• Journal of the Korean Society for Nondestructive Testing
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• v.14 no.1
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• pp.16-22
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• 1994

In contrast to the machineries using rolling element bearings, systems with journal bearings generally operate in large scale and under severe loading condition such as steam generator turbines and internal combustion engines. Failure of the bearings in these machineries can result in the system breakdown. To avoid the time consuming repair and considerable economic loss, the detection of incipient failure in journal bearings becomes very important. In this experimental approach, acoustic emission monitoring is applied to the detection of incipient failure caused by several types of abnormal operating condition most probable in the journal bearing systems. It has been known that the intervention of foreign materials, insufficient lubrication and misassembly etc. are principal factors to cause bearing failure and distress. The experiment was conducted under such designed conditions as hard particles in the lubrication layer, insufficient lubrication, and metallic contact in the simulated journal bearing system. The results showed that acoustic emission could be an effective tool to detect the incipient failure in journal bearings.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.2
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• pp.147-152
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• 2012

This paper dealt with the frequency component analysis of acoustic signals produced by corona and series-arc discharges as a diagnostic technique for closed-switchboards. Corona and series-arc discharge were simulated by a needle-plane electrode and an arc generator specified in UL1699, respectively. Acoustic signal was detected by a wideband acoustic sensor with a frequency bandwidth of 4 Hz~100 kHz (-3 dB). We analyzed frequency spectrums of the acoustic signals detected in various discharge conditions. The results showed that acoustic signals mainly exist in ranges from 30 kHz to 60 kHz. From the experimental results, an acoustic detection system which consists of a constant current power supply (CCP), a low noise amplifier (LNA) and a band pass filter was designed and fabricated. The CCP separates the signal component from the DC source of acoustic sensor, and the LNA has a gain of 40 dB in ranges of 280 Hz~320 kHz. The high and the low cut-off frequency are 30 kHz and 60 kHz, respectively. We could detect corona and series-arc discharges without any interference by the acoustic detection system, and the best frequency is considered in ranges of 30 kHz~60 kHz.

• Design & Manufacturing
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• v.14 no.2
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• pp.14-20
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• 2020

In OLED panel production process, it is necessary to cut a part of protective film as a preprocess for lighting inspection. The current method is to recognize only the fiducial mark of the cut-out panel. Bare Glass Cutting does not compensate for machining cumulative tolerances. Even though process defects still occur, it is necessary to develop technology to solve this problem because only the Align Mark of the panel that has already been cut is used as the reference point for alignment. There is a lot of defective lighting during panel lighting test because the correct protective film is not cut on the panel power and signal application pad position. In laser cutting process to remove the polarizing film / protective film / TSP film of OLED panel, laser processing is not performed immediately after the panel alignment based on the alignment mark only. Therefore, in this paper, we performed real time inspection which minimizes the mechanism tolerance by correcting the laser cutting path of the protective film in real time using Machine Vision. We have studied calibration algorithm of Vision Software coordinate system and real image coordinate system to minimize inspection resolution and position detection error and edge detection algorithm to accurately measure edge of panel.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.435-441
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• 2017

Detecting an inter-harmonic accurately is not easy work, because it has small magnitude, and its frequency which can be observed is not an integer multiple of fundamental frequency. In this paper, a new method using filter bank system and adaptive predictor is proposed. Filter bank system decomposes input signal to sub bands. In adaptive predictor, inter-harmonic is detected with decomposed sub band signal as input, and error signal as output. In this scheme, input-output characteristic of adaptive predictor is notch filter, as predicted harmonic is canceled in error signal, so detecting an inter-harmonic can be possible. Magnitude and frequency of detected inter-harmonic is estimated by recursive algorithm. The performances of proposed method are evaluated to sinusoidal signal model synthesized with harmonics and inter-harmonics. And validity of the method is proved as comparing the inter-harmonic detection results to MUSIC and ESPRIT.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.947-950
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• 2015

