• 전자공학회논문지 IE
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• 제45권4호
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• pp.33-41
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• 2008

텔레매틱스 시스템의 기능 중 현실적으로 상품성 있는 기능으로 "차량 원격 진단 기능", "운전 패턴 분석 기능"이 있으며 이를 구현하기 위한 기술로는 차량 신호 인터페이스 기술, 자가 진단 인터페이스 기술, 가속도/자이로 센서 인터페이스 기술, PS 신호 처리 기술, 운전 패턴 분석 기술, 무선통신(CDMA) 처리 기술 등이 사용된다. 이러한 기술을 기반으로 본 논문에서는 차량 주행 중에 자각의 EMS(Engine Management System), TMS(Transmission Management System), ABS/TCS, A/BAG 능에서 진단된 차량의 이상 유무를 실시간으로 분석하고, 운전자 주행 패턴 및 차량 관리에 대한 사항을 점검하여 무선통신(CDMA)을 통해 정보센터로 전송하여 이를 DB화함으로써 효율적 차량 관리 및 운전자 관리가 가능하다. 본 연구는 이러한 차량 원격진단 및 운전 패턴 분석기능을 구현하는 H/W와 S/W를 설계 및 제작하고 실차 시험을 통해 이를 검증한다.

• Current Optics and Photonics
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• 제8권5호
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• pp.456-462
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• 2024

We propose a novel fade-free optical fiber interferometric vibration sensor using a simple setup with a 90° optical hybrid. The interferometer consists of all-optical components without the phase modulators and complex demodulation processes that were previously used to compensate for signal fading induced by phase bias change. Fade-free output was successfully obtained by in-phase and quadrature detection with a π/2 phase shifting scheme. Theoretical analysis and measurement results showed that the proposed interferometric vibration sensor operates independently of the phase bias state of interfering waves.

• 대한가정학회지
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• 제42권3호
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• pp.179-193
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• 2004

The purpose of this study was to develop the Family System Diagnosis Scale and to examine its reliability and validity. The subscales of the questionnaire included scores on seven constructs. In order to define constructs accurately, a careful review of Minuchin's writings, the writings of other family therapists, and relevant articles on family interaction was undertaken. A pool of 150 items was given to eight family counselors along with a description of Minuchin' s concepts. The counselors were asked to choose the category each statement fit and to rate the degree of fit using the 3-point scale. Using exploratory factor analysis, confirmatory factor analysis and Linear Structural Relationship(LISREL), six subdimensions of individuation and 55 items of FSDS were identified; enmeshmen disengagement(16 items), parent coalition generational coalition(6 items), flexibility rigidity(5 items), spouse conflict resolved unresolved(8 items), mother-child cohesion estrangement(10 items), father-child cohesion estrangement(10 items). 356 adolescents(ages 13∼18), 356 fathers, 356 mothers in Seoul, Busan, Dague, Incheun, Dajeun, Ulsan, and Kwangju were completed the Family System Diagnosis Scale(FSDS). The reliability of the scale was calculated by Cronbach's a Coefficient and the total a = .94 and the calculation for each factor was .87, .60, .77, .80 and .79 respectively.

• 한국산학기술학회논문지
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• 제13권11호
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• pp.5442-5446
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• 2012

본 논문에서는 만성질환자 및 의료취약계층을 대상으로 지속적이고 체계적으로 건강상태를 체크하고 가장 최적의 환경을 지원하여 삶의 질을 향상시킬 수 있는 u-헬스케어용 원격진료서비스 시스템에 대한 것이다. u-헬스케어용 원격진료서비스 시스템은 무선을 통해 흉부에서 들리는 생체음을 측정하는데 이때 시스템에 사용하는 무선주파수에 대해 전자파의 적합성을 확인하고 의사와 환자에게 발생되는 전자파의 해에 대한 실험을 통해 u-헬스케어용 원격진료서비스 시스템이 진단시 의사와 환자 인체에 무해하다는 진단 환경을 제시한다.

