• Ecology and Resilient Infrastructure
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• v.8 no.1
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• pp.9-21
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• 2021

In this study, fish and flow surveys were conducted at 12 survey points to calculate the fish habitat suitability index of Miho Stream in the Geum River Water System. The field surveys were conducted four times from September 2019 to May 2020. The results show the presence of 8 families, 37 species, and 5,754 individuals. The number of water purification species that preferred waters with a low flow rate was the highest. The habitat suitability index was calculated according to the Washington Department of Fish and Wildlife method based on the populations collected at various water depths and flow rate sections and the flow rate survey results. For the dominant species, Zacco platypus and swimming species, the results were compared by calculating at Gasan Bridge and Palgye Bridge at the upper stream. The single species showed no significant difference between the upstream and downstream at water depths of 0.1 - 0.5 m and flow rates of 0.2 - 0.5 m/s. The species swimming ability was similarly calculated at water depths of 0.2 - 0.5 m and flow rates of 0.2 - 0.5 m/s. The dominant species, Pyramid, had a wide range of physical habitats. The habitat suitability index between the swimming species was similarly calculated. These results can be effectively used as basic data for calculating the environmental ecological flow rate and establishing a river restoration plan of the Miho Stream.

• Smart Structures and Systems
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• v.16 no.2
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• pp.243-262
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• 2015

Optimal sensor placement (OSP) is a critical issue in construction and implementation of a sophisticated structural health monitoring (SHM) system. The uncertainties in the identified structural parameters based on the measured data may dramatically reduce the reliability of the condition evaluation results. In this paper, the information entropy, which provides an uncertainty metric for the identified structural parameters, is adopted as the performance measure for a sensor configuration, and the OSP problem is formulated as the multi-objective optimization problem of extracting the Pareto optimal sensor configurations that simultaneously minimize the appropriately defined information entropy indices. The nondirective movement glowworm swarm optimization (NMGSO) algorithm (based on the basic glowworm swarm optimization (GSO) algorithm) is proposed for identifying the effective Pareto optimal sensor configurations. The one-dimensional binary coding system is introduced to code the glowworms instead of the real vector coding method. The Hamming distance is employed to describe the divergence of different glowworms. The luciferin level of the glowworm is defined as a function of the rank value (RV) and the crowding distance (CD), which are deduced by non-dominated sorting. In addition, nondirective movement is developed to relocate the glowworms. A numerical simulation of a long-span suspension bridge is performed to demonstrate the effectiveness of the NMGSO algorithm. The results indicate that the NMGSO algorithm is capable of capturing the Pareto optimal sensor configurations with high accuracy and efficiency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.435-438
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• 2012

Today, In all fields, As combination of ubiquitous computing-based technologies between electronic space and physical space, has been active trend research about wireless integration sensor network between sensors and wireless technology. Also, but in ship is underway research about Ship Area Network(SAN) of intelligent ship to integrate wireless technology, ship is required SAN-bridge technology of a variety of wired, wireless network integration and heterogeneous sensor and interoperability of the controller and SAN configuration management technology of remote control. Ship keep safe of all the surrounding environment including crew besides structural safety and freight management monitoring. In this paper, for monitoring design such as on climate change detection and temperature, pressure about various structures, there identify technology trends for routing and data aggregation to use energy efficiency in wireless sensor network. And to analyze self-organizing clustering method, study For wireless sensor network configuration in ship.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.465-476
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• 2005

The wireless sensor network consists of a number of sensor nodes which have physical constraints. Each sensor node senses surrounding environments and sends the sensed information to Sink. In order to alleviate the inherent vulnerability in security of the wireless sensor nodes with the hardware constraints, the lightweight security protocol is needed and a variety of research is ongoing. In this paper, we propose a non-hierarchical sensor network and a security protocol that is suitable for monitoring man-made objects such as bridges. This paper, furthermore, explores a two-layer authentication, key distribution scheme which distributes the key and location of a sensor node in advance, and an effective security routing protocol which can take advantage of the Sleep and Awake state. This also results in the increased data transfer rate by increasing the number of alternative routing paths and the reduced energy consumption rate.

• Structural Engineering and Mechanics
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• v.56 no.4
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• pp.625-648
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• 2015

Modern super-tall buildings are more sensitive to strong winds. The evaluation of wind loads for the design of these buildings is of primary importance. A direct monitoring of wind forces acting on super-tall structures is quite difficult to be realized. Indirect measurements interpreted by inverse techniques are therefore favourable since dynamic response measurements are easier to be carried out. To this end, a Kalman filtering based inverse approach is developed in this study so as to estimate the wind loads on super-tall buildings based on limited structural responses. The optimum solution of Kalman filter gain by solving the Riccati equation is used to update the identification accuracy of external loads. The feasibility of the developed estimation method is investigated through the wind tunnel test of a typical super-tall building by using a Synchronous Multi-Pressure Scanning System. The effects of crucial factors such as the type of wind-induced response, the covariance matrix of noise, errors of structural modal parameters and levels of noise involved in the measurements on the wind load estimations are examined through detailed parametric study. The effects of the number of vibration modes on the identification quality are studied and discussed in detail. The made observations indicate that the proposed inverse approach is an effective tool for predicting the wind loads on super-tall buildings.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.372-377
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• 2002

