한국정밀공학회지 (Journal of the Korean Society for Precision Engineering)
- 제14권12호
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- Pages.48-55
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- 1997
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- 1225-9071(pISSN)
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- 2287-8769(eISSN)
신경망과 절삭력신호 특성을 이용한 공구이상상태 감지에 관한 연구
A Study on Damage Detection of Cutting Tool Using Neural Network and Cutting Force Signal
초록
A useful method to detect tool breakage suing neural network of cutting force signal is porposed and implemented in a basic cutting process. Cutting signal is gathered by tool dynamometer and normalized as a preprocessing. The cutting force signal level is continually monitored and compared with the predefined level. The neural network has been trained normalized sample data of the normal operation and cata-strophic tool failure using backpropagation learning process. The develop[ed system is verified to be very effective in real-time usage with minor modification in conventional cutting processes.