• 한국CDE학회논문집
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• 제18권4호
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• pp.250-257
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• 2013

This paper introduces a failure analysis procedure that underpins real-time fault prognosis. In the previous study, we developed a systematic eventization procedure which makes it possible to reduce the original data size into a manageable one in the form of event logs and eventually to extract failure patterns efficiently from the reduced data. Failure patterns are then extracted in the form of event sequences by sequence-mining algorithms, (e.g. FP-Tree algorithm). Extracted patterns are stored in a failure pattern library, and eventually, we use the stored failure pattern information to predict potential failures. The two practical case studies (marine diesel engine and SIRIUS-II car engine) provide empirical support for the performance of the proposed failure analysis procedure. This procedure can be easily extended for wide application fields of failure analysis such as vehicle and machine diagnostics. Furthermore, it can be applied to human health monitoring & prognosis, so that human body signals could be efficiently analyzed.

• 한국정밀공학회지
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• 제30권7호
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• pp.679-686
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• 2013

The reduction unit is one of the most important components in railway cars, due to the transmission of torque from the motor to the wheels. Faulty reduction gears in high-speed trains result from excessive wear on the gear or damage to the gear. These types of gear defects have a significant effect on high-speed rail operation and safety; thus, a diagnosis system for the reduction unit is needed. Vibration diagnosis technology is one of the most effective diagnostics. In this paper, the vibration parameters of a reduction unit were evaluated during a driving-gear test and a full-vehicle test, using kurtosis and the crest factor. These tests were performed under normal operating conditions; a specimen tester was used to diagnose problems in defective gears.

• 한국인터넷방송통신학회논문지
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• 제13권4호
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• pp.215-220
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• 2013

최근 심장마비로 사망한 사례가 전 세계적으로 급속도로 늘고 있다. 그러므로 이러한 문제점을 개선하기 위해서, 공항, 학교, 가정에서에도 자동제세동기 설치가 의무화 되었고 AED 설치를 의무화 하고 있는 추세이다. 그러나, AED는 응급상황에서 사용 시 오작동이나 장비의 고장이 생긴 경우 AED가 비치되어 있어도 무용지물이 될 수 있다. 본 논문에서는, 이러한 문제점을 개선하기위해서, AED Simulator를 이용한 퍼지기법 시뮬레이션은 기존의 방법과 비교해서 외부 온도 조건 및 Tilt 조건을 고려 해서, 자가 진단시에 이상 검출 유무를 판단하는 지능형 모의 실험을 개발하였다. 모의실험 결과, 기존의 방법보다 고장 검출 확률이 30 % 정도 개선되는 것을 확인하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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• pp.115-120
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• 1997

System identification is the task of inferring a mathematical description of a dynamic system from a series of measurements of the system. There are several motives for establishing mathematical descriptions of dynamic systems. Typical applications encompass simulation, prediction, fault diagnostics, and control system design. The paper demonstrates that neural networks can be used effective for the identification of nonlinear dynamical systems. The content of this paper concerns dynamic neural network models, where not all inputs to and outputs from the networks are measurable. Only one model type is treated, the well-known Innovation State Space model(Kalman Predictor). The identification is based only on input/output measurements, so in fact a non-linear Extended Kalman Filter problem is solved. Even for linear models this is a non-linear problem without any assurance of convergence, and in spite of this fact an attempt is made to apply the principles from linear models, an extend them to non-linear models. Computer simulation results reveal that the identification scheme suggested are practically feasible.

• Smart Structures and Systems
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• 제4권4호
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• pp.429-438
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• 2008

The aim of this paper is to define the required measurements and processing tools necessary for developing a maintenance approach applied to rotating machines in the presence of multiple faults. The system responses measured were accelerations and transmission errors. Acceleration measurements provide most of the information on bearing conditions, while transmission error measurements provide pertinent information on gear conditions. The measurements were carried out for several operating conditions (loads and speeds). System responses were processed in several analyzing domains (Time, Spectrum, and Cepstrum domains). The approach developed enables the detection and identification of combined faults and it can be applied to other types of rotating machines once the critical elements and their associated faults have been defined.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.61-66
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• 1992

In this paper, a method for implementing software for the control system with dual structure in processor module is proposed and implemented to enhance its reliability. In this implementation the multi-tasking function which is provided by a real-time operating system is applied. The overall softwre is divided into five tasks and is performed in each of the dual processor module, independently. By this, the processor module with dual structure can achieve a control objective and fault diagnostics effectively. An experimental result shows that the backup processor module can be substituted for the primary processor module immediately when it happens to fail, because data relating the failure information are exchanged continuously done via shared memories.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1997년도 추계학술발표회논문집(1)
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• pp.244-250
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• 1997

The mean time to failure (MTTF) expressing the mean value of the system life is a measure of system effectiveness. To estimate the remaining life of component and/or system, the dynamic mean time to failure concept is suggested. It is the time-dependent Property depending on the status of components. The Kalman filter is used to estimate the reliability of components using the on-line information (directly measured sensor output or device-specific diagnostics in the intelligent sensor) in form of the numerical value (state factor). This factor considers the persistency of the fault condition and confidence level in measurement. If there is a complex system with many components, each calculated reliability's or components are combined, which results in the dynamic MTTF or system. The illustrative examples are discussed. The results show that the dynamic MTTF can well express the component and system failure behaviour whether any kinds of failure are occurred or not.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2005년도 전력전자학술대회 논문집
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• pp.643-646
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• 2005

The paper discusses the main problems in induction motor diagnosis by motor current and vibration signals, possible faults and effects produced by these faults in the signal spectrums. Decision Tree is introduced as a tool to diagnose the motor status, this expert system is implemented to detect the incipient defects, supervise and predict them, and plan the maintenance of the motor.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1999년도 춘계학술대회 논문집
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• pp.403-405
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• 1999

Power transformers have a tendency of ultra-high voltage and huge capacity as power demand increases day after day. Therefore, the fault by insulation destruction gives rise to large area of power failure in huge capacity transformers. On-line predictive diagnostics is very important In power transformers because of economic loss and its spreading effect. Hence, this study presents experiments of partial discharge method using ultrasonic sensor in order to confirm the possibility of ultrasonic sensor in power transformers. It carries out the experiments of measuring delay time between ultrasonic sensor and transducer, sensitiities by temperature change of oil and by barriers inside transformers. It is also Included wave analysis by ultrasonic sensor for needle-plate electrode powered on through high-voltage equipments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 C
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• pp.1903-1905
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• 2000

Power transformers have a tendency of ultra-high voltage capacity as power demand increases day after day KEPCO also will have plan to supply transmission power from 345KV to 765KV in the early of 2000. Therefore, the fault by insulation destruction gives rise to large area of power failure in huge capacity transformers. On-line predictive diagnostics is very important in power transformers because of economic loss and its spreading effect. This study presents the algorithm for transformer oil analysis used KEPCO code, IEC code, gas pattern method and Dornenburg & Roger Ratio method. We also describe the MMI display of expert system programmed by Element Expert Tool(Neuron Data Inc.).