• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1357-1359
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• 1999

This paper presents fault detection in cables. We developed the device for detecting pinpoint location of faults in power cables using acoustic method. The proposed device consists of hardware and software for the fault detection. Using the device, we explain how to detect the pinpoint of faults and introduce that the other method use the time delay between electro-magnetic and acoustic signals for the pinpoint of the faults.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.4
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• pp.29-35
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• 2003

The rotating machineries always generate harmonic frequencies of their own rotating speed, and increment of vibration amplitude affects to the equipments which connected to the vibrational source and causes industrial calamities. The life cycle of equipments can be extended and damages to the human beings could be prevented by identifying the cause of malfunctions through prediction of the increment of vibration and records of vibrational history. In this study, therefore, diagnostic expert algorithm for the centrifugal pump is developed by integrating fuzzy inference method and signal processing techniques. And the validity of the developed diagnostic system is examined via various computer simulations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.257-260
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• 1997

Bluetooth is the most promising network paradigm which ca open the new area in the information technology. Especially, bluetooth can link all the electrical products and PCs(Personal Computer) to cellular phone or PDA. In this paper, the data from ECU which are gathered by scanner are communicated between tow PCs using the bluethooth modules. The acquired data are ECU's self diagnosis signal and sensor output signal. Self diagnosis signals are very important to check the ECU's state and sensor output signals. Using these data, the possibility of wireless communication with ECU is developed and verified. Protocol stack of bluetooth is L2CAP through HCI and wireless communication software of ECU's signal is developed using VC++ in Windows 98 environment.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.676-682
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• 2007

In this paper we introduce the Failure Management System for AREX's Signalling System which is applied by RAMS management. The corrective action report is classified into 3 group, scheduled maintenance, non-scheduled maintenance and the reported failure maintenance. The scheduled maintenance is for the failure detected by periodic inspection and it is concerned as the Preventive Maintenance. The reported failure maintenance is for the failure reported by non-maintenance staff and non-scheduled maintenance includes all corrective action except the works of the previous 2 group. RAMS analysis is based on the FRACAS data connected with the corrective action reports. AREX computerize the all process by the Facility Management System of Integrated Information System.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.10
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• pp.1882-1888
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• 2010

It is widely known that ESA(Electric Signature Analysis) method is very useful one for fault diagnosis of an induction motor. Online fault diagnosis system of induction motors using LabVIEW is proposed to detect the fault of broken rotor bars and shorted turns in stator. This system is not model-based system of induction motor but LabVIEW-based fault diagnosis system using FFT spectrum of stator current in faulty motor without estimating of motor parameters. FFT of stator current in faulty induction motor is measured and compared with various reference fault data in data base to diagnose the fault. This paper is focused on to predict and diagnose of the health state of induction motors in steady state. Also, it can be given to motor operator and maintenance team in order to enhance an availability and maintainability of induction motors. Experimental results are demonstrated that the proposed system is very useful to diagnose the fault and to implement the predictive maintenance of induction motors.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.661-662
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• 2015

최근 친환경적인 기술 개발에 대한 요구가 증가함에 따라 기존 엔진의 역할을 직접적으로 대체하게 되는 전기자동차용 전동기에 대한 연구가 활발히 진행되고 있다. 영구자석을 사용한 전동기의 경우, 계자 권선이 없기 때문에 회전자 동손이 없어지면서 효율이 높아지는 장점이 있지만 온도 상승 및 과부하 등으로 인한 영구자석의 불가역 감자로 인한 고장 가능성이 존재한다. 본 논문에서는 이러한 영구자석 감자현상을 진단하기 위한 방법 중 하나로 회전자 구속 조건에서 저전압 고주파 주입을 통한 입력전류 파형의 스펙트럼 분석을 제안한다. 제안한 방법은 전동기의 회전자를 구속시킨 상태에서 진단신호를 입력하고 인버터의 출력전류 파형을 측정하여 스펙트럼 분석을 수행하는 방법이다. 제안한 방법은 시뮬레이션을 통해 검증하였다.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.185-186
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• 2015

TSC는 전력계통의 무효전력 보상을 위한 SVC 시스템의 주요 장치이다. 본 논문에서는 TSC의 커패시터 뱅크의 열화 및 고장진단에 활용할 수 있는 커패시터 용량 측정 기법을 제안한다. 제안한 커패시터 용량 측정 기법은 시간영역 해석 기법으로서 커패시터의 전압 및 전류 신호에 포함된 고조파 및 잡음, 주파수 변동, 과도 상태 전이 등의 왜란에 강인하다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1545-1550
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• 2014

Fault detection and diagnosis (FDD) of photovoltaic (PV) power systems is one of significant techniques for reducing economic loss due to abnormality occurred in PV modules. This paper presents a new FDD method against PV power systems by using statistical comparison. This comparative approach includes deviation signals between the outputs of two neighboring PV modules. We first define a binary hypothesis testing under such deviation and make use of a generalized likelihood ratio testing (GLRT) theory to derive its FDD algorithm. Additionally, a recursive computational mechanism for our proposed FDD algorithm is presented for improving a computational effectiveness in practice. We carry out a real-time experiment to test reliability of the proposed FDD algorithm by utilizing a lab based PV test-bed system.

• Annual Conference of KIPS
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• 2016.10a
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• pp.595-596
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• 2016

열차의 진로를 변경시키는 선로전환기의 고장은 탈선 등과 같은 대형 사고를 유발시킬 수 있는 중요한 시설이다. 따라서 열차운행 안전 측면에서 해당 설비에 대한 모니터링은 필수적이다. 본 논문에서는 선로전환기의 구동 시 발생하는 소리 정보를 이용하여 선로전환기의 이상상황을 탐지하는 시스템을 제안한다. 먼저 제안한 시스템은 소리 센서에서 실시간으로 취득하는 소리 신호를 Power Spectral Density(PSD) 특징으로 변환한다. 추출된 PSD 특징은 이미 성능이 입증된 딥러닝의 대표적인 모델인 Convolutional Neural Network(CNN)에 적용하여 이상상황을 탐지한다. 실제 선로전환기의 전환 시 발생하는 소리 데이터를 취득하여 모의실험을 수행한 결과, 비정상 상황을 안정적으로 탐지함을 확인하였다.

• Proceedings of the KIEE Conference
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• 2001.04a
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• pp.19-21
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• 2001

Induction motors are a critical component of many industrial machines and are frequently integrated in commercial equipment. The many economical losses and the deterioration of system reliability might be caused by the failure of induction motors in industrial field. Based on the reliability and cost competitiveness of driving system(motors), the faults detection and diagnosis of system is considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method is used for induction motor fault diagnosis. This method analyzes the motor's supply current, since this diagnoses the motor's condition. The diagnostic system is constructed by using LabVIEW of National Instruments.