• 전자공학회논문지SC
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• 제40권6호
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• pp.58-67
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• 2003

각종 성인병과 난치성질환인 뇌졸중과 치매, 중풍의 원인으로는 혈액순환장해에 의한 고혈압과 두부혈압의 상승이 주된 요인으로 작용하고 있다. MRI , X-ray 같은 의료장비는 뇌졸중이나 중풍 등의 발병전 예방보다는 발병후의 치료를 위한 목적으로 이용되고 있다. 최근에는 이러한 난치성 질환이 정상인에서도 발생하고 있어서, 상완혈압에 의한 진단보다는 뇌혈류 상태를 반영하는 두부혈압을 진단하는 것이 더 정확한 임상진단을 할 수 있다 그러나 기존 혈압계나 전자혈압계로는 두부혈압을 측정하거나 개선할 수 있는 기능을 수행할 수 없다. 따라서, 본 논문에서는 혈압과 두부혈압을 쉽고 간편하게 측정하고, 상완혈압에 대한 두부 혈압의 상관성을 추출하여 뇌혈류 상태 및 건강상태를 조기 진단/예방할 수 있는 시스템 및 알고리즘을 개발하였다. 임상실험 결과, 기존의 혈압계보다 측정오차가 작고 재현성이 우수하여 신뢰성을 확인하였고 ,두부혈압의 최고압은 상완 최고압의 62%, 최저혈압은 상완 최저혈압의 46%에 해당하는 상관성을 확인하였다. 정상인과 환자간의 상관성에 큰 차이가 있고, 이는 상완혈압 측정에 의존한 진단보다 두부혈압 측정에 의해 더 중요한 진단요소론 추출할 수 있어서 더 정차한 진단을 할 수 있음을 의미한다. 따라서, 뇌혈류에 이상이 있을 때 달라지는 두부혈압을 측정하여 상완혈압과의 상관성을 추출하고, 환자를 대상으로 분석하여 뇌혈류 상태를 진단/개선함으로서 새로운 진단체계를 구축할 수 있는 시스템을 개발하였다.

• 한국수소및신에너지학회논문집
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• 제28권3호
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• pp.252-272
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• 2017

Fuel cell systems have to satisfy acceptable operating reliability, sufficient lifetime and price to enter the market in competition with existing products. Fuel cells are made up of complex element technologies and various problems related to the failure of the components can affect the reliability and safety of the system. This problem can be overcome by introducing a monitoring and supervisory control system in addition to automatic control to detect the failure of the fuel cell quickly and properly diagnose the performance degradation. For the fault detection and diagnosis of polymer electrolyte fuel cells, the model based method using the theoretical superposition value and the non-model based method of checking the signal tendency or the converted signal characteristic can be applied. The methods analyzed in this paper can contribute to the development of integrated monitoring and control technology for the whole system as well as the stack.

• 한국군사과학기술학회지
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• 제24권4호
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• pp.457-466
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• 2021

This paper describes the design of model-based fault diagnosis software to apply to the propulsion system in tracked amphibious assault vehicle which consists of an engine, a transmission, a cooling system, and two waterjets. This software includes specific functions to detect the failures regarding sensor malfunctions, mechanical malfunctions, control errors, and communication errors. This software generates the proper malfunction codes which are classified as the warning and caution. In order to validate the fault diagnosis software, the manual and automatic test are performed using the test program with 32 test cases. Test results show that the designed fault diagnosis software is reliable and effective for applying to the propulsion system.

• 대한전자공학회논문지
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• 제26권8호
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• pp.1217-1226
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• 1989

This paper describes a design of hardware system for real time automatic diagnosis of ECG arrhythmia based on pipeline processor consisting of three microcomputer. ECG data is acquisited by 12 bit A/D converter with hardware QRS triggered detector. Four diagnostic parameters-heart rate, morpholigy, axis, and ST segment-are used for the classification and the diagnosis of arrhythmia. The functions of the main CPU were distributed and processed with three microcomputers. Therefore the effective data process and the real time process using microcomputer can be obtained. The interconnection structure consisting of two common memory unit is designed to decrease the delay time caused by data transfer between processors and be which the delay time can be taken 1% of one clock period.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권1호
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• pp.68-80
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• 2013

Lung cancer is considered to be the leading cause of cancer death worldwide. A technique commonly used consists of analyzing sputum images for detecting lung cancer cells. However, the analysis of sputum is time consuming and requires highly trained personnel to avoid errors. The manual screening of sputum samples has to be improved by using image processing techniques. In this paper we present a Computer Aided Diagnosis (CAD) system for early detection and diagnosis of lung cancer based on the analysis of the sputum color image with the aim to attain a high accuracy rate and to reduce the time consumed to analyze such sputum samples. In order to form general diagnostic rules, we present a framework for segmentation and extraction of sputum cells in sputum images using respectively, a Bayesian classification method followed by region detection and feature extraction techniques to determine the shape of the nuclei inside the sputum cells. The final results will be used for a (CAD) system for early detection of lung cancer. We analyzed the performance of a Bayesian classification with respect to the color space representation and quantification. Our methods were validated via a series of experimentation conducted with a data set of 100 images. Our evaluation criteria were based on sensitivity, specificity and accuracy.

