• Title/Summary/Keyword: Relectivity

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Morphological Anaylsis of Wear Debris for Lubricated Moving Machine Surfaces by Image Processing (화상처리에 의한 기계윤활 운동면의 마멸분 형태해석)

  • 박흥식;전태옥;서영백;김형자
    • Tribology and Lubricants
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    • v.12 no.3
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    • pp.72-78
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    • 1996
  • This paper was undertaken to analyze the morphology of wear debris generated from lubricated moving machine surfaces by image processing. The lubricati, ng wear test was performed under different experimental conditions using the wear test device made in our laboratory and wear test specimen of the pin on disk type wear rubbed in paraffme 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 outlined in the paper. A system using such techniques promises to obviate the need for subjective, human interpretation of particle morphology in machine condition monitoring, thus to overcome many of the difficulties with current methods and to facilitate wider use of wear particle analysis in machine condition monitoring.

Image Analysis of Wear Debris on Operating Condition of Lubricated Machine Surface (윤활운동면의 작동상태에 따른 마멸분 화상해석)

  • 서영백;박흥식;전태옥;진동규;김형자
    • Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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    • 1996.04b
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    • pp.60-67
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    • 1996
  • This paper was undertaken to analyze the morphology of wear debris on operating condition of lubricated machine surfaces. The lubricating wear test was carried out under different experimental conditions using the wear test device was made in our laboritory and wear testing spcimen of the pin on disk type was rubbed in paraffine series base oil, by varying specimen, applied load, sliding distance. The four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) to describe morphology of wear debris have been developed and are outlined in the paper. A system using such techniques promises to obviate the need for subjective, human interpretation of particle morphology for machine condition monitoring.

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