• 제어로봇시스템학회논문지
• /
• 제3권3호
• /
• pp.244-251
• /
• 1997

In this paper, we propose a fault diagnosis algorithm to detect and isolate multiple faults in a system. The proposed fault diagnosis algorithm is based on a multiple fault classifier which consists of two ART2 NN(adaptive resonance theory2 neural network) modules and the algorithm is composed of three main parts - parameter estimation, fault detection and isolation. When a change in the system occurs, estimated parameters go through a transition zone in which residuals between the system output and the estimated output cross the threshold, and in this zone, estimated parameters are transferred to the multiple faults classifier for fault isolation. From the computer simulation results, it is verified that when the proposed diagnosis algorithm is performed successfully, it detects and isolates faults in the position control system of a DC motor.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2004년도 심포지엄 논문집 정보 및 제어부문
• /
• pp.95-97
• /
• 2004

This paper estimates Adaptive Resonance Theory 1(ART1) as a vigilance parameter of pattern clustering algorithm. Inherent characteristics of the model are analyzed. In particular the vigilance parameter ${\rho}$ and its role in classification of patterns is examined. Our estimates show that the vigilance parameter as designed originally does not necessarily increase the number of categories with its value but can decrease also. This is against the claim of solving the stability-plasticity dilemma. However, we have proposed a modified vigilance parameter estimate criterion which takes into account the problem of subset and superset patterns and stably categorizes arbitrarily many input patterns in one list presentation when the vigilance parameter is closer to one.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2004년도 춘계학술발표대회
• /
• pp.781-784
• /
• 2004

본 시스템은 어항속에 있는 물고기 움직임을 추적하기 위해 두 대의 카메라로부터 동시에 독립된 영상을 획득하고 획득된 영상을 처리하여 좌표를 얻어내고 3차원 좌표로 생성해내는 시스템이다. 제안하는 방법은 크게 두 대의 카메라로부터 동시에 영상을 획득하는 방법과 획득된 영상에 대한 처리 및 물체 위치 검출, 그리고 3차원 좌표 생성으로 구성된다. Frame grabber를 사용하여 두 개의 카메라로부터 동시에 영상을 획득하며, 3개의 연속된 프레임에 대한 차영상과 ART2(Adaptive Resonance Theory)를 이용하여 각각의 영상에서의 물고기 위치를 검출한다. 검출된 각각의 좌표를 병합하여 3차원 좌표를 생성하며, 추적 결과는 OpenGL을 이용하여 3차원으로 재생한다.

• 한국항행학회논문지
• /
• 제17권3호
• /
• pp.332-345
• /
• 2013

본 논문에서는 최근, 압전 변압기 기술의 급속한 발전을 이용하므로 자계의 잡음이 없고, 크기가 소형화되며 고효율과 고 전력 밀도, 누설자속이 없어 노이즈 발생이 없고, 공진주파수만을 이용하므로 출력파형이 정현파에 가까워 고조파 잡음이 없는 점을 이용하여 전기적인 등가회로를 적용하여 DC-DC 컨버터를 구현 하였다. 유도전동기 회전자 속도 개념에 자속 기준 모델 적용 시스템(FMRAS)을 적용하였다. 유도전동기의 벡터제어는 회전자 속도 정의의 추정값을 이용하여 실행 할 수 있고, 부가된 변화되는 모델로 회전자 목표값 계산을 수행 할 수 있다. 이 시스템은 PWM 공간 전압기법과 DC-DC 컨버터를 이용하여 벡터전류제어와 속도제어를 위한 PI제어기로 구성되어 있다. 제어를 위한 실행과 높은 속도계산을 디지털 신호 원칩 마이크로프로세서에 의해 수행 되었고, 시뮬레이션과 실험을 통해서 다양한 제어 방법의 타당성을 제시 하였다.

• 한국항만학회지
• /
• 제14권3호
• /
• pp.321-329
• /
• 2000

Welding is essential for the manufacture of a range of engineering components which may vary from very large structures such as ships and bridges to very complex structures such as aircraft engines, or miniature components for microelectronic applications. Especially, a domestic situation of the welding automation is still depend on the arc sensing system in comparison to the vision sensing system. Specially, the gap-detecting of workpiece using conventional arc sensor is proposed in this study. As a same principle, a welding current varies with the size of a welding gap. This study introduce to the fuzzy membership filter to cancel a high frequency noise of welding current, and ART2 which has the competitive learning network classifies the signal patterns the filtered welding signal. A welding current possesses a specific pattern according to the existence or the size of a welding gap. These specific patterns result in different classification in comparison with an occasion for no welding gap. The patterns in each case of 1mm, 2mm, 3mm and no welding gap are identified by the artificial neural network.

