Gearbox Fault Diagnosis Based on Empirical Mode Decomposition and Hilbert Transform

Yan Li Liu; De Xiang Zhang; Ming Wei Ji

doi:10.4028/www.scientific.net/AMR.542-543.238

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 542-543Gearbox Fault Diagnosis Based on Empirical Mode...

Gearbox Fault Diagnosis Based on Empirical Mode Decomposition and Hilbert Transform

Abstract:

Gearbox is vital components in a wide range of industrial and transport applications. It is very important how to monitor operating state of automobile gearbox and detect incipient faults. This paper applies the empirical mode decomposition (EMD) and Hilbert spectrum methods to gearbox vibration signal analysis capture from vibrating acceleration sensor for gearbox fault diagnosis. The original modulation fault vibration signals are firstly decomposed into a number of intrinsic mode function (IMF) by the EMD method. Then Hilbert spectrum of intrinsic mode function at different fault characteristic frequencies is obtained by Hilbert transform. Finally, the time-frequency fault characteristics of gearbox are analyzed by the Hilbert spectrum value of intrinsic mode function. Experiment result has shown the feasibility and efficiency of the EMD algorithms and Hilbert spectrum characteristic method in fault diagnosis and fault message abstraction.