• Smart Structures and Systems
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• 제23권4호
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• pp.359-371
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• 2019

As part of a structural health monitoring system, the relative geometric relationship between a ship and bridge has been recognized as important for bridge authorities and ship owners to avoid ship-bridge collision. This study proposes a novel computer vision method for the real-time geometric parameter identification of moving ships based on a single shot multibox detector (SSD) by using transfer learning techniques and monocular vision. The identification framework consists of ship detection (coarse scale) and geometric parameter calculation (fine scale) modules. For the ship detection, the SSD, which is a deep learning algorithm, was employed and fine-tuned by ship image samples downloaded from the Internet to obtain the rectangle regions of interest in the coarse scale. Subsequently, for the geometric parameter calculation, an accurate ship contour is created using morphological operations within the saturation channel in hue, saturation, and value color space. Furthermore, a local coordinate system was constructed using projective geometry transformation to calculate the geometric parameters of ships, such as width, length, height, localization, and velocity. The application of the proposed method to in situ video images, obtained from cameras set on the girder of the Wuhan Yangtze River Bridge above the shipping channel, confirmed the efficiency, accuracy, and effectiveness of the proposed method.

• Structural Engineering and Mechanics
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• 제77권3호
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• pp.305-314
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• 2021

In order to reduce enormous cost of real-scale underwater explosion experiments on ships, the mechanical response of the ships have been analyzed by combining scaled-down experiments and Hopkinson's scaling law. However, the Hopkinson's scaling law is applicable only if all variables vary in an identical ratio; for example, thickness of ship, size of explosive, and distance between the explosive and the ship should vary with same ratio. Unfortunately, it is infeasible to meet such uniform scaling requirement because of environmental conditions and limitations in manufacturing scaled model systems. For the facile application of the scaling analysis, we propose a generalized scaling law that is applicable for non-uniform scaling cases in which different parts of the experiments are scaled in different ratios compared to the real-scale experiments. In order to establish such a generalized scaling law, we conducted a parametric study based on numerical simulations, and validated it with experiments and simulations. This study confirms that the initial peak value of response variables in a real-scale experiment can be predicted even when we perform a scaled experiment composed of different scaling ratios for each experimental variable.

• 한국인공지능학회지
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• 제11권3호
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• pp.17-22
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• 2023

In this paper, we propose a black ice detection system using Convolutional Neural Networks (CNNs). Black ice poses a serious threat to road safety, particularly during winter conditions. To overcome this problem, we introduce a CNN-based architecture for real-time black ice detection with an encoder-decoder network, specifically designed for real-time black ice detection using thermal images. To train the network, we establish a specialized experimental platform to capture thermal images of various black ice formations on diverse road surfaces, including cement and asphalt. This enables us to curate a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Additionally, in order to enhance the accuracy of black ice detection, we propose a multi-scale dilation convolution feature fusion (MsDC-FF) technique. This proposed technique dynamically adjusts the dilation ratios based on the input image's resolution, improving the network's ability to capture fine-grained details. Experimental results demonstrate the superior performance of our proposed network model compared to conventional image segmentation models. Our model achieved an mIoU of 95.93%, while LinkNet achieved an mIoU of 95.39%. Therefore, it is concluded that the proposed model in this paper could offer a promising solution for real-time black ice detection, thereby enhancing road safety during winter conditions.

• 한국인공지능학회지
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• 제11권4호
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• pp.1-8
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• 2023

In this paper, we propose a black ice detection platform framework using Convolutional Neural Networks (CNNs). To overcome black ice problem, we introduce a real-time based early warning platform using CNN-based architecture, and furthermore, in order to enhance the accuracy of black ice detection, we apply a multi-scale dilation convolution feature fusion (MsDC-FF) technique. Then, we establish a specialized experimental platform by using a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Experimental results of a real-time black ice detection platform show the better performance of our proposed network model compared to conventional image segmentation models. Our proposed platform have achieved real-time segmentation of road black ice areas by deploying a road black ice area segmentation network on the edge device Jetson Nano devices. This approach in parallel using multi-scale dilated convolutions with different dilation rates had faster segmentation speeds due to its smaller model parameters. The proposed MsCD-FF Net(2) model had the fastest segmentation speed at 5.53 frame per second (FPS). Thereby encouraging safe driving for motorists and providing decision support for road surface management in the road traffic monitoring department.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2002년도 춘계 학술발표회 논문집
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• pp.203-210
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• 2002

