• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1157-1158
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• 2007

자동차, 항공기, 철도 및 선박 등과 같은 각종 교통수단에 발생하는 이상현상에 대한 사용자의 정확한 복구 조치 능력 향상을 위하여, 발생한 고장코드에 대한 신속하고 정확한 해석은 매우 중요하다. 이에 따라 본 논문에서는 차량의 고장 진단 프로토콜 중 SAE(미국 자동차 기술자 협회) J1979[1]의 방식을 사용하여 차량의 통신방식을 정의 하고 이에 따라 발생되는 ECU 정보들을 수집 분석하여 각각의 고장 코드들을 해석하였고 배기가스뿐만 아니라 차량에서 발생되는 총제적인 문제점들을 GUI(Graphic User Interface) 기반의 응용 프로그램을 이용하여 차량의 단계별, 부품별 고장코드를 실시간으로 발생시킬 수 있는 시뮬레이터를 개발하였다

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.221-226
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• 2018

Special-purposed vehicles are customized according to the user's requirements. When these vehicles are out of oder, they are costly and time consuming to repair. In order to solve these problems, we want to remotely check whether the vehicle is abnormal and remotely identify the fault area, thereby shortening the repair cost and the repair period. In this study, the faulty part of the electric control part is automatically identified, and it is immediately grasped through the user's mobile phone application and an instant fault code is notified to the car manufacturer for quick and smooth fault repair. In order to realize this, we want to build a system that uses the technology of IoT to determine the fault area according to the items required in the field of the special purpose vehicle and notify the manufacturer of the fault on its own.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.106-117
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• 2016

Recently, solar power plants have spread widely as part of the transition to greater environmental protection and renewable energy. Therefore, regular solar plant inspection is necessary to efficiently manage solar-light modules. This study implemented a test that can detect solar-light module faults using an UAV based thermal infrared camera and GIS spatial analysis. First, images were taken using fixed UAV and an RGB camera, then orthomosaic images were created using Pix4D SW. We constructed solar-light module layers from the orthomosaic images and inputted the module layer code. Rubber covers were installed in the solar-light module to detect solar-light module faults. The mean temperature of each solar-light module can be calculated using the Zonalmean function based on temperature information from the UAV thermal camera and solar-light module layer. Finally, locations of solar-light modules of more than $37^{\circ}C$ and those with rubber covers can be extracted automatically using GIS spatial analysis and analyzed specifically using the solar-light module's identifying code.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.7
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• pp.75-83
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• 2007

IEC code based decision nile have been widely applied to detect incipient faults in power transformers. However, this method has a drawback to achieve the diagnosis with accuracy without experienced experts. In order to resolve this problem, we propose an artificial diagnosis algorithm to detect faults of power transformers using Self-Organizing Feature Map(SOM). The proposed method has two stages such as model construction and diagnostic procedure. First, faulty model is constructed by feature maps obtained by unsupervised learning for training data. And then, diagnosis is performed by compare feature map with it obtained for test data. Also the proposed method usぉms the possibility and degree of aging as well as the fault occurred in transformer by clustering and distance measure schemes. To demonstrate the validity of proposed method, various experiments are unformed and their results are presented.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.3
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• pp.271-278
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• 2015

This paper develops an OBD Diagnostic Program (Program) using Visual Studio (C#), which was used to diagnosis malfunction information from OBD-II system vehicles. We accomplished this using the Program, Diagnostic tests, Board (STN1110), FTDI Basic Cable, Mini USB Cable, OBD Data Cable, and both hybrid and regular vehicles. The Program tests real-time data output, DTC output, sensor value output, engine RPM, waveform data, OBD type check, PID inspection, and whole monitoring. We found vehicles used in this research had 19 PIDs, which was within OBD-II regulations. We also gathered data on control and diagnostic code regulated by OBD-II system, such as, sensor output value, engine RPM, DTC output, each PID analytic value, OBD type, fuel mode, and whole monitoring result value. Using the data collected through the Program appropriately can lead to more effective diagnostic practices and contribute to education.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.4
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• pp.329-336
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• 2008

