• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2198-2202
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• 2005

In this paper we have presented a condition monitoring method of check valve using neural network. The acoustic emission sensor was used to acquire the condition signals of check valve in direct vessel injection (DVI) test loop. The acquired sensor signal pass through a signal conditioning which are consisted of steps; rejection of background noise, amplification, analogue to digital conversion, extract of feature points. The extracted feature points which represent the condition of check valve was utilized input values of fault diagnosis algorithms using pre-learned neural network. The fault diagnosis algorithm proceeds fault detection, fault isolation and fault identification within limited ranges. The developed algorithm enables timely diagnosis of failure of check valve’s degradation and service aging so that maintenance and replacement could be preformed prior to loss of the safety function. The overall process has been experimented and the results are given to show its effectiveness.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 춘계학술대회
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• pp.355-357
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• 2017

최근 자동화 기술의 발전으로 산업체에는 대규모 자동화 시스템으로 변화되고 있다. 그에 따른 시스템 감시와 파라미터 측정에 사용되는 센서 또한 자동화 시스템에서 중요한 요소로 차지하고 있다. 따라서, 자동화 시스템에서 센서의 고장으로 인한 시스템 오작동으로 고장이 발생한다면 경제적 피해 및 인명피해를 초래할 수 있다. 본 논문에서는 센서의 직접적인 고장진단을 위해 Kung's Algorithm을 이용하여 센서 출력값 모델링과 결정이론을 통한 고장진단방법에 대해 제시한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2612-2616
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• 2003

Method for performance monitoring and diagnosis of a MIMO control system has been studied aiming at application to model predictive control (MPC) for industrial processes. The performance monitoring part is designed on the basis of the traditional SPC/SQC method. To meet the underlying premise of Schwart chart observation that the observed variable should be univariate and independent, the process variables are decorrelated temporally as well as spatially before monitoring. The diagnosis part was designed to identify the root of performance degradation among the controller, process, and disturbance. For this, a method to estimate the model-error and disturbance signal has been devised. The proposed methods were evaluated through numerical examples.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 C
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• pp.1831-1834
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• 1996

Diagnosis of cable insulation degradation has important meaning from a viewpoint of reliability enhancement of CV cable systems. So, we diagnosed 3.3kV & 6.6kV CV distribution cable on live-line which is judged to a most poor installation condition because they have been used in water condition after installation at the Yeochon chemical complex. The paper describes the analysis of the measured data, the problems at diagnosis, and the items which are considered at the development of diagnosis technology and equipment hearafter.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2018년도 추계 학술논문 발표대회
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• pp.191-192
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• 2018

This study presents the standard methods of diagnosis and repair to prevent and maintain the durability degradation caused by leakage cracks in underground structures in Korea. The third part after the announcement of the existing maintenance plan, The environmental characteristics and leakage condition of underground structures, the causes of deterioration of underground concrete structures, and countermeasures and leakage equipment were described.

• Journal of information and communication convergence engineering
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• 제17권2호
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• pp.128-134
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• 2019

Based on the concept of Industry 4.0, various sensors are attached to facilities and equipment to collect data in real time and diagnose faults using analyzing techniques. Diagnostic technology continuously monitors faults or performance degradation of facilities and equipment in operation and diagnoses abnormal symptoms to ensure safety and availability through maintenance before failure occurs. In this paper, we propose a model to analyze the data and diagnose the state or failure using machine learning. The diagnosis model is based on a support vector machine (SVM)-based diagnosis model and a self-learning one-class SVM-based diagnostic model. In the future, it is expected that this model can be applied to facilities used in the entire industry by applying the actual data to the diagnostic model proposed in this paper, conducting the experiment, and verifying it through the model performance evaluation index.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2002년도 춘계학술대회 논문집 유기절연재료 전자세라믹 방전플라즈마 일렉트렛트 및 응용기술
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• pp.148-151
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• 2002

In order to prevent the failures of underground distribution power cables we need to measure insulation condition in the field. Until now we used DC high voltage as a power source for the cable diagnosis but it was not proper method to the XLPE insulation cables because DC high voltage can affect sound insulation and can't diagnose exactly insulation degradation. For these reasons we imported isothermal relaxation current measurement system called by KDA-1 from germany but it's reliability did not proved in our URD cables. DC voltage decay measurement system was developed by domestic company but they don't have field experience. In this paper we tried to prove reliability of these two systems in the field. Through the field diagnosis and Ac breakdown test the two systems showed similar results.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집A
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• pp.914-919
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• 2000

In most case high temperature components in fossil power plant are damaged by fatigue, creep and degradation. Design of power plant components is based on ideal loading such as temperature, pressure and so on. But in many cases unexpected loadings are applied at components. A key ingredient in plant life extension is the preventive diagnosis technology and remaining-life-assessment technology. This paper describes diagnosis technology and life-assessment technology for power plant boiler. It helps in setting up proper inspection schedules, maintenance procedures, and operating procedure.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1998년도 춘계학술대회 논문집
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• pp.297-300
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• 1998

In this paper, we obtained the data, which is required in training the neural network and diagnosing the degradation degree, by introducing the AE detection that is effective method in ordinary degradation diagnosis on activation. Automatic detection system to detect acoustic. As the results of generalization tests by appling neural network to the unknown AE patterns obtained from specimens, firstly as to evaluate an objective performance of neural network, the recognition ratio for no-void specimen is appeared. Also, in the evaluation for the adaptability of neural network with a untrained type of no-void specimen, it is confirmed that the result appears.

• 대한기계학회논문집A
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• 제41권1호
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• pp.57-62
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• 2017

이 논문의 목적은 원자력 발전소의 급수 펌프인 왕복동식 펌프의 연속적인 사용으로 인한 점진적인 성능저하의 정도를 진단하는 방법을 개발하는 것이다. 일반적으로 이러한 점진적인 성능 저하는 너무 서서히 진행되기 때문에 기존의 진단 방법으로는 그 성능 저하의 정도를 판단하기 어렵다. 하지만 정상 상태의 파라미터들을 제공하는 기계가 있다면, 현재의 상태와 비교하여 성능 저하의 정도를 파악하는 것이 가능해 진다. 이 논문은 점진적인 성능 저하를 식별하는데 사용할 수 있는 새로운 방법을 제안한다. 건강한 상태의 펌프의 정보를 제공하는 에뮬레이터를 FPGA 사용하여 개발하는 과정을 보이고, 실제 펌프로부터 수집한 데이터와 비교하여 에뮬레이터가 동작한다는 것을 보인다.