• Proceedings of the Korean Geotechical Society Conference
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• 1997.10a
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• pp.141-150
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• 1997

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1189-1192
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• 1996

In this paper, a fault diagnosis method is proposed for self-diagnostics of PLC(Programmable Logic Controller), process controller in industrial fields, and diagnosis of its external devices such as sensors and actuators. The aim of this research is proposition of systematic method of fault diagnosis of PLC control system and development of its equipment. A PLC fault diagnosis algorithm consists of self-diagnostics given by PLC makers, Inpuot/Output tracking method by analyzing sequence PLC programs, searching method of past fault cases in database using an expert system, and diagnosis of PLC units such as CPU, DI, and DO board. Finally usability of PLC fault diagnostic system is verified by testing a MELSEC PLC.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.278-281
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• 2001

Identifying the fault location has to deal with multiple possible candidates. It presents a new technique to diagnosis a fault region. The proposed diagnosis scheme identifies accurately the location based on the protective device operations and load current change at the substation. An Expert system is presented using these facts.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.128-130
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• 1993

In this paper, we introduce 'Expert System(ES)' for Fault Diagnosis(FD) in unmanned-Substation(S/S). In contrast with the co nventional ES, this ES has the following characteristics. First, this ES performs the function that judges the right or false operation of Relays(Ry's) and Circuit Breakers(CB's) in S/S. Then, with this information of the above judgments and the operating times of Ry's and CB's, the candidates of the feasible fault areas are generated. Several examples are presented to show the validity of this system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.6
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• pp.57-69
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• 2001

Expert system is one of AI area. It simulates the human's way of thinking to give solutions of problem in many applications. Most expert system consists of many components such as inference engine, knowledge base, and so on. Especially the performance of expert system depend on the control of efficiency of inference engine. Inference engine has to get features; first, if possible to minimize restrictions when it constructed the knowledge base. second, it has to serve various kinds of inferencing methods. In this paper we propose knowledge scheme for representing domain knowledge in ease, knowledge implementation technique for inferencing, and integrated knowledge-base engine with blackboard and inference engine. And we describe a expert system prototype that implemented in this paper using proposed methods, it perform diagnose about heavy industrial device. The fault diagnosis system prototype has been studied in this paper will be practical foundation in the research area of knowledge based system.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.95-113
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• 1997

This paper outlines a framework for a diagnosis of a complex system with uncertain information. Sensor validation ploys a vital role in the ability of the overall system to correctly determine the state of a system monitored by imperfect sensors. Here, emphases are put on the heuristic technology and post-processor for reasoning. Heuristic Sensor Validation (HSV) exploits deeper knowledge about parameter interaction within the plant to cull sensor faults from the data stream. Finally the modified probability distributions and validated data are used as input to the reasoning scheme which is the runtime version of the influence diagram. The output of the influence diagram is a diagnostic mapping from the symptoms or sensor readings to a determination of likely failure modes. Once likely failure modes are identified, a detailed diagnostic knowledge base suggests corrective actions to improve performance. This framework for a diagnostic expert system with sensor validation and reasoning under uncertainty applies in $HEATXPRT^{TM}$ a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants [1].

• International Journal of Precision Engineering and Manufacturing
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• v.8 no.3
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• pp.54-59
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• 2007

It is widely recognized that increasing the accuracy and diversity of rotating machinery necessitates an appropriate diagnostic technique and maintenance system. Until now, operators have monitored machinery using their senses or by analyzing simple changes to root mean square output values. We developed an expert diagnostic system that uses fuzzy inference to expertly assess the condition of a machine and allow operators to make accurate judgments. This paper describes the hardware and software of the expert diagnostic system. An assessment of the diagnostic performance for five fault phenomena typically found in pumps is also described.

• Journal of Biosystems Engineering
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• v.26 no.2
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• pp.141-146
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• 2001

Lots of the agricultural information come from human experiences and are in non-numerical forms. Therefore, it is difficult to process to be processed in a conventional data processing way. An internet expert system for agricultural application using the ASP(active server page) was developed to solve this problem and consisted of databases, an inference engine, and an user interface. The databases were composed of rule base, question base and link data. The inference engine was developed with the ASP for connection with web between databases. The used interface was developed with the CGI(common gateway interface), so that question could be answered on a web browser, and the session technique was used to provide proper result to each of multi-users. A prototype internet expert system was developed for diagnosis of diseases and nutritional disorders of paddy rice. The expert system was interactively worked through WWW(world wide web) at remote sites by multi-users, even at the same time. The rule base could be easily updated and modified from a web server computer by a knowledge engineer.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.9
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• pp.512-519
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• 2000

A Neural networks has been used for a expert system and fault diagnosis system. It is possible to nonlinear function mapping and parallel processing. Therefore It has been developing for a Diagnosis system of nuclear plower plant. In general Neural Networks is a static mapping but Dynamic Neural Network(DNN) is dynamic mapping.쪼두 a fault occur in system a state of system is changed with transient state. Because of a previous state signal is considered as a information DNN is better suited for diagnosis systems than static neural network. But a DNN has many weights so a real time implementation of diagnosis system is in need of a rapid network architecture. This paper presents a algorithm for RCP monitoring Alarm diagnosis system using Self Dynamic Neural Network(SDNN). SDNN has considerably fewer weights than a general DNN. Since there is no interlink among the hidden layer. The effectiveness of Alarm diagnosis system using the proposed algorithm is demonstrated by applying to RCP monitoring in Nuclear power plant.

• Journal of Environmental Science International
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• v.8 no.5
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• pp.611-616
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• 1999

The diagnostic software for the wastewater treatment plant using activated-sluge process is developed in order to increase the efficiency of management of the wastewater treatment plant. This software is based on the expert system and the visualized user interface, including the diagnosis of quantitative and qualitative data. For the generalization of this software, the initialization of each unit process and updating the files can be possible.