In the cause of car accidents in Korea, drowsy driving has shown that it is larger fctors than drunk driving. Therefore, in order to prevent drowsy driving accidents, drowsiness detection and warning system for drivers has recently become a very important issue. Furthermore, Many researches have been published that measuring alpha wave of EEG signals is the effective way in order to be aware of drowsiness of drivers. In this study, we have developed EEG measuring device that applies a signal processing algorithm using the LabView program for detecting drowsiness. According to results of drowsiness inducement experiments for small test subjects, it was able to detect the pattern of EEG, which means drowsy state based on the changing of power spectrum, counterpart of alpha wave. After all, Comparing to the results of drowsiness pattern between commercial equipments and developed device, we could confirm acquiring similar pattern to drowsiness pattern. With this results, the driver's drowsiness prevention system expect that it will be able to contribute to lowering the death rate caused by drowsy driving accidents.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.819-834
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• 2022

Artificial Intelligence (AI) techniques have been effectively used for image classification, object detection, and image segmentation. Along with the recent advancement of computing power, deep learning models can build deeper and thicker networks and achieve better performance by creating more appropriate feature maps based on effective activation functions and optimizer algorithms. This review paper examined technical and academic trends of Convolutional Neural Network (CNN) and Transformer models that are emerging techniques in remote sensing and suggested their utilization strategies and development directions. A timely supply of satellite images and real-time processing for deep learning to cope with disaster monitoring will be required for future work. In addition, a big data platform dedicated to satellite images should be developed and integrated with drone and Closed-circuit Television (CCTV) images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.101-103
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• 2022

CCTV is mainly used as a real-time detection system for critical facilities. In the case of CCTV, although the accuracy is high, the viewing angle is narrow, so it is used in combination with a sensor such as a radar. LiDAR is a technology that acquires distance information by detecting the time it takes to reflect off an object using a high-power pulsed laser. In the case of lidar, there is a problem in that the utilization is not high in terms of cost and technology due to the limitation of the number of simultaneous processing sensors in the server due to the data throughput. The detection method by the optical mesh sensor is also vulnerable to strong winds and extreme cold, and there is a problem of maintenance due to damage to animals. In this paper, by using the 1550nm wavelength band instead of the 905nm wavelength band used in the existing lidar sensor, the effect on the weather environment is strong and we propose to develop a system that can integrate and control multiple sensors.

• Journal of the korean academy of Pediatric Dentistry
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• v.37 no.1
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• pp.13-23
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• 2010

This study was performed to compare the quality of image processing between the newly developed prototype using light emitting diode(LED) and the conventional $DIFOTI^{TM}$ system(EOS Inc., USA). To estimate the optimal light emitting power for the improved images, primary enamel surfaces treated under Carbopol 907 de-mineralizing solution were taken daily during 20 days of experimental periods by both DIFOTI systems. The results of comparative analyses on the images obtained from both systems with polarized image as gold standard can be summarized as follows: 1. Trans-illumination indices of images taken from primary enamel surfaces were decreased with time in both systems. 2. The differences of intensity of luminance between sound and de-mineralized enamel surface in prototype DIFOTI system was shown to be relatively smaller than conventional $DIFOTI^{TM}$ system. 3. From the comparative analysis of images from both DIFOTI system with polarized images as gold standard, the difference between sound and de-mineralized enamel surface of intensity of luminance of $DIFOTI^{TM}$ system was more correlated to polarized images than prototype of DIFOTI system. With the optimal LED emitting power, the control of aperture of digital camera is considered as the another key factor to improve the DIFOTI images. For the best image quality and analysis, the development of the improved image processing software is required.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.32-33
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• 2016

Due to the frequent occurrence of dangerous wild animals in rural or mountainous areas. it has been increasing damage of crops in every year. Fight bell or electric fence is typically installed to chase those wild animals. But there are problems that it is impossible to drive out birds and spends high installation and maintenance cost. In addition, it is inefficient to the risk of electric shock effect. In this study, the proposed system can drive out hazardous wildlife and birds regardless of installation location through realtime detection with the multi-sensing based IoT platform technology. This study showed a very large significance effect that can reduce crop damage by wildlife and birds.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.521-522
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• 2016

This paper presents a novel scheme to estimate the rotor position of a single-phase hybrid switched reluctance motor (HSRM). The proposed method uses the differential of back-EMF within a position region to estimate rotor position. By detecting the crossing-zero signal of back-EMF differential value, the minimum position of back-EMF corresponding to an absolute rotor position can be captured and used for position estimation four times in every mechanical rotation. In this way, a sensorless operation with adjustable turn on/off angle can be achieved without substantial computation. For the starting, two current comparators are adopted. The experimental verification using a prototype drive system is provided to demonstrate the viability of the proposed sensorless scheme.