• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.267-272
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• 2004

In this paper a new intelligent diagnostic system for a refrigerator used for a cold-storage of farm produce was propose. It is verified that the developed system is useful for the fault observation and diagnose of a refrigerator by experimental implementation. The basic idea of the proposed system in that the temperature of major pipes at fault status differs from those at normal status. In order to realize the proposed system, the temperature measuring system and diagnostic program were developed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.25-28
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• 2004

This paper describes an intelligent diagnostic system for the refrigerator which is used for the cold-storage of farm produce. The propose method measures the temperature of the compressor, condenser and evaporator in the refrigerator and uses the measured values to diagnose the system. It is shown through the implementation that the developed system is efficient for the fault observation and diagnose of the refrigerator.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.78-83
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• 2014

Recently, a rapid growth of wind power system as a leading renewable energy source has compelled a number of companies to develop intelligent monitoring and diagnostic system. Such systems can detect early mechanical faults, which prevents from costly repairs. Generally, fault diagnostic system for wind turbines is based on vibration and process signal analysis. In this work, different type of mechanical faults such as mass unbalance and shaft misalignment which can always happen in wind turbine system is considered. The proposed intelligent fault diagnostic algorithm utilizes artificial neural network and Wavelet transform. In order to verify the feasibility of the proposed algorithm, mechanical fault generation experimental system manufactured by Gaon corporation is utilized.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.301-308
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• 2009

In the modern life, machines are used for various areas in industries as the advance of science and industrial development has proceeded. In many machines, the rotating machines play an important role in many processes. Therefore, the development of fault diagnosis and monitoring system for rotating machines is required. An ubiquitous sensor network (USN) is a combination of the key computer science and engineering area technology including the wireless network, embedded system hardware and software, communication, real-time system, etc. It collects environmental information to realize a variety of functions. In this work, a data reduction algorithm for USN based remote fault diagnostic system which can be easily applied to previously built factories is proposed. To verify the feasibility of the proposed scheme, some simulations and experiments are executed.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1271-1287
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• 2022

When abnormal operating conditions occur in nuclear power plants, operators must identify the occurrence cause and implement the necessary mitigation measures. Accordingly, the operator must rapidly and accurately analyze the symptom requirements of more than 200 abnormal scenarios from the trends of many variables to perform diagnostic tasks and implement mitigation actions rapidly. However, the probability of human error increases owing to the characteristics of the diagnostic tasks performed by the operator. Researches regarding diagnostic tasks based on Artificial Intelligence (AI) have been conducted recently to reduce the likelihood of human errors; however, reliability issues due to the black box characteristics of AI have been pointed out. Hence, the application of eXplainable Artificial Intelligence (XAI), which can provide AI diagnostic evidence for operators, is considered. In conclusion, the XAI to solve the reliability problem of AI is included in the AI-based diagnostic algorithm. A reliable intelligent diagnostic assistant based on a merged diagnostic algorithm, in the form of an operator support system, is developed, and includes an interface to efficiently inform operators.

• 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.

• Journal of radiological science and technology
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• v.22 no.1
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• pp.49-53
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• 1999

To inquire its usefulness of the clinical application of intelligent replenishment system of automatic X-ray film processor based on film density, we processed the serial 300 sheets of radiographic film of chest [$14{\times}14"$, HR-C type] and bone [elbow & ankle($8{\times}10"$), skull($10{\times}12"$), hand & foot($11{\times}14"$), pelvis($14{\times}17"$), HR-G type, 68, 70, 77, 85 sheets respectively]. We analyzed the characteristic corves, relative speeds, average gradients and base plus fog densities every twenty five sheets. We also evaluated the developer and fixer replenishment volumes every that time. In the chest and bone radiograph two all, the characteristic curves were little change, and the relative speeds, average gradients and base plus fog densities were within the maximum control limits. The average developer replenishment volumes were about 43m1/sheet and 39m1/sheet respectively. It brings decreased results about 29% in comparison with the conventional replenishment system. In our experiences, we conclude that the intelligent replenishment system of automatic X-ray film processor based on film density maintains image quality consistently, decreases also the replenishment volumes. Therefore, this system will be resulted in economic and environmental effects, and solve problems of over and low replenishment volume.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.600-605
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• 2003

PCA(Principle Component Analysis) has emerged as a useful tool for process monitoring and fault diagnosis. The general approach requires the user to identify the root cause by interpreting the residual or principle components. This could be tedious and often impossible for a large process. In this paper, PCA scheme is combined with the FCM-based fault diagnostic algorithm to enhance the diagnostic results. The implementation of the FCM-based fault diagnostic system by using PCA is done and its application is illustrated on the two-tank system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.247-251
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• 1997

FCM(Fuzzy Cognitive Map) is a fuzzy signed directed graph for representing causal reasoning which has fuzziness between causal concepts. Authors have already proposed FCM-based fault diagnostic scheme and verified its usefulness. However, the previously proposed scheme has the problem of lower diagnostic resolution as in the case of other qualitative approaches. In order to improve the diagnostic resolution, a concept of fuzzy number is introduced into the basic FCM-based fault diagnostic algorithm. By incorporation the fuzzy number into fault FCM models, quantitative information such as the transfer gain between the state variables can be effectively utilized for better diagnostic resolution. Furthermore, an enhanced TAM(Temporal Associative Memory) recall procedure and modified and modified pattern matching scheme are also proposed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.420-424
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• 2008

The new MOV(motor-operated valve) diagnostic system MOVIDS(MOV intelligent diagnostic system) was developed. Its remote diagnostic methods with high accuracy have improved the applicability. This enables the diagnostic tests and the evaluations of many MOVs not only at the valves but also in remote places like MCCs(motor control centers). The remote diagnostic ability of the new system reduces the cost and the man power for diagnosing MOVs and eliminates the danger of the toxic or radioactive environments to which workers might be exposed.