• 한국산업융합학회 논문집
• /
• 제22권4호
• /
• pp.447-457
• /
• 2019

The intelligent sensory system is required to ensure the accurate welding performance. This paper describes the development of an intelligent vision sensor for the robotic laser welding. The sensor system includes a PC based vision camera and a stripe-type laser diode. A set of robust image processing algorithms are implemented. The laser-stripe sensor can measure the profile of the welding object and obtain the seam line. Moreover, the working distance of the sensor can be changed and other configuration is adjusted accordingly. The robot, the seam tracking system, and CW Nd:YAG laser are used for the laser welding robot system. The simple and efficient control scheme of the whole system is also presented. The profile measurement and the seam tracking experiments were carried out to validate the operation of the system.

• 한국전자파학회논문지
• /
• 제23권4호
• /
• pp.475-483
• /
• 2012

본 논문은 차세대 재구성 전력증폭기용을 위해서, 새로운 타입의 다중 모드 혼합형 전압 공급기를 제안한다. 이를 위한 핵심 회로인 스위칭 증폭기의 새로운 구조를 제안하였다. 혼합형 전압 공급기의 가장 중요한 성능지표 중의 하나인 효율을 증가시키기 위해 멀티 스위칭 증폭기 구조를 이용하였고, 또한 다중 모드 구현을 위해서 멀티 스위칭 증폭기와 입력 신호 검출단을 이용하였다. 성능 비교를 위해서 기본 구조를 지닌 혼합형 가변전압 공급기도 같이 설계되었으며, 새롭게 제안하는 구조 이외에는 모두 동일하게 설계하여 비교를 용이하도록 하였다. 설계된 혼합형 전압 공급기의 효율을 측정하기 위해 384 kHz/3.84 MHz/5 MHz 대역폭을 가지는 EDGE, WCDMA, LTE 신호를 적용하였다. EDGE를 적용한 효율은 85 %, WCDMA를 적용한 효율은 84 % 그리고 LTE를 적용한 효율은 79 %의 결과를 얻게 되었다. 이는 기본 구조보다 최대 9 %의 성능 향상을 얻었으며, 차세대 재구성 송신기인 다중 대역 및 다중 모드 송신기 구현에 적용 가능함을 입증한다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
• /
• pp.745-749
• /
• 1998

Mathematical morphology (MM) has been introduced as a powerful tool for studying the geometrical properties of images, MM is a good approach to digital image processing , which is based on the shape feature. The MM operators such as dilation, erosion, closing and opening have been applied successfully to image noise reduction. The MM filters can easily filter the noise when the noise factors are known. However it is very difficult to reduce the noise when images are ambiguous, because the boundary between the noise and object is vague. In this paper, we propose a new method to reduce noise from ambiguous images by using Fuzzy Mathematical Morphology (FMM) operators. Performance evaluation via simulations show that the FMM filters efficiently reduce the image noise. Furthermore, the FMM filters show a good performance compared with the conventional filters.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제13권1호
• /
• pp.73-82
• /
• 2013

In pattern classification, feature selection is an important factor in the performance of classifiers. In particular, when classifying a large number of features or variables, the accuracy and computational time of the classifier can be improved by using the relevant feature subset to remove the irrelevant, redundant, or noisy data. The proposed method consists of two parts: a wrapper part with an improved genetic algorithm(GA) using a new reproduction method and a filter part using mutual information. We also considered feature selection methods based on mutual information(MI) to improve computational complexity. Experimental results show that this method can achieve better performance in pattern recognition problems than other conventional solutions.

• 한국ITS학회 논문지
• /
• 제10권5호
• /
• pp.93-98
• /
• 2011

ITS와 WAVE 등의 도입 및 스마트 폰의 광범위한 보급에 따라 WMN 기술은 IEEE802.11 기반의 AP의 무선접속 범위를 확장시키기 위한 효율적인 기술로서 인정받고 있다. 본 논문에서는 WMN 구현에 있어서 대부분의 메쉬 라우터가 갖고 있는 다중 인터페이스/다중 채널 기능을 활용하여 전반적인 통신 속도 및 처리율 향상을 위한 MAC 프로토콜을 제안하고 컴퓨터 시뮬레이션을 통하여 성능을 검증하였다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1995년도 추계학술대회 학술발표 논문집
• /
• pp.71-77
• /
• 1995

In this paper are proposed robust iterative learning control(ILC) algorithms for both linear continuous time-invariant system and linear discrete-time system. In contrast to conventional methods, the proposed learning algorithms are constructed based on both time domain performance and iteration-domain performance. The convergence of the proposed learning algorithms is proved. Also, it is shown that the proposed method has robustness in the presence of external disturbances and the convergence accuracy can be improved. A numerical external disturbances and the convergence accuracy can be improved. A numerical example is provided to show the effectiveness of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권9호
• /
• pp.3444-3457
• /
• 2021

In the field of anti-jamming based on dynamic spectrum, most methods try to improve the ability to avoid jamming and seldom consider whether the jammer would perceive the user's signal. Although these existing methods work in some anti-jamming scenarios, their long-term performance may be depressed when intelligent jammers can learn user's waveform or decision information from user's historical activities. Hence, we proposed a hidden anti-jamming method to address this problem by reducing the jammer's sense probability. In the proposed method, the action correlation between the user and the jammer is used to evaluate the hiding effect of the user's actions. And a deep reinforcement learning framework, including specific action correlation calculation and iteration learning algorithm, is designed to maximize the hiding and communication performance of the user synchronously. The simulation result shows that the algorithm proposed reduces the jammer's sense probability significantly and improves the user's anti-jamming performance slightly compared to the existing algorithms based on jamming avoidance.

• International Journal of Advanced Culture Technology
• /
• 제2권2호
• /
• pp.1-6
• /
• 2014

In this paper, we propose an intelligent streetlight system that has a complex sensor module of temperature, humidity, luminance and motion detection and controlled by the fuzzy logic based central monitoring system in order to get flexible and precise manipulation of the streetlight system in USN environment. The proposed streetlight system provides low power consumption and high efficiency by using sensed data from the complex sensor module, which were collected, processed, and analyzed by the fuzzy logic based central monitoring system. The performance of the proposed streetlight system is to be evaluated by a simulation study in terms of power savings and safety at the fields constructed as a test-bed under several suggested scenarios. Finally, we know that the proposed intelligent streetlight system can maximize the energy savings efficiently with the fuzzy logic based central monitoring system and selective remote dimming control by connecting it to the wireless ubiquitous sensor network (USN) using a Zigbee module.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
• /
• pp.145-154
• /
• 1999

An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes th hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.

• 한국원자력학회:학술대회논문집
• /
• 한국원자력학회 1996년도 추계학술발표회논문집(1)
• /
• pp.73-78
• /
• 1996

In this study, we proposed a fuzzy gain scheduler with intelligent learning algorithm for a reactor control. In the proposed algorithm, we used the gradient descent method to learn the rule bases of a fuzzy algorithm. These rule bases are learned toward minimizing an objective function, which is called a performance cost function. The objective of fuzzy gain scheduler with intelligent learning algorithm is the generation of adequate gains, which minimize the error of system. The condition of every plant is generally changed as time gose. That is, the initial gains obtained through the analysis of system are no longer suitable for the changed plant. And we need to set new gains, which minimize the error stemmed from changing the condition of a plant. In this paper, we applied this strategy for reactor control of nuclear power plant (NPP), and the results were compared with those of a simple PI controller, which has fixed gains. As a result, it was shown that the proposed algorithm was superior to the simple PI controller.