• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.677-679
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• 1999

This paper introduces a implementation of fault detection for national highway line 3. Fault detection system was installed and operated on national highway line 3, environmental elements caused by abnormal status or faults has often happened. Therefore, the function of fault detection system is to speedy notify fault site, cause as well as scale of fault to manager. Though the fault detection and diagnosis system has been imported in the field of process of water and electric power, it is just beginning step in the field of ITS(Intelligent Transportation Systems). In general, Maintenance system is performed the online/offline process of detection, diagnosis and measure. This paper is studied online detection process, which is realtime remote detection.

• 한국공작기계학회논문집
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• 제11권2호
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• pp.103-111
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• 2002

Out of all metal-cutting process, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. There are two systems, Basic system and Online system, to detect the drill wear. Basic system comprised of spindle rotational speed, feed rates, thrust torque and flank wear measured by tool microscope. Outline system comprised of spindle rotational speed feed rates, AE signal, flank wear area measured by computer vision, On-line monitoring system does not need to stop the process to inspect drill wear. Backpropagation neural networks (BPNs) were used for on-line detection of drill wear. The output was the drill wear state which was either usable or failure. This paper deals with an on-line drill wear monitoring system to fit the detection of the abnormal tool state.

• Nuclear Engineering and Technology
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• 제52권12호
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• pp.2687-2698
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• 2020

Most of the machine learning-based intrusion detection tools developed for Industrial Control Systems (ICS) are trained on network packet captures, and they rely on monitoring network layer traffic alone for intrusion detection. This approach produces weak intrusion detection systems, as ICS cyber-attacks have a real and significant impact on the process variables. A limited number of researchers consider integrating process measurements. However, in complex systems, process variable changes could result from different combinations of abnormal occurrences. This paper examines recent advances in intrusion detection algorithms, their limitations, challenges and the status of their application in critical infrastructures. We also introduce the discussion on the similarities and conflicts observed in the development of machine learning tools and techniques for fault diagnosis and cybersecurity in the protection of complex systems and the need to establish a clear difference between them. As a case study, we discuss special characteristics in nuclear power control systems and the factors that constraint the direct integration of security algorithms. Moreover, we discuss data reliability issues and present references and direct URL to recent open-source data repositories to aid researchers in developing data-driven ICS intrusion detection systems.

• 품질경영학회지
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• 제47권1호
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• pp.75-86
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• 2019

Purpose: It is essential for the steel industry to produce steel products without unexpected downtime to reduce costs and produce high quality products. A hot strip rolling mill consists of many mechanical and electrical units. In condition monitoring and diagnosis, various units could fail for unknown reasons. Methods: In this study, we propose an effective method to detect units with abnormal status early to minimize system downtime. The early warning problem with various units was first defined. An autoencoder was modeled to detect abnormal states. An application of the proposed method was also implemented in a simulated field-data analysis. Results: We can compare images of original data and reconstructed images, as well as visually identify differences between original and reconstruction images. We confirmed that normal and abnormal states can be distinguished by reconstruction error of autoencoder. Experimental results show the possibility of prediction due to the increase of reconstruction error from just before equipment failure. Conclusion: In this paper, hot strip roughing mill monitoring method using autoencoder is proposed and experiments are performed to study the benefit of the autoencoder.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.475-483
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• 2023

The high-flux advanced neutron application reactor (HANARO) is a multi-purpose research reactor at the Korea Atomic Energy Research Institute (KAERI). HANARO has been used in scientific and industrial research and developments. Therefore, stable operation is necessary for national science and industrial prospects. This study proposed an anomaly detection system based on deep learning, that supports the stable operation of HANARO. The proposed system collects multiple sensor data, displays system information, analyzes status, and performs anomaly detection using deep autoencoder. The system comprises communication, visualization, and anomaly-detection modules, and the prototype system is implemented on site in 2021. Finally, an analysis of the historical data and synthetic anomalies was conducted to verify the overall system; simulation results based on the historical data show that 12 cases out of 19 abnormal events can be detected in advance or on time by the deep learning AD model.

