• 조명전기설비학회논문지
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• 제19권3호
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• pp.10-16
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• 2005

본 논문에서는 퍼지 이득 조정기를 이용한 황전등 전원장치를 제안하고, 회로를 설계하고 제작을 통해 성능을 확인하였다. 직렬 공진 하프 브리지 인버터를 기본으로 하여 전원변동 및 출력 보상을 위한 PFM(Pulse Frequency Modulation), 영전압 스위칭, 소프트 스위칭, 소프트 스타트를 적용하고 퍼지 이득 조정 알고리즘을 통해 역률과 효율을 개선하여 마그네트론의 수명 연장 및 안정된 출력을 얻을 수 있도록 하였고, 기존의 고정 출력에서 $900\~1250[W]$ 연속 가변 출력이 가능하게 하였다. 제작된 전원장치는 전원 전압의 변동에 대하여 상용 전원 $220V{\pm}15[\%]$에서 안정적인 출력 특성과 광효율 97[1m/W], 역률 $96[\%]$로서 만족한 결과를 얻을 수 있었다.

• Smart Structures and Systems
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• 제26권4호
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• pp.495-506
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• 2020

Monitoring of complex processes faces several challenges mainly due to the lack of relevant sensory information or insufficient elaborated decision-making strategies. These challenges motivate researchers to adopt complex data processing and analysis in order to improve the process representation. This paper presents the development and implementation of quality monitoring framework based on a model-driven approach using embedded artificial intelligence strategies. In this work, the strategies are applied to the supervision of a microfabrication process aiming at showing the great performance of the framework in a very complex system in the manufacturing sector. The procedure involves two methods for modelling a representative quality variable, such as surface roughness. Firstly, the hybrid incremental modelling strategy is applied. Secondly, a generalized fuzzy clustering c-means method is developed. Finally, a comparative study of the behavior of the two models for predicting a quality indicator, represented by surface roughness of manufactured components, is presented for specific manufacturing process. The manufactured part used in this study is a critical structural aerospace component. In addition, the validation and testing are performed at laboratory and industrial levels, demonstrating proper real-time operation for non-linear processes with relatively fast dynamics. The results of this study are very promising in terms of computational efficiency and transfer of knowledge to manufacturing industry.

• 전자공학회논문지CI
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• 제38권6호
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• pp.26-37
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• 2001

일반적인 역전파 알고리즘의 여러 가지 문제점들을 개선하기 위하여 활성화 함수의 이득을 퍼지 로직 시스템을 이용하여 자동 조절하는 방식을 제안하였다. 퍼지 로직 시스템을 구성하기 위하여 먼저 활성화 함수의 이득의 변화가 학습율, 연결강도 바이어스 등의 변화와 등가인 관계를 조사하였다 퍼지 로직 시스템의 입력은 마지막층에 대한 오차의 감도와 은닉층에 대한 오차의 평균 감도를 사용하였고, 출력은 활성화 함수의 이득을 사용하였다. 제안한 방식과 일반적인 역전파 알고리즘을 패리티 문제, 함수 근사화 문제 및 패턴 인식 문제등에 대하여 시뮬레이션하여 비교 검토한 결과 수렴비, 평균 학습 반복수, 정말도 및 새로운 입력 에 대한 원하는 오차 범위의 출력을 얻는 등의 성능이 개선됨을 알았다.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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• pp.1886-1900
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• 2018

This paper proposes a confronting feedback control structure and controllers for positive output elementary super lift Luo converters (POESLLCs) working in discontinuous conduction mode (DCM). The POESLLC offers the merits like high voltage transfer gain, good efficiency, and minimized coil current and capacitor voltage ripples. The POESLLC working in DCM holds the value of not having right half pole zero (RHPZ) in their control to output transfer function unlike continuous conduction mode (CCM). Also the DCM bestows superlative dynamic response, eliminates the reverse recovery troubles of diode and retains the stability. The proposed control structure involves two controllers respectively to control the voltage (outer) loop and the current (inner) loop to confront the time-varying ON/OFF characteristics of variable structured systems (VSSs) like POESLLC. This study involves two different combination of feedback controllers viz. the proportional integral controller (PIC) plus sliding mode controller (SMC) and the fuzzy logic controller (FLC) plus SMC. The state space averaging modeling of POESLLC in DCM is reviewed first, then design of PIC, FLC and SMC are detailed. The performance of developed controller combinations is studied at different working states of the POESLLC system by MATLAB-Simulink implementation. Further the experimental corroboration is done through implementation of the developed controllers in PIC 16F877A processor. The prototype uses IRF250 MOSFET, IR2110 driver and UF5408 diodes. The results reassured the proficiency of designed FLC plus SMC combination over its counterpart PIC plus SMC.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 에너지변화시스템부문
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• pp.29-31
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• 2009

