• 조명전기설비학회논문지
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• 제20권1호
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• pp.132-137
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• 2006

유도전동기에 대한 결함 검출의 도구로서 축방향 누설자속 측정 방법을 사용할 수 있는가를 평가하고 전동기고장 검출에 관한 진단 알고리즘을 개발하기 위한 회전자에 관한 2번째 논문이다. 결함 검출을 위해 운전 중인 전동기의 끝단에 설치된 자속코일 센서로 누설자속 신호를 수집하며 전동기의 각종 결함을 검출하기 위해 시간과 주파수 영역에서 신호를 분석하였다. 센서 신호 형상이 전동기 각각의 결함에 대해 시간과 주파수 영역에서 해석하였다. 전동기의 회전자 관련 격함인 회전자봉 파손, 단락환 파손 및 회전자 편심이 축방향에서 측정된 고해상도의 스펙트럼으로부터 검출할 수 있는 방법을 확인하였다. 누설자속 스펙트럼으로부터 특정 주파수와 회전자봉 통과주파수의 측파대를 분석함으로서 회전자 결함을 검출하는 방법을 알았다. 또 유도전동기에 대하여 축방향 누설자속 측정을 위한 최적의 자속코일센서 및 측정시스템을 검증하고 회전자 결함을 검출하기 위한 방법을 개발하였다.

• 한국소음진동공학회논문집
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• 제12권4호
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• pp.287-293
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• 2002

The unexpected failure of the induction motor makes the downtime of production, and the cost of the process cessation enormous. To reduce the downtime and increase the reliability of the motor, the vibration measurements for the fault detection have been used previously. Recently motor current signature analysis(MCSA) has been adapted for the fault detection and diagnosis of the motors. MCSA provides a powerful analysis tool for detecting the presence of mechanical and electrical faults in both the motor and driven equipment. In this paper, the fault severity of the rotor bar has been derived in terms of the resistance change which is calculated from the equivalent circuit model. Results show that the fault of the rotor can be easily detected and the measured value of the resistance change is verified by the detected fault from on-site tests using MCSA for the induction motors in an iron foundry.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.638_639
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• 2009

The motors faults including mechanical rotor imbalances, broken rotor bar, bearing failure and eccentricities problems are reflected in electric, electromagnetic and mechanical quantities. This paper presents a study and the practical implementation of an induction motor for reactor containment fan cooler in nuclear power plant with Electric Signature Analysis(ESA). The results obtained present a good degree of reliability hence; the ESA predictive maintenance tools enable a pro-active evaluation of induction motors performance prior to failure.

• 한국소음진동공학회논문집
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• 제14권8호
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• pp.675-683
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• 2004

The motor current signature provides an important source of the information for the faults diagnosis of three-phase induction motor. The theoretical principles behind the generation of unique signal characteristics, which are indicative of failure mechanisms, are Presented. The fault detection techniques that can be used to diagnose mechanical Problems, stator and rotor winding failure mechanisms, and air-gap eccentricity are described. A theoretical analysis is presented which predicts the presence of unique signature patterns in the current that are only characteristics of the fault. The predictions are verified by experimental results from a special fault Producing test rig and on-site tests in a steel company. And this study have made new diagnostic algorithm for the operating induction motors with the test results. These developments are including the use of monitoring and analysis of electric current to diagnose mechanical and electrical problems and gave the precise test results automatically.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.539-542
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• 2003

A motor is the workhorse of our industry. The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. Different internal motor faults (e.g., inter-turn short circuits, broken bearings, broken rotor bars) along with external motor faults (e.g., phase failure, mechanical overload, blocked rotor) are expected to happen sooner or later. This paper introduces the fault detection technique of induction motors based upon the stator current. The fault motors have rotor bar broken or rotor unbalance defect, respectively. The stator currents are measured by the current meters and stored by the time domain. The time domain is not suitable to represent the current signals, so the frequency domain is applied to display the signals. The Fourier Transformer is used for the conversion of the signal. After the conversion of the signals, the features of the signals have to be extracted by the signal processing methods like a wavelet analysis, a spectrum analysis, etc. The discovered features are entered to the pattern classification model such as a neural network model, a polynomial neural network, a fuzzy inference model, etc. This paper describes the fault detection results that use wavelet decomposition. The wavelet analysis is very useful method for the time and frequency domain each. Also it is powerful method to detect the features in the signals.

• 한국소음진동공학회논문집
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• 제16권4호
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• pp.404-413
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• 2006

Induction motors are the workhorse of our industry because of their versatility and robustness. The diagnosis of mechanical load and power transmission system failures is usually carried out through mechanical signals such as vibration signatures, acoustic emissions, motor speed envelope. The motor faults including mechanical rotor imbalances, broken rotor bar, bearing failure and eccentricities problems are reflected in electric, electromagnetic and mechanical quantities. The recent research has been directed toward electrical monitoring of the motor with emphasis on inspecting the stator current of the motor, The stator current spectrum has been widely used for fault detection in induction motor systems. The motor current signature analysis is the useful technique to assess machine electrical condition. This paper describes the motor condition detected by the current signatures Paralleled with vibration signatures analysis of induction motors with the roller bearing and the journal bearing type for large vertical pumps in power plant as examples to discuss for motor fault detection and diagnosis.

• 조명전기설비학회논문지
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• 제19권8호
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• pp.131-137
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• 2005

본 논문은 유도 전동기에 대한 상태 모니터링 시스템의 도구로서 축방향 누설자속 측정 방법을 사용할 수 있는가를 평가하고 전동기에 대한 진단 알고리즘을 개발하는 것이다. 결함검출을 위해 전동기를 정지시키지 않고 전동기의 코일단에 설치된 자속코일로 누설자속 신호를 수집하여 전동기의 각종 결함을 검출하기 위해 시간과 주파수영역으로 신호를 분석한다. 전동기 각각의 결함에 대해 시간과 주파수 영역에서 특정 신호 현상이 검출되었다. 전원전압 불평형과 고정자 권선의 선간 단락은 축방향에서 측정된 고해상도의 누설자속 스펙트럼으로부터 특정 측대파와 회전자봉 통과주파수의 측대파를 분석함으로서 결함을 검출할 수 있다. 주파수 영역에서의 스펙트럼이 모니터링 목적으로 더욱 유용하다는 결론을 얻었다. 본 논문에서는 유도 전동기의 축방향 누설자속 측정이 진단 방법으로서 적합한 도구임을 증명하고 결함을 검출하기 위한 알고리즘을 개발하였다.