• Journal of Power Electronics
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• 제11권2호
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• pp.163-172
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• 2011

Oxidation models of a rotor bar and end ring segment in an induction motor are presented to simulate the behavior of an induction machine working with oxidized rotor parts which are modeled as rotor faults in progress. The leakage inductance and resistance of the rotor parts arc different from normal values because of the oxidation process. The impedance variations modify the current density and magnetic flux which pass through the oxidized parts. Consequently, it causes the rotor asymmetry which induces abnormal harmonics in the stator current spectra of the faulty machine. The leakage inductances of the oxidation models are derived by the Ampere's law. Using the proposed oxidation models, the rotor bar and end ring faults in progress can be modeled and simulated with the motor current signature analysis (MCSA). In addition, the oxidation process of the rotor bar and end ring segment can motivate the rotor asymmetry, which is induced by electromagnetic imbalances, and it is one of the major motor faults. Results of simulations and experiments are compared to each other to verify the accuracy of the proposed models. Experiments are achieved using 3.7 kW, 3-phase, and squirrel cage induction motors with a motor drive inverter.

• 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.

• Journal of Mechanical Science and Technology
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• 제20권7호
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• pp.929-940
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• 2006

Early detection and diagnosis of incipient induction machine faults increases machinery availability, reduces consequential damage, and improves operational efficiency. However, fault detection using analytical methods is not always possible because it requires perfect knowledge of a process model. This paper proposes a neural network based expert system for diagnosing problems with induction motors using vibration analysis. The short-time Fourier transform (STFT) is used to process the quasi-steady vibration signals, and the neural network is trained and tested using the vibration spectra. The efficiency of the developed neural network expert system is evaluated. The results show that a neural network expert system can be developed based on vibration measurements acquired on-line from the machine.

• 조명전기설비학회논문지
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• 제19권3호
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• pp.75-84
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• 2005

유도전동기 구동시스템의 예상치 않은 고장은 많은 산업 응용분야에서 심각한 문제를 초래시킬 수 있으므로, 유도전동기 구동을 위한 전압형 PWM 인버터의 고장진단에 대해 연구한다. 진단의 고려 대상은 정류기 다이오드, 스위칭 장치 및 입력단의 개방회로 고장이며, 진단신호는 전동기 전류로부터 유도한다. 고장의 특징추출은 dq-전류 경로의 크기를 이용하였고, 진단은 PCA와 LDA를 적용한다. 또한, 본 논문에서는 일반적인 중${\cdot}$소형 유도전동기 구동 시스템의 제어기에 진단 소프트웨어를 추가하여 사용하는 것에 대한 가능성을 제시하며, 그에 관련해 수행속도에 따른 진단결과들을 보여준다. 최종적으로, MATLAB을 이용하여 인버터의 고장진단에 대한 모의실험을 수행 하였고, 제안된 알고리즘의 유용성을 검증하였다.

• 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.

• 제어로봇시스템학회논문지
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• 제4권1호
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• pp.123-133
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• 1998

In this paper, an algorithm of fault detection and diagnosis during operation of induction motors under the condition of various loads and rates is investigated. For this purpose, the spectrum pattern of input currents is used in monitoring the state of induction motors, and by clustering the spectrum pattern of input currents, the newly occurrence of spectrum patterns caused by faults are detected. For the diagnosis of the fault detected, a fuzzy fault tree is designed, and the fuzzy relation equation representing the relation between an induction motor fault and each fault type, is solved. The solution of the fuzzy relation equation shows the possibility of occurence of each fault. The results obtained are summarized as follows : (1) Using clustering algorithm by unsupervised learning, an on-line fault detection method unaffected by the characteristics of loads and rates is implemented, and the degree of dependency for experts during fault detection is reduced. (2) With the fuzzy fault tree, the fault diagnosis process become systematic and expandable to the whole system, and the diagnosis for sub-systems can be made as an object-oriented module.

