpose to detect localized faults of damage at an early stage. EEMD is a self adaptive analysis method for non-linear and non-stationary signals and it was recently proposed by Huang and Wu to overcome the drawbacks of the traditional empirical mode decomposition (EMD). The vibration signal is usually noisy. To detect the fault at an early stage of its development, generally the residual signal is used. There exist different methods in literature to calculate the residual signal, in this paper we mention some of them and we propose a new method which is based on EEMD. The results given by the different methods are compared by using simulated and experimental signals.

Keywords

Ensemble empirical mode decomposition (EEMD)residual signalgearbox fault diagnosisfault detectionrotating machines
Type
Research Article
Information
Mechanics & Industry , Volume 13 , Issue 1 , 2012 , pp. 33 - 44
Copyright
© AFM, EDP Sciences 2012

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