• 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.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.1
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• pp.99-111
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• 2016

This paper presents an integrated fault diagnosis algorithm for driving motor of In-wheel independent drive electric vehicle. Especially, this paper proposes a method that integrated the high level fault diagnosis and the low level fault diagnosis in order to improve a robustness and performance of the fault diagnosis system. The high level fault diagnosis is performed using the vehicle dynamics analysis and the low level fault diagnosis is carried using the motor system analysis. The validity of the high level fault diagnosis algorithms was verified through $Carsim^{(R)}$ and MATLAB/$Simulink^{(R)}$ cosimulation and the low level fault diagnosis's validity was shown by applying it to a MATLAB/$Simulink^{(R)}$ interior permanent magnet synchronous motor control system. Finally, this paper presents a fault diagnosis strategy by combining the high level fault diagnosis and the low level fault diagnosis.

• Journal of Magnetics
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• v.21 no.3
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• pp.413-420
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• 2016

The permanent magnet synchronous motor has high efficiency driving performance and high power density output characteristics compared with other motors. In addition, it has good regenerative operation characteristics during braking and deceleration driving condition. For this reason, permanent magnet synchronous motor is generally applied as a power train motor for electrical vehicle. In permanent magnet synchronous motor, the most probable causes of fault are demagnetization of rotor's permanent magnet and short of stator winding turn. Therefore, the demagnetization fault of permanent magnet and turn fault of stator winding should be detected quickly to reduce the risk of accident and to prevent the progress of breakdown of power train system. In this paper, the fault diagnosis method using high frequency low voltage injection was suggested to diagnose the demagnetization fault of rotor permanent magnet and the turn fault of stator winding. The proposed fault diagnosis method can be used to check the faults of permanent magnet synchronous motor during system check-up process at vehicle starting and idling stop mode. The feasibility and usefulness of the proposed method were verified by the finite element analysis.

• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.500-504
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• 2007

In this paper, the induction motor rotor fault diagnosis system using current signals, which are measured using axis-transformation method, and speed, which is estimated using current information, are presented. In inverter-fed motor drives unlike line-driven motor drives the stator currents have numerous harmonics components and therefore fault diagnosis using stator currents is very difficult. The current and speed signal for rotor fault diagnosis needs to be precise. Also, high resolution information, which means the diagnosis system, demands additional hardware such as low pass filter, high resolution ADC, encoder and etc. Therefore, the proposed axis-transformation and speed estimation method are expected to contribute to low cost fault diagnosis systems in inverter-fed motor drives without the need for an encoder and any additional hardware. In order to confirm validity of the developed algorithms, various experiments for rotor faults are tested and the line current spectrum of each faulty situation using Park transformation and speed estimation method are compared with the results obtained from fast Fourier transforms.

• Journal of Power Electronics
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• v.7 no.4
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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).

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.9
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• pp.675-681
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• 2014

This paper proposes a fault diagnosis system for an induction motor. This system uses empirical mode decomposition(EMD) to extract fault signatures and multi-layer perceptron(MLP) neural network to facilitate an accurate fault diagnosis. EMD can not only decompose a signal adaptively but also provide intrinsic mode functions(IMFs) containing natural oscillatory modes of the signal. However, every IMF does not represent fault signature, an IMF selection algorithm based on harmonics and their energy of each IMF is proposed. The selected IMFs are utilized for fault classification using MLP and this system shows approximately 98 % diagnosis accuracy for the fault vibration signal of the induction motor.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.2
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• pp.304-310
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• 2016

This paper proposes a fault diagnosis method for an open-fault in inverter driving five-phase induction motor. The five-phase induction motor has a high output torque and small torque ripple in comparison to three-phase. The best advantage of the five-phase induction motor is fault diagnosis and tolerant control using redundancy of phases. This paper uses an inverter as a power converter for driving a five-phase induction motor. If a switch of inverter occurs to the open-fault, this problem is the influence on the output current and output torque. To solve this problem, there is need of an accurate diagnosis and fault switch distinction. Therefore, this paper propose a fault detection method of the open-fault switches for the fault diagnosis. First, analyzing the pattern for the open-circuit fault of one phase. next, analyzing the pattern for the open-circuit fault of each inverter switches. Through the pattern analysis, It defines the scope of each of the failure switch. Thereafter, By using an algorithm that proposes to perform a fault diagnosis method. The proposed algorithm is verified from the experiment with the 1.5 kW five-phase induction motor.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.24-26
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• 2005

At present, KS-1000 which is one of a commercial measurement instrument for motor fault diagnosis has been used in industrial field. The measurement system of KS-1000 is composed of three part : harmonic acquisition, signal processing by KS-1000 algorithm, diagnosis for motor fault. First of all, voltage signal taken from harmonic sensor is analysed for frequency by KS-1000 algorithm. Then, based on the result values of analysis skilled expert makes a judgment about whether motor system is the abnormality or degradation state. But the expert system such a motor fault diagnosis is very difficult to bring the expectable results by mathematical modeling due to the complexity of judgment process. In this reason, we propose an automation system using fuzzy model based on genetic algorithm(GA) that builded a qualitative model of a system without priori knowledge about a system provided numerical input output data.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07a
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• pp.518-521
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• 2003

A new measurement system was developed by fault diagnosis system for traction motor using current signal analysis. The motor current signature analysis method is used for traction motor fault diagnosis. The diagnosis system program is constructed by artificial neural networks algorithm, those results from the program are used to train neural networks. The trained neural networks have the ability to compute adaptive results for non-trained inputs, and to calculate very fast due to original parallel structure of neural networks with high accuracy within destined tolerance. This system suggested that available test for checking, the probable extent of aging, and the rate of which aging is taking place.

• Journal of Power Electronics
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• v.9 no.2
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• pp.224-231
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• 2009

The induction motor rotor fault diagnosis system using current signals, which are measured using an axis-transformation method, is presented in this paper. In inverter-fed motor drives, unlike line-driven motor drives, the stator currents are rich in harmonics; 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, and encoder, etc. The proposed axis-transformation method with encoder and without encoder 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 Park transformation is compared with the results obtained from fast Fourier transforms.