• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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• pp.1774-1779
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• 2016

This paper proposes a portable cable fault detection system with automatic fault distinction and distance measurement using time-frequency correlation and reference signal elimination method and automatic fault classification algorithm in order to have more accurate fault determination and location detection than conventional time domain refelectometry (TDR) system despite increased signal attenuation due to the long distance to cable fault location. The performance of the developed system method was validated via an experiment in the test field constructed for the standardized performance test of power cable fault location equipments. The performance evaluation showed that accuracy of the developed system is less than 1.34%. Also, an error of automatic fault type and location by detection of phase and peak value through elimination of the reference signal and normalization of correlation coefficient and automatic fault classification algorithm not occurred.

• Structural Engineering and Mechanics
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• v.80 no.5
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• pp.563-583
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• 2021

Composite materials, composed of multiple constituent materials with dissimilar properties, are actively adopted in a wide range of industrial sectors due to their remarkable strength-to-weight and stiffness-to-weight ratio. Nevertheless, the failure mechanism of composite materials is highly complicated due to their sophisticated microstructure, making it much harder to predict their residual material lives in real life applications. A promising solution for this safety issue is structural damage detection. In the present paper, damage detection of composite material via electrical resistance-based technique and infrared thermography is reviewed. The operating principles of the two damage detection methodologies are introduced, and some research advances of each techniques are covered. The advancement of IR thermography-based non-destructive technique (NDT) including optical thermography, laser thermography and eddy current thermography will be reported, as well as the electrical impedance tomography (EIT) which is a technology increasingly drawing attentions in the field of electrical resistance-based damage detection. A brief comparison of the two methodologies based on each of their strengths and limitations is carried out, and a recent research update regarding the coupling of the two techniques for improved damage detection in composite materials will be discussed.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.240-241
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• 2008

We are presenting the efficient and robust simplified module based self-collision detection of humanoid robot simulator. For safe and reliable operations of humanoid robot, the self-collision detection is essential and extremely important. The main methods of self-collision detection are inverse X-Y-Z fixed angles and module distance filtering (MDF). According to experiments on the humanoid robot simulator with the self-collision detection, we could have a confidence about the efficiency of the self-collision.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.6
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• pp.540-549
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• 2015

Unintentional islanding results in safety hazards, reliability, and many other issues. Therefore, the islanding detection of a power conditioning system of a distributed generation, such as a grid-connected photovoltaic inverter, is a key function for standard compliance. Currently, many anti-islanding schemes have been examined, but existing anti-islanding schemes have poor power quality and non-detection zone issues. Therefore, this study analyzes the non-detection zone in a more deliberate manner than the existing analysis of the non-detection zone and proposes a new anti-islanding scheme, which has negligible power quality degradation and no non-detection zone. Simulation and experimental results validate that the proposed scheme shows much better performance than other existing schemes.

• Journal of the Korean Society of Safety
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• v.22 no.3 s.81
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• pp.7-12
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• 2007

This paper presents the development of an electrical fire detection system using digital temperature and current detectors in order to sound for electrical fire in advance. As the demand for electricity is increasing and industrial facilities are getting more complex and larger in size, the losses of human life and property are on the increase by electrical fires. In order to prevent electrical fires, it is required to find out fire signatures, or electric signal of the overcurrent and overheating. Therefore, in this paper, developed is an electrical fire detection system based on the detection of signal for overcurrent and overheating to prevent electrical accidents in advance that happen in electrical wires. The developed system gives an alarm by computer monitor, speaker system and mobile phone before electrical fires occur and give severe damages to human beings and properties, and the system can be implemented and supplied for business and residental buildings at a low price. The usefulness and validity of the system, also, verified in this paper by case study and experiments.

• Annual Conference of KIPS
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• 2015.10a
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• pp.1408-1410
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• 2015

Information about the painted road markings and other painted road objects play an important part in keeping safety of drivers. Some researchers have presented research approaches and dealt with road markings detection. In this paper, we present comprehensive survey of these techniques, and review some of them like a machine learning method, template matching method for road markings detection and classification, method of detection and classification of road markings using curve-based prototype fitting, signed edge signature method.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.3
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• pp.144-149
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• 2017

There is a little research on DC arc detection when compared to a large number of literature and patents on AC arc detection. However, as DC energy sources such as photovoltaic power generation facilities and fuel cells are introduced, research on DC arc has become as important as AC arc detection in terms of circuit protection and system reliability enhancement. In this paper, we have developed an arc detection method for photovoltaic system using frequency analysis. Through various experiments, it was confirmed that the proposed method effectively detects the arc.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.549-551
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• 1999

Recently, Several type of motors are used more widely in Fan system because of their low cost and high reliability. Therefore, the importance of fault detection and isolation of fan system significantly increases. The motor is a important factor bring out the fan system fault. So the problem of a fault detection for motor based on a parameter identification will be considered in this paper. After an introduction into fault detection with parameter estimation, a mathematical model for motor with special emphasis on motor itself. In the fault detection system, current and motor speed are used as parameter. Finally, simulation results are used to demonstrate the efficiency of the fault detection system.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1272-1275
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• 2002

Watermark detection plays a crucial role in multimedia copyright protection and has traditionally been tackled using correlation-based algorithms. However, correlation-based detection is not actually the best choice, as it does not utilize the distributional characteristics of the image being marked. Accordingly, an efficient watermark detection scheme for DWT coefficients is proposed as optimal for non-additive schemes. Based on the statistical decision theory, the proposed method is derived according to Bayes' decision theory, the Neyman-Pearson criterion, and the distribution of the DWT coefficients, thereby minimizing the missed detection probability subject to a given false alarm probability. The proposed method was tested in the context of robustness, and the results confirmed the superiority of the proposed technique over conventional correlation-based detection method.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.280-284
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• 2008

In this paper, a best channel matrix selection scheme(BCMS) is proposed to approximate maximum likelihood(ML) detection for a multiple-input multiple-output system. For a one stage BCMS scheme, one of the transmitted symbols is selected to perform ML detection and the other symbols are detected by zero forcing(ZF). To increase the diversity of the symbols that are detected by ZF, multi-stage BCMS detection scheme is used to further improve the system performance. Simulation results show that the performance of the proposed BCMS scheme can approach that of ML detection with a significant reduction in complexity.