• 전기학회논문지
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• 제57권12호
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• pp.2313-2321
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• 2008

In order to develop reliable on-site partial discharge(PD) pattern recognition algorithm, the fuzzy neural network based on fuzzy set(FNN) and the polynomial network pattern classifier based on fuzzy Inference(PNC) were investigated and designed. Using PD data measured from laboratory defect models, these algorithms were learned and tested. Considering on-site situation where it is not easy to obtain voltage phases in PRPDA(Phase Resolved Partial Discharge Analysis), the measured PD data were artificially changed with shifted voltage phases for the test of the proposed algorithms. As input vectors of the algorithms, PRPD data themselves were adopted instead of using statistical parameters such as skewness and kurtotis, to improve uncertainty of statistical parameters, even though the number of input vectors were considerably increased. Also, results of the proposed neuro-fuzzy algorithms were compared with that of conventional BP-NN(Back Propagation Neural Networks) algorithm using the same data. The FNN and PNC algorithms proposed in this study were appeared to have better performance than BP-NN algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.1811-1812
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• 2008

This paper represents a absolute position tracking system with sensor fusion and PD-gain. this paper presents an accurate localization method by relative and absolute sensor fusion and PD control for position tracking of mobile robot. we developed a sensor based absolution position tracking and smooth moving algorithm using this algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.195-195
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• 2000

In this paper, intelligent control method using neural network as a nonlinear controller is presented, Neural network controller is implemented on DSP board in PC to make real time computing possible, On-line training algorithm for neural network control is proposed, As a test-bed, a large a-x table was build and interface with PC has been implemented, Experimental results under different PD controller gains show excellent position tracking for circular trajectory compared with those for PD controller only.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2004년도 추계학술대회 논문집 Vol.17
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• pp.653-657
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• 2004

In this study, PD(partial discharge) signals which occurrs at stator coil of traction Motor are acquired. these data are used for classifying the PD sources. W(Neural Network) has recently applied to classify the PB 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.

• 대한불안의학회지
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• 제12권1호
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• pp.47-55
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• 2016

30% of patients with panic disorder (PD) show treatment-resistant and chronic waxing and waning course. Therefore, adequate treatment strategies for PD by evidence based pharmacotherapy and combined cognitive behavioral therapy (CBT) are recommended. Regarding how and why CBT for PD works, three hypotheses include the cognitive theory, anxiety control theory, and behavioral theory were discussed. The recent findings that the altered activation in frontal lobe is normalized after CBT, suggest a reduction of an altered top-down fear processing in the neural correlates of CBT in PD. In order to improve accessibility to CBT, brief CBT and internet based CBT for PD were suggested. Despite limitations of sample sizes and study design, most of studies suggest that brief CBT is more effective than control conditions, and even as equally effective as standard CBT. The evidences suggest that internet based CBT may not be significantly different from face-to-face CBT in reducing anxiety. Several advances within the field of third-wave CBT for PD have led to the development of new techniques based on mindfulness, such as mindfulness-based cognitive therapy and acceptance and commitment therapy. Based on Korean algorithm project for panic disorder, especially the psychological education and cognitive reconstruction components were recommended in CBT with PD.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 D
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• pp.2221-2223
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• 2004

본 논문에서는 유전알고리즘을 기반으로 하여 설계된 광 디스크 드라이브의 광학헤드 구동기용 퍼지 PI/PD 제어기를 제안한다. 본 논문에서 제안하는 제어기는 광디스크 드라이브의 광학헤드용 구동기의 포커싱 서보계, 트랙킹 서보계를 제어할 수 있는 퍼지 제어기이며 유전알고리즘을 통해 최적의 퍼지 규칙을 도출한다. 그리고 이를 토대로 모의실험을 수행한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 B
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• pp.468-470
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• 1997

This paper presents an estimation method of the number of partial discharge(PD) sources and their locations in power transformer. To identify multiple PD sources and their locations, the directions-of-arrival estimation algorithm is employed. The results of simulations shows that the proposed method could be accurately detect the number of PD sources and their locations in power transformer.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 C
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• pp.1304-1306
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• 1995

In this study, a neural network algorithm through a data standardization method was developed to discriminate the phase-shifted partial discharge(PD) patterns such as a $\phi$-q-n pattern. Considering the PD measurement in the field, it is not so easy to acquire absolute phase angles of PD pulses. As a consequence, one of the significant problems to be solved in applying the neural network algorithm to practical systems is to develop a method that can discriminate phase-shifted $\phi$-q-n patterns. Therefore, authors established a new method which could convert phase-shifted $\phi$-q-n patterns to a standardized $\phi$-q-n pattern which was not influenced by phase shifting. This new standardization method improved the recognition performance of a neural network for the phase-shifted $\phi$-q-n patterns considerably.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 추계학술대회논문집
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• pp.736-742
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• 2008

This paper proposes new searching algorithm for the optimal PD gains of flexible rotor supported by active magnetic bearings. Under the assumption of linearized bearing parameters with respect to PD gains, the performance index in quadratic form is defined and steepest descent method is adopted for determining local minimum. Moreover, the eigenpair sensitivity concept is utilized to evaluate the sensitivity of performance index. To evaluate the effectiveness of suggested algorithm, the finite element model is constructed and its reduced model is retained in modal domain. Given starting gains, the optimal gains are successfully found and the control performance is demonstrated by simulation to show the efficiency of the proposed method.

• 전자공학회논문지CI
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• 제37권5호
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• pp.19-28
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• 2000

구륜 이동 로봇(Wheeled Mobile Robot)은 제어기 설계에 있어 Nonholonomic Constraints등에 의해 많은 어려움을 지닌다. 본 논문에서는 구륜 이동 로봇의 제어를 위해 PD와 퍼지 시스템이 결합된 제어기가 설계되며, 유전알고리즘에 기초되어 최적 퍼지시스템이 형성된다. 시스템의 최적화 과정은 독립적으로 수행되는 여러 단계들로 이루어지며, 각 단계마다 다른 형식의 알고리즘이 적용되며 효율적 탐색을 위해 Niche알고리즘 및 면역 알고리즘이 결합되어 적용된다. 각 출력용어집합은 최적의 원소들을 얻기 위해 수행되는 탐색에 의해 그 구성이 변화되며, 변화된 출력용어집합의 구성 원소와 관계된 규칙기반이 동시에 조절된다. 출력용어집합의 추가된 원소들 및 조절된 규칙에 대한 적합성이 평가되고 제어 성능의 향상에 기여하지 못한 부분들은 제거된다. 출력변수의 용어집합 및 규칙에 대한 반복적 조절 과정이 완료된 후, 입력 소속함수들에 대한 조정이 제약조건을 가지고 수행되며, 진화연산에 의한 출력소속함수들에 대한 조정이 수행된다.