Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing

Mechanical Systems and Signal Processing

Volumn 100, Issue , 2018, Pages 743-765

  Shao, Haidong ^a   Jiang, Hongkai ^a   Zhang, Haizhou ^a   Duan, Wenjing ^a   Liang, Tianchen ^a   Wu, Shuaipeng ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

Author keywords

Compressed sensing; Exponential moving average; Feature learning; Improved convolutional deep belief network; Rolling bearing

Indexed keywords

BEARINGS (MACHINE PARTS); COMPRESSED SENSING; CONVOLUTION; DEEP LEARNING; FAULT DETECTION; SIGNAL RECONSTRUCTION; VIBRATION ANALYSIS;

COMPRESSIVE SENSING; DEEP BELIEF NETWORKS; EXPONENTIAL MOVING AVERAGES; FEATURE LEARNING; GENERALIZATION PERFORMANCE; ROLLING BEARING VIBRATION; ROLLING BEARINGS; VIBRATION SIGNAL;

ROLLER BEARINGS;

EID: 85028716822     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2017.08.002     Document Type: Article

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