• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.10
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• pp.17-26
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• 2010

This is concerned with the technology to monitor the vehicle operation, failure and disorder by using WiBro portable device. More precisely, the technology makes it possible that the information collection device is connected to both ECU(Electronic Control Unit) which is the device for controlling engine, transmission, brake, air-bag, etc that are connected to in-vehicle network and OBD-II connector that is for data collection from various sensors. In addition, with a WiBro portable device (cell phone, PDA, PMP, UMPC, etc). equipped with a vehicle diagnostic programs, information for operation, failure and malfunction can be obtained and analyzed in real-time, and alarm is alerted when the vehicle is in abnormal status, which makes the early reactions to the status. Furthermore, the collected data can be sent through WiBro network to the server managed by the company specialized in managing the vehicles, thus the technology could help the drivers who have less knowledge about their auto-vehicles have safe and economic driving. There is always a possibility of malfunction due to various types of noise that are caused by wring-harness when the device is wired-connected. In this research, in order to overcome this problem, we propose a system configuration that can do monitoring and diagnosis with a device for collecting data from vehicle and a personal WiBro device. Also, we performed research on data acquisition and interlock for the system defined by the definition for information and data sharing platform.

• The Journal of Bigdata
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• v.6 no.1
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• pp.23-35
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• 2021

In the era of the 4th industrial revolution, smart factories have received great attention, where production and manufacturing technology and ICT converge. With the development of IoT technology and big data, automation of production systems has become possible. In the advanced manufacturing industry, production systems are subject to unscheduled performance degradation and downtime, and there is a demand to reduce safety risks by detecting and reparing potential errors as soon as possible. This study designs a model based on supervised and unsupervised learning for detecting anomalies. The accuracy of XGBoost, LightGBM, and CNN models was compared as a supervised learning analysis method. Through the evaluation index based on the confusion matrix, it was confirmed that LightGBM is most predictive (97%). In addition, as an unsupervised learning analysis method, MD, AE, and LSTM-AE models were constructed. Comparing three unsupervised learning analysis methods, the LSTM-AE model detected 75% of anomalies and showed the best performance. This study aims to contribute to the advancement of the smart factory by combining supervised and unsupervised learning techniques to accurately diagnose equipment failures and predict when abnormal situations occur, thereby laying the foundation for preemptive responses to abnormal situations. do.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.1
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• pp.132-137
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• 2006

The second part of paper related rotor failure is to evaluate that the axial magnetic flux measurement could be used as a tool of the condition monitoring system for the induction motor and to develope the diagnostic algorithm for the various fault in the electric motors. The magnetic leakage flux signal is captured by the flux coil located at the end of motor without the disturbance of the operation. And the signal is analyzed both time and frequency domain to detect the failure of the motor. Specific signature can be described in tin and frequency domain for each fault of the motor. The experimental test found that the rotor failures - broken rotor bar, broken end ing and rotor eccentricity, could be detected from the spectrum with high resolution. The method of detecting the rotor fault was found by analysing the specific frequency and the sideband of the rotor bar pass frequency from axial leakage flux spectrum. In addition the optimal flux coil and measuring equipment for the axial leakage flux measurement was verified and the diagnostic method for the detection of the rotor related failure was developed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.83-89
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• 2022

Internet of Things technology is rapidly developing due to the recent development of information and communication technology. IoT technology utilizes various sensors to generate unique data from each sensor, enabling diagnosis of system status. However, the equipment management system currently in effect is a post-preservation concept in which administrators must deal with the problem after the problem occurs, which could mean system reliability and availability problems due to system errors, and could result in economic losses due to negative productivity disruptions. Therefore, this study confirmed that edge controller control decision algorithms for more efficient operation of rectifiers in the factory by applying intelligent IoT (AIoT) technology and domain knowledge-based modeling for each sensor data collected based on this, outputting appropriate status messages for each scenario.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1173-1179
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• 2015

In this paper is given to implements the Android-based integration platform to provide convenience for gender development and scalability , easy access for the user. Sensor-based smart home-related products have a different way of the data exchange so platform can be integrated easily and connect heterogeneous network products and external data transmission security processing for data communication and supported to enable the integration

• Information and Communications Magazine
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• v.24 no.9
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• pp.86-95
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• 2007

