• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1999년도 제29회 춘계학술대회
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• pp.101-108
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• 1999

This paper was undertaken to do morphological analysis of wear particles for sliding members hydrauric rotary acuator. The lubricating wear test was performed under different experimental conditions using the wear test device and wear specimens of the pin on disk type was rubbed in paraffinic base oil by three kinds of lubricating materials, varying applied load, sliding distance. The four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) are used for morphological analysis of wear particles. The results showed that the four shape parameters of wear particles depend on a kind of the lubricating materials. It was capable of presuming wear volume for three kinds of materials on driving time.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2000년도 제31회 춘계학술대회
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• pp.62-67
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• 2000

This paper was undertaken to do morphological analysis of wear debris for slipper-Pad of hydraulic rotary acuator. The lubricating wear test was performed under different experimental conditions using the wear test device and wear specimens of the pin on disk type was rubbed in paraffinic base oil by three kinds of lubricating materials, varying applied load, sliding distance. The four shape parameters(50% volumetric diameter, aspect, roundness and reflectivity) are used for morphological analysis of wear debris. The results showed that the four shape parameters of wear debris depend on a kind of the lubricating condition. It was capable of presuming wear volume for slipper-pad of hydraulic rotary acuator on driving time.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 춘계학술대회 논문집
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• pp.87-92
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• 1999

This paper was undertaken to do morphological analysis of wear particles for sliding members hydraulic rotary actuator. The lubricating wear test was performed under different experimental conditions using the wear test device and wear specimens of the pin on disk type was rubbed in paraffinic base oil by three kinds of lubricating materials, varying applied load, sliding distance. The four-shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) are used for morphological analysis of wear particles. The results showed that the four shape parameters of wear particles depend on a kind of the lubricating materials. It was capable of presuming wear volume for three kinds of materials on driving time.

• 한국생산제조학회지
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• 제9권6호
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• pp.127-132
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• 2000

Morphological analysis of wear particles is one of useful methods for machine condition monitoring because it is well reflected in machine driving state. This paper was undertaken to apply to the condition monitoring of hydraulic piston motor. The lubricating wear test was performed under different experimental conditions using the wear test device and wear specimens of the pin on disk type was rubbed in paraffinic base oil by three kinds of lubricating materials, varying applied load, sliding distance. The four shape parameters(50% volumetric diameter, aspect, roundness and reflectivity) are used for morphological analysis of wear particles. The results showed that the four shape parameters of wear particles depend on a kind of the lubricating materials. It was capable of calculating presumed wear volume for three kinds of materials on driving time to foresee as damage condition of lubricating materials.

• 한국공작기계학회논문집
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• 제12권5호
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• pp.53-58
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• 2003

Wear debris can be collected from the lubricants of operating machinery and its morphology is directly related to the fiction condition of the interacting materials from which the wear particles originated in lubricated machinery. But in order to predict and estimate working conditions, it is need to analyze the shape characteristics of wear debris and to identify. Therefore, if the shape characteristics of wear debris is identified by computer image analysis and the neural network, The four parameter (50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction. It is shown that identification results depend on the 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 neural network. We resented how the neural network recognize wear debris on driving condition.

• Tribology and Lubricants
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• 제14권3호
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• pp.74-80
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• 1998

The morphologies of the wear particles are directly indicative of wear process occuring in the machine. The analysis of wear particle morphology can therefore provide very early detection of a fault and can also ofen facilitate a dignosis. For this work, the neural network was applied to identify friction coefficient through four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) of wear debris generated from the machine. The averages of these parameters were used as inputs to the network. It is shown that collect identification of friction coefficient depends on the ranges of these shape parameters learned. The various kinds of the wear debris had a different pattern characteristics and recognized relation between the friction condition and materials very well by neural network. We discuss how the network determines difference in wear debris feature, and this approach can be applied for machine condition monitoring and fault diagnosis.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1998년도 제27회 춘계학술대회
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• pp.83-90
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• 1998

The morphologies of the wear debris are directly indicative of wear processes occuring in machinery and their severity. The neural network was applied to identify friction condition from the lubricated moving system. The four parameter(50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction coefficient. 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. We dicuss between the characteristic of wear debris and the friction coefficient and how the network determines difference in wear debris feature.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1997년도 제26회 추계학술대회
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• pp.135-144
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• 1997

This wear debris can be harvested from the lubricants of operating machinery and its morphology is directly related to the damage to the interacting surfaces from which the particles originated. The morphologies of the wear particles are therefore directly indica- rive of wear processes occuring in machinery and their severity. The neural network was applied to identify wear debris generated from the lubricated moving system. The four 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 characteristic and recognized the friction condition and materials very well by neural network. We dicuss how the network determines difference in wear debris feature, and this approach can be applied to condition diagnosis of the lubricated moving system.

• 한국생산제조학회지
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• 제7권5호
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• pp.92-97
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• 1998

The morpholgies 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 the ranges of these shape parameters learned. The three kinds of the wear debris had a different patter characteristic and recognized the friction condition and materials very well by artificial neural network. We discussed how the network determines differencee in wear debris feature, and this approach can be applied to foreseeability and decisio for moving condition of the Machine driving system.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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• pp.563-567
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• 1996

This paper was undertaken to analyze the morphology of wear debris generating from moving lubricated machine surfaces by image processing. The lubricating wear test was carried out under different experimentaal 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, byvarying 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 obviate the need for subjective, human interpretation of particle morphology in machine condition monitoring, thus overcoming many of the difficulties with current methods and facilitating wider use of wear particle analysis in machine condition monitoring.