Optimal efficiency control of synchronous reluctance motor(SynRM) is very important in the sense of energy saving and conservation of natural environment because the efficiency of the SynRM is generally lower than that of other types of AC motors. This paper is proposed an efficiency optimization control for the SynRM which minimizes the copper and iron losses. The design of the speed controller based on fuzzy-neural networks (FN)-PI controller that is implemented using fuzzy control and neural networks. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization control is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses In variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the proposed controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• 한국사회정책
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• 제25권4호
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• pp.301-321
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• 2018

이 논문의 목적은 공적연금제도의 양적인 측면과 질적인 측면의 어떠한 결합형태가 노인빈곤감소율을 설명하는 원인조건이 되는지를 분석하는데 있다. 이를 위해 노인빈곤감소율을 결과조건변수로, 공적연금지출 비중, 재분배지수, 1층 공적연금비중, 2층 공적연금비중과 2층 강제적 사적연금비중을 원인조건변수로 하는 퍼지셋 질적비교분석을 수행했다. 분석결과, 높은 공적연금지출 비중, 낮은 2층 공적연금비중과 높은 2층 강제적 사적연금비중의 결합은 높은 노인빈곤감소율의 원인조건이 되고 있었다. 그리고 낮은 노인빈곤감소율의 원인조건으로는 보다 다양한 결합 형태가 발견되었다. 이 논문은 이상의 연구결과를 토대로 정책적 제언을 제시했다.

• Computers and Concrete
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• 제21권5호
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• pp.525-530
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• 2018

As a nondestructive testing method, the Schmidt rebound hammer is widely used for structural health monitoring. During application, a Schmidt hammer hits the surface of a concrete mass. According to the principle of rebound, concrete strength depends on the hardness of the concrete energy surface. Study aims to identify the main variables affecting the results of Schmidt rebound hammer reading and consequently the results of structural health monitoring of concrete structures using adaptive neuro-fuzzy inference system (ANFIS). The ANFIS process for variable selection was applied for this purpose. This procedure comprises some methods that determine a subsection of the entire set of detailed factors, which present analytical capability. ANFIS was applied to complete a flexible search. Afterward, this method was applied to conclude how the five main factors (namely, age, silica fume, fine aggregate, coarse aggregate, and water) used in designing concrete mixture influence the Schmidt rebound hammer reading and consequently the structural health monitoring accuracy. Results show that water is considered the most significant parameter of the Schmidt rebound hammer reading. The details of this study are discussed thoroughly.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권4호
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• pp.238-245
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• 2016

Inverters are considered the basic building blocks of industrial electrical drive systems that are widely used for various applications; however, the failure of electronic switches mainly affects the constancy of these inverters. For safe and reliable operation of an electrical drive system, faults in power electronic switches must be detected by an efficient system that is capable of identifying the type of faults. In this paper, an open switch fault identification technique for a three-phase inverter is presented. Single, double, and triple switching faults can be diagnosed using this method. The detection mechanism is based on stator current analysis. Discrete wavelet transform (DWT) using Daubechies is performed on the Clarke transformed (-) stator current and features are extracted from the wavelets. An artificial neural network is then used for the detection and identification of faults. To prove the feasibility of this method, a Simulink model of the DWT-based feature extraction scheme using a neural network for the proposed fault detection system in a three-phase inverter with an induction motor is briefly discussed with simulation results. The simulation results show that the designed system can detect faults quite efficiently, with the ability to differentiate between single and multiple switching faults.

• 조명전기설비학회논문지
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• 제25권4호
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• pp.45-56
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• 2011

This paper is proposed artificial neural network(ANN) rotor resistance estimation of induction motor drive controlled by multi-adaptive fuzzy learning controller(AFLC). A simple double layer feedforward ANN trained by the back-propagation technique is employed in the rotor resistance identification. In this estimator, double models of the state variable estimations are used; one provides the actual induction motor output states and the other gives the ANN model output states. The total error between the desired and actual state variables is then back propagated to adjust the weights of the ANN model, so that the output of this model tracks the actual output. When the training is completed, the weights of the ANN correspond to the parameters in the actual motor. The estimation and control performance of ANN and multi-AFLC is evaluated by analysis for various operating conditions. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.5-8
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• 2003

This paper presents a methodology to be able to select an appropriate RP system that suits the end use of a part. Evaluation factors used in process selection include major attributes such as accuracy, roughness, strength, elongation, part cost and build time that greatly affect the performance of RP systems. Crisp values such as accuracy and surface roughness are obtained with a new test part developed. The test part is designed with conjoint analysis to reflect users' preference. The part cost and build time that have approximate ranges due to cost and many variable parameters are presented by linguistic values that can be described with triangular fuzzy numbers. Based on the evaluation values obtained, an appropriate RP process for a specific part application is selected by using the modified TOPSIS(Technique of Order Preference by Similarity to Ideal Solution) method. It uses crisp data as well as linguistic variables, and each weight on the alternatives is assigned by using pair-wise comparison matrix. The ranking order helps the decision making of the selection of RP systems.