• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.5-11
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• 2003

The number of the enterprises which utilize network technology has been increasing for solving problems such as productivity improvement, market trend analysis, and material collection for making decision. Especially, the management of equipment and the recovery time reduction when machines break down are very important factors in productivity improvement of the enterprise. Currently, most of the remote trouble diagnosis of equipment using the internet have just one function of transmitting the trouble information to the user. Therefore it does not directly reflect the user's recovery experience or the developer's new recovery methods. If the user's experienced recovery methods or the developer's recovery methods as well as the basic recovery methods are reflected online or on the internet, it makes it possible to recover faster than before. In this paper, we develop a Remote Monitoring Server (RMS) for chip mounters, and make it possible to reduce the recovery time by reflecting the user's experience and developer's new methods in addition to presenting the basic recovery methods. For this, trouble recovery concept will be defined. Based on this, many functions(trouble diagnosis, the presentation of the basic recovery methods, user's and developer's recovery method, counting function of the trouble number of each code, and presentation of usage number of each recovery methods) were developed. By utilizing the reports of the actual results of chip mounter and the notice function of the parts change time, the rate of operation of the chip mounter can be improved.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.264-270
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• 1998

This research broadens the prime concern of nuclear power plant operations from safe performance to both economic and safe performance. First emergency diesel generator is identified as one of main contributors for the lost plant availability through the review of plants forced outage records. The framework of an integrated architecture for performing modern on-line condition for operational availability improvement is configured in this work. For the development of the comprehensive sensor networks for complex target systems, an integrated methodology incorporating a structural hierarchy, a functional hierarchy, and a fault-system matrix is formulated. The second part of our research is development of intelligent diagnosis and maintenance advisory system, which employs Bayesian Belief networks (BBNs) as a high level reasoning tool incorporating inherent uncertainty use in probabilistic inference. Our prototype diagnosis algorithms are represented explicitly through topological symbols and links between them in a causal direction. As new evidence from sensor network development is entered into the model especially, our advisory of system provides operational advice concerning both availability and safety, so that the operator is able to determine the likely modes, diagnose the system state, locate root causes, and take the most advantageous action. Thereby, this advice improves operational availability

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.132-139
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• 2009

Yield is a very important measure that can expresses simply for productivity and performance of company. So, yield is used widely in many industries nowadays. With the development of the information technology and online based real-time process monitoring technology, many industries operate the production lines that are developed into automation system. In these production lines, the product structures are very complexity and variety. So, there are many multi-variate processes that need to be monitored with many quality characteristics and associated process variables at the same time. These situations have made it possible to obtain super-large manufacturing process data sets. However, there are many difficulties with finding the cause of process variation or useful information in the high capacity database. In order to solve this problem, neural networks technique is a favorite technique that predicts the yield of process for process control. This paper uses a neural networks technique for improvement and maintenance of yield in manufacturing process. The purpose of this paper is to model the prediction of a sub process that has much effect to improve yields in total manufacturing process and the prediction of adjustment values of this sub process. These informations feedback into the process and the process is adjusted. Also, we show that the proposed model is useful to the manufacturing process through the case study.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1125-1136
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• 2010

Lately there exist increasing demands for online abnormality monitoring over trajectory stream, which are obtained from moving object tracking devices. This problem is challenging due to the requirement of high speed data processing within limited space cost. In this paper, we present a FADA (Fuzzy Anomaly Detection Algorithm) which constructs normal profile by computing mobility feature information from the GPS (Global Positioning System) logs of mobile devices in MANETs (Mobile Ad-hoc Networks), computes a fuzzy dissimilarity between the current mobility feature information of the mobile device and the mobility feature information in the normal profile, and detects effectively the anomaly behaviors of mobile devices on the basis of the computed fuzzy dissimilarity. The performance of proposed FADA is evaluated through simulation.

• Journal of Information Technology Applications and Management
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• v.21 no.3
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• pp.65-77
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• 2014

Ubiquitous learning has aroused great interest and is becoming a new way for foreign language education in today's society. However, how to increase the learners' initiative and their community cohesion is still an issue that deserves more profound research and studies. Emotional intelligence can help to detect the learner's emotional reactions online, and therefore stimulate his interest and the willingness to participate by adjusting teaching skills and creating fun experiences in learning. This is, actually the new concept of smart education. Based on the previous research, this paper concluded a neural mechanism model for analyzing the learners' emotional characteristics in ubiquitous environment, and discussed the intelligent monitoring and automatic recognition of emotions from the learners' speech signals as well as their behavior data by multi-agent system. Finally, a framework of emotional intelligence system was proposed concerning the smart foreign language education in ubiquitous learning.

