• 한국멀티미디어학회논문지
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• 제20권11호
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• pp.1811-1819
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• 2017

As the induction motor is the core production equipment of the industry, it is necessary to construct a fault prediction and diagnosis system through continuous monitoring. Many researches have been conducted on motor fault diagnosis algorithm based on signal processing techniques using Fourier transform, neural networks, and fuzzy inference techniques. In this paper, we propose a fault diagnosis method of induction motor using LPC and DNN. To evaluate the performance of the proposed method, the fault diagnosis was carried out using the vibration data of the induction motor in steady state and simulated various fault conditions. Experimental results show that the learning time of our proposed method and the conventional spectrum+DNN method is 139 seconds and 974 seconds each executed on the experimental PC, and our method reduces execution time by 1/8 compared with conventional method. And the success rate of the proposed method is 98.08%, which is similar to 99.54% of the conventional method.

• 전기학회논문지
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• 제66권1호
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• pp.144-152
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• 2017

A motor model and off-line diagnosis method of the induction motor having an interturn fault(ITF) is studied. The proposed method is based on the magnitude comparison of the six impedance in the d-q plane. To prove the impedance unbalance, the induction motor model is presented with an ITF circuit loop with a fault resistance. Then, six impedance components in the stationary d-q plane are defined depending on the connected phase windings. Finding the maximum and minimum magnitude of the six impedance, the ITF and the faulty phase can be founded. To verify the proposed method, the experimental results with an induction motor having an ITF are shown.

• Journal of Power Electronics
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• 제7권4호
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• pp.271-277
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• 2007

In this paper, an induction motor rotor fault diagnosis system using current signals, which are measured using the axis-transformation method is presented. Inverter-fed motor drives, unlike line-driven motor drives, have stator currents which are rich in harmonics and therefore fault diagnosis using stator current is not trivial. The current signals for rotor fault diagnosis need precise and high resolution information, which means the diagnosis system demands additional hardware such as a low pass filter, high resolution ADC, an encoder and additional hardware. Therefore, the proposed axis-transformation method is expected to contribute to a low cost fault diagnosis system in inverter-fed motor drives without the need for any additional hardware. In order to confirm the validity of the developed algorithms, various experiments for rotor faults are tested and the line current spectrum of each faulty situation, using the Park transformation, is compared with the results obtained from the FFT(Fast Fourier Transform).

• Journal of Electrical Engineering and Technology
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• 제4권3호
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• pp.389-395
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• 2009

Industrial motors are subject to incipient faults which, if undetected, can lead to motor failure. The necessity of incipient fault detection can be justified by safety and economical reasons. The technology of artificial neural networks has been successfully used to solve the motor incipient fault detection problem. This paper develops inexpensive, reliable, and noninvasive NN based incipient fault detection scheme for small and medium sized induction motors. Detailed design procedure for achieving the optimal NN model and Principal Component Analysis for dimensionality reduction is proposed. Overall thirteen statistical parameters are used as feature space to achieve the desired classification. GFFD NN model is designed and verified for optimal performance in fault identification on experimental data set of custom designed 2 HP, three phase 50 Hz induction motor.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.761-768
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• 2017

This paper deals with the performance analysis of three phase induction motor considering its stator side faults and operating thermal limits. The speed control of induction motor using three phase boost converter operated by a MOSFET switch and a PI controller is demonstrated and presented in this article. IGBTs switches are used for inverter drive mechanism. The experimental result of speed control of induction motor using voltage control technique clearly shows better accuracy than conventional methods of speed control. A three phase 1HP 415V 0.78 kW 4 Pole induction motor is designed using motor solver software. Based on the parameters used in the software thermal analysis of induction motor is done and torque variation with conductor area, efficiency, output curve, losses in different parts of motor has been obtained. Also different types of faults namely under voltage, over voltage, stator imbalanced voltage, turn to turn, locked rotor bar, wrong alignment of rotor bar with respect to stator are studied and fault analysis is performed. Hence comparison is made based upon the results obtained before and after faults.

• 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.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.702-705
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• 1996

Recently, induction motors are used more widely because of their low cost and simple structure. Therefore, the importance of fault detection and isolation of induction motors significantly increases. In most case the line current is used for fault detection and isolation. But in case that an induction motor has an inverter for control, it distorts the information of faulty state included in the line current. This paper proposes a new method for fault detection and isolation of induction motors that is speed controlled by the inverter using frequency analysis of the reference current instead of the line current for fault detection and isolation.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 추계학술대회논문집
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• pp.401-406
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• 2006

This paper presents the fault diagnosis of induction motor based on support vector machine(SVMs). SVMs are well known as intelligent classifier with strong generalization ability. Application SVMs using kernel function is widely used for multi-class classification procedure. In this paper, the algorithm of SVMs will be combined with feature extraction and reduction using component analysis such as independent component analysis, principal component analysis and their kernel(KICA and KPCA). According to the result, component analysis is very useful to extract the useful features and to reduce the dimensionality of features so that the classification procedure in SVM can perform well. Moreover, this method is used to induction motor for faults detection based on vibration and current signals. The results show that this method can well classify and separate each condition of faults in induction motor based on experimental work.

• 전기학회논문지P
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• 제65권1호
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• pp.1-6
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• 2016

Recently, proportion of the induction motor load is gradually increased. When a contingency in the power systems, it has been discovered phenomenon that the voltage is delayed recover caused mechanical characteristics of the induction motor load. It can be a serious impact on the voltage stability of the power system considering induction motor load. The scheme to mitigate this phenomenon tripping off the motors to prevent voltage drop and delayed voltage recovery on the load demand side. Fault induced delayed voltage recovery phenomenon is caused by stalling of small induction motor load in transmission level contingencies. In this paper, fault induced delayed voltage recovery phenomenon mitigation method implementation under voltage load shedding on the korean power system considering induction motor load.