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The prediction of fatigue life of muffler by artificial neural network

인공신경망을 이용한 머플러의 피로 수명 예측

  • Park, Soon-Cheol (Research & Development Division, Hyundai Motors) ;
  • Kang, Sung-Su (Division of Mechanical Engineering, Pusan National University) ;
  • Yoon, Jin-Ho (Division of Mechanical Engineering, Pusan National University) ;
  • Kim, Gug-Yong (Division of Mechanical Engineering, Pusan National University)
  • Received : 2013.09.04
  • Accepted : 2013.11.13
  • Published : 2013.11.30

Abstract

In order to estimate the fatigue life of mufflers at the early stage of researches and designs, the new prediction process was developed by the artificial neural network, which has the algorism of weldment properties. Bending fatigue test was carried out for defining the characteristics of muffler weldment fatigue life and damage. For considering and predicting mechanical and fatigue properties of the muffler, the maximum stress of weldment was adapted as the variable of artificial neural network training. Also, it was compared with the fatigue life predicting results using fatigue notch factors, for proving the newly developed process of the artificial neural network.

본 연구에서는 초기 개발 단계에서 신속하면서도 정확한 머플러의 피로 수명을 예측하기 위하여 인공신경망을 통해서 용접부 특성을 고려한 머플러의 피로 수명을 예측하는 프로세스를 개발하였다. 머플러 피로와 파손 특성을 파악하기 위하여 굽힘 피로 시험을 수행하였다. 머플러 용접부 특성을 고려하기 위하여 인공신경망 학습 변수로 용접부 최대 응력을 선정하였으며 이를 이용하여 피로수명을 예측하였다. 인공신경망과 기존 피로 노치 계수를 이용한 피로 수명 예측 결과 비교를 통하여 인공신경망을 이용한 머플러 피로 수명 예측 방법의 타당성을 검증하였다.

Keywords

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