• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.3
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• pp.48-53
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• 1985

A real time digital subtraction angiographic system (RTDSA) was developed and utilized for diagnosis of the diseases related with the blood vessel conditions in 200 patients. In this paper, we present the system configurations and the real time processed images of the patients'abdominal, renal, femoral, and hepatic arteries.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8B
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• pp.701-706
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• 2006

System-level diagnosis plays an important technique for fault detection in multi-processor systems. Efficient diagnosis is very important for real time systems as well as multiprocessor systems. Feng(1) proposed two adaptive diagnosis algorithms HADA and IHADA for hypercube system. The diagnosis cost, measured by diagnosis time and the number of test links, depends on the number and location of the faults. In this paper, we propose an adaptive diagnosis algorithm using the syndrome analysis. This removes unnecessary overhead generated in HADA and IHADA algorithm sand give a better performance compared to Feng's Method.

• Nuclear Engineering and Technology
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• v.27 no.5
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• pp.670-686
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• 1995

This paper provides an improvement on our previous study ［1］ for multi-fault diagnosis in real time in large-scale systems. In the method, fault propagation probability(FPP) and fault propagation time(FPT) in a fuzzy sense are additively used to describe the fault propagation model(FPM) in more practical manner. A modified fault diagnosis procedure is also given. This method is applied for diagnosis of the primary system in the Kori nuclear power plant unit 2 under a transient condition in case of unit value of FPP on each branch of the FPM.

• Design & Manufacturing
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• v.16 no.4
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• pp.52-59
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• 2022

Currently, Korea is an aging society and is expected to become a super-aged society in about four years. X-ray devices are widely used for early diagnosis in hospitals, and many X-ray technologies are being developed. The development of X-ray device technology is important, but it is also important to increase the reliability of the device through accurate data management. Sensor nodes such as temperature, voltage, and current of the diagnosis device may malfunction or transmit inaccurate data due to various causes such as failure or power outage. Therefore, in this study, the temperature, tube voltage, and tube current data related to each sensor and detection circuit of the diagnostic X-ray imaging device were measured and analyzed. Based on QC data, device failure prediction and diagnosis algorithms were designed and performed. The fault diagnosis algorithm can configure a simulator capable of setting user parameter values, displaying sensor output graphs, and displaying signs of sensor abnormalities, and can check the detection results when each sensor is operating normally and when the sensor is abnormal. It is judged that efficient device management and diagnosis is possible because it monitors abnormal data values (temperature, voltage, current) in real time and automatically diagnoses failures by feeding back the abnormal values detected at each stage. Although this algorithm cannot predict all failures related to temperature, voltage, and current of diagnostic X-ray imaging devices, it can detect temperature rise, bouncing values, device physical limits, input/output values, and radiation-related anomalies. exposure. If a value exceeding the maximum variation value of each data occurs, it is judged that it will be possible to check and respond in preparation for device failure. If a device's sensor fails, unexpected accidents may occur, increasing costs and risks, and regular maintenance cannot cope with all errors or failures. Therefore, since real-time maintenance through continuous data monitoring is possible, reliability improvement, maintenance cost reduction, and efficient management of equipment are expected to be possible.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1847-1853
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• 2008

This paper presents stochastic methodology based fault detection algorithm for induction motor systems. We measure current of healthy induction motors by means of hall sensor systems and then establish its probability distribution. We propose online probability density estimation which is effective in real-time implementation due to its simplicity and low computational burden. In addition, we accomplish theoretical analysis to demonstrate convergence property of the proposed estimation by using statistical convergence and system stability theory. We apply our fault diagnosis approach to three-phase induction motors and achieve real-time experiment for evaluating its reliability and practicability in industrial fields.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.

• Journal of Power Electronics
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• v.17 no.3
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• pp.725-732
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• 2017

This paper proposed a real-time, low-cost, fast transistor open-circuit fault diagnosis method for voltage-source inverter fed induction motors. A transistor open-circuit changes the symmetry of the inverter topology, leading to different similarities among three phase load currents. In this paper, dynamic time warping is proposed to describe the similarities among load currents. The proposed diagnosis is independent of the system model and needs no extra sensors or electrical circuits. Both simulation and experimental results show the high efficiency of the proposed fault diagnosis method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.10
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• pp.717-727
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• 2022

An algorithm is realized for estimating the component fault and health diagnosis such as a deterioration. Based on the turbofan engine health diagnosis model, from the health parameters which are estimated by a real time tracking filter, the outliers are eliminated efficiently by an effective median filter to minimize an false alarm. The difference between the fault and deterioration trends is identified by the detection measure for abrupt change, thereby the clear diagnosis classifying the fault and the health condition is possible. The effectiveness of the algorithm for fault and health diagnosis is verified from the simulated results of engine component faults and deterioration.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.959-964
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• 1993

We developed fault diagnosis fuzzy expert system for ACS(Advanced Control System). ACS is a DCS(Distributed Control System) with advanced control algorithm fault tolerance capabilities, fault diagnosis functions, and so on. Fuzzy expert system developed for an ACS in this paper gives an operator alarm signal depending on the state of process value and manipulated value, and the cause of alarm in real time. Simple experiment result with several rules for the-fault-diagnosis of drum level loop in Seoul-Power-Plant.

• Tuberculosis and Respiratory Diseases
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• v.78 no.4
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• pp.473-473
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• 2015