• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.669-674
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• 2007

To develop a promising hybrid structural health monitoring (SHM) system, a combined use of structural vibration and electro-mechanical (EM) impedance is proposed. The hybrid SHM system is designed to use vibration characteristics as global index and EM impedance as local index. The proposed health monitoring scheme is implemented into prestressed concrete (PSC) girder bridges for which a series of damage scenarios are designed to simulate various prestress-loss situations at which the target bridges car experience during their service life. The measured experimental results, modal parameters and electro-magnetic impedance signatures, are carefully analyzed to recognize the occurrence of damage and furthermore to indicate its location.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.301-304
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• 2001

In this paper, a method which can detect tracking caused by the insulation deterioration of conduct wiring, is proposed. The computer which take experiment data is learned by neural network algorithm, which has recently been used for the load recognition. The proposed method in our study can be applied to the development of several measuring equipments such as hot-line insulation tester, car earth tester for the detection of tracking under hot-line state.

• Proceedings of the KIEE Conference
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• 2000.11b
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• pp.405-407
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• 2000

The most generally implemented method to detect the ground speed of the railway vehicles is to use the rotary type speed sensor attached to wheel axle. The Slip or sliding phenomenon on the railway vehicles occurs frequently caused by the weak viscosity of the wheel. Thus, precisely to control the car, the slip/sliding detection system is required. In this paper we proposed for the speed data management system, which uses rotary type speed sensor. Proposed speed management system can detect the slip/sliding with wheel axle as well as correct the generated speed error during in error time, to provide accurate speed and precise location data. The effectiveness for adapting to the railway system is clarified by the computer simulation.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.1
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• pp.8-15
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• 2011

This paper presents an effective method for detecting vehicles in front of the camera-assisted car during nighttime driving. The proposed method detects vehicles based on detecting vehicle headlights and taillights using techniques of image segmentation and clustering. First, in order to effectively extract spotlight of interest, a pre-signal-processing process based on camera lens filter and labeling method is applied on road-scene images. Second, to spatial clustering vehicle of detecting lamps, a grouping process use light tracking method and locating vehicle lighting patterns. For simulation, we are implemented through Da-vinci 7437 DSP board with visible light mono-camera and tested it in urban and rural roads. Through the test, classification performances are above 89% of precision rate and 94% of recall rate evaluated on real-time environment.

• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.7-12
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• 2019

AEB (Autonomous Emergency Braking system), a system in which vehicles automatically recognize forward objects or pedestrians and actively brake when forward collisions are expected, has been mandated by NHTSA (National Highway Traffic Safety Administration) and IIHS (Insurance Institute for Highway Safety) for all vehicles sell in the United States since 2022, and AEB research is also actively underway in korea. In this study, it can be confirmed that the passenger injury is reduced according to the AEB detection distance when it is assumed that the AEB is mounted in the actual event generated from KIDAS (Korea New Car Assessment Program) data through various analysis programs.

• Journal of Electrochemical Science and Technology
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• v.15 no.1
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• pp.152-160
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• 2024

In this study, ZnCo₂O₄ nanoparticles were synthesized via the coprecipitation method using different annealing temperatures from 200℃ to 800℃. By varying the treatment temperature, the morphology changed from amorphous to tetragonal, and finally to polygonal particles. As temperature increased, the sizes of the nanoparticles also changed from 5 nm at 200℃ to approximately 500 nm at 800℃. The fabricated material was used to modify the working electrode of a screen-printed carbon electrode (SPE), which was subsequently used to survey the detection performance of the antibiotic, chloramphenicol (CAP). The electrochemical results revealed that the material exhibits a good response to CAP. Further, the sample that annealed at 600℃ displayed the best performance, with a linear range of 1-300 μM, and a limit of detection (LOD) of 0.15 μM. The sensor modified with ZnCo₂O₄ also exhibited the potential for utilitarian application when the recovery in a real sample was above 97%.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.643-650
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• 2013

In this paper, we propose a novel method for enhancing the detection speed and rate by reducing the computation in Hough Circle Transform on real-time iris detection of smartphone camera image. First of all, we find a face and eyes from input image to detect iris and normalize the iris region into fixed size to prevent variation of size for iris region according to distance from camera lens. Moreover, we carry out histogram equalization to get regular image in bright and dark illumination from smartphone and calculate minimal iris range that contains iris with the distance between corner of the left eye and corner of the right eye on the image. Subsequently, we can minimize the computation of iris detection by applying Hough Circle Transform on the range including the iris only. The experiment is carried out in two case with bright and dark illumination. Our proposed method represents that detection speed is 40% faster and detection rate is 14% better than existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1516-1529
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• 2023

In this paper, a motor gearbox fault-detection system based on a hierarchical flow-based model is proposed. The proposed system is used for the anomaly detection of a motion sound-based actuator module. The proposed flow-based model, which is a generative model, learns by directly modeling a data distribution function. As the objective function is the maximum likelihood value of the input data, the training is stable and simple to use for anomaly detection. The operation sound of a car's side-view mirror motor is converted into a Mel-spectrogram image, consisting of a folding signal and an unfolding signal, and used as training data in this experiment. The proposed system is composed of an encoder and a decoder. The data extracted from the layer of the pretrained feature extractor are used as the decoder input data in the encoder. This information is used in the decoder by performing an interlayer cross-scale convolution operation. The experimental results indicate that the context information of various dimensions extracted from the interlayer hierarchical data improves the defect detection accuracy. This paper is notable because it uses acoustic data and a normalizing flow model to detect outliers based on the features of experimental data.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.447-453
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• 2009

This paper introduces the method for detect voices and exact end point at low SNR by maximizing voice energy. Conventional VAD (Voice Activity Detection) algorithm estimates noise level so it tends to detect the end point inaccurately. Moreover, because it uses relatively long analysis range for reflecting temporal change of noise, computing load too high for application. In this paper, the SEM-VAD (Speech Energy Maximization-Voice Activity Detection) method which uses psycho-acoustical bark scale filter banks to maximize voice energy within frames is introduced. Stable threshold values are obtained at various noise environments (SNR 15 dB, 10 dB, 5 dB, 0 dB). At the test for voice detection in car noisy environment, PHR (Pause Hit Rate) was 100%accurate at every noise environment, and FAR (False Alarm Rate) shows 0% at SNR15 dB and 10 dB, 5.6% at SNR5 dB and 9.5% at SNR0 dB.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2135-2140
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• 2015

In this paper, proposed a new lighting control system which can reduce power consumption compared to conventional street lamps and intelligently control the light efficiently depending on whether there is a vehicle on the street. The new lighting control system proposed by this paper detects the presence of cars by collecting and analyzing sounds generated by the movement of cars. Then, the system controls lighting of street lamps based on the above car detection information, and turns on the street lamps sequentially by transmitting the car detection information. Experimental results showed that lightings were controlled based on the presence of cars and that operations of the lamps were made by turning on the lights sequentially by determining the moving direction of cars. This system is considered a technology that can reduce energies by applying to local roads with a few cars moving or national highways where lights are always turned on with low energy efficiency.