• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.537-538
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• 2013

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.317-325
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• 2022

In this study, we propose a technological system designed to provide machine vision-based automatic inspection and autonomous operation services for an entire process related to product inspection in wire harness manufacturing. The smart factory paradigm is a valuable and necessary goal, small companies may encounter steep barriers to entry. Therefore, the best approach is to develop towards this approach gradually in stages starting with the relatively simple improvement to manufacturing processes, such as replacing manual quality assurance stages with machine vision-based inspection. In this study, we consider design issues of a system based on the proposed technology and describe an experimental implementation. In addition, we evaluated the implementation of the proposed technology. The test results show that the adoption of the proposed machine vision-based automatic inspection and operation service system for multi-wire harness production may be considered justified, and the effectiveness of the proposed technology was verified.

• Journal of Electrical Engineering and Technology
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• v.5 no.3
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• pp.503-510
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• 2010

This paper proposes the use of fuzzy applications to a 4-machine and 10-bus system to check stability in open conditions. Fuzzy controllers and the excitation of a synchronous generator are added. Power system stabilizers (PSSs) are added to the excitation system to enhance damping during low frequency oscillations. A fuzzy logic power system stabilizer (PSS) for stability enhancement of a multi-machine power system is also presented. To attain stability enhancement, speed deviation ($\Delta\omega$) and acceleration ($\Delta\varpi$) of the Kota Thermal synchronous generator rotor are taken as inputs to the fuzzy logic controller. These variables have significant effects on the damping of generator shaft mechanical oscillations. The stabilizing signals are computed using fuzzy membership functions that are dependent on these variables. The performance of the fuzzy logic PSS is compared with the open power system, after which the simulations are tested under different operating conditions and changes in reference voltage. The simulation results are quite encouraging and satisfactory. Similarly, the system is tested for the different defuzzification methods, and based on the results, the centroid method elicits the best possible system response.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.4
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• pp.7-15
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• 2009

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.430-439
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• 2016

Estimation and analysis of traffic jams plays a vital role in an intelligent transportation system and advances safety in the transportation system as well as mobility and optimization of environmental impact. For these reasons, many researchers currently mainly focus on the brilliant machine learning-based prediction approaches for traffic prediction systems. This paper primarily addresses the analysis and comparison of prediction accuracy between two machine learning algorithms: Naïve Bayes and K-Nearest Neighbor (K-NN). Based on the fact that optimized estimation accuracy of these methods mainly depends on a large amount of recounted data and that they require much time to compute the same function heuristically for each action, we propose an approach that applies multi-threading to these heuristic methods. It is obvious that the greater the amount of historical data, the more processing time is necessary. For a real-time system, operational response time is vital, and the proposed system also focuses on the time complexity cost as well as computational complexity. It is experimentally confirmed that K-NN does much better than Naïve Bayes, not only in prediction accuracy but also in processing time. Multi-threading-based K-NN could compute four times faster than classical K-NN, whereas multi-threading-based Naïve Bayes could process only twice as fast as classical Bayes.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.10a
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• pp.54-59
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• 1998

In order to minimize straightness error of deflected shafts, a automatically bending process control system is designed, fabricated, and studied. The multi-step straightening process and the three-point bending process are developed for the geometric adaptive straightness control. Load-deflection relationship, on-line identification of variations of material properties, on-line springback prediction, and studied for the three-point bending processes. Selection of a loading point supporting condition are derved form fuzzy inference and fuzzy self-learning method in the multi-step straighternign process. Automatic straightening machine is fabricated by using the develped ideas. Validity of the proposed system si verified through experiments.

• Transactions on Electrical and Electronic Materials
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• v.18 no.5
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• pp.287-297
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• 2017

Novel power system stabilizers (PSSs) have been proposed to effectively dampen low frequency oscillations (LFOs) in multi-machine power systems and have attracted increasing research interest in recent years. Due to this attention, recently, fractional order controllers (FOCs) have found new applications in power system stability issues. Here, a tilt-integral-derivative power system stabilizer (TID-PSS) is proposed to enhance the dynamic stability of a multi-machine power system by providing additional damping to the LFOs. The TID is an extended version of the classical proportional-integral-derivative (PID) applying fractional calculus. The design of the proposed three-parameter tunable TID-PSS is systematized as a nonlinear time domain optimization problem in which the tunable parameters are adjusted concurrently using a modified group search optimization (MGSO) algorithm. An integral of the time multiplied squared error (ITSE) performance index is considered as the objective function. The proposed stabilizer is simulated in the MATLAB/SIMULINK environment using the FOMCON toolbox and the dynamic performance is evaluated on a 3-machine 6-bus power system. The TID-PSS is compared with both classical PID-PSS (PID-PSS) and conventional PSS (CPSS) using eigenvalue analysis and time domain simulations. Sensitivity analyses are performed to assess the robustness of the proposed controller against large changes in system loading conditions and parameters. The results indicate that the proposed TID-PSS provides the better dynamic performance and robustness compared with the PID-PSS and CPSS.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.6
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• pp.114-121
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• 1996

This paper presents an useful technique for assessing the volumetric errors in multi-axis machine tools using the kinematic double ball bar. This system has been developed based on the volumetric error map which describes the 3 dimensional errors of machine tools. The developed system inputs the measured radial data of 3 different planes, respectively XY,YZ,ZX, analysing the volumetric errors such as positional. straightness, angle, and squareness errors, etc. The developed system has been tested in a practical machine tool, and showed high potential for the error assessment of multi-axis machine tools.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.2914-2935
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• 2016

With the increasing popularization of cloud computing, how to reduce physical energy consumption and increase resource utilization while maintaining system performance has become a research hotspot of virtual machine deployment in cloud platform. Although some related researches have been reported to solve this problem, most of them used the traditional heuristic algorithm based on greedy algorithm and only considered effect of single-dimensional resource (CPU or Memory) on energy consumption. With considerations to multi-dimensional resource utilization, this paper analyzed impact of multi-dimensional resources on energy consumption of cloud computation. A multi-dimensional resource constraint that could maintain normal system operation was proposed. Later, a novel virtual machine deployment method (NVMDM) based on improved particle swarm optimization (IPSO) and Euclidean distance was put forward. It deals with problems like how to generate the initial particle swarm through the improved first-fit algorithm based on resource constraint (IFFABRC), how to define measure standard of credibility of individual and global optimal solutions of particles by combining with Bayesian transform, and how to define fitness function of particle swarm according to the multi-dimensional resource constraint relationship. The proposed NVMDM was proved superior to existing heuristic algorithm in developing performances of physical machines. It could improve utilization of CPU, memory, disk and bandwidth effectively and control task execution time of users within the range of resource constraint.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.102-105
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• 1995

In power system stability analysis, modelling of the synchronous machine is necessary and vary important. In this paper, a synchronous machine is modeled and simulated by using Object-Oriented method. The mathematical equations describing the dynamic behavior of the synchronous machine is represented by block diagram and Objected-Oriented Digital Computer Simulater(ODCS). The developed method is tested for a one-machine-to-infinite-bus system, which is accurate and very useful for a multi-machine system simulation.