• 전기학회논문지
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• 제59권10호
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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.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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• pp.802-808
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• 2000

This paper characterizes the electromechanical parameters due to the fault of rotor bars in a squirrel cage induction motor. Simulation is performed to investigate how broken rotor bars have effect on them by solving the time-stepping finite element equation coupled with magnetic field equation, circuit equation and mechanical equation of motion. It shows that the asymmetry of magnetic flux due to the broken rotor bar introduces the beating phenomenon in time domain and the sideband frequencies in frequency spectra, respectively, to the stator current, torque, speed, magnetic force and vibration of a rotor. However, vibration of a rotor would be the most effective monitoring parameters to detect the faults of rotor bars.

• Journal of Electrical Engineering and Technology
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• 제8권2호
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• pp.288-294
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• 2013

The diagnosis of motor failures using an on-line method has been the aim of many researchers and studies. Several spectral analysis techniques have been developed and are used to facilitate on-line diagnosis methods in industry. This paper discusses the first application of a motor flux spectral analysis to the identification of broken rotor bar (BRB) faults in induction motors using a multiple signal classification (MUSIC) technique as an on-line diagnosis method. The proposed method measures the leakage flux in the radial direction using a radial flux sensor which is designed as a search coil and is installed between stator slots. The MUSIC technique, which requires fewer number of data samples and has a higher detection accuracy than the traditional fast Fourier transform (FFT) method, then calculates the motor load condition and extracts any abnormal signals related to motor failures in order to identify BRB faults. Experimental results clearly demonstrate that the proposed method is a promising candidate for an on-line diagnosis method to detect motor failures.

• 전기학회논문지
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• 제57권9호
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• pp.1589-1593
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• 2008

The condition of a high voltage motor was monitored with the motor performance monitor (MPM) at the motor control center. The MPM detected defects in the rotor bar and end ring and input power according to motor and load conditions. The assessment of the condition of a coal pulverizer motor indicated it was clearly in good condition in terms of the rotor bars, over voltage, and motor performance. However, the side bands at frequency, 56.48 Hz indicated existence of rotor end-ring fault. The large torque ripple indicated abnormal operating conditions. After visual inspection, it has been observed that an impeller blade of the circulating water pump was broken off causing the irregular torque pattern.

• 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.

• 한국정보통신학회논문지
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• 제6권6호
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• pp.873-878
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• 2002

고정자 전류 스펙트럼(stator current spectrum)은 유도전동기의 고장 검출에 널리 사용되어왔다. 본 논문에서는 고정자 전류 스펙트럼 중에서 회전자 고장에 의해서 큰 영향을 받는 주파수 성분들로 특징벡터(feature vector)를 구성하고, 특징벡터와 기준벡터(reference vector)와의 평균 절대치 차이(mean absolute difference)를 구함으로써, 회전자 고장을 검출하는 방법을 제안한다. 제안한 방법에서는 전류 스펙트럼 중에서 추출된 매우 작은 크기(dimension)의 특징 벡터에 대한 평균 절대치 차이를 이용하기 때문에 신경회로망에 의한 고장 검출 알고리즘 둥에 비해서 훨씬 적은 계산량만으로 모터의 고장을 효율적으로 검출할 수 있다

• 전력전자학회:학술대회논문집
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• 전력전자학회 2003년도 춘계전력전자학술대회 논문집(2)
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• pp.644-647
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• 2003

The predictive maintenance can help to avoid the serious plant breakdowns and catastrophies. This paper deals with the fault diagnosis of the rotor of the induction motor which is widely used in the plants. In order to detect the broken bar, the Extended Kalman Filter is adopted to estimate the rotor resistance on the base of model-based method. The proposed estimation method is simulated with the aid of Matlab.

• 조명전기설비학회논문지
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• 제21권3호
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• pp.27-34
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• 2007

농형유도전동기에서 회전자 도체의 고장은 전동기 성능에 나쁜 영향을 미친다. 본 논문에서는 이와 같은 고장유무를 수치해석적 방법으로 분석하는 방법을 제안하였다. 정상이 아닌 회전자 도체가 있는 농형유도전동기의 회전자에서 고장에 따라 나타나는 특징적인 파형을 수치 해석적 방법으로 분석하였다. 이와 같은 방법으로 정상적인 도체와 고장 도체가 있는 경우의 특징을 분석함으로써 고장의 유무, 상태를 파악할 수 있다. 회전자 고장진단 실험 장치를 제작하고 실험을 통하여 제안한 방법의 타당성과 유용성을 확인하였다.

• Journal of Advanced Marine Engineering and Technology
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• 제31권1호
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• pp.95-102
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• 2007

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signals onto frequency domain. The raw signals can not show the significant feature, therefore difference values between the signal of the health conditions and that of the fault conditions are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the fault type. This study describes the results of detecting fault using wavelet analysis.

• 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.