• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.2017_2018
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• 2009

DFT는 보호계전기의 알고리즘이나 디지털 미터에서 필수적으로 사용되고 있다. 그런데 DFT 필터는 시간 영역의 신호를 주파수 영역으로 변환하는 과정에서 시간 정보가 손실된다는 단점이 있기 때문에 이를 개선한 DWT가 제안되었다. 본 연구에서는 광역보호계전 지능화를 위한 네트워크 기반 주파수 모니터링 및 고장예측 시스템 개발을 위한 기초적인 연구로서 전력시스템의 초기고장검출과 고장징후 판단을 DWT의 상세계수 에너지성분의 합에 의하여 모색하였다.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.7
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• pp.726-735
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• 2009

In this paper, we propose an approach to signal model-based fault detection and diagnosis system for induction motors. The current fault detection techniques used in the industry are limit checking techniques, which are simple but cannot predict the types of faults and the initiation of the faults. The system consists of two consecutive processes: fault detection process and fault diagnosis process. In the fault detection process, the system extracts the significant features from sound signals using combination of variance, cross-correlation and wavelet. Consequently, the pattern classification technique is applied to the fault diagnosis process to recognize the system faults based on faulty symptoms. The sounds generated from different kinds of typical motor's faults such as motor unbalance, bearing misalignment and bearing loose are examined. We propose two approaches for fault detection and diagnosis system that are waveletand-variance-based and wavelet-and-crosscorrelation-based approaches. The results of our experiment show more than 95 and 78 percent accuracy for fault classification, respectively.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.2
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• pp.48-55
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• 2006

Performance characteristics of the position-domain Hatch filter is analyzed for differential global navigation satellite systems. It is shown that the position-domain Hatch filter generates white measurement residual sequences, which is beneficial property for fault detection. It is also shown that the position-domain Hatch filter yields more accurate a priori state estimate than the position-domain Kalman-type filter. Thus, it can be concluded that the position-domain Hatch filter is beneficial in wide application areas where fault-tolerance and accuracy are required at the same time.

• Journal of Aerospace System Engineering
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• v.17 no.6
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• pp.100-107
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• 2023

Open-phase fault in a Permanent Magnet Synchronous Motor (PMSM) occurs due to disconnection of phases of motor windings or inverter switch failures. When an open-phase occurs, it leads to the generation of torque ripples and vibrations in the motor, which can have a critical impact on the safety of the vehicle (including aircraft) using a PMSM as an actuator. Therefore, rapid fault detection and classification are essential. This paper proposes a classification method for detecting open-phase faults and locating fault positions in a PMSM used in aircraft applications. The proposed approach uses an Extended Kalman Filter for fault diagnosis, and it subsequently classifies faults using a Multiple Model filter.

• Journal of IKEEE
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• v.26 no.2
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• pp.265-270
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• 2022

This paper proposes the detection algorithm for switch open fault of asymmetric 6-phase PMSM based on stationary reference frame dq-axis currents. In this paper, target motor has an asymmetric structure in which two upper three windings have an electrical phase difference of 30° and a neutral point is separated. As a result, dual 3-phase PWM inverters and the detection techniques due to open failures of switch are definitely required. In this paper, the dual dq-axis current control method is used for driving the asymmetric 6-phase PMSM and the open fault switch should be detected by using variable all pass filter and low pass filter in order to detect the current amplitude. The effectiveness and usefulness of the proposed method is verified by several experiments.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.4
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• pp.311-320
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• 2021

A study is performed for the real time fault diagnosis during operation and health estimation relating to performance deterioration in a turbojet engine used for an unmanned air vehicle. For this study the real time dynamic model is derived from the transient thermodynamic gas path analysis. For real fault conditions which are manipulated for the simulation, the detection techniques are applied such as Kalman filter and probabilistic decision-making approach based on statistical hypothesis test. Thereby the effectiveness is verified by showing good fault detection and isolation performances. For the health estimation with measurement parameters, it shows using an assumed performance degradation that the method by adaptive Kalman filter is feasible in practice for a condition based diagnosis and maintenance.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2245-2247
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• 2004

본 논문에서는 미지의 유계를 가진 불확실성을 포함한 비선형 시스템에 대한 고장 진단 설계를 제안한다. 제안된 고장 진단 필터는 비선형 관측기 설계 기술에 기초하여 설계되며, 신경망을 이용하여 고장 성분과 불확실성 성분을 추정하고 추정된 불확실성의 상한값을 고장 진단에 이용한다. 제안된 근사기는 불확실성과 고장 함수를 추정함으로써 고장 검출뿐만 아니라 고장 진단을 확인할 수 있도록 설계된다. 모의실험을 통해서 제안된 고장 진단 설계의 성능을 검증하였다.

• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.822-831
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• 2009

The porcelain insulators are important devices, that are used to isolate electrically and hold mechanically in the high-voltage power transmission systems. The faults of the insulators induce very serious problems to the power transmission line. In this paper, we introduce techniques for fault detections of insulators by acoustic radiation noises from them. We measured radiation noises from normal state insulators and fault state insulators. The used insulators were two different type porcelain insulators, a cut out switch, two different type line posters, and a lightning arrester. Each results was compared each other in time domain, frequency domain and filter banks' outputs. We found the possibility of detection of insulators' faults and also suggested techniques for fault detections.

• The KIPS Transactions:PartB
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• v.18B no.3
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• pp.147-156
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• 2011

This paper proposes a 3-stage (preprocessing, feature extraction, and classification) fault detection and classification algorithm for induction motors. In the first stage, a low-pass filter is used to remove noise components in the fault signal. In the second stage, a discrete cosine transform (DCT) and a statistical method are used to extract features of the fault signal. Finally, a back propagation neural network (BPNN) method is applied to classify the fault signal. To evaluate the performance of the proposed algorithm, we used one second long normal/abnormal vibration signals of an induction motor sampled at 8kHz. Experimental results showed that the proposed algorithm achieves about 100% accuracy in fault classification, and it provides 50% improved accuracy when compared to the existing fault detection algorithm using a cross-covariance method. In a real-world data acquisition environment, unnecessary noise components are usually included to the real signal. Thus, we conducted an additional simulation to evaluate how well the proposed algorithm classifies the fault signals in a circumstance where a white Gaussian noise is inserted into the fault signals. The simulation results showed that the proposed algorithm achieves over 98% accuracy in fault classification. Moreover, we developed a testbed system including a TI's DSP (digital signal processor) to implement and verify the functionality of the proposed algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.2
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• pp.156-165
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• 2009

Threat due to malfunction of space launch vehicles is significant since it is bigger and flights longer range than military missiles or scientific rockets. It is necessary to implement a flight safety system to minimize the possible hazard. Design objective of the tracking filter for the flight safety system is different from conventional tracking filters since estimation reliability is more emphasized than estimation accuracy. In this paper, a fusion tracking filter was implemented for processing multi-sensor data from a space launch vehicle. The filter performance is evaluated by analyzing the error of the estimated position and instantaneous impact point. Also a fault detection algorithm is implemented to guarantee fusion filter's reliability under any sensor failure and verified to maintain stability successfully.