• 한국주조공학회지
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• 제42권6호
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• pp.369-376
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• 2022

다이캐스팅 공정은 다양한 산업군의 인프라 역할을 수행하는 중요한 공정이지만, 높은 불량률로 인하여 관련 기업들의 수익성 및 생산성의 한계가 있는 상황이다. 이를 타개하기 위하여, 본 연구에서는 다이캐스팅 공정의 불량 검출을 위한 산업인공지능 기반 모듈을 구성하였다. 개발된 불량 검출 모듈은 제공되는 데이터의 특징에 따라서 3단계로 동작되는 모델로 구성된다. 1단계 모델은 비지도학습 기반 이상 검출을 진행하며, 레이블이 없는 데이터셋을 대상으로 작동한다. 2단계 모델은 반지도학습 기반으로 이상 검출을 진행하며, 양품 데이터의 레이블만 존재하는 데이터셋을 대상으로 작동하며, 3단계 모델은 소수의 불량 데이터가 제공된 상황의 지도학습 모델을 기반으로 작동한다. 개발된 모델은 실제 다이캐스팅 양품 데이터를 바탕으로 96% 이상의 우수한 양품 검출 성능을 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.426-430
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• 1987

The reliability is the critical issue in many computer applications, particularly in process control system. In this paper we describe how to achieve the reliability improvement in controller system based multiprocessor. The proposed method is accomplished by using the techniques of fault detection, fault isolation, safe action, and fault diagnosis.

• 설비공학논문집
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• 제27권11호
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• pp.587-595
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• 2015

In this study, fault symptoms were simulated and analyzed for a single-effect absorption chiller. The fault patterns of fault detection parameters were tabulated using the fault symptom simulation results. Fault detection and diagnosis by a process history-based method were performed for the in-situ experiment of a single-effect absorption chiller. Simulated fault modes for the in-situ experimental study are the decreases in cooling water and chilled water mass flow rates. Five no-fault reference models for fault detection of a single-effect absorption chiller were developed using fault-free steady-state data. A sensitivity analysis of fault detection using the normalized distance method was carried out with respect to fault progress. When mass flow rates of the cooling and chilled water decrease by more than 19.3% and 17.8%, respectively, the fault can be detected using the normalized distance method, and COP reductions are 6.8% and 4.7%, respectively, compared with normal operation performance. The pattern recognition method for fault diagnosis of a single-effect absorption chiller was found to indicate each failure mode accurately.

• 전기학회논문지
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• 제59권12호
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• pp.2306-2313
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• 2010

This paper describes a model based fault detection algorithm for an Advanced ESC System which consists of Hydraulic Control Unit (HCU) with built-in wheel pressure sensors. Advanced ESC System can be used for various value-added functions such as Stop & Go Function and Regenerative Brake Function. Therefore, HCU must have a reliable fault detection. Due to the huge amount of sensor signals, existing specific sensor based fault detection of HCU cannot guarantee the safety of vehicle. However, proposed algorithm dose not require the sensors. When model based fault detection algorithm detects severe failures of the HCU, it warns the driver in advance to prevent accidents due to the failures. For this purpose, a mathematical model is developed and validated in comparison to actual data. Simulation results and data acquired from an actual system are compared with each other to obtain the information needed for the fault detection process.

• 한국정보처리학회논문지
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• 제7권7호
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• pp.2169-2178
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• 2000

This paper proposes the structure of an agent and rules for fault detection and location on LAN. To find out a reason of critical fault incurred LAN, collision detection rule, error detection rule, broadcast detection rule, system location rule, and Internet application location rule ar shown. Also, the structure of multi-agent system and state transition diagram is portrayed to have connectivity with he set of rules. To verify availability of proposed rules, the process to find a faulty system is shown by monitoring and analyzing the LAN fault occurrences from the proposed set of rules. Such an rule based agent system is helpful to an Internet manager to solve a reason of fault and make ad decision from gathering management information.

• 한국정보전자통신기술학회논문지
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• 제14권1호
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• pp.22-28
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• 2021

화학공정, 기계공정, 발전소와 같은 다변량 공정은 여러 설비들이 복잡하게 연결되어 운영되기 때문에 특정 시스템에 고장이 발생하면 전체 공정에 치명적인 영향을 미칠 수 있다. 또한, 공정 데이터는 불안정한 환경에서 계측되므로, 데이터에 이상치가 포함될 가능성이 크다. 따라서 계측된 데이터의 이상치를 제거하고 시스템의 고장을 사전에 탐지할 수 있는 모니터링 기술이 필수적이다. 본 논문에서는 여러 종류의 공정에서 고장탐지를 수행하기 위해 다이나믹 공정과 다변량 공정 모델에서 생성된 데이터를 이용하였다. 다이나믹 공정은 자기회귀 특성을 가지는 공정을 모델링한 것이고 다변량 공정은 특정 센서의 고장이 발생했을 때 상황을 묘사한 공정이다. 본 논문에서는 두 공정에서 생성된 데이터에 마할라노비스 거리를 이용하여 데이터에 포함된 이상치를 제거한 후, 독립성분분석을 적용하여 고장탐지를 수행하였다. 제안된 방법의 성능 비교를 위해 기존의 단일모델 ICA와 성능을 비교하였다. 실험결과, 제안된 방법이 기존의 ICA 보다 다이나믹 공정의 바이어스 데이터의 경우에 0.84%p, 드리프트 데이터의 경우 6.82%p 성능이 개선되었다. 다변량 공정의 경우 3.78%p 성능이 개선되었으므로, 제안된 방법이 우수한 고장탐지 성능을 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1705-1711
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• 1991

