Large rotating machinery fault diagnosis and knowledge rules acquiring based on improved RIPPER

2009 2nd International Conference on Intelligent Computing Technology and Automation, ICICTA 2009

Volumn 2, Issue , 2009, Pages 549-552

  Jiang'hong, Sun ^a   Xiao'li, Xu ^a  

^a BEIJING INFORMATION SCIENCE AND TECHNOLOGY UNIVERSITY   (China)

Author keywords

Data mining; Fault monitoring; Improved RIPPER; Large rotating machine; Real time diagnosis)

Indexed keywords

COMMON FAULTS; DATA MINING TECHNOLOGY; ERROR REDUCTION; FAULT MONITORING; FAULT SAMPLE; KNOWLEDGE RULES; LARGE ROTATING MACHINE; LARGE ROTATING MACHINERY; PROPERTY VALUE; REAL-TIME DIAGNOSIS; ROTATING MACHINE; RULE LEARNING ALGORITHMS;

COMPUTER SCIENCE; FAILURE ANALYSIS; LEARNING ALGORITHMS; ROTATING MACHINERY; ROTATION; TECHNOLOGY;

INTELLIGENT COMPUTING;

EID: 71949084818     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICICTA.2009.367     Document Type: Conference Paper

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