Rolling Bearing Fault Diagnosis Based on STFT-Deep Learning and Sound Signals

Shock and Vibration

Volumn 2016, Issue , 2016, Pages

  Liu, Hongmei ^a   Li, Lianfeng ^a   Ma, Jian ^a,b  

^a BEIHANG UNIVERSITY   (China)

^b Science and Technology on Reliability and Environmental Engineering Laboratory   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; BEARINGS (MACHINE PARTS); CHARACTER RECOGNITION; CLASSIFICATION (OF INFORMATION); FACE RECOGNITION; FAILURE ANALYSIS; FOURIER SERIES; IMAGE CLASSIFICATION; IMAGE RECOGNITION; LEARNING SYSTEMS; ROLLER BEARINGS; SPEECH RECOGNITION; TEXT PROCESSING;

DEEP ARCHITECTURES; EMPIRICAL MODE DECOMPOSITION; MULTI-LAYER NETWORK; SHORT TIME FOURIER TRANSFORMS; SOFTMAX REGRESSIONS; TEAGER ENERGY OPERATORS; TEXT CLASSIFICATION; VIBRATION SIGNAL;

FAULT DETECTION;

EID: 84988723839     PISSN: 10709622     EISSN: None     Source Type: Journal    
DOI: 10.1155/2016/6127479     Document Type: Article

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