• 전기전자학회논문지
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• 제25권3호
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• pp.548-555
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• 2021

본 논문에서는 산업 공정, 설비 및 모터 드라이브에 적용되는 고장 진단 및 고장 허용 제어 기술의 기본 개념, 접근법과 연구 동향에 대해서 개괄적으로 기술하였다. 산업 공정을 위한 고장 진단의 주요 역할은 공정의 결함 상태를 파악할 수 있는 효과적인 지표를 만든 후 고장이나 위험한 사고에 대해 적절한 조치를 취하는 것이다. 산업 공정에 패턴이 있는지 특정 프로세스 변수가 정상적으로 동작하는지 확인하기 위해 많은 고장 검출 및 진단 기법이 개발되었다. 먼저 본 논문에서는 데이터 기반 기법과 모델 기반 기법에 대하여 살펴본다. 두 번째로 산업 공정을 위한 고장 검출 및 진단 기법을 살펴본다. 세 번째로 수동형 및 능동형 고장 허용 제어 기법을 살펴본다. 마지막으로 AC 모터 드라이브에서 발생하는 주요 고장을 열거, 그 특성을 살펴보고 이를 위한 고장 진단 및 고장 허용 제어 기술을 살펴본다.

• 대한기계학회논문집B
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• 제41권11호
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• pp.735-742
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• 2017

본 연구에서는 PEM 연료전지 온도 센서의 고장을 감지 및 판별할 수 있는 모델 기반 센서 고장 감지 방법이 적용된다. 연료전지 차량이 작동하는 과정에서 스택 온도는 연료전지의 내구성에 영향을 미친다. 따라서 고장 진단 알고리즘이 고장 신호를 감지하는 것은 중요하다. 센서 고장 감지의 주요 목적은 연료전지 시스템의 안정적인 작동을 보장하여 고온과 저온으로부터 스택을 보호하는 것이다. 상태 공간에 기반한 패러티 방정식이 스택 온도와 냉각수 입구 온도와 같은 센서 고장을 감지하는데 적용되며, 잔차는 정상적인 온도 신호와 비교된다. 그리고 잔차는 현재의 센서 고장을 감지하는 다양한 고장 시나리오에 의해 평가된다. 결론적으로, 본 연구에서 설계된 고장 알고리즘이 고장 신호를 감지할 수 있다.

• 대한전기학회논문지:전력기술부문A
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• 제49권10호
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• pp.516-523
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• 2000

In this paper, intelligent methods using digital protective relay in power supervisory control system is developed in order to protect power systems by means of timely fault detection and diagnosis during operation for induction motor which has various load environments and capacities in power systems. The spectrum pattern of input currents was used to monitor to state of induction motors, and by clustering the spectrum pattern of input currents, the newly occurrence of spectrums pattern caused by faults were detected. For diagnosis of the fault detected, the fuzzy fault tree was derived, and the fuzzy relation equation representing the relation between an induction motor fault and each fault type, was solved. The solution of the fuzzy relation equation shows the possibility of each fault's occurring. The results obtained are summarized as follows: 1) The test result on the basis of KEMC1120 and IEC60255, show that the operation time error of the digital motor protective relay is improved within ${\pm}5%$. 2) Using clustering algorithm by unsupervisory learning, an on-line fault detection method, not affected by the characteristics of loads and rates, was implemented, and the degree of dependency by experts during fault detection was reduced. 3) With the fuzzy fault tree, fault diagnosis process became systematic and expandable to the whole system, and the diagnosis for sub-systems can be made as an object-oriented module.

• 한국소음진동공학회논문집
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• 제16권1호
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• pp.27-33
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• 2006

Fault diagnosis and condition monitoring for rotating machines are important for efficiency and accident prevention. The process of fault diagnosis is to extract the feature of signals and to classify each state. Conventionally, fault diagnosis has been developed by combining signal processing techniques for spectral analysis and pattern recognition, however these methods are not able to diagnose correctly for certain rotating machines and some faulty phenomena. In this paper, we add a minimum detection error algorithm to the previous method to reduce detection error rate. Vibration signals of the induction motor are measured and divided into subband signals. Each subband signal is processed to obtain the RMS, standard deviation and the statistic data for constructing the feature extraction vectors. We make a study of the fault diagnosis system that the feature extraction vectors are applied to K-means clustering algorithm and minimum detection error algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.589-594
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• 1993

This paper presents a fault detection strategy that discriminates the faulty sensor and that detects the component fault using a bank of observers for the system in which sensor fault and component fault can occur simultaneously. Observers as many as the number of measurements are designed, and each observer uses measurements excluding sequentially one measurement, to estimate the state variables. The faulty sensor can be found out by comparing each state variable from different observer. Next, component fault can be detected by using measurements from the sensors excluding the faulty sensor. The suggested strategy is applied to a nonisothermal, series reaction with unknown reaction kinetics in a CSTR. This strategy is found out to perform well even in the case that the sensor and component fault occur simultaneously. Since each observer is designed to be independent of reaction kinetics, this strategy is not affected by the model uncertainty and nonlinearity of the reaction kinetics.

