Time-frequency atoms-driven support vector machine method for bearings incipient fault diagnosis

Mechanical Systems and Signal Processing

Volumn 75, Issue , 2016, Pages 345-370

  Liu, Ruonan ^a,b   Yang, Boyuan ^a,b   Zhang, Xiaoli ^a,b   Wang, Shibin ^a,b   Chen, Xuefeng ^a,b  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b XI'AN JIAOTONG UNIVERSITY   (China)

Author keywords

Bearing; Fault diagnosis; Short time matching; Support vector machine (SVM); Weak signal detection

Indexed keywords

BEARINGS (MACHINE PARTS); BEARINGS (STRUCTURAL); EXTRACTION; FAILURE ANALYSIS; FEATURE EXTRACTION; IDENTIFICATION (CONTROL SYSTEMS); MECHANICS; ROLLER BEARINGS; SIGNAL DETECTION; SIGNAL TO NOISE RATIO; SUPPORT VECTOR MACHINES;

INCIPIENT FAULT DIAGNOSIS; LOW SIGNAL-TO-NOISE RATIO; NON-STATIONARY VIBRATION SIGNALS; ROLLER BEARING FAULT; SUPPORT VECTOR MACHINE METHOD; TIME MATCHING; TIME-FREQUENCY ATOMS; WEAK SIGNAL DETECTION;

FAULT DETECTION;

EID: 84961285424     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2015.12.020     Document Type: Article

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