사무실과 가정의 컴퓨터, 대중화된 휴대폰 사용 그리고 인터넷으로 특징지어지는 정보통신 기술덕택에 현대인은 어느 정도 시간과 공간의 제약을 극복하고 있다. 그러나, 아직도 현대인은 예전에 비해 가까워진 지구촌을 여러 가지 이동체를 타고 이동을 하여야한다. 특히 현대인에게 있어서 자동차는 가정과 직장을 이어주고 업무 목적지와 휴식을 위한 휴양지를 찾아가기 위한 실질적인 이동 수단으로서 가정과 직장에 이은 또 하나의 정보통신기술이 필요한 중요한 영역이다. 따라서 미래형 자동차는 편의 주행, 쾌적 주행을 제공하고 그리고 안전 주행이 보장되는 지능형 자동차의 수요가 예견되고 있으며 이를 구현하기위해 첨단 정보통신, 전자, 제어기술이 요구되고 있다. [1][5][6] 이상과 같은 지능형 자동차 관련 응용 분야는 위 그림과 같이 자동차 여러 부위에 장착되는 첨단 전장품들에 의해서 구현이 된다. 그러나, 기존의 자동차와 달리 미래형 지능형 자동차에서는 많은 전장품들이 장착됨에따라 소요되는 전원의 용량이 증가하게되어 기존 12V에서 42V 시스템으로 바뀔 예정이다. 또한 각종 센서로부터 정보신호를 받아서 정보처리를 하고 Actuator를 제어하기 위해서 많은 전장품들간에 연결되는 신호선들의 배선이 복잡해짐에따라 생산부서에서의 공정비용이 증가하게된다. 또한 향후 석유 에너지의 고갈에 따른 전기 자동차로의 전환이 예상되는데 위에서 언급된 많은 전자장치들간 신호를 주고 받기위해 차량내 여러부위로 퍼져있는 배선들이 차지하는 무게가 상당하므로 차체의 무게를 가볍게 해야하는 차세대 전기 자동차의 성능 향상을 위해서 효율적인 In Vehicular Network 기술이 요구된다. 또한 향후 자동차에 장착된 많은 전자장치들의 고장 진단 및 내장된 SW를 효율적으로 갱신하기 위해서는 여러 전자장치들이 하나의 버스로 연결되는 In Vehicle network이 필수적이다.

• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1844-1846
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• 2001

광섬유는 저손실, 광대역의 전송특성을 가지며 세경(細徑), 경량등 많은 장점을 가지고 있지만 동케이블과 같이 파단점, 불연속점등의 장해점 탐색에 대한 어려움이 있다. 이러한 문제점을 해결하기 위하여 OTDR(Optical Time Domain Reflectometer)은 고감도, 고정도의 광센싱 기술, 극초단 광펄스 레이다 기술, 광다중화 센서 네트웍기술, 실시간 광신호처리 기술 등 정밀 광계측 및 신호처리기술을 적용하여 설치된 광섬유의 손실 정도를 측정하는 시스템으로 광섬유에 입사된 광의 산란 가운데 Rayleigh 산란에 의해서 생기는 후방산란광을 관측하여 광파이버의 파단점 탐색 및 손실측정이 가능하다. 최근 대부분의 유선통신망은 광섬유를 이용한 광통신방식으로 이루어지고 있으며 이러한 광섬유의 고장점을 찾기 위한 방법은 OTDR방식이 유일하다고 할 수 있다. 본 논문은 Rayleigh 후방산란에 의한 광학적 특성을 규명하고 이러한 특성을 이용하여 이용한 광섬유 유지보수용 계측시스템을 설계, 제작하고 실험한 결과에 대하여 설명하고 고찰하였다. 측정거리를 40Km까지 측정하도록 하였으며, 모니터상에서의 거리 분해능은 5m정도를 가지며 1310nm의 파장을 사용하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.147-152
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• 2016

This paper proposes a new TPC (Transmission Priority Change) algorithm which is used to diagnose failures of a CAN (Controller Area Network) based network system for the oil tank monitoring. The TPC algorithm is aimed to increase the total amount of data transmission and to minimize the latency for an urgent message by changing transmission priority. The urgency of the data transmission has been determined by the conditions of sensors. There are multiple sensors inside of the oil tank, such as temperature, valve, pressure and level sensors. When the sensors operate normally, the sensory data can be collected through the CAN network by the monitoring system. However when there is a dangerous situation or failure situation happened at a sensor, the data need to be handled quickly by the monitoring system, which is implemented by using the TPC algorithm. The effectiveness of the TPC algorithm has been verified by the real experiments. In addition, this paper introduces a method that people can figure out the condition of oil tanks and also can perform the fault diagnosis in real-time by using transmitted packet data. By applying this TPC algorithm to various industries, the convenience and reliability of multiple sensors network system can be improved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.7
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• pp.630-642
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• 2013

To transmit vital signal stream of mobile patients remotely, it requires mobility of patient and watcher, sensing function of patient's abnormal symptom and self-organizing service binding of related computing resources. In the existing relative researches, the vital signal stream is transmitted as a centralized approach which exposure the single point of failure itself and incur data traffic to central server although it is localized service. Self-organizing middleware platform based on heterogenous overlay network is a middleware platform which can transmit real-time data from sensor device(including vital signal measure devices) to Smartphone, TV, PC and external system through overlay network applied self-organizing mechanism. It can transmit and save vital signal stream from sensor device autonomically without arbitration of management server and several receiving devices can simultaneously receive and display through interaction of nodes in real-time.