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Titre: An early gear fault diagnosis method based on rlmd, hilbert transform and cepstrum analysis
Auteur(s): Afia, Adel
Rahmoune, Chemseddine
Benazzouz, Djamel
Mots-clés: Cepstrum analysis
Gear
Hilbert transform
Kurtosis
Local mean decomposition
RLMD
Date de publication: 2021
Editeur: Acta Press
Collection/Numéro: Mechatronic Systems and Control/ Vol.49, N°2 (2021);pp. 115-123
Résumé: Gear fault diagnosis requires an adaptive decomposition method to extract defect signature. As a self-adaptive approach, local mean decomposition (LMD) decomposes the signal to a set of product functions (PFs). However, LMD suffers from two limits: mode mixing and end effect. To overcome this problem, an optimized technique named “robust LMD (RLMD) uses an integrated frame- work: a mirror extending method to find the real extrema in data as well as a self-adaptive tool to select the size of the fixed sub- set for the moving average algorithm for the envelope estimation and finally, a soft sifting stopping criterion to automatically stop the sifting process after determining the most optimum number of sifting iterations. In this article, a combination between RLMD, Hilbert transform (HT), kurtosis and cepstrum analysis is made to monitor a gearbox with chipped tooth using experimental signals. Data are first decomposed using RLMD into a couple of PFs, then HT is applied to each PF to get the envelope for every decom- posed component and highlights the modulated signal related to the gear fault. Subsequently, kurtosis is applied to each envelope to obtain the kurtosis vector for each signal. As healthy vibration characteristics are always taken as a reference, in this article every faulty kurtosis vector is subtracted from the healthy vector, and the PF with the largest kurtosis difference will be selected. Finally, cepstrum analysis is applied to the selected PF to extract the fault signature. Results indicate that our method can detect the chipped tooth in an earlier stage even in a noisy environment
URI/URL: DOI: 10.2316/J.2021.201-0217
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/6680
ISSN: 25611771
Collection(s) :Publications Internationales

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