Fault Diagnosis of Planetary Gearbox Based on Adaptive Order Bispectrum Slice and Fault Characteristics Energy Ratio Analysis.

adaptive order bispectrum slice fault characteristics energy ratio fault diagnosis planetary gearbox

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
24 Apr 2020
Historique:
received: 12 03 2020
revised: 19 04 2020
accepted: 20 04 2020
entrez: 30 4 2020
pubmed: 30 4 2020
medline: 30 4 2020
Statut: epublish

Résumé

The vibration of a planetary gearbox (PG) is complex and mutually modulated, which makes the weak features of incipient fault difficult to detect. To target this problem, a novel method, based on an adaptive order bispectrum slice (AOBS) and the fault characteristics energy ratio (FCER), is proposed. The order bispectrum (OB) method has shown its effectiveness in the feature extraction of bearings and fixed-shaft gearboxes. However, the effectiveness of the PG still needs to be explored. The FCER is developed to sum up the fault information, which is scattered by mutual modulation. In this method, the raw vibration signal is firstly converted to that in the angle domain. Secondly, the characteristic slice of AOBS is extracted. Different from the conventional OB method, the AOBS is extracted by searching for a characteristic carrier frequency adaptively in the sensitive range of signal coupling. Finally, the FCER is summed up and calculated from the fault features that were dispersed in the characteristic slice. Experimental data was processed, using both the AOBS-FCER method, and the method that combines order spectrum analysis with sideband energy ratio (OSA-SER), respectively. Results indicated that the new method is effective in incipient fault feature extraction, compared with the methods of OB and OSA-SER.

Identifiants

pubmed: 32344737
pii: s20082433
doi: 10.3390/s20082433
pmc: PMC7219498
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : National Natural Science Foundation of China
ID : 51875166; 51705127; U1813222

Références

ISA Trans. 2018 Oct;81:329-341
pubmed: 29903426
Sensors (Basel). 2018 Sep 01;18(9):
pubmed: 30200505
Sensors (Basel). 2019 Sep 16;19(18):
pubmed: 31527448

Auteurs

Zhaoyang Shen (Z)

Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles, School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China.

Zhanqun Shi (Z)

Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles, School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China.

Dong Zhen (D)

Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles, School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China.

Hao Zhang (H)

Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles, School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China.

Fengshou Gu (F)

Centre for Efficiency and Performance Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK.

Classifications MeSH