Tool wear monitoring and pattern recognition of tool failure

Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis

Volumn 29, Issue 1, 2009, Pages 5-9

  Kang, Jing ^a   Feng, Changjian ^a   Hu, Hongying ^a  

^a DALIAN NATIONALITIES UNIVERSITY   (China)

Author keywords

Discrete hidden Markov model (DHMM); Pattern recognition; Prediction; Tool wear; Vector quantification

Indexed keywords

CODE-BOOKS; CUTTING FORCES; CUTTING PROCESS; DISCRETE HIDDEN MARKOV MODEL (DHMM); FAILURE PREDICTIONS; INTEGER NUMBERS; MACHINE-LEARNING; MAXIMUM PROBABILITIES; PREDICTION; SELF-ORGANIZING FEATURE MAPS; TOOL FAILURES; TOOL WEAR; TOOL WEAR MONITORING;

CONFORMAL MAPPING; CUTTING TOOLS; FAST FOURIER TRANSFORMS; LEARNING SYSTEMS; OBJECT RECOGNITION;

HIDDEN MARKOV MODELS;

EID: 64249170832     PISSN: 10046801     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (9)

1. Kang Jing, Kang Ni, Feng Changjian, et al. Research on tool failure prediction and wear monitoring based on HMM pattern recognition theory[C]//Proceedings of IEEE-ICWAPR2007, 2007. Beijing: IEEE SMC Society, 2007: 1167-1172.
2. Ertunc H M, Loparo K A, Ozdernir E, et al. Real time monitoring of tool wear using multiple modeling method[C]//Proceedings of IEEE IEMDC. USA, MA, Cambridge: [s. n], 2001: 687-691.
3. Kang Jing, Feng Changjian, Hu Hongying, et al. Prediction of chatter in machining process based on hybrid SOM-DHMM architecture[C]//Proceedings of IEEE-ICAL. China, Jinan: [s.n.], 2007: 1368-1372.