On-line fault detection and diagnosis has an increasing interest in a chemical process industry, especially for a process control and automation. The chemical process needs an intelligent operation-aided workstation which can do such tasks as process monitoring, fault detection, fault diagnosis and action guidance in semiautomatic mode. These tasks can increase the performance of a process operation and give merits in economics, safety and reliability. Aiming these tasks, series of researches have been done in our lab. Main results from these researches are building appropriate knowledge representation models and a diagnosis mechanism for fault detection and diagnosis in a chemical process. The knowledge representation schemes developed in our previous research, the symptom tree model and the fault-consequence digraph, showed the effectiveness and the usefulness in a real-time application, of the process diagnosis, especially in large and complex plants. However in our previous approach, the diagnosis speed is its demerit in spite of its merits of high resolution, mainly due to using two knowledge models complementarily. In our current study, new knowledge representation scheme is developed which integrates the previous two knowledge models, the symptom tree and the fault-consequence digraph, into one. This new model is constructed using a material balance, energy balance, momentum balance and equipment constraints. Controller related constraints are included in this new model, which possesses merits of the two previous models. This new integrated model will be tested and verified by the real-time application in a BTX process or a crude unit process. The reliability and flexibility will be greatly enhanced compared to the previous model in spite of the low diagnosis speed. Nexpert Object for the expert system shell and SUN4 workstation for the hardware platform are used. TCP/IP for a communication protocol and interfacing to a dynamic simulator, SPEEDUP, for a dynamic data generation are being studied.

• Journal of Electrical Engineering and Technology
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• 제7권5호
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• pp.797-806
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• 2012

Fault detection and isolation (FDI) algorithms provide fault monitoring methods in GPS measurement to isolate abnormal signals from the GPS satellites or the acquired signal in receiver. In order to monitor the occurred faults, FDI generates test statistics and decides the case that is beyond a designed threshold as a fault. For such problem of fault detection and isolation, this paper presents and evaluates position domain integrity monitoring methods by formulating various pseudorange prediction methods and investigating the resulting test statistics. In particular, precise measurements like carrier phase and Doppler rate are employed under the assumption of fault free carrier signal. The presented position domain algorithm contains the following process; first a common pseudorange prediction formula is defined with the proposed variations in pseudorange differential update. Next, a threshold computation is proposed with the test statistics distribution considering the elevation angle. Then, by examining the test statistics, fault detection and isolation is done for each satellite channel. To verify the performance, simulations using the presented fault detection methods are done for an ideal and real fault case, respectively.

• 산업공학
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• 제25권2호
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• pp.170-177
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• 2012

Process control is essential to operate the semiconductor process efficiently. This paper consider fault classification of semiconductor based cyclic signal for process control. In general, process signal usually take the different pattern depending on some different cause of fault. If faults can be classified by cause of faults, it could improve the process control through a definite and rapid diagnosis. One of the most important thing is a finding definite diagnosis in fault classification, even-though it is classified several times. This paper proposes the method that one-class classifier classify fault causes as each classes. Hotelling T2 chart, kNNDD(k-Nearest Neighbor Data Description), Distance based Novelty Detection are used to perform the one-class classifier. PCA(Principal Component Analysis) is also used to reduce the data dimension because the length of process signal is too long generally. In experiment, it generates the data based real signal patterns from semiconductor process. The objective of this experiment is to compare between the proposed method and SVM(Support Vector Machine). Most of the experiments' results show that proposed method using Distance based Novelty Detection has a good performance in classification and diagnosis problems.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 D
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• pp.2182-2184
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• 2004

This paper presents a systematic and straightforward fault estimation approach for process fault detection. isolation and accommodation. The approach includes the design of a reduced-order observer and an algebraic-fault estimator. The observer is designed for an unknown input and fault-free system, which is obtained by coordinate transformations of original systems with unknown inputs and faults. The observer information is devoted to- the fault estimation for fault detection and isolation. The fault estimates can be used to form an additional control input to accommodate the fault. The suggested scheme is verified through simulation studies performed on the control of a vertical takeoff and landing (VTOL) aircraft in the vertical plane.