• 전자공학회논문지B
• /
• 제33B권2호
• /
• pp.168-177
• /
• 1996

In this paper, we propose an on-line recognition system of chinese characters using an adaptive resonance theory-1(ART-1) neural network. Strokes, primitive components of chinese characters are usually warped into a cursive form and classifying them is very difficult. To deal with such cursive strokes, we use an ART-1 neural network that has the following advantages: (1) it automatically assembles similar patterns together to form classes in a self-organized manner: (2) it directly accesses the recognition codes corresponding to binary input patterns after self-stabilizing; (3) it doesn't tends to get trapped in local minima, or globally incorrect solutions. A database for character recognition also dynamically constructed with generalized character lists, and a new character can be included simply by adding a new sequence to the list. Character recognition is achieved by traversing the chinese datbase with a sequence of recognized strokes and positional relations between the strokes. To verify the performance of the system. We tested it for 1800 daily-used basic chinese second per character. This results suggest that the proposed system is pertinent to be put into practical use.

• 한국지능시스템학회논문지
• /
• 제14권7호
• /
• pp.830-837
• /
• 2004

본 논문에서는 비선형시스템에서 발생한 고장을 감지하고 분류하기 위한 신경회로망기반 고장진단 방법을 제안한다. 제안한 알고리듬에서는 시스템의 출력과 다층신경회로망 공칭모델 출력 사이의 오차가 미리 설정한 문턱값을 넘으면 고장을 감지한다. 고장이 감지되면 다층신경회로망과 ART2 신경회로망을 이용한 고장분류기에서 시스템에서 발생한 고장을 분류한다. 컴퓨터 시뮬레이션 결과로부터 제안한 고장진단방법이 비선형시스템에서의 고장감지 및 분류문제에 잘 적용됨을 알 수 있다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제2권1호
• /
• pp.43-48
• /
• 2002

This paper discusses the application of fuzzy-ARTMAP neural network to compensate the nonlinearity of satellite communication channel. The fuzzy-ARTMAP is the class of ART(adaptive resonance theory) architectures designed fur supervised loaming. It has capabilities not fecund in other neural network approaches, that includes a small number of parameters, no requirements fur the choice of initial weights, automatic increase of hidden units, and capability of adding new data without retraining previously trained data. By a match tracking process with vigilance parameter, fuzzy-ARTMAP neural network achieves a minimax teaming rule that minimizes predictive error and maximizes generalization. Thus, the system automatically leans a minimal number of recognition categories, or hidden units, to meet accuracy criteria. As a input-converting process for implementing fuzzy-ARTMAP equalizer, the sigmoid function is chosen to convert actual channel output to the proper input values of fuzzy-ARTMAP. Simulation studies are performed over satellite nonlinear channels. QPSK signals with Gaussian noise are generated at random from Volterra model. The performance of proposed fuzzy-ARTMAP equalizer is compared with MLP equalizer.

• International Journal of Korean Welding Society
• /
• 제1권1호
• /
• pp.23-30
• /
• 2001

Among the various welding conditions, the welding current that is inversely proportional to the tip-to-work-piece distance is an essential parameter as to monitor the GMAW process and to implement the welding automation. Considering the weld pool surface geometry including weld defects, it should modify the signal processing method for automatic seam tracking in horizontal fillet welding. To meet the above necessities, a mathematical model related with the weld pool geometry was proposed as in a conjunction with the two-dimensional heat flow analysis of the horizontal fillet welding. The signal processing method based on the artificial neural network (Adaptive Resonance Theory) was proposed for discriminating the sound weld pool surface from that with the weld defects. The reliability of the numerical model and the signal processing method proposed were evaluated through the experiments of which showed that they are effective for predicting the weld bead shape with or without the weld defects in a horizontal fillet welding.

• 대한용접접합학회:학술대회논문집
• /
• 대한용접접합학회 1996년도 특별강연 및 추계학술발표 개요집
• /
• pp.139-141
• /
• 1996

Among various welding parameters, the welding current which is inversely proportional to the tip-to-workpiece distance in GMAW is an essential parameter to monitor the GMAW process of horizontal fillet joints. For the case of weld defect such as overlap in horizontal fillet welding, therefore, the signal processing for process monitoring or automatic seam tracking should be modified by considering the weld pool surface geometry including the corresponding weld defect. In other words, the adequate signal processing algorithm is indispensible to improve the performance of the arc sensor. However, arc sensor algorithm already developed usually focus on weld seam tracing but do not considering the weld qualities. In this paper, various experiments were carried out to investigate the tendencies of the weld defects when weaving motion is added, and the experimental method based on 2$^n$ factorial design was proposed for deriving the mathematical model between the leg length and the various welding conditions. Moreover, a signal processing method based on the artificial neural network(Adaptive Resonance Theory) was proposed far discriminating the current signal of sound weld beads from that of weld beads with overlap. Finally, the algorithm for weld seam tracking combined with the mathematical modeling and the signal processing method was carried out to track the weld line in conjunction with the improvement of the weld qualities. The reliability of the proposed algorithms were evaluated through various experiments, which showed that the proposed algorithms could be effectively used for arc welding automation.