Artificial intelligence for fault diagnosis of rotating machinery: A review

Mechanical Systems and Signal Processing

Volumn 108, Issue , 2018, Pages 33-47

  Liu, Ruonan ^a,b   Yang, Boyuan ^a,b   Zio, Enrico ^c,d   Chen, Xuefeng ^a,b  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b XI'AN JIAOTONG UNIVERSITY   (China)

^c UNIVERSITÉ PARIS SACLAY   (France)

^d POLITECNICO DI MILANO   (Italy)

Author keywords

Artificial intelligence; Artificial neural network; Deep learning; Fault diagnosis; k Nearest neighbour; Naive Bayes; Rotating machinery; Support vector machine

Indexed keywords

ACCIDENT PREVENTION; ARTIFICIAL INTELLIGENCE; CLASSIFIERS; DEEP LEARNING; FAILURE ANALYSIS; MACHINERY; NEAREST NEIGHBOR SEARCH; NEURAL NETWORKS; ROTATING MACHINERY; SUPPORT VECTOR MACHINES;

EFFECTIVE SOLUTION; FAULT DIAGNOSIS OF ROTATING MACHINERIES; INDUSTRIAL SYSTEMS; K-NEAREST NEIGHBOURS; MACHINERY FAULT DIAGNOSIS; NAIVE BAYES; REAL OPERATING CONDITIONS; RELIABILITY AND SAFETIES;

FAULT DETECTION;

EID: 85042943940     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2018.02.016     Document Type: Review

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