• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2222-2224
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• 2002

Induction motors are critical components of many industrial machines and are frequently integrated in commercial equipment. The heavy economical losses and the deterioration of system reliability might be caused by the failure of induction motors in industrial field. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and diagnosis of system is considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method are used for induction motor fault diagnosis. This method analyzes the motors supply current. since this diagnoses faults of the motor. The diagnostic algorithm is based on the artificial neural network, and the diagnosis system is programmed by using LabVIEW and MATLAB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.5
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• pp.244-250
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• 2014

The Most Serious Engine Faults Are Those That Occur Within The Engine. Traditional Engine Fault Diagnosis Is Highly Dependent On The Engineer'S Technical Skills And Has A High Failure Rate. Neural Networks And Support Vector Machine Were Proposed For Use In A Diagnosis Model. In This Paper, Noisy Sound From Faulty Engines Was Represented By The Mel Frequency Cepstrum Coefficients, Zero Crossing Rate, Mean Square And Fundamental Frequency Features, Are Used In The Hidden Markov Model For Diagnosis. Our Experimental Results Indicate That The Proposed Method Performs The Diagnosis With A High Accuracy Rate Of About 98% For All Eight Fault Types.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2015-2020
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• 2011

Key set the current non-urban rail power failure of equipment to operate the railway will generate a lot of problems. I know in advance the ideal of power equipment to prevent the failure to derive an efficient replacement cycle for the power equipment monitoring and diagnosis of the condition can become necessary to develop a system. In order to determine the status of the power plant during operation and behavior of the partial discharge current state data, regular monitoring and inspection requirements also stamp the basic current, voltage, temperature and humidity should be identified.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.358-361
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• 1996

In this paper, we discuss decentralized optimal fault tolerant supervisory control issues on the basis of failure analysis and diagnosis from the angle of discrete event dynamic system. We address the detectability and the observability problems, and develope fault tolerant supervisory control system upon the failure analysis and diagnosis schemes. A complete min-cut is introduced and the procedure for finding the achievable or nonachievable layered optimal legal sublanguages is suggested for a preferential option among the reachable states in the controlled plant. A layered optimal supervisory control framework is proposed upon these. We extend the concept of decentralized supervisory control by considering the problem of combination of decentralized with centralized control in case pure decentralized control happens to be inadequate. We introduce the concept of locally controllable pair and present a hybrid decentralized supervisory control framework. Finally, we propose the analytical framework for a decentralized optimal fault tolerant supervisory control systems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.594-597
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• 2001

As many industrial systems become more complex, they become extremely difficult to diagnose the cause of failures. The subject of this paper is ECCS(Emergency Core Cooling System) part of PWR(Pressurized Water Reactor). This paper presents modeling and diagnoser construction of ECCS based on discrete event system theory. Also, this paper presents that the ECCS system is diagnosible in our approach.

• Journal of Veterinary Clinics
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• v.19 no.1
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• pp.103-106
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• 2002

Specific diagnosis of orthopedic disease can be diffcult in canine practice. Failure to detect the clinical signs of a disorder during physical examination of dogs with acute or chronic lameness is the most common reason for failure to make specific diagnosis. A 6-month-old, female doberman with history of swelling and non-weight-bearing lameness in the left forelimb was referred to Beterinary Teaching Hospital of Chungbuk National University. Physical examination, plain radiography, and conventional three-phase radionuclide bone scan were performed in the patient. Based on the physical exam and radiography, this case was diagnosed as elbow strain and subluxation. Conventional three-phase bone scan detected soft tissue inflammation and osteochondral lesions of elbow joint, and revealed good agreement with clinical findings. Therefore, conventional three-phase bone scan was able to provide the precise information about inflammation of soft tissue and osteochondral lesions of joint.

• Journal of The Korean Society of Clinical Toxicology
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• v.2 no.2
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• pp.129-132
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• 2004

Ethylene glycol poisoning can cause profound morbidity and is almost universally fatal if untreated. Central nervous system depression, pulmonary edema, and acute oligulic renal failure with crystalluria are among the most commonly encountered complication of ingestion. Ingestion of ethylene glycol may be an important contributor in patients with metabolic acidosis and subsequent renal failure. The diagnosis of ethylene glycol poisoning is based on nonspecific clinical symptoms and signs and indirect and direct laboratory measurement of ethylene glycol. As a result, diagnosis and treatment sometimes can be delayed. We describe 52-year-old man who visited to emergency department with mental change of unknown origin. The patient has high anion gap metabolic acidosis and renal failure due to ingestion of antifreeze that contained ethylene glycol. We used hemodialysis for elimination technique. The patient was discharged with minimal complication.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2004.11a
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• pp.158-161
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• 2004

In recent, the automotive number of korea has risen above 14millions vehicles. The automotive was settled down goods haying to live. In a flood of this automotive the accuracy diagnosis for the vehicle certainly need for people referencing car. To do this diagnosis, the researcher has to experience many example in the field and need to system them. Expecially, the study for failure of the engine nearly research in the korea. When moving parts of engine no problem. In order to work, the engine must operate normality state. In this paper the purpose study the failure for the tribological example of engine.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.97-110
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• 2012

High performance sensors and modern data logging technology with real-time telemetry facilitate system fault diagnosis in a very precise manner. Fault detection, isolation and identification in fault diagnosis systems are typical steps to analyze the root cause of failures. This systematic failure analysis provides not only useful clues to rectify the abnormal behaviors of a system, but also key information to redesign the current system for retrofit. The main barriers to effective failure analysis are: (i) the gathered data (event) logs are too large in general, and further (ii) they usually contain noise and redundant data that make precise analysis difficult. This paper therefore applies suitable pre-processing techniques to data reduction and feature extraction, and then converts the reduced data log into a new format of event sequence information. Finally the event sequence information is decoded to investigate the correlation between specific event patterns and various system faults. The efficiency of the developed pre-filtering procedure is examined with a terminal box data log of a marine diesel engine.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1644-1651
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• 2010

VLF $tan{\delta}$ diagnosis technology is introduced in IEEE Std 400 and proposed as evaluation criterion in an effective way of detecting water tree which mainly causes the failure of XLPE insulated cables. In order to inspect the accuracy of the VLF $tan{\delta}$ method for XLPE insulated power cables in Korean distribution system, diagnosis for 41 cables which were being serviced in the fields has been carried out and they were removed for AC breakdown voltage test after. Regarding the 41 cables, it was hard to confirm any relation between the VLF $tan{\delta}$ values and AC breakdown voltages and also water tree in the insulation was not detected. However, the other cables were failed several days after the diagnosis of the 41 cables. Water trees were found and their VLF $tan{\delta}$ values were also much higher than the criterion of IEEE standard. It has been ascertained that we need to change the IEEE criteria in order to improve the accuracy of detecting water trees by additional analyzing of field examples of failure and case studies from overseas countries and therefore amended VLF $tan{\delta}$ test voltage and evaluation criteria have been proposed.