• The Transactions of the Korean Institute of Electrical Engineers P
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• v.56 no.1
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• pp.51-55
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• 2007

In this paper, a portable rotor bar fault diagnosis system for small 3 phase induction motors is suggested. For portable real-tine diagnosis system, an USB-DAQ board for collecting the 3 phase current data, three current probes, and a notebook computer are used. The LabVIEW graphical language is used for filtering, analysis, storing, and monitoring the current data. The three phase stator current are filtered and transformed to frequency level by FIT. An analysis window programed by LabVIEW is located in front panel to show the FIT results and this suggested window has a zooming function to detect the fault feature more easily near the feature frequency range which is varying by the slip frequency. To show the possibility of portable rotor bar diagnosis system, three types(healthy, one rotor bar fault, two rotor bar fault) of rotor bar are intentionally prepared and compared by the suggested window of front panel. Experimental results are shown that a suggested diagnosis system is applicable to portable diagnosis system and the rotor bar fault is detected by the frequency window in front panel programed in LabVIEW graphical language.

• 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).

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.11
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• pp.1657-1662
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• 2017

Rotor bar faults in induction machines, which are a part of main distribution of power system, can even stop the entire system by causing contact between a stator and a rotor. There are two methods of diagnosing rotor bar faults in induction motors, online and offline tests, and existing diagnosis methods have many limitations which can lead to misdiagnosis. This paper proposes a potable rotor bar faults diagnosis system based on single phase rotation test, one of offline test methods, which detects rotor bar faults through impedance interpretation by exciting AC current in a stator winding. The test was conducted on a motor of 0.4kW in the laboratory and a motor of 1500kW in industry field.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.89-99
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• 2018

Downtime and malfunction of industrial rotor machines represents a crucial cost burden and productivity loss. Fault diagnosis of this equipment has recently been carried out to detect their fault(s) and cause(s) by using fault classification methods. However, these methods are of limited use in detecting rotor faults because of their hypersensitivity to unexpected and different equipment conditions individually. These limitations tend to affect the accuracy of fault classification since fault-related features calculated from vibration signal are moved to other regions or changed. To improve the limited diagnosis accuracy of existing methods, we propose a new approach for fault diagnosis of rotor machines based on the model generated by supervised learning. Our work is based on feature residual values from vibration signals as fault indices. Our diagnostic model is a robust and flexible process that, once learned from historical data only one time, allows it to apply to different target systems without optimization of algorithms. The performance of the proposed method was evaluated by comparing its results with conventional methods for fault diagnosis of rotor machines. The experimental results show that the proposed method can be used to achieve better fault diagnosis, even when applied to systems with different normal-state signals, scales, and structures, without tuning or the use of a complementary algorithm. The effectiveness of the method was assessed by simulation using various rotor machine models.

• 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.

• Journal of KSNVE
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• v.3 no.3
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• pp.279-283
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• 1993

A diagnostic method of anisotropy and asymmetry in rotor systems utilizing the two-sided directional spectra of the operating responses has been presented and tested with a laboratory flexible rotor-bearing system. The experimental results show that the directional spectra can be effectively used for the diagnosis of anisotropy and/or asymmetry in rotor systmes by the investigation of -1X and +2X components in the directional spectrum of unbalance and gravity responses.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.48 no.11
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• pp.742-747
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• 1999

On-line diagnosis system has been developed and is now applied the detection of shorted turns in the field winding of large generator. This system consists of data aquisition system and display PC. The data aquisition system detects voltage waveforms from flux probe sensor installed in the stator slot. The display PC shows theshorted-turn situation of generator rotor winding. A shorted-turn diagnosis test wasperformed on five gas turbine generators at the Seoinchon combined cycle power plant. The test was conducted using an new diagnosis system and digital oscilloscope which can identify the pole location, the slot number and the number of shorted turns within each slot. It is confirmed that results of two systems are very same in the field tests.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.827-838
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• 2023

Centrifugal pump is a key part of nuclear power plant systems, and its health status is critical to the safety and reliability of nuclear power plants. Therefore, fault diagnosis is required for centrifugal pump. Traditional fault diagnosis methods have difficulty extracting fault features from nonlinear and non-stationary signals, resulting in low diagnostic accuracy. In this paper, a new fault diagnosis method is proposed based on the improved particle swarm optimization (IPSO) algorithm-based variational modal decomposition (VMD) and relevance vector machine (RVM). Firstly, a simulation test bench for rotor faults is built, in which vibration displacement signals of the rotor are also collected by eddy current sensors. Then, the improved particle swarm algorithm is used to optimize the VMD to achieve adaptive decomposition of vibration displacement signals. Meanwhile, a screening criterion based on the minimum Kullback-Leibler (K-L) divergence value is established to extract the primary intrinsic modal function (IMF) component. Eventually, the factors are obtained from the primary IMF component to form a fault feature vector, and fault patterns are recognized using the RVM model. The results show that the extraction of the fault information and fault diagnosis classification have been improved, and the average accuracy could reach 97.87%.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.655-656
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• 2015

In this paper, diagnosis for 85 high voltage induction motors which have operated for more than 20 years in 18 wide area water supply offices were applied and the results of diagnosis were analysed. Furthermore, main factors that would be affecting rotor defects were selected and correlations between dependent variables which was magnitude for sideband frequency on current during operation and independent variables such as starting characteristic, operating time, number of operation, load factor, maker, rotation speed, capacity were analysed. It was clear that factors including starting characteristic, number of operation, maker, rotation speed caused break by correlation analysis. From this, regression equation was deduced through regression analysis. Based on suggested regression equation, it is applied usefully that we can estimate the condition of rotor without onsite diagnosis and plan the schedule of diagnosis.