• Journal of Power Electronics
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• 제15권1호
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• pp.131-145
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• 2015

The voltage-source inverters (VSI) supplying a motor drive are prone to open transistor faults. To address this issue in fault-tolerant drives applicable to electric vehicles, a new open transistor fault diagnosis (FD) method is presented in this paper. According to the proposed method, in order to define the FD index, the phase angle of the converter output current is estimated by a simple trigonometric function. The proposed FD method is adaptable, simple, capable of detecting multiple open switch faults and robust to load operational variations. Keeping the FD in mind as a mandatory part of the fault tolerant control algorithm, the FD block is applied to a five-phase converter supplying a multiphase fault-tolerant PM motor drive with non-sinusoidal unbalanced current waveforms. To investigate the performance of the FD technique, the fault-tolerant sliding mode control (SMC) of a five-phase brushless direct current (BLDC) motor is developed in this paper with the embedded FD block. Once the theory is explained, experimental waveforms are obtained from a five-phase BLDC motor to show the effectiveness of the proposed FD method. The FD algorithm is implemented on a field programmable gate array (FPGA).

• 대한전기학회논문지:시스템및제어부문D
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• 제49권12호
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• pp.643-650
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• 2000

Using neural network approach, the diagnosis of faults in industrial process that requires observing multiple data simultaneously are studied. Two-stage diagnosis is proposed to analyze system faults. By using neural network, the first stage detects the dynamic trend of each normalized date patterns by comparing a proposed pattern. Instead of using neural network, the difference between stored fault pattern and real time data is used for fault diagnosis in the second stage. This method reduces the amount of calculation and saves storing space. Also, we dealt with unknown faults by normalizing the data and calculating the difference between the value of steady state and the data in case of fault. A model of tank reactor is given to verify that the proposed method is useful and effective to noise.

• Journal of Power Electronics
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• 제15권6호
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• pp.1664-1672
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• 2015

This paper proposes a series arc fault detection algorithm which incorporates peak voltage and harmonic current detectors for single-phase boost power factor correction (PFC) rectifiers. The series arc fault model is also proposed to analyze the phenomenon of the arc fault and detection algorithm. For arc detection, the virtual dq transformation is utilized to detect the peak input voltage. In addition, multiple combinations of low- and high-pass filters are applied to extract the specific harmonic components which show the characteristics of the series arc fault conditions. The proposed model and the arc detection method are experimentally verified through a boost PFC rectifier prototype operating under the grid-tied condition with an artificial arc generator manufactured under the guidelines for the Underwriters Laboratories (UL) 1699 standard.

• Transactions on Control, Automation and Systems Engineering
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• 제1권1호
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• pp.54-61
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• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. By using the FCM, authors have proposed FCM-based fault diagnostic algorithm. However, it can offer multiple interpretations for a single fault. In process engineering, as experience accumulated, some form of quantitative process knowledge is available. If this information can be integrated into the FCM-based fault diagnosis, the diagnostic resolution can be further improved. The purpose of this paper is to propose an enhanced FCM-based fault diagnostic scheme. Firstly, the membership function of fuzzy set theory is used to integrate quantitative knowledge into the FCM-based diagnostic scheme. Secondly, modified TAM recall procedure is proposed. Considering that the integration of quantitative knowledge into FCM-based diagnosis requires a great deal of engineering efforts, thirdly, an automated procedure for fusing the quantitative knowledge into FCM-based diagnosis is proposed by utilizing self-learning feature of neural network. Finally, the proposed diagnostic scheme has been tested by simulation on the two-tank system.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권10호
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• pp.575-582
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• 2003

A new FDOs (fault diagnostic observers) and the residual generation schemes using the FDOs are suggested for the process fault detection and isolation of linear (control) systems. The design method of the FDO is described, first, for the full measurement systems. Then it is extended for the systems with unmeasurable state variables. An unknown input observer is proposed and applied for the extension. The size of the observer bank may be the smallest, specially in full measurement systems, because the order of the proposed FDO is very low. In spite of the simplicity, the scheme provides the same information for the detection and isolation of the anticipated faults as the conventional multiple observer based schemes. The residuals may be structured so that fault isolation can be performed by pre-selected logic. An FDIS using the proposed scheme is constructed for the model of the four-tank system. Simulation results show the practical feasibility of the proposed scheme.

• 한국정보통신학회논문지
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• 제24권11호
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• pp.1558-1561
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• 2020

In this paper, we propose a blockchain scheme to enhance fault tolerance in distributed storage blockchain systems. Traditional blockchain systems suffer from ever-increasing storage cost. To overcome this problem, distributed storage blockchain techniques have been proposed. Distributed storage blockchain schemes effectively reduce the storage cost, but there are still limitations in reducing recovery cost and fault tolerance. The proposed approach recovers multiple errors within a group by utilizing locally repairable codes with availability. This improves the fault tolerance of the blockchain systems. Simulation results show that the proposed scheme enhances the fault tolerance while minimizing storage cost and recovery cost compared to other state-of-art schemes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2576-2581
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• 2003

We consider fault detection and isolation (FDI) problem for inertial navigation systems (INS) which use redundant inertial sensors and propose an FDI method using average of multiple parity vectors which reduce false alarm and wrong isolation, and improve correct isolation. We suggest optimal isolation threshold based on navigation performance, and suggest optimal sample number to obtain short detection time and to enhance detectability of faults little larger than threshold.

• Journal of Mechanical Science and Technology
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• 제19권3호
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• pp.731-742
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• 2005

A magnetic bearing even with multiple coil failure can produce the same decoupled magnetic forces as those before failure if the remaining coil currents are properly redistributed. This fault-tolerant, force invariance control can be achieved with simply replacing the distribution matrix with the appropriate one shortly after coils fail, without modifying feedback control law. The distribution gain matrix that satisfies the necessary constraint conditions of decoupling linearized magnetic forces is determined with the Lagrange Multiplier optimization method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2188-2191
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• 2005

We consider a fault detection and isolation problem for inertial navigation systems which use redundant inertial sensors. We propose a FDI method using average of multiple parity vectors which reduce false alarm and wrong isolation, and improve correct isolation. We suggest the number of redundant sensors required to isolate simultaneous faults. The performance of the proposed FDI algorithm is analyzed by Monte-Carlo simulation.

• 대한전자공학회논문지
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• 제12권4호
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• pp.21-27
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• 1975

본 논문에서는 분기가 있는 일반조합논리회로의 다중결함을 검출할 수 있는 테스트집합을 구하는 절차를 유도하였다. 일반논리회로를 우선 내부분기점을 전후하여 이를 분기가 없는 부분회로로 분리하고 각 부분회로에 대한 최소테스트집합을 구한다. 다음에 각 부분테스트를 최대한으로 병립시켜 합성테스트를 구하여 종합적인 일차입력벡터를 정한다. 이러날 수 있는 모든 결함을 빠짐없이 피복할 수 있는 최소테스트집합을 구해가는 과정에 대해서는 각 를 들어 상세히 설명하였다. In this paper, a procedure for deriving of multiple fault detection test sets is presented for fan-out reconvergent combinational logic networks. A fan-out network is decomposed into a set of fan-out free subnetworks by breaking the internal fan-out points, and the minimal detecting test sets for each subnetwork are found separately. And then, the compatible tests amonng each test set are combined maximally into composite tests to generate primary input binary vectors. The technique for generating minimal test experiments which cover all the possible faults is illustrated in detail by examples.