Incipient Fault Diagnosis of Roller Bearing Using Optimized Wavelet Transform Based Multi-Speed Vibration Signatures

IEEE Access

Volumn 5, Issue , 2017, Pages 19442-19456

  Huo, Zhiqiang ^a,b   Zhang, Yu ^a   Francq, Pierre ^c   Shu, Lei ^a,b   Huang, Jianfeng ^b  

^a UNIVERSITY OF LINCOLN   (United Kingdom)

^b GUANGDONG UNIVERSITY OF PETROCHEMICAL TECHNOLOGY   (China)

^c ECOLE DES MINES D ALBI CARMAUX   (France)

Author keywords

continuous wavelet transforms; Fault diagnosis; fault signatures; particle swarm optimization; quasi Newton minimization; roller bearing; vibration measurement

Indexed keywords

BEARINGS (MACHINE PARTS); CONDITION MONITORING; FAILURE ANALYSIS; MACHINERY; PARTICLE SWARM OPTIMIZATION (PSO); ROLLER BEARINGS; ROLLERS (MACHINE COMPONENTS); VIBRATION MEASUREMENT; WAVELET TRANSFORMS;

ADAPTIVE WAVELET TRANSFORMS; CONTINUOUS WAVELET TRANSFORM; FAULT SIGNATURE; INCIPIENT FAULT DIAGNOSIS; INDUSTRIAL ENVIRONMENTS; NEAREST NEIGHBOR CLASSIFIER; QUASI-NEWTON; STATISTICAL PARAMETERS;

FAULT DETECTION;

EID: 85021762568     PISSN: None     EISSN: 21693536     Source Type: Journal    
DOI: 10.1109/ACCESS.2017.2661967     Document Type: Article

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