• 한국항공운항학회지
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• 제29권2호
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• pp.84-93
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• 2021

Airline schedule is the most basic data for flight operations and has significant importance to an airline's management. It is crucial to know the airline's current schedule status in order to effectively manage the company and to be prepared for abnormal situations. In this study, machine learning techniques were applied to actual schedule data to examine the possibility of whether the airline's fleet state could be artificially learned without prior information. Given that the schedule is in categorical form, One Hot Encoding was applied and t-SNE was used to reduce the dimension of the data and visualize them to gain insights into the airline's overall fleet status. Interesting results were discovered from the experiments where the initial findings are expected to contribute to the fields of airline schedule health monitoring, anomaly detection, and disruption management.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.210-212
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• 2022

제조업에서 생산 설비의 상태를 모니터링하기 위해 각종 센서를 부착하고 있으며, 이를 통해 획득된 데이터의 경우 시계열 데이터인 경우가 많다. 생산 설비의 이상 여부를 판단하기 위해서는시계열 데이터로부터 패턴을 추출하는 과정이 선행되어야 하며 다양한 방법이 연구되고 있다. 본 논문에서는 수집된 다변량 시계열 데이터로부터 패턴을 추출하기 위해 매트릭스 프로파일 알고리즘을 적용하였으며, 이를 통해 현재 CNC 머신으로부터 수집 중인 다중 센서 데이터의 패턴을 추출하였다.

• 조명전기설비학회논문지
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• 제21권7호
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• pp.1-5
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• 2007

형광램프를 오랜 기간 사용하게 되면 전극에서 열 전자 방출을 돕는 보조 물질이 램프 외벽으로 흡수되어 램프 점등 조건 및 정상 상태 조건이 변화하게 된다. 이러한 경우를 오랜 시간 방치한다면 램프 전극에서 과도한 열이 발생하게 되어 등 기구 소켓을 녹이는 안전사고가 발생할 가능성이 크다. 본 논문은 형광램프 수명 말기에 나타나는 현상(정류 효과)을 검출하고, 이로부터 안정기를 보호하기 위한 방법을 제시하였다.

• 한국산학기술학회논문지
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• 제20권7호
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• pp.151-157
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• 2019

최근 비침투 또는 비접촉 방식을 활용한 호흡상태 관찰에 대한 관심이 높아지고 있다. 여러 가지 많은 생체신호들 중 호흡신호를 활용하여 건강상태를 점검하는 것은 비정상적인 건강 상태에 대한 신속한 대응을 가능하게 해 준다. 본 논문에서는 국소 퓨리에 변환을 활용한 실시간 무호흡 상태 검출에 대한 방법을 제시한다. 기존의 고속 퓨리에 변환을 활용한 신호해석과 달리, 본 논문에서는 국소 퓨리에 변환을 사용하여 짧은 신호 구간에서의 주파수 응답을 분석한다. 본 연구에서 호흡 신호는 비접촉 방식을 활용하였으며, 초광대역 레이더 모듈을 활용하여 신호를 획득하였다. 국소 퓨리에 변환을 활용하여 호흡 상태를 검출한 후, 검출 결과에 따라 호흡 상태에 대한 분류가 가능하다. 특히 국소 퓨리에 변환은 실시간으로 호흡 상태에 대한 주파수 분석이 가능하도록 하였다. 호흡신호에 잡음이 존재할 경우를 대비하여 적절한 필터링 알고리즘이 적용되었다. 본 논문에서 제안하는 방법은 직관적으로 구현이 가능하고, 실질적으로 사람의 호흡상태에 대한 분석이 가능하도록 해준다. 제안한 방법을 검증하기 위해 호흡신호를 활용한 실험결과를 제시한다.

• 디지털산업정보학회논문지
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• 제5권4호
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• pp.39-49
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• 2009

Nowadays, according to rapid development of computing environments, information processing and analysis system are very interesting research area. As a viewpoint of data preparation-processing-analysis in knowledge technology, the goal of automated information system is to satisfy high reliability and confidence and to minimize of human-administrator intervention. In addition, we expect the system which can deal with problem and abnormal error effectively as a fault detection and fault tolerance. In this paper, we design a monitoring system as follows. A productive monitoring information from various systems has unstructured forms and characteristics and crawls informative data by conditions and gathering rules. For representing of monitering information which requested by administrator, running-status can be able to check dynamically and systematic like connection/closed status in real-time. Our proposed system can easily correct and processing for monitoring information from various type of server and support to make objective judgement and analysis of administrator under operative target of information system. We implement semi-realtime monitering system using AJAX technology for dynamic browsing of web information and information processing using XML and XPATH. We apply our system to SMS server for checking running status and the system shows that has high utility and reliability.