절삭조건과 절삭력 파라메타를 이용한 공구상태 진단에 관한 연구(II) -의사결정 -

A Study on the Diagnosis of Cutting Tool States Using Cutting Conditions and Cutting Force Parameters(II) -Decision Making-

In this study, statistical and neural network methods were used to recognize the cutting tool states. This system employed the tool dynamometer and cutting force signals which are processed from the tool dynamometer sensor using linear discriminent function. To learn the necessary input/output mapping for turning operation diagnosis, the weights and thresholds of the neural network were adjusted according to the error back propagation method during off-line training. The cutting conditions, cutting force ratios and statistical values(standard deviation, coefficient of variation) attained from the cutting force signals were used as the inputs to the neural network. Through the suggested neural network a cutting tool states may be successfully diagnosed.