• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.241-248
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• 2009

This paper presents stochastic methodology based fault detection algorithm for induction motor systems. We measure current of healthy induction motors by means of hall sensor systems and then establish its probability distribution. We propose online probability density estimation which is effective in real-time implementation due to its simplicity and low computational burden. In addition, we accomplish theoretical analysis of the proposed estimation to demonstrate its convergence property by using statistical convergence and system stability theories. We apply our fault detection approach to three-phase induction motors and achieve real-time experiment for evaluating its reliability and practicability in industrial fields.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.43-48
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• 2007

In this study, an ANN-based damage detection algorithm using acceleration signals is developed for alarming locations of damage in beam-type structures. A new ANN-algorithm using output-only acceleration responses is designed for damage detection in real time. The cross-covariance of two acceleration signals measured at two different locations is selected as the feature representing the structural condition. Neural networks are trained for potential loading patterns and damage scenarios of the target structure for which its actual loadings are unknown. The feasibility and practicality of the proposed method are evaluated from laboratory-model tests on free-free beams for which accelerations were measured before and after several damage cases.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.123.2-123.2
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• 2013

Etching endpoint detection with plasma impedance monitoring (PIM) is demonstrated for small area dielectric layers inductive coupled plasma etching. The endpoint is determined by the impedance harmonic signals variation from the I-V monitoring system. Measuring plasma impedance has been examined as a relatively simple method of detecting variations in plasma and surface conditions without contamination at low cost. Cluster analysis algorithm is modified and applied to real-time endpoint detection for sensitivity enhancement in this work. For verification, the detected endpoint by PIM and real-time cluster analysis is compared with widely used optical emission spectroscopy (OES) signals. The proposed technique shows clear improvement of sensitivity with significant noise reduction when it is compared with OES signals. This technique is expected to be applied to various plasma monitoring applications including fault detections as well as end point detection.

• Journal of the Semiconductor & Display Technology
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• v.9 no.2
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• pp.79-85
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• 2010

In this paper, we propose a web inspection system (WIS) for real-time detection of paper defects which can cause critical fractures during papermaking process. Our system incorporates high speed line-scan camera, lighting system, and detection algorithm to provide robust and precise detection of paper defects in real-time. Since edge defects are very crucial to the paper fractures, our system focuses on the edge region of the paper instead of inspecting the whole paper area. In our algorithm, image projection and sub-pixel operation are utilized to detect the edge defects precisely and connected component labeling and shape analysis techniques are adopted to extract various kinds of the region defects. Experimental results revealed that our web inspection system is very efficient for detecting paper defects during papermaking processes.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1360-1363
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• 1996

EPD(End Point Detection) is used to decide etching degree of layer which must be removed at wafer etching process in plasma etching process which is one of the most important process in semiconductor manufacturing. In this thesis, the method which detects malfunction of etching process in real-time will be discussed. Several EPD signal traces are collected in normal plasma etching condition and used as reference EPD signal traces. Critical points can be detected by applying differentiation and zero-crossing techniques to reference EPD signal. Mean and standard deviation of critical parameters which is memorized from reference EPD signal are calculated and these determine the lower and higher limit of control chart. And by applying statical control chart to EPD signals which are collected in real etching process malfunctions of process are detected in real-time. By means of applying this method to the real etching process we prove our method can accurately detect the malfunction of etching process and can compensate disadvantage of current industrial method.

• Korean Journal of Veterinary Research
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• v.44 no.4
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• pp.655-662
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• 2004

The aim of this work was the validation of a rapid real-time PCR assay based on TaqMan technology for the unequivocal identification of infectious canine hepatitis (ICH) virus, to be used directly on DNA purified from blood specimens. A real-time PCR system targeting at the E3 ORFA gene sequence of canine adenovirus type 1 was optimized and validated through comparative analysis of samples using conventional PCR system. The real-time PCR assay based on TaqMan technology could disclose 23 (37.7%) out of 61 samples as PCR positive. In contrast, 18 (29.5%) samples were found PCR positive when conventional PCR was applied on these samples. The use of the ABI Prism 7700 sequence detection system allowed the efficient determination of the amplified product accumulation through a fluorogenic probe. The entire real-time TaqMan PCR assay, including DNA extraction, amplification, and detection could be completed within 3 hours. The detection method of real-time TaqMan PCR assay was 1,000 times more sensitive than conventional PCR. Real-time TaqMan probe and primer set developed and optimized in this study is a sensitive, rapid and accurate method for detection of ICH virus and can be effective screening tool for the detection of ICH in a diagnostic laboratory routines.

