Convolutional Neural Network Based Fault Detection for Rotating Machinery

Journal of Sound and Vibration

Volumn 377, Issue , 2016, Pages 331-345

  Janssens, Olivier ^a   Slavkovikj, Viktor ^a   Vervisch, Bram ^a   Stockman, Kurt ^a   Loccufier, Mia ^a   Verstockt, Steven ^a   Van de Walle, Rik ^a   Van Hoecke, Sofie ^a  

^a GHENT UNIVERSITY   (Belgium)

Author keywords

Condition monitoring; Convolutional neural network; Fault detection; Feature learning; Machine learning; Vibration analysis

Indexed keywords

ARTIFICIAL INTELLIGENCE; CONDITION MONITORING; CONVOLUTION; DECISION TREES; ENGINEERING EDUCATION; FEATURE EXTRACTION; LEARNING ALGORITHMS; LEARNING SYSTEMS; MACHINERY; NEURAL NETWORKS; ROTATING MACHINERY; VIBRATION ANALYSIS;

AUTOMATIC FAULT DETECTION; BEARING FAULT DETECTION; CONVOLUTIONAL NEURAL NETWORK; FAULT DETECTION SYSTEMS; FEATURE LEARNING; FEATURE LEARNING SYSTEM; RANDOM FOREST CLASSIFIER; WELL-ESTABLISHED TECHNIQUES;

FAULT DETECTION;

EID: 84973470244     PISSN: 0022460X     EISSN: 10958568     Source Type: Journal    
DOI: 10.1016/j.jsv.2016.05.027     Document Type: Article

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