• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.4
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• pp.57-63
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• 2003

Aluminum Stranded Conductors Steel Reinforced (ACSR) in overhead transmission lines have slowly degraded due to pollutants in the air for a long period of time, so in the 2000, a number of them has been exceeded over their forecasted useful life. Since most of them are faced with assessment their present conditions in regard to economical maintenance, in this paper, we have suggested a method in order to evaluate the current condition of aged conductors by using dominant parameters such as elapsed years, environment index, and conductor configuration. A diagnostic system for predicting the deterioration grades corresponding to the lifetime of aged conductors is described, which is designed as an Adaptive Neuro-fuzzy Inference System (ANFIS) based on knowledge and experiences of experts. Applying this diagnostic system to practical transmission lines in domestic, it is shown that the system can be effectively used as a guide to perform nondestructive diagnosis and economical operation for old ACSR conductors.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1681-1684
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• 2003

We propose the intelligent tutoring system for the mobile english learning. The proposed system is based on the item response theory to analyze the level of learner. We define the types of item, teaching method and item disposition according to contents modeling. The system estimates the learner level and it gives the learning contents, the evaluation results, and feedback. The system gives those by inference engine which consists of learner's level estimation value, method diagnostic value and disposition diagnostic value.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.689-691
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• 1995

In this paper, a fault detection and isolation unit(FDIU) for a centrifugal pump system driven by DC-motor is proposed. The proposed scheme can be classified into the dedicated observer scheme(DOS). A fuzzy logic based inference engine is adopted for the isolation of each faults. Having the fuzzy inference engine, the proposed FDIU resolve a few important problems of the conventional DOSs with conventional two valued logic. The ouputs of the proposed FDIU are not "ith fault occurred" but the grade of memberships that indicate the consistency of observered symptoms(residuals) with each fault symptoms stored in the rule base. The ouputs can easily be transferred to the ranking of the fault possibilities and it will provide very useful informations in monitoring the process. The simulation results show that the FDIU has very good diagnostic ability even in the noisy environment.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.62-68
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• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. Authors have already proposed a diagnostic system based on FCM to utilized to identify the true origin of fault by on-line pattern diagnosis. In FCM based fault diagnosis, Temporal Associative Memories (TAM) recall of FCM is utilized to identify the true origin of fault by on-line pattern match where predicted pattern sequences obtained from TAM recall of fault FCM models are compared with actually observed ones. In engineering processes, the propagation delays are induced by the dynamics of processes and may vary with variables involved. However, disregarding such propagation delays in FCM-based fault diagnosis may lead to erroneous diagnostic results. To solve the problem, a concept of FTCM(Fuzzy Time Cognitive Map) is introduced into FCM-based fault diagnosis in this work. Expecially, translation method of FTCM makes it possible to diagnose the fault for some discrete time. Simulation studies through two-tank system is carried out to verify the effectiveness of the proposed diagnostic scheme.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.849-855
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• 2008

The Diagnostic Unit of CLINAID can infer working diagnoses for general diseases from the information provided by a user. This user-provided information in the form of signs and symptoms, however, is usually not sufficient to make a final decision on a working diagnosis. In order for the Diagnostic Unit to reach a diagnostic conclusion, it needs to select suitable clinical investigations for the patients. Because different investigations can be selected for the same patient, we need a process that can optimize the selection procedure employed by the Diagnostic Unit. This process, called a selection algorithm, must work with the fuzzy relational method because CLINAID uses fuzzy relational structures extensively for its knowledge bases and inference mechanism. In this paper we present steps of the selection algorithm along with simulation results on this algorithm using fuzzy relational products, both harsh product and mean product. The computation results of applying several different fuzzy implication operators are compared and analyzed.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.2
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• pp.55-62
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• 2004

In this paper, the diagnostic expert system for silicone oil-filled transformer is developed using dissolved gas analysis(DGA). There are many diagnostic methods for diagnostic oil-immersed transformer. But DGA is used to the proposed expert system since it has been verified that DGA is very efficient diagnostic method for transformer. In addition, it is resonable that fuzzy rule, degree of inclusion and fuzzy measure must be considered to handle the uncertainty nature of gas boundary and rules. The proposed expert system consists of knowledge base module, inference engine module and human-machine interface(HMI) module. The knowledge base module consists of the knowledge using the rule. The inference engine module is used to the fuzzy rule. The history of the transformer gas data is managed by the database. the effect of the proposed expert system is verified by case studies.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.11
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• pp.515-524
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• 2017

In this paper, we design and implement an expert system for diagnosing ADHD. As a result of the analysis with DSM-IV-TR, the ADHD diagnostic criteria are changed according to the age group. With this analyzed diagnostic, objects and their values are set and rules are created. We design a diagnostic system consisting of 'ADHD diagnostic system engine' and 'user query response program'. The ADHD diagnostic system engine is a rule-based reasoning engine that is implemented in the Prolog language and receives INPUT from the user query response program. By INPUT, the rule is executed based on the ADHD diagnostic criteria and the OUTPUT is sent back to the 'user query response program' by inferring the diagnostic result. The 'user query response program' is implemented in the Python language and serves as an interface for handling conversation with the user. The bridge between 'ADHD diagnostic system engine' and 'user query response program' is performed through the Pyswip library. As a result, the ADHD Diagnostic Expert System will help you plan your treatment with reduced diagnostic costs and use-complexity.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.2
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• pp.34-42
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• 2009

Gas turbine performance diagnostics is a method for detecting, isolating and quantifying faults in gas turbine gas path components. On-line precise fault diagnosis can promote greatly reliability and availability of gas turbine in real time operation. This work proposes a GUI-type on-line diagnostic program using SIMULINK and Fuzzy-Neuro algorithms for a helicopter turboshaft engine. During development of the diagnostic program, a look-up table type base performance module are used for reducing computer calculating time and a signal generation module for simulating real time performance data. This program is composed of the on-line condition monitoring program to monitor on-line measuring performance condition, the fuzzy inference system to isolate the faults from measuring data and the neural network to quantify the isolated faults. Evaluation of the proposed on-line diagnostic program is performed through application to the helicopter engine health monitoring.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.3
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• pp.35-43
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• 2001

This thesis proposes a diagnostic formula for student's responses based on linguistic variable concept of fuzzy that makes domain expert to input the kernel elementeasily that constructs domain independent student module. And the domain expert can construct the rule with linguistic variable that is used to inference student's recognition state. This study designs a student module that can inference student's recognition state using this rule represented by linguistic variable.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.677-682
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• 1997

Vibration diagnosis of steam turbine generator is essential for safe operation. For a fast few decades, several data base systems for diagnosis of steam turbine generators have been developed and proved useful. However, there still remains a problem in using data base systems such that they require an expert engineer who has a deep insight or knowledg into the system. Moreover,such data base systems can not give any information if the input is not completely fit with data base. This paper presents an effective method for vibration diagnosis of steam turbine generators using fuzzy inference. The proposed method includes also a strategy to overcome the drawback of data base system such that one cannot obtain any information when the input is insufficient or not exact. A computer program is written to realize the entire procedure for the diagnosis. Three realistic problems are dealt with to show the effectiveness of the proposed method.