• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.540-545
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• 2001

In case of small motors, coil bundle occupies a large portion of stator in view of mass and volume as well as dynamics. It is observed through modal test on the stator of an IPM BLDC (interior permanent magnet brushless direct current) motor that coil bundle wound on the stator core causes the first and second natural frequencies to decrease by about 20-30% compared with those of bare stator. Especially the third natural frequency is newly observed below 3 KHz, which is not observed on the bare stator. It is found that at the third mode the end-coil and the core vibrate out of phase in radial direction. In this paper, the stator is dynamically modeled in terms of the core and the coil bundle consisting of the end-coil and the slot coil based on the above observations for the prediction of dynamic properties. The core can easily be modeled using finite element method with its actual material properties and geometric shape. The concept of equivalent bending stiffness is used for modeling of the end-coil so that predictions may match with the measured natural frequencies for the end-coil cut out of the stator. Although the same concept can be applied to the slot coil, separation of the slot coil from the stator is impractical. Therefore, equivalent bending stiffness of the slot coil is determined through iterative comparisons with the measurements of natural frequencies of the stator with the slot coil in it.

• Journal of Sensor Science and Technology
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• v.22 no.5
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• pp.333-337
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• 2013

This study proposes a simply fabricated micro stator for higher output power than previously reported micro stators. The stator has been fabricated by inserting enamel coil in silicon mold formed by micro etching process. The most merits of the proposed micro stator are the simple fabrication process and high output power. Previously reported micro stators have high resistance because the micro coil is fabricated by relatively thin-film-based deposition process such as sputtering and electroplating. In addition, the previously reported micro coil has many electrical contact points for forming the coil structure. These characteristics of the micro stator can lead to low performance in output power. However, the proposed micro stator adopts commercially available enamel coil without any contact point. Therefore, the enamel coil of the proposed micro stator has low junction resistance due to the good electrical quality compared with the deposited or electroplated metal coil. Power generation tests were performed and the fabricated stator can produce 5.4 mW in 4000 RPM, $1{\Omega}$ and 0.3 mm gap. The proposed micro stator can produce larger output power than the previously reported stator spite of low RPM and the larger gap between the permanent magnet and the stator.

• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.571-575
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• 2008

Stator insulation quality assessment for high voltage motors is a major issue for the reliable maintenance of industrial and power plants. To assess the condition of stator insulation, nondestructive tests were performed on the sixty coil groups of twelve motors. After completing the nondestructive tests, the AC voltage applied to the stator winding was gradually increased until insulation failure in order to obtain the breakdown voltage. The stator winding of each motor was classified into five coil groups; one group with healthy insulation and four groups with four different types of artificial defects. To analyze the breakdown voltage statistically, Weibull distribution was employed for the tests on the fifty coil groups of ten motors. The 50th percentile values of the measured breakdown voltages based on the statistical data of the five coil groups of ten motors were 26.1kV, 25.0kV, 24.4kV, 26.7kV and 30.5kV, respectively. Almost all of the failures were located in the line-end coil at the exit of the core slot. The breakdown voltages and the types of defects showed strong relation to the stator insulation tests such as in the case of dissipation factor and ac current. It is shown that the condition of the motor insulation can be determined from the relationship between the probability of failure and the type of defect.

• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.3
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• pp.197-203
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• 2009

This paper presents a novel method to diagnose magnetization faults produced during magnetization process using stator coils of a brushless dc motor with concentrated windings. It is demonstrated that the stator coil magnetization faults can cause a drop of energy efficiency of the brushless dc motor through computer simulations using a magnetization fault model and efficiency test using compressors. The proposed method diagnoses the stator coil magnetization faults by using an inverter during the brushless dc motor driving test after the magnetization process is completed. An experimental study on the brushless dc motor for compressor shows that the stator coil magnetization faults can be detected with high sensitivity.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.8
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• pp.766-771
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• 2005

In this study, PD(partial discharge) signals which occur at stator coil of traction Motor are acquired these data are used for classifying the PD sources. NN(neural network) has recently applied to classify the PD pattern. The PD data are used for the learning process to classify PD sources. The PD data come from normal specimen and defective specimens such as internal void discharges, slot discharges and surface discharges. PD distribution parameters are calculated from a set of the data, which is used to realize diagnostic algorithm. NN which applies distribution parameters is useful to classify the PD patterns of defective sources generating in stator coil of traction motor.

• KIEE International Transactions on Electrophysics and Applications
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• v.5C no.6
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• pp.223-227
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• 2005

Insulation failure of traction motor stator coil depends on the continuous stress imposed on it and knowing its insulation condition is an issue of significance for proper safety operation. In this paper, application of the NN (Neural Network) as a scheme of the off-line PD (partial discharge) diagnosis method that occurs at the stator coil of a traction motor was studied. For PD data acquisition, three defective models were made; internal void discharge model, slot discharge model and surface discharge model. PD data for recognition were acquired from a PD detector. Statistical distributions and parameters were calculated to perform recognition between model discharge sources. These statistical distribution parameters are applied to classify PD sources by the NN with a good recognition rate on the discharge sources.

• Proceedings of the KIEE Conference
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• 2005.07c
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• pp.2226-2228
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• 2005

High voltage induction motor is the important equipment for ensuring the driving performance of the electric train. PD(partial discharge) is a good indicator for showing the insulation performance of stator coil in HV induction motor. This paper has investigated the characteristics of PD occurrence aspects for both the sound and defective stator coil which consist of maximum PD amplitude(V), total occurrence number, average PD amplitude(V) and PD amplitude(v) - PD occurrence number(n). They were compared with each other depending on applied voltages and reconstructed to $60{\times}60$ matrices of PD amplitude(v)-occurrence phase (${\phi}$)-occurrence number(n) which is the good way to estimate the PD sources in stator coil.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.1183-1186
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• 2004

Degradation and insulation failure of traction motor depend on the continuous stress imposed on it. And knowing on insulation condition is important thing for safety operation of EMU(electric multiple unit). In this paper, PD(partial discharge) characteristics for degradation analysis of stator coil is studied. For PD data acquisition, two models are made; one is normal condition coil, the other is aged condition coil. And PD data for discrimination were acquired from PD detector. And these data making use of a computer-aided discharge analyser, statistical and other discharge parameters is calculated to discrimination between different discharge sources. And also these parameter is applied to classify PD sources by neural networks. Neural Networks has good recognition rate for degradation of stator coil.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2219-2226
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• 2017

This paper deals with artificial neural network approach for automatic detection of severity level of stator winding fault in induction motor. The problem is faced through modelling and simulation of induction motor with inter coil shorting in stator winding. The sum of the absolute values of difference in the peak values of phase currents from each half cycle has been chosen as the main input to the classifier. Sample values from workspace of Simulink model, which are verified with experiment setup practically, have been imported to neural network architecture. Consideration of a single input extracted from time domain simplifies and advances the fault detection technique. The output of the feed forward back propagation neural network classifies the short circuit fault level of the stator winding.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.3
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• pp.46-51
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• 2002

Recently, High capacity alternator are used fur some special equipments in industry. But, several serious problem are occured, especially, broken coil of rotor, caused by crash with stator on rotating the rotor. Although added coil cover thor protect coil of rotor, coil cover is broken. In this study purpose 2 step for corrected that problems. First, three dimensional finite element method far investigate what is most important point. For that purpose, performed stress analysis of coil and coil cover that modeling and finite analysis by ANSYS software. Second, Apply prestress when winding the coil on stator to modify direction of net force. Vector analysis is used for determine corrected prestress. Result of the analysis and prestress are reviewed.