Comparison of FDA-based and PCA-based features in fault diagnosis of automobile gearboxes

Neurocomputing

Volumn 121, Issue , 2013, Pages 150-159

  Gharavian, M H ^a   Almas Ganj, F ^a   Ohadi, A R ^a   Heidari Bafroui, H ^a  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Automobile gearbox; Continuous wavelet transform; Fault diagnosis; Fisher discriminant analysis; Gaussian mixture model; K nearest neighbor

Indexed keywords

AUTOMOBILE GEARBOX; CONTINUOUS WAVELET TRANSFORM; FISHER DISCRIMINANT ANALYSIS; GAUSSIAN MIXTURE MODEL; K-NEAREST NEIGHBORS;

CONDITION MONITORING; FAILURE ANALYSIS; FEATURE EXTRACTION; FISHER INFORMATION MATRIX; MOTION COMPENSATION; PRINCIPAL COMPONENT ANALYSIS; RESEARCH; WAVELET TRANSFORMS;

FAULT DETECTION;

ACCELEROMETER; ARTICLE; AUTOMOBILE GEARBOX; CLASSIFICATION; CLASSIFIER; CONTINUOUS WAVELET COEFFICIENT; CONTINUOUS WAVELET TRANSFORM; CONTROLLED STUDY; DISCRIMINANT ANALYSIS; ENGINEERING; FAULT DIAGNOSIS; FISHER DISCRIMINANT ANALYSIS; GAUSSIAN MIXTURE MODEL; INTERMETHOD COMPARISON; K NEAREST NEIGHBOR; MACHINE; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SENSOR; SIGNAL PROCESSING; TACHOMETER SENSOR; VIBRATION;

EID: 84884138735     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2013.04.033     Document Type: Article

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