The past bridge design specifications of Korea didn't include 1imitation on the amount of lap splices in the plastic hinge zone of piers, and so do current specifications. But these specifications include just limitation on the minimal length of lap splices. Thus, a large majority of non-seismically designed bridge piers may have lap splices in plastic hinge zone. In this study, model pier was selected among existent bridge piers whose failure mode is complex shear-flexure mode. Full scaled RC pier models whose aspect ratio is about 2.67 were constructed and quasi static test according to the drift level history was implemented. From the test results, effect of the lap splices on the seismic performance of bridges piers was analyzed, and the seismic capacity of the model bridges was evaluated by capacity spectrum method.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.720-725
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• 1997

This paper is to study the wind effect of the large scale gantry crane. It is used to control the sway of gantry crane in the loadingiunloading job of containers. I'hls is very important in the automated container terminal because the sway of handling equipments in pard is caused by thc l~nexpected disturbance such as wind and dynamic inertia by deriving force. This study shows the process of the modelling simulation of the wind effect of the sway motion of the gantry crane. Pro-Engineer, ANSYS and DAD'; ~ rr . used for 3D solid modelling and dynamic simulation. Though this study did not use the real parameters. the ; cwl ~ shows the trend of the wind effect is very large in the large scale crane and should be considered in design of the large scale gantry crane. In future, if the study is done by using the real parameters, the result is much more ~ise!'ul for dynamic control and design of gantry crane.

• 한국철도학회논문집
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• 제9권3호
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• pp.305-312
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• 2006

Gravel ballasted tracks are used as a basic structure for the domestic railway tracks. However, such kind of tracks has few disadvantages with service life of the structure, such as rapid deterioration of the tracks. Due to this reason, there is a need to develop low maintenance track to improve the service life of the conventional line tracks. CMP paved tacks are one of the kind of concrete tracks those were manufactured by using the prepacked concrete techniques. The purpose to develop paved tracks is to reduce the maintenance cost. The most important controlling factors to design the paved tracks are surrounding environmental condition and repeated train loading. In this study, in order to investigate the deformation characteristics such as displacement, earth pressure, strain ratio, and crack along the repeated loading cycle, cyclic loading test through real scale model was carried out.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제54권8호
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• pp.371-377
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• 2005

This paper Presents the Potential gradient characteristics of structure grounding electrode when a test current flows through grounding electrode. In order to analyze the potential gradient of ground surface on structure grounding electrode, the reduced scale model has been used. The potential gradient has been measured and analyzed for types of structure using the hemispherical grounding simulation system in real time. The structures were designed through reducing real buildings and fabricated with four types on a scale of one-one hundred sixty. The supporter was made to put up with weight of structure and could move into vertical, horizontal, rotary direction. When a test current flowed through structure grounding electrodes, ground potential rise was the lowest value at electric cage type(type B). According to resistivity and absorption percentage In concrete attached to structure, the potential distribution of ground surface appeared differently.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.670-673
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• 2002

This paper proposes a digital algorithm for gray-scale/color image segmentation of real-time video signals and a cell-network-based implementation architecture in state-of-the-art CMOS technology. Through extrapolation of design and simulation results we predict that about 300$\times$300 pixels can be integrated on a chip at 100nm CMOS technology, realizing very high-speed segmentation at about 1600sec per color image. Consequently real-time color-video segmentation will become possible in near future.

• Journal of Mechanical Science and Technology
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• 제15권6호
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• pp.776-787
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• 2001

The turbofan engine performance analysis for a medium scale commercial aircraft was carried out and the LQR control scheme for performance optimization was studied. By using scaled component maps from well-known CF6 engine characteristics, the steady-state performance analysis result was compared with BR715-56 engine performance data. The transient performance analysis was performed with four fuel schedules. The linear simulation was done at the maximum take-off condition. The real time linear simulation was performed by interpolation of the system matrices, which used the least square method as the function of LPC rotational speed. By using linear system matrices of design point, the LQR controller which used control variables for the fuel flow and the LPC bleed air was designed.