• Journal of Power Electronics
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• v.10 no.6
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• pp.702-708
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• 2010

In this paper, a fault diagnosis algorithm for brushless DC (BLDC) motor drives is proposed to maintain control performance under switch open-damage. The proposed fault diagnosis algorithm consists of a simple algorithm using measured phase current information and it detects open-circuit faults based on the operating characteristic of BLDC motors. The proposed algorithm quickly recovers control performance due to its short detection time and its reconfiguration of the system topology. It can be embedded into existing BLDC drive software as a subroutine without additional sensors. The feasibility of the proposed fault diagnosis algorithm is proven by simulation and experimental results.

• Journal of Power Electronics
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• v.10 no.6
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• pp.686-693
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• 2010

In this paper, a fault diagnosis method based on fuzzy logic for the three-parallel power converter in a wind turbine system is presented. The method can not only detect both open and short faults but can also identify faulty switching devices without additional voltage sensors or an analysis modeling of the system. The location of a faulty switch can be indicated by six-patterns of a stator current vector and the fault switching device detection is achieved by analyzing the current vector. A fault tolerant algorithm is also presented to maintain proper performance under faulty conditions. The reliability of the proposed fault detection technique has been proven by simulations and experiments with a 10kW simulator.

• Proceedings of the KIPE Conference
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• 2015.07a
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• pp.11-12
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• 2015

This study has looked into ways to cut the power supply by predicting electrical fire that may occur in low-voltage cable, which is most frequently used in industrial settings and households. In addition, we have designed a system that cuts off electricity to prevent the fire upon occurrence of events that may cause electrical fire, including short circuit, tracking and contact failure. A lot of previous researches have designed arc suppressors built in analog circuit, which left much to be desired such as difficulty in remote control and inability to identify the location of arc suppressor when it is activated. To address these issues, the study seeks to develop an arc suppressor using micom and to verify its performance through simulations designed to detect arc faults.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.4
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• pp.444-450
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• 2008

There are several ways to bond to building grounding systems for reducing GPR(ground potential rise) and EMI resulting from power system faults or lightning stroke to building. In order to verify effective bonding practice, the GPR and voltage of equipment due to the direct stroke to building are calculated with ATP-EMTP model for transformer, transmission line and MOV(Metal oxide varistor). The simulated model shows a satisfactory accuracy compared with experimental result for the $8/20{\mu}s$ simulated current pulse. It is observed that separate grounding can cause dangerous voltage to the building equipment and the performance of surge protective device can improve when it is installed to the protected equipment in distance as short as possible.

• Proceedings of the KIEE Conference
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• summer
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• pp.304-306
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• 2004

Recently, operating equipment with the high quality is necessary as technology is developing rapidly and equipment becomes more accurate. Therefore, the importance of diagnosis has been rising in modem industries. This paper presents that the induction motor is driven by invertor. We were using EMTP (Electromagnetic Transient Program) to study different characteristics of induction motor caused by faults; single phasing and the short circuit fault. After having the fault occurred in feeder cable, motor current, flux and torque waveform are analyzed

• International conference on construction engineering and project management
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• 2009.05a
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• pp.388-392
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• 2009

Operation of LNG (Liquefied Natural Gas) plants requires an effective maintenance strategy. To this end, the long-term and short-term trend of faults, such as mechanical and electrical troubles, should be identified so as to take proactive approach for ensuring the smooth and productive operation. However, it is not an easy task to predict the fault trend in LNG plants. Many variables and unexpected conditions make it quite difficult for the facility manager to be well prepared for future faulty conditions. This paper presents a model to predict the fault trend in a LNG plant. ARIMA (Auto-Regressive Integrated Moving Average) model is combined with Wavelet Transform to enhance the prediction capability of the proposed model. Test results show the potential of the proposed model for the preventive maintenance strategy.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.5
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• pp.18-28
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• 2009

To analyze influences under faults caused by a stator winding short and to evaluate an effectiveness of a diagnostic algorithm a faulty model for an inverter-driven permanent magnet synchronous motor is presented. Even though the conventional dq motor model obtained through the transformation of phase voltage model is widely used to analyze and control the motor, it can not be used in the analysis of a faulty motor since the 3-phase balanced condition is no longer hold under the fault caused by a stator winding short, and thus, it is very difficult to obtain motor input voltages from the pole voltage of an inverter. To overcome this problem, a faulty model for an inverter-driven permanent magnet synchronous motor is proposed by considering the line voltage of 3-phase variables. The effectiveness of the proposed faulty model is verified through comparative simulations and experiments using DSP TMS320F28335 and motor built to allow a partial short of inter-turn.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.539-542
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• 2003

A motor is the workhorse of our industry. The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. Different internal motor faults (e.g., inter-turn short circuits, broken bearings, broken rotor bars) along with external motor faults (e.g., phase failure, mechanical overload, blocked rotor) are expected to happen sooner or later. This paper introduces the fault detection technique of induction motors based upon the stator current. The fault motors have rotor bar broken or rotor unbalance defect, respectively. The stator currents are measured by the current meters and stored by the time domain. The time domain is not suitable to represent the current signals, so the frequency domain is applied to display the signals. The Fourier Transformer is used for the conversion of the signal. After the conversion of the signals, the features of the signals have to be extracted by the signal processing methods like a wavelet analysis, a spectrum analysis, etc. The discovered features are entered to the pattern classification model such as a neural network model, a polynomial neural network, a fuzzy inference model, etc. This paper describes the fault detection results that use wavelet decomposition. The wavelet analysis is very useful method for the time and frequency domain each. Also it is powerful method to detect the features in the signals.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.8 s.350
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• pp.27-34
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• 2006

During Built-In Self-Test(BIST), The set of patterns generated by a pseudo-random pattern generator may not provide sufficiently high fault coverage and many patterns were undetected fault. In order to reduce the test time, we can remove useless patterns or change from them to useful patterns. In this paper, we reseed modify the pseudo-random and use an additional bit flag to improve test length and achieve high fault coverage. the fat that a random tset set contains useless patterns, so we present a technique, including both reseeding and bit modifying to remove useless patterns or change from them to useful patterns, and when the patterns change, we choose number of different less bit, leading to very short test length. the technique we present is applicable for single-stuck-at faults. the seeds we use are deterministic so 100% faults coverage can be achieve.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.5
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• pp.94-105
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• 2010

To detect faults in an inverter-fed permanent magnet synchronous motor (PMSM) drive under the circumstance having faults in a stator winding and inverter switch, an on-line basis fault detecting scheme during operation is presented. The proposed scheme is achieved by monitoring the second-order harmonic component in q-axis current and the fault is detected by comparing these components with those in normal conditions. The linear interpolation method is employed to determine the harmonic data in normal operating conditions. As soon as the fault is detected, the operating mode is changed to identify a fault type using the phase current waveform. To verify the effectiveness of the proposed fault detecting scheme, a test motor to allow inter-turn short in the stator winding has been built. The entire control algorithm is implemented using DSP TMS320F28335. Without requiring an additional hardware, the fault can be effectively detected by the proposed scheme during operation so long as the steady-state condition is satisfied.