• Title, Summary, Keyword: Machine Condition Diagnosis

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A Study on the Correlation of Condition Monitoring Parameters of Functional Machine Failures. (기계시스템 파손에 따른 상태진단 파라미터의 상관관계 해석에 관한 연구)

  • 장래혁;강기홍;공호성;최동훈
    • Tribology and Lubricants
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    • v.18 no.4
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    • pp.285-290
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    • 2002
  • Integrated condition monitoring is required to monitor effectively the machine conditions since machine failures could not be monitored accurately by any single measurement parameter. Application of various condition monitoring techniques is therefore preferred in many cases in order to diagnosis the machine condition. However it inevitably requires lots of maintenance cost and sometimes it could be proved to over-maintenance unnecessarily. This could happen especially when one measurement parameter closely correlates to another. Therefore correlation analysis of various monitoring parameters has to be performed to improve the reliability of diagnosis. In this work, Pearson correlation coefficient was used to analyze the correlation between condition monitoring parameters of an over-loaded machine system where the vibration, wear and temperature were monitored simultaneously. The result showed that Pearson correlation coefficient could be regarded as a good measure for evaluating the availability of condition monitoring technology.

A Study on the Correlation of Condition Monitoring Parameters of Functional Machine Failures. (기계시스템 파손에 따른 상태진단 파라미터의 상관관계 해석에 관한 연구)

  • 장래혁;강기홍;공호성;최동훈
    • Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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    • pp.252-259
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    • 2001
  • Integrated condition monitoring is required to monitor effectively the machine conditions since machine failures could not be monitored accurately by any single measurement parameter. Application of various condition monitoring techniques is therefore preferred in many cases in order to diagnosis the machine condition. However it inevitably requires lots of maintenance cost and sometimes it could be proved to over-maintenance unnecessarily. This could happen especially when one measurement parameter closely correlates to another. Therefore correlation analysis of various monitoring parameters has to be performed to improve the reliability of diagnosis. In this work, Pearson correlation coefficient was used to analyze the correlation between condition monitoring parameters of an over-loaded machine system where the vibration, wear and temperature were monitored simultaneously. The result showed that Pearson correlation coefficient could be regarded as a good measure for evaluating the availability of condition monitoring technology.

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Adaptive Maintenance Using Machine Condition Diagnosis Technique (설비진단기술를 활용한 적응보전)

  • 송원섭;강인선
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.17 no.30
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    • pp.73-79
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    • 1994
  • This paper propose Adaptive Maintenance as a new type of maintenance for machine failures which are unpredictable. A purpose of adpative maintenance is to decrease inconsistency. In order to pick up some of problems the traditional maintenance policy, We discussed Time Based Maintenance(TBM) and Condition Based Maintenance(CBM) with Bath-Tub Curve. By using Machine Condition Diagnosis Technique (CDT), Monitored condition maintenance deals with the dynamic decision making for diagnosis procedures at maintenance and caution level. Adaptive Maintenance is a powerful tool for Total Production Maintenance(TPM).

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Analysis of Wear Debris for Machine Condition Diagnosis of the Lubricated Moving Surface (기계윤활 운동면의 작동상태 진단을 위한 마멸분 해석)

  • Seo, Yeong-Baek;Park, Heung-Sik;Jeon, Tae-Ok
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.21 no.5
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    • pp.835-841
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    • 1997
  • Microscopic examination of the morphology of wear debris is an accepted method for machine condition and fault diagnosis. However wear particle analysis has not been widely accepted in industry because it is dependent on expert interpretation of particle morphology and subjective assessment criteria. This paper was undertaken to analyze the morphology of wear debris for machine condition diagnosis of the lubricated moving surfaces by image processing and analysis. The lubricating wear test was performed under different sliding conditions using a wear test device made in our laboratory and wear testing specimen of the pin-on-disk-type was rubbed in paraffine series base oil. In order to describe characteristics of debris of various shape and size, four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) 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 in current methods and to facilitate wider use of wear particle analysis in machine condition monitoring.

New Machine Condition Diagnosis Method Not Requiring Fault Data Using Continuous Hidden Markov Model (결함 데이터를 필요로 하지 않는 연속 은닉 마르코프 모델을 이용한 새로운 기계상태 진단 기법)

  • Lee, Jong-Min;Hwang, Yo-Ha
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.21 no.2
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    • pp.146-153
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    • 2011
  • Model based machine condition diagnosis methods are generally using a normal and many failure models which need sufficient data to train the models. However, data, especially for failure modes of interest, is very hard to get in real applications. So their industrial applications are either severely limited or impossible when the failure models cannot be trained. In this paper, continuous hidden Markov model(CHMM) with only a normal model has been suggested as a very promising machine condition diagnosis method which can be easily used for industrial applications. Generally hidden Markov model also uses many pattern models to recognize specific patterns and the recognition results of CHMM show the likelihood trend of models. By observing this likelihood trend of a normal model, it is possible to detect failures. This method has been successively applied to arc weld defect diagnosis. The result shows CHMM's big potential as a machine condition monitoring method.