• Nuclear Engineering and Technology
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• 제50권8호
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• pp.1306-1313
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• 2018

The randomness and incipient nature of certain faults in reactor systems warrant a robust and dynamic detection mechanism. Existing models and methods for fault diagnosis using different mathematical/statistical inferences lack incipient and novel faults detection capability. To this end, we propose a fault diagnosis method that utilizes the flexibility of data-driven Support Vector Machine (SVM) for component-level fault diagnosis. The technique integrates separately-built, separately-trained, specialized SVM modules capable of component-level fault diagnosis into a coherent intelligent system, with each SVM module monitoring sub-units of the reactor coolant system. To evaluate the model, marginal faults selected from the failure mode and effect analysis (FMEA) are simulated in the steam generator and pressure boundary of the Chinese CNP300 PWR (Qinshan I NPP) reactor coolant system, using a best-estimate thermal-hydraulic code, RELAP5/SCDAP Mod4.0. Multiclass SVM model is trained with component level parameters that represent the steady state and selected faults in the components. For optimization purposes, we considered and compared the performances of different multiclass models in MATLAB, using different coding matrices, as well as different kernel functions on the representative data derived from the simulation of Qinshan I NPP. An optimum predictive model - the Error Correcting Output Code (ECOC) with TenaryComplete coding matrix - was obtained from experiments, and utilized to diagnose the incipient faults. Some of the important diagnostic results and heuristic model evaluation methods are presented in this paper.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2001년도 춘계학술대회 논문집 센서 박막재료
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• pp.66-70
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• 2001

The partial discharge testing is widely used in diagnostic measuring technology because it gives low stress to power equipment which is undertaken tests. Therefore it is very useful method compare to previous destructive methods and effective diagnosis method in power system that requires on-line/on-site diagnosis. But partial discharges have very complex characteristics of discharge pattern, so it is required continuous research to development of precise analysis method. In recent, the study of partial discharge is carrying out discover of initial defect of power equipment through condition diagnosis and system development of degradation diagnosis using HFPD(High Frequency Partial Discharge) detection. In this study, simulated system is manufactured and HFPD occurred from those simulator is measured with broad-band antenna in real time, the degradation grade of system is analyzed through produced patterns in simulated target according to the AI/statistics processing.

• 산업경영시스템학회지
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• 제18권36호
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• pp.61-69
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• 1995

The diagnosis has an very important role in curing dementia. But there was not the effective method to diagnose it until now. In this paper we analyzed the EEG in Alzheimer's disease and normal control groups to differentiated them by nonlinear parameter such as the correlation dimension. And we propose the nonlinear analysis of EEG in Alzheimer's disease as a useful tool of early diagnosis of it.

• 한국정밀공학회지
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• 제11권5호
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• pp.110-123
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• 1994

The development of automatic production systems have required inteligent diagnostic and monitoring function to repair system failure and reduce production loss by the failure. In order to perform accurate functions of intelligent system, inferencing about total system failure and fault analysis due to each mechanical component failures are required. Also the solution about repair and maintenance can be suggested from these analysis results. As an essential component of mechanical system, a bearing system is investigated to define the failure behavior. The bearing failure is caused by lubricant system failure, metallurgical defficiency, mechanical condition(vibration, overloading, misalignment) and environmental effect. This study described roller bearing fault train due to stress variation and metallurgical defficiency from lubricant failure by using FTA.

• 동의생리병리학회지
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• 제29권3호
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• pp.218-222
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• 2015

Facial diagnosis based on quantitative facial features has been studied in many Korean medicine fields, especially in Sasang constitutional medicine. By the rapid growing of 3D measuring technology, generic and cheap 3D sensors, such as Microsoft Kinect, is popular in many research fields. In this study, the possibility of using Kinect in facial diagnosis is examined. We introduce the development of facial feature extraction system and verify its accuracy and repeatability of measurement. Furthermore, we compare Sasang constitution diagnosis results between DSLR-based system and the developed Kinect-based system. A Sasang constitution diagnosis algorithm applied in the experiment was previously developed by a huge database containing 2D facial images acquired by DSLR cameras. Interrater reliability analysis result shows almost perfect agreement (Kappa = 0.818) between the two systems. This means that Kinect can be utilized to the diagnosis algorithm, even though it was originally derived from 2D facial image data. We conclude that Kinect can be successfully applicable to practical facial diagnosis.

• 드라이브 ㆍ 컨트롤
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• 제18권1호
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• pp.24-30
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• 2021

There is an increasing interest in condition-based maintenance for the prevention of economic loss due to failure. Moreover, immense research is being carried out in related technologies in the field of construction machinery. In particular, data-based failure diagnosis methods that employ AI (machine & deep learning) algorithms are in the spotlight. In this study, we have focused on the failure diagnosis and mode classification of reduction gear of excavator's travel device by using the AI algorithm. In addition, a remote monitoring system has been developed that can monitor the status of the reduction gear by using the developed diagnosis algorithm. The failure diagnosis algorithm was performed in the process of data acquisition of normal and abnormal under various operating conditions, data processing and analysis by the wavelet transformation, and learning. The developed algorithm was verified based on three-evaluation conditions. Finally, we have built a system that can check the status of the reduction gear of travel devices on the web using the Edge platform, which is embedded with the failure diagnosis algorithm and cloud.