• Proceedings of the KSR Conference
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• 2003.10c
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• pp.574-580
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• 2003

This research heightens use efficiency of existent train railroad equipment by maximum through communication based train control system, and because system that take advantage of new skill compares with safety of old signal system same or it that show that is high be. Examined MBS Embodiment method of most suitable by presenting calculation that find out location of train that this treatise runs free curved line department to embody MBS(Moving Block System) through communication

• Journal of Intelligence and Information Systems
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• v.1 no.2
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• pp.17-32
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• 1995

본 논문에서는 추론엔진 (inference engine)내에 퍼지정보 검색부(Fuzzy Information Retrieval part)를 갖는 교통신도 제어 전문가 시스템을 제안한다. 제안하는시스템은 다양하고 복잡한 도로 상화을 고려하여 그에 따른 적절한 주기를 각 도로별로 할당함으로써 원활한 교통 흐름을 제어한다. 추론엔진내의 퍼지정보 검색부는 퍼지 삼각 논리곱을 이용하여 도로의 상황을 분석한 후 각 도로에 맞는 가장 적절한 신호주기를 생성한다.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1675-1678
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• 2004

In this paper, web based monitoring systems are implemented for multi-axis force control systems of an intelligence robot. A brief review about the principle of multi-axis force sensors and a method that can reduce the effect of noise signal to sensor performance is presented. A web based monitoring system is implemented by porting Linux at embedded systems which include Xscale processors. A device driver is developed to receive data from multi-axis force sensors in Linux operation systems. To control this device driver, a socket program for web browser is also developed. The experiments are performed to investigate the effectiveness of proposed methods. The experimental results show that the values of force sensors can be monitored by remote PCs.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.3
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• pp.100-107
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• 2002

In this paper, we propose an expert system for electronic interlocking which enhances the safty, efficiency and expanability of the existing system by designing real-time interlocking control based on the interlocking table automatically generated using artificial intelligence approach. The expert system consists of two parts; an interlocking table generation part and a real-time interlocking control part. The former generates automatically the interlocking relationship of all possible routes by searching dynamically the station topology which is obtained from station database. On the other hand, the latter controls the status of station facilities in real-time by applying the generated interlocking relationship to the signal facilities such as signal devices, points, track circuits for a given route. The expert system is implemented in C language which is suitable to implement the interlocking table generation part using the dynamic memory allocation technique. Finally, the effectiveness of the expert system is proved by simulating for the typical station model.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.86-88
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• 2007

In the semiconductor manufacturing industry, the heterodyne laser interferometer plays as an ultra-precise measurement system. However, the heterodyne laser interferometer has some unwanted nonlinearity error which is caused from frequency-mixing. This is an obstacle to improve the measurement accuracy in nanometer scale. In this paper we propose a compensation algorithm based on RLS(recursive least square) method and artificial intelligence method, which reduce the nonlinearity error in the heterodyne laser interferometer. With the capacitance displacement sensor we get a reference signal which can be transformed into the intensity domain. Using the back-propagation Neural Network method, we train the network to track the reference signal. Through some experiments, we demonstrate the effectiveness of the proposed algorithm in measurement accuracy.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.585-590
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• 2000

Recently, It is gradually raised necessity that thickness of thin film is measured accuracy and managed in industrial circles and medical world. Ultrasonic Signal processing method is likely to become a very powerful method for NDE method of detection of microdefects and thickness measurement of thin film below the limit of Ultrasonic distance resolution in the opaque materials, provides useful information that cannot be obtained by a conventional measuring system. In the present research, considering a thin film below the limit of ultrasonic distance resolution sandwiched between three substances as acoustical analysis model, demonstrated the usefulness of ultrasonic Signal processing technique using information of ultrasonic frequency for NDE of measurements of thin film thickness, sound velocity, and step height, regardless of interference phenomenon. Numeral information was deduced and quantified effective information from the image. Also, pattern recognition of a defected input image was performed by neural network algorithm. Input pattern of various numeral was composed combinationally, and then, it was studied by neural network. Furthermore, possibility of pattern recognition was confirmed on artifical defected input data formed by simulation. Finally, application on unknown input pattern was also examined.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.474-474
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• 2000

