• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.17 no.8
• /
• pp.757-765
• /
• 2007

Enhanced PSPICE circuit model for vented-box loudspeaker system with lumped parameters was proposed to more accurately simulate real vented-box loudspeaker system. Frequency dependent parameters were used to model voice coil inductor. Acoustic pressure response curves and electrical impedance curves were simulated and investigated by PSPICE circuit model according to circuit parameters' variations. Finally, it was used to identify faults detection in woofers manufactured by unskilled persons.

• Journal of Industrial Technology
• /
• v.21 no.A
• /
• pp.105-110
• /
• 2001

A continuous and reliable electrical energy supply is the objective of any power system operation. A transmission line is the part of the power system where faults are most likely to happen. This paler describes the use of wavelet transform for analyzing power system fault transients in order to determine the fault location. Synchronized sampling was made possible by precise time receivers based on GPS time reference, and the sampled data were analyzed using wavelet transform. This paper describes a fault location monitoring system and fault locating algorithm with GPS, DSP processor, and data acquisition board, and presents some experimental results and error analysis.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.32B no.12
• /
• pp.1687-1696
• /
• 1995

An integrated fault diagnosis system for heterogeneous manufacturing environments is developed. This system has a contrast with existing diagnosis systems in the respect that they are mostly for diagnosing faults on individual machines. In addition to the usual (e.g., audio, electrical) diagnostic signals, the characteristics of products from the machines are considered as the unifying diagnostic parameters among heterogeneous machines in the diagnosis. The system is composed of a knowledge representation scheme and a diagnostic query processing mechanism. Its knowledge representation scheme allows the diagnostic knowledges from heterogeneous unit diagnostic systems to be uniformly expressed in terms of the causal relations among relevant data items. It is flexible in the sense that causes for one relation can be effects for another may be reflected on our knowledge representation scheme. The diagnosis mechanism is based on a probabilistic inferencing method. This probablistic diagnosis mechanism provides more general diagnosis than existing ones in that it accommodates multiple causes and takes complication among causes into account. These scheme and mechanism are applied to a typical example to demonstrate how our system works.

• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.1
• /
• pp.19-25
• /
• 1998

Remote fault diagnosis and maintenance system using general telecommunication network is necessary for an effective fault diagnosis and higher productivity of NC machine tools. In order to monitor machine tool condition and diagnose alarm states due to electrical and mechanical faults, a remote data communication system for monitoring of NC machine fault diagnosis and status is developed. The developed system consists of (1) remote communication module among NC's and host PC using PSTN. (2) 8 channels analog data sensing module, (3) digital I/O module for control or NC machine, (4) communication module between NC machine and remote data communication system via RS-232C, and (5) software man-machine interface. Diagnostic monitoring results generated through a successive type inference engine are displayed in user-friendly graphics. The validity and reliability of the developed system is verified to be a powerful commercial version on a vertical machining center through a series of experiments.

• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.135-137
• /
• 2006

To improve device yield and throughput, faults in plasma processing equipment should be quickly and accurately diagnosed. Despite many useful information of ex-situ sensor measurements, their applications to recognize plasma faultshave not been investigated. In this study, a new technique to identify fault causes by recognizing X-ray photoelectron spectroscopy (XPS) using neural network and continuous wavelet transformation (CWT). The presented technique was evaluated with the plasma etch data. A totalof 17 experiments were conducted for model construction. Model performance was investigated from the perspectives of training error, testing error, and recognition accuracy with respect to various thresholds. CWT-based BPNN models demonstrated a higher prediction accuracy of about 26%. Their advantages over pure XPS-based models were conspicuous in all three measures at small networks.

• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.132-134
• /
• 2006

To improve equipment throughput and device yield, a malfunction in plasma equipment should be accurately diagnosed. A recognition model for plasma diagnosis was constructed by applying neural network to scanning electron microscope (SEM) image of plasma-etched patterns. The experimental data were collected from a plasma etching of tungsten thin films. Faults in plasma were generated by simulating a variation in process parameters. Feature vectors were obtained by applying direct and wavelet techniques to SEM Images. The wavelet techniques generated three feature vectors composed of detailed components. The diagnosis models constructed were evaluated in terms of the recognition accuracy. The direct technique yielded much smaller recognition accuracy with respect to the wavelet technique. The improvement was about 82%. This demonstrates that the direct method is more effective in constructing a neural network model of SEM profile information.

• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.138-140
• /
• 2006

A new diagnosis model was constructed by combining atomic force microscopy (AFM), wavelet, and neural network. Plasma faults were characterized by filtering AFM-measured etch surface roughness with wavelet. The presented technique was evaluated with the data collected during the etching of silicon oxynitride thin film. A total of 17 etch experiments were conducted. Applying wavelet to AFM, surface roughness was detailed into vertical, horizon%at, and diagonal components. For each component, neural network recognition models were constructed and evaluated. Comparisons revealed that the vertical component-based model yielded about 30% improvement in the recognition accuracy over others. The presented technique was evaluated with the data collected during the etching of silicon oxynitride thin film. A total of 17 etch experiments were conducted

• Proceedings of the KIEE Conference
• /
• 1995.11a
• /
• pp.516-518
• /
• 1995

This paper presents an integrated fault diagnosis expert system for power systems. The proposed system diagnoses various faults occurred in both substations and transmission lines even in the case that substation fault is spreaded over the network. To cope with this problem, A meta-inference method is proposed. This scheme shares same the data structure with the pre-developed intelligent operational aid expert system installed in a practical sub-control center, without modification. This advanced integrated diagnosis system is developed using a low cost personal computer owing to the special modular programming technique. Case studies show a promising possibility of the proposed method.

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.107-108
• /
• 2008

This paper surveys areas of vulnerability to voltage sags in KEPCO system. The area of vulnerability can be defined as the region where the occurrence of faults will lead to voltages lower than the sensitivity threshold of equipment. The analysis of the area of vulnerability is essential for estimating system voltage sag performance and establishing efficient countermeasures for voltage sag problems. In this paper, two buses in KEPCO system were randomly selected and the areas of vulnerability for the buses were calculated by using dedicated software.

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.307-308
• /
• 2008

This paper presents the effects of operating Backup Dispatch Center as a System Dispatch Center(SDC). SDC operates the 154kV transmission lines outside of Seoul metropolitan area, and acts as the backup dispatch center in case of central dispatch center's failure. With SDC, it became possible not only to divide operation of Korean transmission lines to separate control centers according to voltage and region, but to clear faults faster and more accurately. It has paved the way to improve power system reliability and advance the power system operation in general.