• 한국지능시스템학회논문지
• /
• 제14권3호
• /
• pp.267-272
• /
• 2004

본 논문에서는 농산물 저온저장시설의 냉동기용 지능형 진단 시스템을 제안한다. 제안하는 방법은 냉동기에 고장이 발생하면 냉동기 주요배관의 온도가 변화하는 성질을 이용하였다. 주요배관의 온도와 고장부위의 관계를 신경회로망을 이용하여 학습함으로써 고장상태를 추론할 수 있다. 제안된 방법을 구현하기 위하여 온도계측시스템 및 진단프로그램을 개발하였다. 개발된 시스템을 현장에 적용 실험하여 제안된 방법의 유용성을 검증하였다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
• /
• pp.25-28
• /
• 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.

• 한국지능시스템학회논문지
• /
• 제24권1호
• /
• pp.78-83
• /
• 2014

최근 신재생 에너지원으로서의 선두주자인 풍력발전은 다수의 풍력발전 회사들로 하여금 모니터링 및 고장진단 시스템의 개발을 가속화시키고 있다. 이러한 모니터링 및 진단시스템은 조기의 고장검출을 통해 고장이 발생되었을 경우 발생되는 고가의 수리비용을 미연에 방지할 수 있게 한다. 일반적으로 풍력발전과 관련된 고장진단 시스템은 진동신호 및 신호분석기법에 기반하고 있다. 이에 본 연구에서는 풍력발전 시스템에서 자주 발생되고 있는 질량 불평형 및 축 정렬 불량 등과 같은 기계적인 고장을 효율적으로 진단할 수 있는 시스템을 제안하고자 한다. 본 연구에서 제안된 지능화된 고장진단 알고리즘은 인공신경망기법과 웨이블렛 변환을 이용한 것으로 (주)가온솔루션에서 개발한 풍력발전용 기계적 고장발생 장치에 적용 실험을 통해 제안된 진단기법의 유용성을 확인하고자 하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제9권4호
• /
• pp.301-308
• /
• 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
• /
• 제54권4호
• /
• pp.1271-1287
• /
• 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.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅲ
• /
• pp.1681-1684
• /
• 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.

• 대한방사선기술학회지:방사선기술과학
• /
• 제22권1호
• /
• pp.49-53
• /
• 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.

• 한국지능시스템학회논문지
• /
• 제13권5호
• /
• pp.600-605
• /
• 2003

주성분 분석은 공정의 모니터링과 고장진단을 위한 유용한 방법으로 알려져 있으며 일반적으로 잔차와 주성분의 해석을 통하여 고장의 원인을 분류하고 있다. 대규모 공정에서는 이러한 방법이 적용상의 한계를 가지고 있다. 본 논문에서는 보다 향상된 고장진단을 위해 주성분 분석에 FCM-기반 고장 진단 알고리즘을 결합하였고 Two-tank 시스템을 이용하여 주성분 분석을 이용한 FCM-기반 고장진단 알고리즘의 구현하여 적용하였다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
• /
• pp.247-251
• /
• 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.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2008년도 춘계학술대회논문집
• /
• pp.420-424
• /
• 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.