Effect of SVM kernel functions on classification of vibration signals of a single point cutting tool

Expert Systems with Applications

Volumn 38, Issue 12, 2011, Pages 15202-15207

  Elangovan, M ^a   Sugumaran, V ^b   Ramachandran, K I ^a   Ravikumar, S ^a  

^a AMRITA UNIVERSITY   (India)

^b SRM UNIVERSITY   (India)

Author keywords

Decision Tree; Feature extraction; Statistical features; Support Vector Machine; Tool condition monitoring

Indexed keywords

BAYES NET; CLASSIFICATION EFFICIENCY; KERNEL FUNCTION; SENSOR SYSTEMS; SINGLE POINT; STATISTICAL FEATURES; STRUCTURAL HEALTH; SUPPORT VECTOR; TOOL CONDITION; TOOL CONDITION MONITORING; VIBRATION SIGNAL; WEAR PARAMETERS; WORK PIECES;

CARBIDES; CONDITION MONITORING; CUTTING; CUTTING TOOLS; DATA MINING; DECISION TREES; FEATURE EXTRACTION; METAL WORKING TOOLS; PLANT EXTRACTS; SIGNAL PROCESSING; SUPPORT VECTOR MACHINES;

EQUIPMENT;

EID: 80052030181     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.05.081     Document Type: Article

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