Application of the fuzzy min-max neural network to fault detection and diagnosis of induction motors

Neural Computing and Applications

Volumn 23, Issue SUPPL1, 2013, Pages 191-200

  Seera, Manjeevan ^d   Lim, Chee Peng ^a   Ishak, Dahaman ^b   Singh, Harapajan ^c  

^a DEAKIN UNIVERSITY   (Australia)

^b SCHOOL OF PHYSICS   (Malaysia)

^c UNIVERSITI TEKNOLOGI MARA   (Malaysia)

^d Intel Technology Malaysia Sdn Bhd   (Malaysia)

Author keywords

Fault detection and diagnosis; Fuzzy min max neural network; Induction motor; Motor current signature analysis; Pattern classification

Indexed keywords

FAULT DETECTION AND CLASSIFICATION; FAULT DETECTION AND DIAGNOSIS; FUZZY MIN-MAX NEURAL NETWORKS; LOAD CONDITION; MIN-MAX; MOTOR CURRENT SIGNATURE ANALYSIS; STATOR CURRENTS; STATOR WINDING FAULTS;

FAULT DETECTION; NEURAL NETWORKS; PATTERN RECOGNITION; POWER SPECTRAL DENSITY; STATORS;

INDUCTION MOTORS;

EID: 84888823881     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-012-1310-x     Document Type: Article

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