Wear Debris Identification of the Lubricated Machine Surface with Neural Network Model

신경회로망 모델을 이용한 기계윤활면의 마멸분 형태식별

  • 박홍식 (동아대학교 기계공학과) ;
  • 서영백 (동아대학교 대학원 기계공학) ;
  • 조연상 (동아대학교 대학원 기계공학과)
  • Published : 1998.03.01

Abstract

The neural network was applied to identify wear debris generated from the lubricated machine surface. The wear test was carried out under different experimental conditions. In order to describe characteristics of debris of various shapes and sizes, the four shape parameter(50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction condition of five values(material 3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristics and recognized the friction condition and materials very well by neural network.