• 제어로봇시스템학회논문지
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• 제8권11호
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• pp.928-934
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• 2002

A natural way to cope with fault tolerant control (FTC) problems is to modify the control parameters according to an online identification of the system parameters when a fault occurs. However. due to not only difficulties Inherent to the online multivariable identification in closed-loop systems, such as modeling errors, noise or the lack of excitation signals, but also long time requirement to identify the post-fault system and implemeutation of control problems during the identification process, we propose an alternative approach based on the observer-based fault detection and isolation (FDI) and model reference adaptive control (MRAC). The proposed robust fault diagnosis method is based on a bank of observers. We also propose a model reference adaptive control with changeable reference models according to the occurred faults. Simulation results of a flight control example show the validity and applicability of the proposed algorithms.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2008년도 하계학술대회 논문집 Vol.9
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• pp.473-474
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• 2008

This paper proposes that the relative transmittance and emission intensity measured via optical emission spectroscopy (OES) is a useful for fault detection of reactive ion etch process. With the increased requests for non-invasive as well as real-time plasma process monitoring for fault detection and classification (FDC), OES is suggested as a useful diagnostic tool that satisfies both of the requirements. Relative optical transmittance and emission intensity of oxygen plasma acquired from various process conditions are directly compared with the process variables, such as RF power, oxygen flow and chamber pressure. The changes of RF power and Pressure are linearly proportional to the emission intensity while the change of gas flow can be detected with the relative transmittance.

• JSTS:Journal of Semiconductor Technology and Science
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• 제11권1호
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• pp.1-5
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• 2011

To enter next process control, numerous approaches, including run-to-run (R2R) process control and fault detection and classification (FDC) have been suggested in semiconductor manufacturing industry as a facilitation of advanced process control. This paper introduces a novel type of optical plasma process monitoring system, called plasma eyes chromatic system (PECSTM) and presents its potential for the purpose of fault detection. Qualitatively comparison of optically acquired signal levels vs. process parameter modifications are successfully demonstrated, and we expect that PECSTM signal can be a useful indication of onset of process change in real-time for advanced process control (APC).

• 한국진공학회:학술대회논문집
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• 한국진공학회 2012년도 제42회 동계 정기 학술대회 초록집
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• pp.241-241
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• 2012

Semiconductor industry has been taking the advantage of improvements in process technology in order to maintain reduced device geometries and stringent performance specifications. This results in semiconductor manufacturing processes became hundreds in sequence, it is continuously expected to be increased. This may in turn reduce the yield. With a large amount of investment at stake, this motivates tighter process control and fault diagnosis. The continuous improvement in semiconductor industry demands advancements in process control and monitoring to the same degree. Any fault in the process must be detected and classified with a high degree of precision, and it is desired to be diagnosed if possible. The detected abnormality in the system is then classified to locate the source of the variation. The performance of a fault detection system is directly reflected in the yield. Therefore a highly capable fault detection system is always desirable. In this research, time series modeling of the data from an etch equipment has been investigated for the ultimate purpose of fault diagnosis. The tool data consisted of number of different parameters each being recorded at fixed time points. As the data had been collected for a number of runs, it was not synchronized due to variable delays and offsets in data acquisition system and networks. The data was then synchronized using a variant of Dynamic Time Warping (DTW) algorithm. The AutoRegressive Integrated Moving Average (ARIMA) model was then applied on the synchronized data. The ARIMA model combines both the Autoregressive model and the Moving Average model to relate the present value of the time series to its past values. As the new values of parameters are received from the equipment, the model uses them and the previous ones to provide predictions of one step ahead for each parameter. The statistical comparison of these predictions with the actual values, gives us the each parameter's probability of fault, at each time point and (once a run gets finished) for each run. This work will be extended by applying a suitable probability generating function and combining the probabilities of different parameters using Dempster-Shafer Theory (DST). DST provides a way to combine evidence that is available from different sources and gives a joint degree of belief in a hypothesis. This will give us a combined belief of fault in the process with a high precision.

• 대한전자공학회논문지
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• 제25권8호
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• pp.906-915
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• 1988

The reliability enhancement is the critical issue in many computer applications, particulary in process control system. In this paper we describe how to achieve the reliability improvement in control system which is based on multiprocessors. The proposed method is accomplished by using the techniques of fault detection which composed by internal and external fault detections, fault isolation for removing the fault propagation, safety action for driving safe input, and fault diagnosis. This approach is experimented and asopted in boiler backup control system constructed by VMEbus system, CPU boards, graphic system, and other interface boards with UNIX operating system.