• Food Science and Preservation
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• v.30 no.2
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• pp.262-271
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• 2023

The objective of this study is to compare and assess the effectiveness of real-time polymerase chain reaction (RT-PCR), loop-mediated isothermal amplification (LAMP), and the selective agar plate method for the detection of Salmonella spp. and Listeria monocytogenes in ready-to-eat (RTE) foods. In RTE foods, the detection performance of the three methods (RT-PCR [SureTect^TM kit and PowerChek^TM kit], LAMP [3M MDS], selective agar) were similar at 0-10, 10-50, 50-100, and 100- CFU/mL of Salmonella spp. and L. monocytogenes. We found that with RT-PCR, the Ct value of salad was significantly higher (p<0.05) than other RTE foods, indicating that fiber plays a critical role as an obstacle to the rapid detection of Salmonella spp. However, the Ct value displayed a mixed pattern according to the inoculation level of L. monocytogenes. The use of rapid detection kits and machines mostly depends on the user's choice, with accuracy, ease of use, and economy being the primary considerations. As an RT-PCR kit, SureTect^TM and PowerChek^TM showed high accuracy in detecting Salmonella spp. and L. monocytogenes in RTE foods, showing that they can replace the existing RT-PCR kits available. Additionally, LAMP also showed excellent detection performance, suggesting that it has the potential to be used as a food safety management tool.

• ETRI Journal
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• v.18 no.2
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• pp.61-74
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• 1996

We propose two new rate control schemes to improve MPEG-2 rate control in view of visual quality when scene changes happen. Two proposed schemes are characterized by real-time and non real-time improvement to reduce the impact of scene changes. We also propose a new target-bit prediction method using spatial activity of pictures and present a simple and efficient scene change detection scheme using signed difference of mean absolute difference (MAD). Computer simulation results show that the proposed real-time algorithm effectively alleviates visual quality degradation after scene changes. The proposed non real-time algorithm gives maximum 2 dB improvement in peak signal-to-noise ratio (PSNR) at a scene-changed picture, compared with MPEG-2 rate control scheme and it shows better quality than the real-time one.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.11b
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• pp.60-76
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• 2000

Early detection in real-time response of slope movements ensures tremendous saving of lives and repair costs from catastrophic disaster Therefore, it is essential to constantly monitor the performance and integrity of slope-stabilizing structures such as Rock bolt, Nail and Pile during or after installation. We developed a novel monitoring system using Fiber Bragg Grating (FBG)sensor. It's advantages are highly sensitivity, small dimension and electro-magnetic immunity. capability of multiplexing, system integrity, remote sensing - these serve real-time health monitoring of the structures. Real-time strain measurement by the signal processing program is shown graphically and it gives a warning sound when the monitored strain state exceeds a given threshold level so that any sign of abnormal disturbance on the spot can be easily perceived.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.428-442
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• 2022

A reliable automatic passenger counting (APC) system is a key point in transportation related to the efficient scheduling and management of transport routes. In this study, we introduce a lightweight head detection network using deep learning applicable to an embedded system. Currently, object detection algorithms using deep learning have been found to be successful. However, these algorithms essentially need a graphics processing unit (GPU) to make them performable in real-time. So, we modify a Tiny-YOLOv3 network using certain techniques to speed up the proposed network and to make it more accurate in a non-GPU environment. Finally, we introduce an APC system, which is performable in real-time on embedded systems, using the proposed head detection algorithm. We implement and test the proposed APC system on a Samsung ARTIK 710 board. The experimental results on three public head datasets reflect the detection accuracy and efficiency of the proposed head detection network against Tiny-YOLOv3. Moreover, to test the proposed APC system, we measured the accuracy and recognition speed by repeating 50 instances of entering and 50 instances of exiting. These experimental results showed 99% accuracy and a 0.041-second recognition speed despite the fact that only the CPU was used.