Automatic diagnosis of defects of rolling element bearings based on computational intelligence techniques

ISDA 2009 - 9th International Conference on Intelligent Systems Design and Applications

Volumn , Issue , 2009, Pages 970-975

  Cococcioni, Marco ^a   Lazzerini, Beatrice ^a   Volpi, Sara Lioba ^a  

^a UNIVERSITY OF PISA   (Italy)

Author keywords

Automatic fault diagnosis; Classifier fusion; Neural networks; Robust classification; Statistical classifiers

Indexed keywords

AUTOMATIC DETECTION; AUTOMATIC DIAGNOSIS; AUTOMATIC FAULT DIAGNOSIS; CLASSIFICATION ACCURACY; CLASSIFICATION PERFORMANCE; CLASSIFICATION TECHNIQUE; CLASSIFIER FUSION; COMPUTATIONAL INTELLIGENCE TECHNIQUES; DEGREE OF ROBUSTNESS; FREQUENCY DOMAINS; HIGH SENSITIVITY; MECHANICAL DEVICE; ROBUST CLASSIFICATION; ROLLING ELEMENT BEARING; STATISTICAL CLASSIFIER; VIBRATION SIGNAL;

BEARINGS (MACHINE PARTS); BEARINGS (STRUCTURAL); CLASSIFIERS; ELECTRIC FAULT CURRENTS; FAILURE ANALYSIS; INTELLIGENT SYSTEMS; SIGNAL TO NOISE RATIO; VIBRATIONS (MECHANICAL);

NEURAL NETWORKS;

EID: 77949512452     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISDA.2009.240     Document Type: Conference Paper

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