• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.544-544
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• 2014

Energy harvesting technology, which scavenges electric power from ambient, otherwise wasted, energy sources, has been explored to develop self-powered wireless sensors and possibly eliminate the battery replacement cost for wireless sensors. Among ambient energy sources, vibration energy can be converted into electric power through a piezoelectric energy harvester. For the last decade, although tremendous advances have been made in design methodology to maximize harvestable electric power under a given vibration condition, the research in reliability assessment to ensure durability has been stagnant due to the complicated nature of the multiple failure modes of a piezoelectric energy harvester, such as the interfacial delamination, fatigue failure, and dynamic fracture. Therefore, this study presents the first-ever system reliability analysis for multiple failure modes of a piezoelectric energy harvester using the Generalized Complementary Intersection Method (GCIM), while accounts for the energy conversion performance. The GCIM enables to decompose the probabilities of high-order joint failure events into probabilities of complementary intersection events. The electromechanically-coupled analytical model is implemented based on the Kirchhoff plate theory to analyze its output performances of a piezoelectric energy harvester. Since a durable as well as efficient design of a piezoelectric energy harvester is significantly important in sustainably utilizing self-powered electronics, we believe that technical development on system reliability analysis will have an immediate and major impact on piezoelectric energy harvesting technology.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.53 no.1
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• pp.41-48
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• 2017

Encircling gill net fishery is a kind of gill net which is generally used in shallow coastal waters. After the fish have been encircled by the gill net, noise stimulus such as a stone or sound is used to force them to gill or entangle themselves in the netting surrounding them. Although the fishing by a stone is a traditional fishing method, it is considered as an illegal fishing method by physical stimulus such as explosives and mechanical vibrator. However, this illegal fishing method has raised some problems to the fishing boat of other fisheries or many anglers due to disturb aggregating fish schools. This study is aimed to provide scientific base data to verify whether to impact the ecosystem caused by this encircling gill net. This study exhibited that the impulse noise by concrete sphere in the encircling gill net was $159dB/{\mu}Pa$, the ambient noise from ship engine was $160dB/{\mu}Pa$, and the maximum noise from continuous artificial vibrator was $175dB/{\mu}Pa$. These may be stimulus to the escape of fish distributed in a wide area in its natural state; it is not likely the cause of death due to catastrophic stress. Therefore, it needs to prepare the consideration of standard limit on fishing stimulus in fishing methods of the fishery laws and regulations, prevent fishermen form using illegal fishing gear (i.e. explosive sound standards: $200{\sim}220dB/{\mu}Pa$ and provide them with countermeasures.

• Structural Engineering and Mechanics
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• v.71 no.4
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• pp.391-405
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• 2019

Compared to the ambient vibration test mainly identifying the structural modal parameters, such as frequency, damping and mode shapes, the impact testing, which benefits from measuring both impacting forces and structural responses, has the merit to identify not only the structural modal parameters but also more detailed structural parameters, in particular flexibility. However, in traditional impact tests, an impacting hammer or artificial excitation device is employed, which restricts the efficiency of tests on various bridge structures. To resolve this problem, we propose a new method whereby a moving vehicle is taken as a continuous exciter and develop a corresponding flexibility identification theory, in which the continuous wheel forces induced by the moving vehicle is considered as structural input and the acceleration response of the bridge as the output, thus a structural flexibility matrix can be identified and then structural deflections of the bridge under arbitrary static loads can be predicted. The proposed method is more convenient, time-saving and cost-effective compared with traditional impact tests. However, because the proposed test produces a spatially continuous force while classical impact forces are spatially discrete, a new flexibility identification theory is required, and a novel structural identification method involving with equivalent load distribution, the enhanced Frequency Response Function (eFRFs) construction and modal scaling factor identification is proposed to make use of the continuous excitation force to identify the basic modal parameters as well as the structural flexibility. Laboratory and numerical examples are given, which validate the effectiveness of the proposed method. Furthermore, parametric analysis including road roughness, vehicle speed, vehicle weight, vehicle's stiffness and damping are conducted and the results obtained demonstrate that the developed method has strong robustness except that the relative error increases with the increase of measurement noise.

• Journal of Korea Multimedia Society
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• v.17 no.2
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• pp.124-131
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• 2014

In this paper, we propose the non-contact gesture recognition algorithm using 4- channel electrometer sensor array. ELF(Extremely Low Frequency) EMI and PLN are minimized because ambient electromagnetic noise around sensors has a significant impact on entire data in indoor environments. In this study, we transform AC-type data into DC-type data by applying a 10Hz LPF as well as a maximum buffer value extracting algorithm considering H/W sampling rate. In addition, we minimize the noise with the Kalman filter and extract 2-dimensional movement information by taking difference value between two cross-diagonal deployed sensors. We implemented the DTW gesture recognition algorithm using extracted data and the time delayed information of peak values. Our experiment results show that average correct classification rate is over 95% on five-gesture scenario.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.31-37
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• 2024

In this study, we propose a machine vision-based pedestrian signal detection algorithm that operates efficiently even in computing resource-constrained environments. This algorithm demonstrates high efficiency within limited resources and is designed to minimize the impact of ambient lighting by sequentially applying HSV color space-based image processing, binarization, morphological operations, labeling, and other steps to address issues such as light glare. Particularly, this algorithm is structured in a relatively simple form to ensure smooth operation within embedded system environments, considering the limitations of computing resources. Consequently, it possesses a structure that operates reliably even in environments with low computing resources. Moreover, the proposed pedestrian signal system not only includes pedestrian signal detection capabilities but also incorporates IoT functionality, allowing wireless integration with a web server. This integration enables users to conveniently monitor and control the status of the signal system through the web server. Additionally, successful implementation has been achieved for effectively controlling 50W LED pedestrian signals. This proposed system aims to provide a rapid and efficient pedestrian signal detection and control system within resource-constrained environments, contemplating its potential applicability in real-world road scenarios. Anticipated contributions include fostering the establishment of safer and more intelligent traffic systems.