한국정밀공학회지 (Journal of the Korean Society for Precision Engineering)

  • 제18권4호
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  • Pages.72-77
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  • 2001
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  • 1225-9071(pISSN)
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  • 2287-8769(eISSN)
한국정밀공학회 (Korean Society for Precision Engineering)
권호 표지

선삭가공 중 신경망을 이용한 채터진동의 감시

Monitoring of Chatter Vibration using Neural Network in Turning Operation

  • Nam, Yong-Seak (Defense Quality Assurance Agency) ;
  • Cho, Jong-Rae (Dept.of Mechanical Engineering, Graduate School of Changwon National University) ;
  • Kim, Chae-Sil (Dept.of Mechanical Engineering, Changwon National University) ;
  • Jung, Youn-Gyo (Dept.of Mechanical Engineering, Changwon National University)
  • 발행 : 2001.04.01
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초록

Monitoring of the chatter vibration is necessarily required to do automatic manufacturing system. Therefore, we constructed a sensing system using tool dynamometer in order to monitor of chatter vibration on cutting process. Furthemore, an application of neural network using behavior of principal cutting force signals Is attempted. With the error back propagation trining process, the neural network memorized and classified the feature of principal cutting force signals. From obtained result, it is shown that the chatter vibration can be monitored effectively by neural network.

키워드

참고문헌

  1. M. Rahman, 'In-Proces Detection of Chatter Threshold,' Trans. ASME, Journal of Engineering for Industry, Vol. 110, pp. 44-50, Feb, 1988
  2. T. Delio, J. Tulsty, S. Smith, 'Use of Audio Signals for Chatter Detection and Control,' Trans. ASME, Journal of Engineering for Industry, Vol. 114, pp. 164-157, May, 1992
  3. T. Blum, I. Suzuki and I. Inasaki, 'Development of a Condition Monitoring System for Cutting Tools Using an Acoustic Emission,' Bull. Japan Soc. of Prec. Eng., Vol. 22, No. 4, pp. 301-308, 1988
  4. J. R. Cho, J. S. Won, and Y. G. Jung, 'A Study on the Behaviors of Acoustic Emission Signals and Cutting Forces by Flank Wear in Turing Process,' J. KSPE, Vol. 16, No. 1, pp. 26-33, 1999
  5. S. Rangwala, D. A. Dornfeld, 'Sensor Integration using Neural Networks for Intelligent Tool Condition Monitoring,' Trans. ASME, Journal of Engineering for Industry, Vol. 112, pp. 219-228, 1990
  6. G. S. Hong, M. Rahman and Q. Zhou, 'Using Neural Network for Tool Condition Monitoring Based on Wavelet Decomposition,' Int. J. Mach. Tools Manufact, Vol. 36, No. 5, pp. 551-566, 1996 https://doi.org/10.1016/0890-6955(95)00067-4
  7. S. C. Lin and C. J. Ting, 'Drill Wear Monitoring Using Neural Networks,' Int. J. Mach. Tools Manufact, Vol. 36, No. 4, pp. 465-475, 1996 https://doi.org/10.1016/0890-6955(95)00059-3
  8. Jacek M. Zurada, 'Introduction to Artificial Neural Systems,' PWS Publishing Company, pp. 186-196, 1992
  9. 곽재섭, 송지복, '신경회로망을 이용한 연삭가공의 트러블 인식(III),' 한국정밀공학회, 제15권, 제2호, pp. 162-169, 1998
  10. 김화영, 안중환, '신경회로망을 이용한 드릴공정에서의 칩 배출 상태 감시,' 한국정밀공학회지, 제16권, 제6호, pp. 133-140, 1999