Intelligent tool condition monitoring system for turning operations

Lecture Notes in Computer Science

Volumn 3498, Issue III, 2005, Pages 883-889

  Gao, Hongli ^a   Xu, Mingheng ^a  

^a SOUTHWEST JIAOTONG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

FUZZY SETS; MATHEMATICAL MODELS; RELIABILITY; WEAR OF MATERIALS;

CUTTING CONDITIONS; FUZZY MODELING; NON-LINEAR RELATIONSHIPS; TOOL WEAR;

TURNING;

EID: 24944442041     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11427469_140     Document Type: Conference Paper

References (8)

1. Quan, Y., Zhou, M., Luo, Z.: On-line Robust Identification of Tool-wear via Multi-Sensor Neural Network Fusion. Engineering Application of Artificial Intelligence, 11 (1998) 717-722
2. Dimla Sr, D.E., Lister, P.M.: On-line Metal Cutting Tool Condition Monitoring.: Tool-state Classification Using Multi-layer Perception Neural Networks, International Journal of Machine Tools & Manufacture, 40 (2000) 769-781.
3. Wilkinson, P., Reuben, R.L.: Tool Wear Prediction from Acoustic Emission and Surface Characteristics via an Artificial Neural Network. Mechanical System and Signal Processing, 13 (1999) 955-966
4. Kuo, R.J.: Multi-sensor Integration for On-Line Tool Wear Estimation Through Artificial Neural Networks and Fuzzy Neural Network
5. Bernhard Sick: On-line and Indirect Tool Wear Monitoring in Turning with Artificial Neural Networks: A Review of More than a Decade of Research. Mechanical System and Signal Processing, 16 (2002) 487-546
6. Chung, K.T., Geddam, A.: A Multi-sensor Approach to the Monitoring of End Milling Operations. Journal of Materials Processing Technology, 139 (2003) 15-20
7. Jemielniak, K.: Some Aspects of AE Application in Tool Condition Monitoring. Ultrasonics, 38 (2000) 604-608
8. Brown, M., Harris, C.: Neurofuzzy Adaptive Modelling and Control[M], Prentice Hall International(UK) limited (1994) 296-308