• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.437-440
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• 1989

In the paper a failure detection and diagnosis method of a stochastic system is proposed. It is based on the comparison of the moving averages generated from outputs of the real plant and a modeled normal plant. The proposed method allows us to locate the failed sensor and can be efficiently used for the failure detection and diagnosis of a plant with many sensors.

• Proceedings of the KIEE Conference
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• 2005.05b
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• pp.4-6
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• 2005

This paper deals with the technical map of diagnosis for power cable systems. For this purpose, failure status, failure and degradation causes, and newly suggested diagnostic techniques were investigated and analyzed. From the analysis, the technical map of diagnosis for power cable systems was proposed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.474-477
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• 2002

Safety is very important to operate nuclear power plant. To guarantee the safety, nuclear power plant should be run without trouble. This paper presents the application of a failure diagnosis approach based on discrete event system theory to the pressurizer pressure control system for Pressurized Water Reactor. Also, this paper shows a scheme of failure diagnosis by distributed diagnoser.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1055-1058
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• 1988

A systematic way of failure diagnosis in a linear system with decentralized estimators is developed. The generalized likelihood ratio (G.L.R) approach to failure detection and identification is used for designing a diagnosis system in each subsystem based on the innovation analysis. For the simplicity of the theoretical formulation, a design scheme of failure diagnosis is developed for the system decomposed into two subsystems. To demonstrate the effectiveness of our approach, several simulation studies have been carried out on a third-order linear system which is constructed of a second-order damped oscillator and a first-order lag.

• Journal of Yeungnam Medical Science
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• v.1 no.1
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• pp.13-23
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• 1984

Acute renal failure refers to a rapid reduction in renal function that usually occurs in an individual with no known previous renal disease. Development of a complication of acue renal failure in critically ill surgical patients is not unusual, and it causes high morbidity and mortality. Acute renal failure can be divided as Pre-renal (functional), Renal (organic), and Post-renal (obstructive) azotemia according to their etiologies. Early recognition and proper correction of pre-renal conditions are utter most important to prevent an organic damage of kidney. These measures include correction of dehydration, treatment of sepsis, and institution of shock therapy. Prolonged exposure to ischemia or nephrotoxin may lead a kidney to permanent parenchymal damage. A differential diagnosis between functional and organic acute renal failure may not be simple in many clinical settings. Renal functional parameters, such as $FENa^+$ or renal failure index, are may be of help in these situations for the differential diagnosis. Provocative test utilyzing mannitol, loop diuretics and renovascular dilators after restoration of renal circulation will give further benefits for diagnosis or for prevention of functional failure from leading to organic renal failure. Converting enzyme blocker, dopamine, calcium channel blocker, and propranolol are also reported to have some degree of renal protection from bioenergetic renal insults. Once diagnosis of acute tubular necrosis has been made, all measures should be utilized to maintain the patient until renal tubular regeneration occurs. Careful regulation of fluid, electrolyte, and acid-base balance is primary goal. Hyperkalemia over 6.5 mEq/l is a medical emergency and it should be corrected immediately. Various dosing schedules for medicines excreting through kidney have been suggested but none was proved safe and accurate. Therefore blood level of specific medicines better be checked before each dose, especially digoxin and Aminoglycosides. Indication for application of ultrafiltration hemofilter or dialysis may be made by individual base.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.5
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• pp.37-47
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• 2019

Recently, as demand for various paper containers has rapidly grown, it is inevitable that paper cup-forming machines have increased their manufacturing speed. However, the faster manufacturing speed naturally brings more frequent manufacturing failures, which decreases manufacturing efficiency. As such, it is necessary to develop a system that monitors the failures in real time and diagnoses the failure progress in advance. In this research, a paper cup-forming machine diagnosis system was developed. Three major failure targets, paper deviation, temperature failure, and abnormal vibration, which dominantly affect the manufacturing process when they occur, were monitored and diagnosed. To evaluate the developed diagnosis system, extensive experiments were performed with the actual data gathered from the paper cup-forming machine. Furthermore, the desired system validation was obtained. The proposed system is expected to anticipate and prevent serious promising failures in advance and lower the final defect rate considerably.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.71-72
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• 2005

Ship system is very complicated. Machine in ship system are in close connection with each other, so one is affected by others. Thus, person who want to be a marine engineer have to study not only each machine but also their relationship. For this, intelligent diagnosis system for advanced education is necessity. In this paper, AMS and failure diagnosis system is developed by using LabVIEW, G programming language.

• Journal of Drive and Control
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• v.16 no.3
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• pp.33-41
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• 2019

This study presents the development of a lifetime test bench for the strain wave reducer which is a precision gear reducer of the robot to realize fault diagnosis and failure prognostics. To this end, the lifetime test bench was designed to detect the vertical forward/reverse direction rotation load. Through the lifetime test bench, it is possible to apply the same load spectrum from robot working scenarios. We developed a data integration gateway for fault data collection. Through the development of dedicated software for fault diagnosis and failure prognostics, these data from vibration, noise and temperature sensors were collected and analyzed along with the operation of the lifetime evaluation.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.6
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• pp.870-875
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• 2013

After introducing diagnosis equipment power failure prevention activities for distribution system have become more active. To do facility diagnosis and maintenance work more efficiently we need to evaluate reliability for the system and should determine the priority line with appropriate criteria. Thus, to calculate risk factor for the power distribution line that are composed of many component facilities its historical failure events for the last 5 years are collected and analysed. The failure statics show that more than 60% of various failures are related to environment factors randomly and about 20% of the failures are refer to the aging. As a strategic evaluation system reflecting these environmental influence is needed, a system on the basis of the probabilistic approach related statical variables in terms of failure rate and failure probability of electrical components is proposed. The figures for the evaluation are derived from the field failure DB. With adopting Bayesian rule we can calculate easily about conditional probability query. The proposed evaluation system is demonstrated with model system and the calculated indices representing the properties of the model line are discussed.