Multi-bearing remaining useful life collaborative prediction: A deep learning approach

Journal of Manufacturing Systems

Volumn 43, Issue , 2017, Pages 248-256

  Ren, Lei ^a,b   Cui, Jin ^a,b   Sun, Yaqiang ^a,b   Cheng, Xuejun ^a,b  

^a BEIHANG UNIVERSITY   (China)

^b BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

Author keywords

Bearing health analysis; Cyber manufacturing; Data analytics; Deep learning; Industrial big data; Remaining useful life prediction

Indexed keywords

BEARINGS (MACHINE PARTS); BIG DATA; DEEP LEARNING; DEEP NEURAL NETWORKS; DISTRIBUTED COMPUTER SYSTEMS; FORECASTING; FREQUENCY DOMAIN ANALYSIS; INDUSTRIAL RESEARCH; LEARNING SYSTEMS; MANUFACTURE; NUMERICAL METHODS; RELIABILITY ANALYSIS; ROLLER BEARINGS;

COLLABORATIVE PREDICTIONS; DATA ANALYTICS; MACHINE LEARNING MODELS; MANUFACTURING INDUSTRIES; MANUFACTURING TECHNIQUES; NUMERICAL EXPERIMENTS; REMAINING USEFUL LIFE PREDICTIONS; REMAINING USEFUL LIVES;

TIME DOMAIN ANALYSIS;

EID: 85014511127     PISSN: 02786125     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jmsy.2017.02.013     Document Type: Article

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