Intelligent fault diagnosis of rolling bearing using one-dimensional multi-scale deep convolutional neural network based health state classification

ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control

Volumn , Issue , 2018, Pages 1-6

  Zilong, Zhuang ^a   Wei, Qin ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

convolutional neural networks; fault diagnosis; multi scale

Indexed keywords

COMPUTER AIDED DIAGNOSIS; CONVOLUTION; DEEP NEURAL NETWORKS; DIGITAL SIGNAL PROCESSING; FAILURE ANALYSIS; LEARNING ALGORITHMS; NEURAL NETWORKS; ROLLER BEARINGS; VIBRATION ANALYSIS;

CONVOLUTIONAL NEURAL NETWORK; DEEP CONVOLUTIONAL NEURAL NETWORKS; FAULT CLASSIFICATION; FEATURE REPRESENTATION; INTELLIGENT FAULT DIAGNOSIS; MACHINE LEARNING TECHNIQUES; MULTI-SCALE; ROLLING ELEMENT BEARING;

FAULT DETECTION;

EID: 85048242203     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNSC.2018.8361296     Document Type: Conference Paper

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