Application of backpropagation neural network for spindle vibration-based tool wear monitoring in micro-milling

International Journal of Advanced Manufacturing Technology

Volumn 61, Issue 1-4, 2012, Pages 53-61

  Hsieh, Wan Hao ^a   Lu, Ming Chyuan ^a   Chiou, Shean Juinn ^a  

^a NATIONAL CHUNG HSING UNIVERSITY   (Taiwan)

Author keywords

Microcutting; Monitoring; Neural network; Tool wear; Vibration

Indexed keywords

BACK PROPAGATION NEURAL NETWORKS; CLASS MEAN; CLASSIFICATION RATES; CONDITION MONITORING SYSTEMS; FREQUENCY DOMAINS; MICRO MILLING; MICRO-CUTTING; MICRO-END MILLS; MICRO-TOOL; RESEARCH PLATFORMS; SENSOR INSTALLATION; SIGNAL TRANSFORMATION; SINGLE SENSOR; SPECTRAL FEATURE; SPINDLE HOUSING; SYSTEM MODELS; THREE AXIS ACCELEROMETERS; TIME DOMAIN; TOOL CONDITION; TOOL WEAR; TOOL WEAR MONITORING; VIBRATION; VIBRATION SIGNAL; WORK PIECES;

ACCELEROMETERS; BANDWIDTH; DAMAGE DETECTION; FAST FOURIER TRANSFORMS; FEATURE EXTRACTION; MILLING MACHINES; MONITORING; NEURAL NETWORKS; SENSORS; VIBRATIONS (MECHANICAL); WEAR OF MATERIALS;

CLASSIFICATION (OF INFORMATION);

EID: 84862526248     PISSN: 02683768     EISSN: 14333015     Source Type: Journal    
DOI: 10.1007/s00170-011-3703-x     Document Type: Article

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