• Journal of Power Electronics
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• 제17권4호
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• pp.972-982
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• 2017

The Park's vector of stator current is a popular technique for the detection of induction motor faults. While the detection of the faulty condition using the Park's vector technique is easy, the classification of different types of faults is intricate. This problem is overcome by the Multiple Park's Vector (MPV) approach proposed in this paper. In this technique, the characteristic fault frequency component (CFFC) of stator winding faults, rotor winding faults, unbalanced voltage and bearing faults are extracted from three phase stator currents. Due to constructional asymmetry, under the healthy condition these characteristic fault frequency components are unbalanced. In order to balanced them, a correction factor is added to the characteristic fault frequency components of three phase stator currents. Therefore, the Park's vector pattern under the healthy condition is circular in shape. This pattern is considered as a reference pattern under the healthy condition. According to the fault condition, the amplitude and phase of characteristic faults frequency components changes. Thus, the pattern of the Park's vector changes. By monitoring the variation in multiple Park's vector patterns, the type of fault and its severity level is identified. In the proposed technique, the diagnosis of faults is immune to the effects of unbalanced voltage and multiple faults. This technique is verified on a 7.5 hp three phase wound rotor induction motor (WRIM). The experimental analysis is verified by simulation results.

• Journal of Electrical Engineering and Technology
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• 제4권2호
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• pp.219-228
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• 2009

The growing application and the numerous qualities of induction motors (1M) in industrial processes that require high security and reliability levels has led to the development of multiple methods for early fault detection. However, various faults can occur, such as stator short-circuits and rotor failures. Traditionally the diagnosis machine is done through a sinusoidal power supply, in the present paper we study experimentally the effects of the rotor failures, such as broken rotor bars in function of the ac supplying, the load and show the impact of the converter from diagnosis of the machine. The technique diagnosis used is based on the spectral analysis of stator currents or stator voltages respectively according to the types of induction motor ac supplying. So, four different ac supplying are considered: ${\odot}$ the IM is directly by the balanced three-phase network voltage source, ${\odot}$ the IM is fed by a sinusoidal current source given the controlled by hysteresis, ${\odot}$ the IM is fed (in open loop) by a scalar control imposing through ratio V/f=constant, ${\odot}$ the IM is controlled through a vector control using space vector pulse width modulation (SVPWM) technique inverter with an outer speed loop.

• 한국지능시스템학회논문지
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• 제16권6호
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• pp.691-697
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• 2006

유도전동기는 산업시스템에 있어서 필수적인 요소이기 때문에 유지 관리, 모니터링 시스템, 고장 진단 등의 다양한 분야에서 많은 연구가 행해지고 있다. 유도전동기의 운전 중 하나의 고장이 발생한 경우 이것은 전동기의 다른 부분에 영향을 미치거나 또 다른 고장을 유발시키는 원인이 된다. 따라서 개별적인 고장뿐만 아니라 결합된 형태의 고장을 검출하고 진단하는 것은 유용한 방법이다. 본 논문에서는 전압불평형 고장과 회전자바 고장이 발생한 경우, 흐리고 두 고장이 동시에 복합적으로 발생한 경우를 모델링하고 이에 대해 고장을 웨이블릿 분해를 이용하여 진단하였다. 제안된 고장 검출 및 진단 알고리즘은 농형유도전동기의 고정자 전류를 이용하였으며 매트랩 시뮬링크를 사용하여 시뮬레이션 하였다.

• 전기전자학회논문지
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• 제27권4호
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• pp.518-523
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• 2023

고정자 권선단락은 미세한 턴이 단락되어 급격히 고장이 심각해짐에 따라 ITSC의 진단이 중요시되고 있다. 그러나, 3상 유도전동기의 노이즈 및 손실등과 유사한 특징을 가짐에 따라 ITSC진단에 많은 어려움이 있다. 이를 효율적으로 진단하기 위해서 인공지능 기법으로 연구되고 있으나, 현장에서는 모델기반 기법이 두루 활용되고 있음에 따라 모델기반 기법에 대한 진단 성능개선 연구가 필요한 실정이다. 이에 본 논문에서는 회전하고 있는 자속에 변화를 무시하며, 전류 성분만을 이용할 수 있도록 Clarke변환 방법을 응용하여 진단방법을 제안하였다. 이에 30분간의 정상 및 ITSC 상태의 측정 결과, 정상상태를 ITSC 상태로 오인식하는 경우 0.2[%], ITSC상태를 정상상태로 오거부하는 경우 0.26[%]로 효율적인 진단 방법임을 실험을 통해 알 수 있었다.