• Journal of the Korean Society for Precision Engineering
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• v.13 no.3
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• pp.102-109
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• 1996

In this paper, we present a new approach for the automation of deburring process. An algorithm for teaching skills of a human expert to a robot manipulator is developed. This approach makes use of TSK fuzzy mode that can wxpress a highly nonlinear functional relation with small number of rules. Burr features such as height, width, area, grinding area are extracted from image processing by use of the vision system. Grinding depth, repetitive number and normal grinding force are chosen as control signals representing actions of the human expert. It is verified that our proposed fuzzy model can accurately express the skills of human experts for the deburring process.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.5
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• pp.35-49
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• 2014

This paper proposes the on-road object detection and classification algorithm by using a detection system consisting of only laser scanners. Each sensor data acquired by the laser scanner is fused with a grid map and the measurement error and spot spaces are corrected using a labeling method and dilation operation. Fuzzy method which uses the object information (length, width) as input parameters can classify the objects such as a pedestrian, bicycle and vehicle. In this way, the accuracy of the detection system is increased. Through experiments for some scenarios in the real road environment, the performance of the proposed detection and classification system for the actual objects is demonstrated through the comparison with the actual information acquired by GPS-RTK.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.12
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• pp.562-570
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• 2002

The Purpose of this paper is to design and manufacture an educational system in order to demonstrate the causes and effects of electromagnetic induction.'rho educational system described in this study is a "jumping ring apparatus". This system demonstrates the principle of electromagnetic induction, a force from AC sources, Lenz's law of repulsion and transformer. The educational system is composed of a jumping ring apparatus, a sensor array, encoder, A/D converter, D/A converter and nonlinear controller. The educational system is controlled by 586 PC using Turbo C program. The sensor array is composed of 20 optical sensors. The nonlinear controller consists of nonlinear control algorithm and control board included SCR, FET and phase controller. The A/D converter is used to show the height of ring position to analog for an education purpose. The control signal calculated from the nonlinear control of algorithm send control board through 8 bit D/A convertor. Experiment results are given to verify that Proposed nonlinear controller is useful in on line control of the educational system.al system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.197-201
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• 2006

In the implementation of a smart home, activity recognition technology using simple sensors is very important. In this paper, we propose a new activity recognition method based on Bayesian network (BN). The structure of the BN is learned by K2 algorithm and is composed of sensor nodes, activity nodes and time node whose state is quantized with reasonable interval. In the proposed method, the BN has less complexity and provides better activity recognition rate than the previous method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.321-326
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• 2009

The mobile air cleaner analyzes a distribution of polluted air to purify the air fast, calculates an optimal position and moves the position so that it can remove indoor dust more quickly. At this time, the self-localization is necessary to make the mobile air cleaner move accurately to the calculated position. This paper proposed a self-localization algorithm having high accuracy without complicated calculation and implemented it by combining a ultrasonic sensor and video processing technologies, so that it is suitable for a mobile air cleaner, and as a test result, the mean error of $\pm1cm$ appeared between the actually measured position and the calculated position.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.421-426
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• 2018

With regard to LED lighting devices which have currently been commercialized, LED operating sequences are being sold in a fixed state. In such a state, the external environmental factors are not taken into consideration as only the illumination environment application is considered. Currently, it is difficult to create an optimal lighting environment which can adapt to changes in external environmental factors in the ship. Therefore, it was concluded that there is a need to input the external environment value so that the optimal illumination value can be reflected in real time in order to adapt more organically and actively to the change of external environmental factors. In this paper, we used a microprocessor as an integrated management system for environmental data that changes in real time according to existing external environmental factors. In addition, a controller capable of lighting control of RGB LED module by combining fuzzy inference system. For this, a fuzzy control algorithm is designed and a fuzzy control system is constructed. The distance and the illuminance value from the external environment element are input to the sensor, and these values are converted to the optimum illumination value through the fuzzy control algorithm, and are expressed through the dimming control of the RGB LED module and the practical effectiveness of the fuzzy control system is confirmed.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.21-31
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• 2012

Threat Evaluation(TE) which has air intelligence attained by identifying friend or foe evaluates the target's threat degree, so it provides information to Weapon Assignment(WA) step. Most of TE data are passed by sensor measured values, but existing techniques(fuzzy, bayesian network, and so on) have many weaknesses that erroneous linkages and missing data may fall into confusion in decision making. Therefore we need to efficient Threat Evaluation system that can refine various sensor data's linkages and calculate reliable threat values under unpredictable war situations. In this paper, we suggest new threat evaluation system based on information fusion JDL model, and it is principle that combine fuzzy which is favorable to refine ambiguous relationships with bayesian network useful to inference battled situation having insufficient evidence and to use learning algorithm. Finally, the system's performance by getting threat evaluation on an air defense scenario is presented.

• International Journal of Safety
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• v.11 no.1
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• pp.6-10
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• 2012

This paper presents a study on the analysis for reducing the number of false alarms in fire detection system. In order to intelligent algorithm fuzzy logic is adopted in developing fire detection system to reduce false alarm. The intelligent fire detection algorithm compared and analyzed the fire and non-fire signatures measured in circuits simulating flame fire and smoldering fire. The algorithm has input variables obtained by fire experiment with K-type thermocouple and optical smoke sensor. Also triangular membership function is used for inference rules. And the antecedent part of inference rules consists of temperature and smoke density, and the consequent part consists of fire probability. A fire-experiment is conducted with paper, plastic, and n-heptane to simulate actual fire situation. The results show that the intelligent fire detection algorithm suggested in this study can more effectively discriminate signatures between fire and similar fire.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.91-96
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• 2003

The forces and moments at the aircraft c.g. have components due to aerodynamic effects and to engine thrust. For the flight stability and autopilot systems we present a attitude control method using an intelligent control algorithm Which is based on the control rules from experts knowledge concerning the motion equations and other experiences. Then a robust fuzzy controller is developed to control the flight attitude. The controller can deal with multiple inputs and outputs. We have made an aircraft model and the orientation sensor for experimental flights. The control rules based on the flight expert s experience and knowledge can be programmed by fuzzy rules, and determined control rules by experimental flight. We can be stable attitude control by fuzzy controller.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.109-115
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• 2005

In the study, Methods for operating measures in equipment security to find out dangerousness timely in the system and to need for the prevention and measures. The method for analyzing and reconstructing the causes of accident of equipment in site, and try to save the information of site in real-time and to analyze the state of equipment to look for the factors of accidents. By this analysis, one plan for efficiency of production, Equipment Fault Diagnosis Management and security is integrating and building module of using the Fuzzy Inference based on fuzzy theory. The case study is applied to the industrial electric motors that are necessarily used to all manufacturing equipment. Using the sensor for temperature is attached to gain the site information in real time and to design the hardware module for signal processing. In software, realize the system supervising and automatically saving to management data base by the algorithm based in fuzzy theory from the existing manual input system