The facilities with new technologies in the recent power plants become larger and need a lot of high cost for maintenance due to stop operations and accidents from the operating machines. Therefore, it claims new systems to monitor the operating status and predict the faults of the machines. This research classifies the normal/abnormal status of the machines into 5 levels which are normal-level/abnormal-level/care-level/dangerous-level/fault and develops the new system that predicts faults without stop operation in power plants. We propose the regional segmentation technique in the frequency domain from the data of the operating machines and generate the Peak-codes similar to the Bar-codes, The high efficient and economic operations of the power plants will be achieved by carrying out the pre-maintenance at the care level of 5 levels in the plants. In order to be utilized easily at power plants, we developed the algorithm appling to a notebook computer from signal acquisition to the discrimination.

• Journal of Korea Multimedia Society
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• v.11 no.10
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• pp.1436-1445
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• 2008

Currently, mobile handset embeds many communication modules including CDMA and Bluetooth, and many applications are developed based on these modules. In this paper, we study about wireless vehicle diagnosis software and user interface based on bluetooth system on mobile handset. We developed Bluetooth communication system on protocol converter between OBD(On Board Diagnostics)-II system. Based on this system, we can communicate ECU(Engine Control Unit) and mobile device based on windows .NET compact framework platform. Therefore we can easily diagnose vehicle state and obtain engine data. All user interface and vehicle diagnosis systems on mobile handset are developed under windows .NET compact framework platform. Using this system we achieved several improvements over existing vehicle diagnostic system; 1) the software download and upgrade can be achieve on wireless environment, 2) no additional diagnostic devices are requires, which saves additional cost and we can diagnose the vehicle easily, 3) we can easily port our system on many embedded systems including PDA and navigator, etc.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.6
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• pp.48-56
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• 2008

This study provides to car driver with car exhaust gas and sensor information which are car trouble code in engine and many sensors when the car has some problems. This is to provide car manager with many information of car sensors when we go to vehicle maintenance. For example, information of engine RPM, fuel system, intake air temperature, air flow sensors and oxygen sensors can provide to owner or garage, and also add to multimedia system for mp3 files and video files. This system consists of embedded linux system of low power while driving the car which uses OBD-II protocols and zigbee communication interface from CAN communication of car system to self-diagnosis embedded system of car. Finally, low power embedded system has a lot of application and OBD-II protocols for embedded linux system and CAN communication which get sensor informations of car control sensor system while driving the car.

• Journal of Advanced Navigation Technology
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• v.8 no.1
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• pp.26-37
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• 2004

Consistent and realistic error covariance information is important for position estimation, error analysis, fault detection, and integer ambiguity resolution for differential GNSS. In designing a position domain carrier-smoothed-code filter where incremental carrier phases are used for time-propagation, formulation of consistent error covariance information is not easy due to being bounded and temporal correlation of propagation noises. To provide consistent and correct error covariance information, this paper proposes two recursive filter algorithms based on carrier-smoothed-code techniques: (a) the stepwise optimal position projection filter and (b) the stepwise unbiased position projection filter. A Monte-Carlo simulation result shows that the proposed filter algorithms actually generate consistent error covariance information and the neglection of carrier phase noise induces optimistic error covariance information. It is also shown that the stepwise unbiased position projection filter is attractive since its performance is good and its computational burden is moderate.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.1
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• pp.41-46
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• 2016

It has been proven that the dissolved gas analysis (DGA) is the most effective and convenient method to diagnose the transformers. The DGA is a simple, inexpensive, and non intrusive technique. Among the various diagnosis methods, IEC 60599 has been widely used in transformer in service. But this method cannot offer accurate diagnosis for all the faults. This paper proposes a fault diagnosis method of oil-filled power transformers using IEC code based neuro-fuzzy model. The proposed method proceeds two steps. First, IEC 60599 method is applied to diagnosis. If IEC code can't determine the fault type, neuro-fuzzy model is applied to effectively classify the fault type. To demonstrate the validity of the proposed method, experiment is performed and its results are illustrated.