한국윤활학회:학술대회논문집 (Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference)
- 한국윤활학회 1997년도 제25회 춘계학술대회
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- Pages.25-32
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- 1997
마멸분 형태식별을 위한 신경회로망의 적용
Shape Identification of Wear Debris with Neural Network
초록
The neural network was applied to identify wear debris generated from the lubricated machine moving 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 parameter(50% volumetric diameter, aspect, roundness and reflec- tivity) 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 characteristic and recognized the friction condition and materials very well by neural network.
키워드