Neural-network approaches for classification of induction machine faults using optimal time-frequency representations

2011 10th International Conference on Environment and Electrical Engineering, EEEIC.EU 2011 - Conference Proceedings

Volumn , Issue , 2011, Pages

  Boukra, Tahar ^a   Lebaroud, Abdesselam ^a   Clerc, Guy ^b,c,d  

^a UNIVERSITY OF SKIKDA   (Algeria)

^b UNIVERSITÉ DE LYON   (France)

^c UNIVERSITÉ LYON 1   (France)

^d Univ Claude Bernard Lyon1   (France)

Author keywords

Artificial Neural Network ANN; Classification Optimal TFR; Induction Machine Diagnosis; Wavelet Neural Network WNN

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CLASSIFICATION-OPTIMAL TFR; CURRENT WAVEFORMS; DIAGNOSIS METHODS; FAULT CLASSIFICATION; FEATURE EXTRACTION AND CLASSIFICATION; INDUCTION MACHINES; INDUCTION MOTOR TESTS; LEVENBERG-MARQUARDT ALGORITHM; SEQUENTIAL PROCESS; TIME-FREQUENCY REPRESENTATIONS; WAVELET NEURAL NETWORKS;

ELECTRICAL ENGINEERING; FEATURE EXTRACTION; INDUCTION MOTORS; OPTIMIZATION;

NEURAL NETWORKS;

EID: 79960018694     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EEEIC.2011.5874698     Document Type: Conference Paper

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