Fault diagnosis for rotating machinery using vibration measurement deep statistical feature learning

Sensors (Switzerland)

Volumn 16, Issue 6, 2016, Pages

  Li, Chuan ^a   Sánchez, René Vinicio ^b   Zurita, Grover ^b   Cerrada, Mariela ^b   Cabrera, Diego ^b  

^a DONGGUAN UNIVERSITY OF TECHNOLOGY   (China)

^b UNIVERSIDAD POLITÉCNICA SALESIANA   (Ecuador)

Author keywords

Deep learning; Fault diagnosis; Rotating machinery; Statistical feature; Vibration sensor

Indexed keywords

DEEP LEARNING; ELECTRIC FAULT CURRENTS; FAILURE ANALYSIS; GEARS; ROTATING MACHINERY; STATISTICS; VENTILATION EXHAUSTS; VIBRATION MEASUREMENT; VIBRATIONS (MECHANICAL);

DEEP BOLTZMANN MACHINES; DIAGNOSIS FOR ROTATING MACHINERY; MACHINERY FAULT DIAGNOSIS; RESTRICTED BOLTZMANN MACHINE; STATISTICAL FEATURE EXTRACTIONS; STATISTICAL FEATURES; TIME FREQUENCY DOMAIN; VIBRATION SENSORS;

FAULT DETECTION;

EID: 84975124887     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s16060895     Document Type: Article

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