Applicaion of Neural Network for Machine Condition Monitoring and Fault Diagnosis (기계구동계의 손상상태 모니터링을 위한 신경회로망의 적용)

  • 박흥식;서영백;조연상
    • Tribology and Lubricants
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    • v.14 no.3
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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.

Implementation of an Integrated Machine Condition Monitoring Algorithm Based on an Expert System (전문가시스템을 기반으로 한 통합기계상태진단 알고리즘의 구현(I))

  • 장래혁;윤의성;공호성;최동훈
    • Tribology and Lubricants
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    • v.18 no.2
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    • pp.117-126
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    • 2002
  • Abstract - An integrated condition monitoring algorithm based on an expert system was implemented in this work in order to monitor effectively the machine conditions. The knowledge base was consisted of numeric data which meant the posterior probability of each measurement parameter for the representative machine failures. Also the inference engine was constructed as a series of statistical process, where the probable machine fault was inferred by a mapping technology of pattern recognition. The proposed algorithm was, through the user interface, applied for an air compressor system where the temperature, vibration and wear properties were measured simultaneously. The result of the case study was found fairly satisfactory in the diagnosis of the machine condition since the predicted result was well correlated to the machine fault occurred.

A Study on Pulse Condition Appeared at Classic with Pulse Condition by Electro Pulse Machine (I) (전자맥진기(電子脈診器)의 맥상(脈狀)과 고전(古典)의 제맥체상(諸脈體狀)에 관한 연구(硏究)(I))

  • Kim, Seog-Ha;Hong, Sub-Hee;Jung, Hyun-Jung;Park, Won-Hwan
    • The Journal of the Korean Medicine Diagnostics
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    • v.13 no.1
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    • pp.36-44
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    • 2009
  • Object : Pulse feeling(脈診) belongs to pulse feeling or palpation(切診) of methods of diagnosis in oriental medical terminology. Pulse appears at bio-energy condition of body, so it is a important part of disease diagnosis but we have been trouble in diagnosis by difficulty of pulse feeling(脈診). Methods : We investigate the books about pulse feeling, which are involved "Hwangjenaegyong", "Nangyong", "Maggyeng" etc. Conclusion : According to these, this paper helps you understand pulse feeling(脈診) through comparision and studying pulse condition at clasics with electro pulse machine.

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Remote Fault Diagnosis and Maintenance System for NC Machine Tools (공작기계용 원격 고장진단 및 보수 시스템)

  • 신동수;현웅근;정성종
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.1
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    • pp.19-25
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    • 1998
  • Remote fault diagnosis and maintenance system using general telecommunication network is necessary for an effective fault diagnosis and higher productivity of NC machine tools. In order to monitor machine tool condition and diagnose alarm states due to electrical and mechanical faults, a remote data communication system for monitoring of NC machine fault diagnosis and status is developed. The developed system consists of (1) remote communication module among NC's and host PC using PSTN. (2) 8 channels analog data sensing module, (3) digital I/O module for control or NC machine, (4) communication module between NC machine and remote data communication system via RS-232C, and (5) software man-machine interface. Diagnostic monitoring results generated through a successive type inference engine are displayed in user-friendly graphics. The validity and reliability of the developed system is verified to be a powerful commercial version on a vertical machining center through a series of experiments.

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Development of Condition Monitoring and Diagnosis System for Rotating Machinery (회전기계의 상태감시 및 진단 시스템 개발)

  • 함종석;이종원;박성호;양보석;황원우;최연선;전오성
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • pp.950-955
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    • 2003
  • This paper introduces an enhanced condition monitoring and diagnosis system recently developed for rotating machinery. In the system, the data aquisition/monitoring signal processing, machine condition classifier, case-based reasoning and demonstration modules are effectively integrated with user-friendliness so that machine operators can easily monitor and diagnose the status of rotating machinery in operation. Some of the new features include the directional spectrum, case-based reasoning and neural network techniques. And the demonstrator modules for fault diagnosis of a Bear driving system and for basic understanding of the rotor dynamics are provided to help the potential users better understand the system.

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