Naslov
Tool Wear Estimation using an Analytic Fuzzy Classifier and Support Vector Machines

Autori
Brezak, Danko ; Majetić, Dubravko ; Udiljak, Toma ; Kasać, Josip

Izvornik
Journal of intelligent manufacturing (0956-5515) 23 (2012), 3; 797-809

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
tool wear estimation ; fuzzy logic ; support vector machines ; dynamic feature selection

Sažetak
A new type of continuous hybrid tool wear estimator is proposed in this paper. It is structured in the form of two modules for classification and estimation. The classification module is designed by using an analytic fuzzy logic concept without a rule base. Thereby, it is possible to utilize fuzzy logic decision-making without any constraints in the number of tool wear features in order to enhance the module robustness and accuracy. The final estimated tool wear parameter value is obtained from the estimation module. It is structured by using a support vector machine nonlinear regression algorithm. The proposed estimator implies the usage of a larger number and various types of features, which is in line with the concept of a closer integration between machine tools and different types of sensors for tool condition monitoring.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo

POVEZANOST RADA