• 한국컴퓨터정보학회논문지
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• 제25권3호
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• pp.89-96
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• 2020

본 논문은 시스템 내부에서 소프트웨어 오류가 발생하였을 경우 컨트롤러 내의 Watchdog Timer를 이용하여 시스템의 상태를 오류 발생시점 이전 상태로 복구하는 시스템을 설계 구현하고, 하드웨어 오류 발생 시 별도의 리셋 회로를 통해 시스템을 재실행할 수 있는 기술을 제안한다. 제안 시스템은 외부 지원 없이 시스템 자체적으로 반영구적으로 작동 할 수 있도록 함으로써, 시스템의 안정적인 작동, 유지비용 절감 및 신뢰성을 제공하며, 고 신뢰성 응용분야에서 요구되는 자가 동작, 진단 및 복구 기능을 통한 시스템의 항상성 유지를 위한 적용이 가능하다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.350-354
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• 1995

The Tension Leveller of Cold Rolling Mill In POSCO performs levelling the strip in high speed line. But minor variations in operating condition of driving machines such as motor, gear box, and support bearings, a small gap-variation of supporter and strip slip by poor roll revolutions can cause serious problems in the quality of strip. In this study, firstly, A condition monitoring standard for each sensor is made through with the detail analysis of vibration and strip slip. Secondly, An automatic monitoring and diagnosing system was developed to monitor the condition of Tension Leveller, and diagnose the cause of abnormal condition. Finally, A diagnosing algorithm for abnormal condition and man-machine interface (MMI) for easy operation are developed.

• 사상체질의학회지
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• 제17권2호
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• pp.46-51
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• 2005

1. Objectives The purpose of this study is to objectify the diagnosis of Sasang Constitution. Using the methods of this study, it will improve to classificate Sasang Constitution. 2. Methods 1) Automatic feature extraction of human frontal faces for Sasang Constitution classification. 2) Color feature extraction of human frontal faces (1)Erosion filtering (skin-white, the other-black) (2) Median median 3. Results and Conclusions Observing a person's shape has been the major method for Sasang Constitution classification, which usually has been dependent upon doctor's intuition as of these days. We are developing an automatic system which provides objective basic data for Sasang Constitution classification. For this, in this paper, firstly, the signal processing techniques are applied to automatic feature extraction of human frontal faces for Sasang Constitution classification. The experiment is conducted to verify the effectiveness of the proposed system.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권9호
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• pp.413-422
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• 2002

In a power plant, disturbance detection and diagnosis are massive and complex problems. Once a disturbance occurs, it can be either persistent, self cleared, cleared by the automatic controllers or propagated into another disturbance until it subsides in a new equilibrium or a stable state. In addition to the Physical complexity of the power plant structure itself, these dynamic behaviors of the disturbances further complicate the fault monitoring and diagnosis tasks. A data structure called a disturbance interrelation analysis graph(DIAG) is proposed in this paper, trying to capture, organize and better utilize the vast and interrelated knowledge required for power plant disturbance detection and diagnosis. The DIAG is a multi-layer directed AND/OR graph composed of 4 layers. Each layer includes vertices that represent components, disturbances, conditions and sensors respectively With the implementation of the DIAG, disturbances and their relationships can be conveniently represented and traced with modularized operations. All the cascaded disturbances following an initial triggering disturbance can be diagnosed in the context of that initial disturbance instead of diagnosing each of them as an individual disturbance. DIAG is applied to a typical cooling water system of a thermal power plant and its effectiveness is also demonstrated.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 C
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• pp.910-912
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• 1998

In this paper, we purpose automatic diagnosis in online, as the fundamental study to diagnose the partial discharge mechanism and to predict the lifetime, by introduction a neural network. In the proposed method, Ire use acoustic emission sensing system and calculate a fixed quantity statistic operator by pulse number and amplitude. Using statically operators such as the center of gravity(G) and the gradient of the discharge distribute(C), we analyzed the early stage and the middle stage. the fixed quantity statistic operators are learned by a neural network. The diagnosis of insulation degradation and a lifetime prediction by the early stage time are achieved. On the basis of revealed excellent diagnosis ability through the neural network learning for the patterns during degradation, it was proved that the neural network is appropriate for degradation diagnosis and lifetime prediction in partial discharge.