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박흥식,전태옥,이충엽,서영백 동아대학교 공과대학부설 생산기술연구소 1997 生産技術硏究所硏究論文集 Vol.2 No.1
This paper was undertaken to analyze the morphology of wear debris generating from moving lubricated machine surfaces by image processing. The lubticating wear test was carried out under different experimental conditions using the wear test device was made in our laboritory and wear testing specimen of the pin on disk type wear rubbed in paraffine series base oil, by varying applied load, sliding distance. The four parameters(50% volumetric diameter, aspect, roundness and reflectivity) to describe the morphology have been developed and are outlined in the paper. A system using such techniques promises to obveate the need for subjective, human interpretation of particle morphology in machine condition monitoring, thus overcoming many of the difficulties with current methods and faciltating wider use of wear particle analysis in maching condition monitoring.
박흥식,서영백,이충엽,조연상 한국공작기계학회 1998 한국생산제조학회지 Vol.7 No.5
The morphologies of the wear particles are directly indicative of wear processes occuring in machinery and their severity. The neural network was applied to identify wear debris generated from the machine driving system. The four parameters (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 ranges of these shape parameters learned. The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by artificial neural network. We dicussed how the network determines difference in wear debris feature, and this approach can be applied to foreseeability and decision fro moving condition of the Machine driving system.