• Journal of Communications and Networks
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• v.13 no.2
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• pp.113-124
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• 2011

Electrocardiography (ECG) is a widely accepted approach for monitoring of cardiac activity and clinical diagnosis of heart diseases. Since cardiologists have been well-trained to accept 12-lead ECG information, a huge number of ECG systems are using such number of electrodes and placement configuration to facilitate fast interpretation. Our goal is to design a wireless ECG system which renders conventional 12-lead ECG information.We propose the three-pad ECG system (W3ECG). W3ECG furthers the pad design idea of the single-pad approach. Signals obtained from these three pads, plus their placement information, make it possible to synthesize conventional 12-lead ECG signals.We provide one example of pad placement and evaluate its performance by examining ECG data of four patients available from online database. Feasibility test of our selected pad placement positions show comparable results with respect to the EASI lead system. Experimental results also exhibit high correlations between synthesized and directly observed 12-lead signals (9 out of 12 cross-correlation coefficients higher than 0.75).

• Structural Engineering and Mechanics
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• v.26 no.3
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• pp.315-341
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• 2007

A sudden change of stiffness in a structure, associated with the events such as weld fracture and brace breakage, will cause a discontinuity in acceleration response time histories recorded in the vicinity of damage location at damage time instant. A new damage index is proposed and implemented in this paper to detect the damage time instant, location, and severity of a structure due to a sudden change of structural stiffness. The proposed damage index is suitable for online structural health monitoring applications. It can also be used in conjunction with the empirical mode decomposition (EMD) for damage detection without using the intermittency check. Numerical simulation using a five-story shear building under different types of excitation is executed to assess the effectiveness and reliability of the proposed damage index and damage detection approach for the building at different damage levels. The sensitivity of the damage index to the intensity and frequency range of measurement noise is also examined. The results from this study demonstrate that the damage index and damage detection approach proposed can accurately identify the damage time instant and location in the building due to a sudden loss of stiffness if measurement noise is below a certain level. The relation between the damage severity and the proposed damage index is linear. The wavelet-transform (WT) and the EMD with intermittency check are also applied to the same building for the comparison of detection efficiency between the proposed approach, the WT and the EMD.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.309-325
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• 2013

Environmental and operational variables are inevitable concerns by researchers and engineers when implementing the damage detection algorithm in practical projects, because the change of structural behavior could be masked by the conditions in a large extent. Thus, reliable damage detection methods should have a virtue of immunity from environmental and operational variables. In this paper, the pair cointegration method was presented as a novel way to remove the effect of environmental variables. At the beginning, the concept and procedure of this approach were introduced, and then the theoretical formulation and numerical simulations were put forward to illustrate the feasibility. The jump exceeding the control limit in the residual indicates the occurrence of damage, while the direction and magnitude imply the most potential damage location. In addition, the simulation results show that the proposed method has strong ability to resist the noise.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.11
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• pp.9-16
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• 2010

This paper examines the temperature characteristics of an Optical CT (optical current transformer) using the Faraday effect for measuring high current in a super high voltage-power apparatus. It is performed as follows by the sensor for embodying Faraday effect. $\cdot$ A single-mode optical fiber capable of maintaining a polarization state is used. $\cdot$ A light source is applied at 1310[nm] to a Laser Diode. $\cdot$ The Linear of Faraday effect to a large current is evaluated and $\cdot$ A possible application using an Optical CT was shown. An Influence of Faraday effect to the surrounding temperature measured -40~50[$^{\circ}C$], and the characteristic of the current sensitivity was reported. An application using the results of the temperature compensation system was used in order to compensate for surrounding temperatures. A possibility of applying Optical CT for electric power apparatus was advanced further. We were able to confirm that this temperature calibration method can minimize the fluctuation of the output signal depending on the temperature conditions.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.695-706
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• 2014

Partial discharge (PD) measurements have emerged as a dominant investigative tool for condition monitoring of insulation in high voltage equipment. But the major problem behind them the PD signal is severely polluted by several noises like White noise, Random noise, Discrete Spectral Interferences (DSI) and the challenge lies with removing these noise from the onsite PD data effectively which leads to preserving the signal for feature extraction. Accordingly the paper is mainly classified into two parts. In first part the PD signal is artificially simulated and mixed with white noise. In second part the PD is measured then it is subjected to the proposed denoising techniques namely Translation Invariant Wavelet Transform (TIWT). The proposed TIWT method remains the edge of the original signal efficiently. Additionally TIWT based denoising is used to suppress Pseudo Gibbs phenomenon. In this paper an attempt has been made to review the methodology of denoising the PD signals and shows that the proposed denoising method results are better when compared to other wavelet-based approaches like Fast Fourier Transform (FFT), Discrete Wavelet Transform (DWT), by evaluating five different parameters like, Signal to noise ratio, Cross-correlation coefficient, Pulse amplitude distortion, Mean square error, Reduction in noise level.