• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.68.2-68
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• 2002

The purpose of this paper is to monitor ECU's self-diagnostic signal without wire. In order to measure the ECU's self-diagnostic signal, the interfaced circuit is developed to communicate ECU with a designed display terminal according to the ISO, SAE regulation of communication protocol standard. An 80C196KC processor is used for communicating ECU's self-diagnostic signal and communication data are sent to PDA monitoring system that is based on the Windows CE. Software on PDA is developed to monitor the ECU's self-diagnostic signal in which RS232 port is programmed by half duplex method. The algorithms for measuring the ECU's self-diagnostic signals are verified to mo...

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.176-180
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• 2008

A field-oriented UHF system for on-line PD monitoring of transformers is designed, which has been installed inside the oil tank of transformer in a substation by two ways: on-line installing mode through the oil-valve and pre-installing mode through the man hole/hand hole cover. This system has successfully captured long intermittent discharge signals that hadn't been detected through conventional techniques, and solved the problem successfully. The results demonstrate that UHF technique has great advantages for on-line PD monitoring of transformers. By adopting the peak detection technique, it becomes easy and effective for the transplantation of the phase-resolved pattern recognition technique from conventional method to UHF method, and then to realize continuous on-line monitoring, source characterization and trending analysis.

• International Journal of Reliability and Applications
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• v.2 no.1
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• pp.57-71
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• 2001

Global competition to increase production output and to improve quality is spurring manufacturing companies to use condition monitoring and fault diagnostic systems for predictive maintenance. As monitoring, testing, and measuring techniques develop, predictive control of components and complete systems have become more practical and affordable. In this article, we will consider the computer based data acquisition system for condition monitoring and the condition parameter analysis techniques for fault detection and diagnostics in the machinery and briefly discuss reliability prediction and the limit value determination in condition monitoring.

• Smart Structures and Systems
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• v.5 no.2
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• pp.139-152
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• 2009

Globally, civil infrastructures are deteriorating at an alarming rate caused by overuse, overloading, aging, damage or failure due to natural or man-made hazards. With such a vast network of deteriorating infrastructure, there is a growing interest in continuous monitoring technologies. In order to provide a true distributed sensor and control system for civil structures, we are developing a Structural Nervous System that mimics key attributes of a human nervous system. This nervous system is made up of building blocks that are designed based on mechanoreceptors as a fundamentally new approach for the development of a structural health monitoring and diagnostic system that utilizes the recently developed piezo-fibers capable of sensing and actuation. In particular, our research has been focused on producing a sensory nervous system for civil structures by using piezo-fibers as sensory receptors, nerve fibers, neuronal pools, and spinocervical tract to the nodal and central processing units. This paper presents up to date results of our research, including the design and analysis of the structural nervous system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.12
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• pp.1238-1244
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• 2009

This work proposes a GUI-type on-line diagnostic program using SIMULINK and Fuzzy-Neuro algorithms for a helicopter turboshaft engine. During development of the diagnostic program, a look-up table type base performance module for reducing computer calculating time and a signal generation module for simulating real time performance data are used. This program is composed of the on-line condition monitoring program to monitor on-line measuring performance condition, the fuzzy inference system to isolate the faults from measuring data and the neural network to quantify the isolated faults. The reliability and capability of the proposed on-line diagnostic program were confirmed through application to the helicopter engine health monitoring.

• Smart Structures and Systems
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• v.17 no.1
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• pp.135-147
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• 2016

This paper describes a smart structural system, which uses smart materials for real-time monitoring and active control of bolted-joints in steel structures. The goal of this research is to reduce the possibility of failure and the cost of maintenance of steel structures such as bridges, electricity pylons, steel lattice towers and so on. The concept of the smart structural system combines impedance based health monitoring techniques with a shape memory alloy (SMA) washer to restore the tension of the loosened bolt. The impedance-based structural health monitoring (SHM) techniques were used to detect loosened bolts in bolted-joints. By comparing electrical impedance signatures measured from a potentially damage structure with baseline data obtained from the pristine structure, the bolt loosening damage could be detected. An outlier analysis, using generalized extreme value (GEV) distribution, providing optimal decision boundaries, has been carried out for more systematic damage detection. Once the loosening damage was detected in the bolted joint, the external heater, which was bonded to the SMA washer, actuated the washer. Then, the heated SMA washer expanded axially and adjusted the bolt tension to restore the lost torque. Additionally, temperature variation due to the heater was compensated by applying the effective frequency shift (EFS) algorithm to improve the performance of the diagnostic results. An experimental study was conducted by integrating the piezoelectric material based structural health monitoring and the SMA-based active control function on a bolted joint, after which the performance of the smart 'self-monitoring and self-healing bolted joint system' was demonstrated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.83-95
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• 1999

Wavelet transform has localization for time or frequency. It is useful to analyze a nonstationary signal. Basic function on wavelet transform is generated dilating and translating the original wavelet(mother wavelet). In this paper, time-frequency analysis method using linear combination wavelet transform is proposed. And it is applied to diagnostic monitoring system using the proposed linear combination wavelet transform. The stationary and nonstationary signal is used linear chirp signal, fan noise signal, a sinusoid signal from revolution body, electronic signal. Transform applied to signal analysis use fast Fourier transform (FFT), Daubechies, Haar and proposed linear combination method. The result of time-frequency analysis using linear combination wavelet transform is suited for portraying nonstationary time signal as well as stationary signal. Also the diagnostic monitoring system carry out the effective the signal analysis.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.473-475
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• 2001

We report the state of the development of monitoring system for 72.5kV GIS. In the first, the usual outline of the monitoring and diagnostic system for GIS was mentioned, and the detailed specifications and state of development were also described. Especially, we present items of monitoring for GIS such as the operating counter of CB, the leakage condition of $SF_6$ gas, the surge counter of LA and the leakage current of LA.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.6
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• pp.115-121
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• 2011

Intelligent distribution equipment is inevitable to realize self-healing which is one of smart grid functions in distribution network. Therefore, most of distribution equipment have been developed with self diagnostic sensors. However, it is not effective to construct on-line monitoring system for underground distribution cable because of high cost and low sensitivity. Recently, optical fiber composite cable is being considered for communication and power delivery in order to cope with increasing communication in distribution network. This paper presents the design and performance assessment results of underground cable on-line monitoring system using DTS(Distributed Temperature Sensing) and optical fiber composite underground cable.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2272-2275
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• 2002

PCA(Principle Component Analysis) has emerged as a useful tool for process monitoring and fault diagnosis. The general approach requires the user to identify the root cause by interpreting the residual or principle components. This could be tedious and often impossible for a large process. In this paper, PCA scheme is combined with the FCM-based fault diagnostic algorithm to enhance the diagnosistic results. The implementation of the PCA-FCM based fault diagnostic system is done and its application is illustrated on the two-tank system.