This paper shows that a system with two-link arm can obtain hand reaching movement to a target object projected on a visual sensor by reinforcement learning using a layered neural network. The reinforcement signal, which is an only signal from the environment, is given to the system only when the hand reaches the target object. The neural network computes two joint torques from visual sensory signals, joint angles, and joint angular velocities considering the urn dynamics. It is known that the trajectory of the voluntary movement o( human hand reaching is almost straight, and the hand velocity changes like bell-shape. Although there are some exceptions, the properties of the trajectories obtained by the reinforcement learning are somewhat similar to the experimental result of the human hand reaching movement.

• Journal of Welding and Joining
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• v.14 no.4
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• pp.24-32
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• 1996

용접공정 해석을 위한 접근방법중에서 우선적으로 결정해야할 사항으로는 비선형적인 요소와 복잡한 물리현상들을 실제적으로 해석하기위한 측정변수의 선정과 이러한 변수를 사용하여 물리적인 현상을 적절히 표현할 수 있는 알고리즘의 개발 등 을 들 수 있다. 최근까지의 연구결과를 바탕으로 해서 측정변수들의 예를 들면 용접 전류(welding current), 아크전압(arc voltage), 음향신호(acoustic signal), 아크 광(arc light) 그리고 온도(temperature)등이 있다. 용접공정을 분석하기 위한 알고 리즘으로는 확률론적 접근(statistical approach), 다양한 실험치를 이용한 인공지능 적 접근(artificial intelligence approach) 그리고 경험치를 바탕으로 인덱스(index) 을 선정하여 이를 직접 사용하는 방법 및 인공지능과 결합된 형태를 이용하는 방법등 이 있다. 또한 용접공정의 특성을 분석하기 위해서는 크게 금속이행모드(metal transfer mode), 아크의 안정성(arc stability) 그리고 용접품질(weld quality) 등을 판별할 수 있는 알고리즘의 개발이 필수적이라 할 수 있다. 본 논문에서는 용접공정 분석과 관련된 최근까지의 연구동향 및 용접신호의 특성을 좀더 심도있게 분석하기 위해 구축해야 할 필수 요건 등을 소개하고자 하며 이를 사용자가 손쉽게 이용할 수 있는 사용자 인터페이스 프로그램을 개괄적으로 설명하고자 한다.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1231-1234
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• 2006

In this study, we detected electromagnetic waves generated in an enclosed switchgear and applied various statistical methods for detecting signals. We calculated the various statistical factors via the appropriate statistical methods. Further, we used these statistics to recognize the characteristics for each pattern by identifying the partial discharge in each case for normal, proceeding and abnormal states. The characteristics of electromagnetic wave patterns occurred in various states at electric power facilities and were used as an output variable for more efficient diagnosis. In this paper, we confirmed that the pattern of partial discharge signal can be used as one of the factors used to analyze the insulation state and to consider while estimating diagnosis of insulation states by recognizing the signal pattern to intelligence. We will utilize the proposed diagnosis method to determine insulation degradation states.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.179-182
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• 2002

In this paper, this system makes use of the analog sensor and converts the feature of fish analog signal when sensor is operating with CPU(80C196KC). Then, After signal processing, this feature Is classified a special feature and a outline of fish by using the neural network, one of the artificial intelligence scheme. This neural network classifies fish pattern of very simple and short calculation. This has linear activation function and the error backpropagation is used as a learning algorithm. And the neural network is learned in off-line process. Because an adaptation period of neural network is too long time when random initial weights are used, off-line learning Is induced to decrease the Progress time We confirmed this method has better performance than somewhat outdated machines.