Minimum sample size determination of vibration signals in machine learning approach to fault diagnosis using power analysis

Expert Systems with Applications

Volumn 37, Issue 12, 2010, Pages 8650-8658

  Indira, V ^a   Vasanthakumari, R ^b   Sugumaran, V ^c  

^a SRI MANAKULA VINAYAGAR ENGINEERING COLLEGE   (India)

^b Department of Mathematics   (India)

^c SRM INSTITUTE OF SCIENCE AND TECHNOLOGY   (India)

Author keywords

Fault diagnosis; Machine learning; Minimum sample size; Power analysis; Statistical features; Vibration signals

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); COMPUTER AIDED DIAGNOSIS; DATA ACQUISITION; FAILURE ANALYSIS; FEATURE EXTRACTION; LEARNING SYSTEMS; PROBABILITY; VIBRATION ANALYSIS;

BEARING FAULT DIAGNOSIS; FEATURE SELECTION AND CLASSIFICATION; MACHINE LEARNING APPROACHES; POWER ANALYSIS; SAMPLE SIZE DETERMINATION; SAMPLE SIZES; STATISTICAL FEATURES; VIBRATION SIGNAL;

FAULT DETECTION;

EID: 77957849085     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.06.068     Document Type: Article

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