Residual stress by welding should be reduced because that decreases the reliability on strength of welded structure. The reason is that the total stiffness of structure decreases by non-linear behavior of weldment under external load. The release of residual stress by mechanical loading and unloading is often performed in the fabrication of box structure for steel bridge. The proper degree of loading and unloading is significant at release method of residual stress by mechanical loading because that degree is changed by material and geometric shape of welded structure. Therefore, the simulation model that could exactly analyze the release of residual stress by mechanical loading is to be necessary. This simulation model should be established on the based of variable and accurate measurement data. In this study, the non-linear behavior of weldments under external loading and unloading, such as the decrease and increase of structure stiffness, was investigated by monitoring of nominal stress and strain. Tensile loading and unloading test under variable load was performed and the proper degree of stress relaxation was measured by sectioning technique using strain gauge.

• International Journal of Korean Welding Society
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• v.2 no.1
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• pp.40-44
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• 2002

Residual stress by welding should be reduced because that decreases the reliability on strength of welded structure. The reason is that the total stiffness of structure decreases by non-linear behavior of weldment under external load. The release of residual stress by mechanical loading and unloading is often performed in the fabrication of box structure for steel bridge. The proper degree of loading and unloading is significant at release method of residual stress by mechanical loading because that degree is changed by material and geometric shape of welded structure. Therefore, the simulation model that could exactly analyze the release of residual stress by mechanical loading is to be necessary. This simulation model should be established on the based of variable and accurate measurement data. In this study, the non-linear behavior of weldments under external loading and unloading, such as the decrease and increase of structure stiffness, was investigated by monitoring of nominal stress and strain. Tensile loading and unloading test under variable load was performed and the proper degree of stress relaxation was measured by sectioning technique using strain gauge.

• Smart Structures and Systems
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• v.29 no.1
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• pp.153-166
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• 2022

Identifying fine cracks in steel bridge facilities is a challenging task of structural health monitoring (SHM). This study proposed an end-to-end crack image segmentation framework based on a one-step Convolutional Neural Network (CNN) for pixel-level object recognition with high accuracy. To particularly address the challenges arising from small object detection in complex background, efforts were made in loss function selection aiming at sample imbalance and module modification in order to improve the generalization ability on complicated images. Specifically, loss functions were compared among alternatives including the Binary Cross Entropy (BCE), Focal, Tversky and Dice loss, with the last three specialized for biased sample distribution. Structural modifications with dilated convolution, Spatial Pyramid Pooling (SPP) and Feature Pyramid Network (FPN) were also performed to form a new backbone termed CrackDet. Models of various loss functions and feature extraction modules were trained on crack images and tested on full-scale images collected on steel box girders. The CNN model incorporated the classic U-Net as its backbone, and Dice loss as its loss function achieved the highest mean Intersection-over-Union (mIoU) of 0.7571 on full-scale pictures. In contrast, the best performance on cropped crack images was achieved by integrating CrackDet with Dice loss at a mIoU of 0.7670.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.914-919
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• 2004

When the motor is rotating, the torque and rpm are varying as the loads or the driving status connecting through reduction units are changing. On the contrary, one can monitor the changes of the loads or the driving status in the manner of measuring motor torque and rpm. There is a torque measuring method using the strain gauge and bridge circuit. But, because this is the contact method, it has the life time which is dependent on rotating velocity and used time. So this system demands on replacement of some Parts or whole system itself for maintenance. And this system is also relatively big and expensive, requiring preceding annoying process. In this paper, we are going to suppose non-contact method to measure torque and rpm using the Hall effects sensor For this we have made the planetary geared reduction motor with Hall sensors and with the monitoring system. The monitoring system displays the sensing data(torque, rpm) and calculated data( power) and also has the network capability with Bluetooth protocol. Our solution is much more inexpensive ;md simple method to measure torque and rpm than before.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.1
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• pp.55-64
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• 2015

Wind turbine market is showed height growth rate of about 30% for year, and is increasingly growing. Total rate of domestic wind turbine installation is showing share of 0.2% of the global market that is 380MW. However, wind turbine installed in domestic are foreign product more than 90%. Similarly, Datalogger of pretest system for ocean wind turbine plant installation has been leaked huge cost to abroad by mostly abroad company product. In this paper, we proposed pretest weather resource measurement system for efficiency and investment cost cutting of wind turbine construction work. Preset weather resource measurement system is ocean weather resource measurement datalogger based on wireless communication(wifi) that have consist of hardware and software(wind rose) that is able to monitoring as datalogger of wireless bridge and battery state, wind direction, wind speed, temperature, humidity, radiation around weather tower and is able to analysis of measured data.