• Journal of the Korea Society of Computer and Information
• /
• v.26 no.1
• /
• pp.45-55
• /
• 2021

This paper has proposed an algorithm that detecting for dense small vehicle in large image efficiently. It is consisted of two Ensemble Deep-Learning Network algorithms based on Coarse to Fine method. The system can detect vehicle exactly on selected sub image. In the Coarse step, it can make Voting Space using the result of various Deep-Learning Network individually. To select sub-region, it makes Voting Map by to combine each Voting Space. In the Fine step, the sub-region selected in the Coarse step is transferred to final Deep-Learning Network. The sub-region can be defined by using dynamic windows. In this paper, pre-defined mapping table has used to define dynamic windows for perspective road image. Identity judgment of vehicle moving on each sub-region is determined by closest center point of bottom of the detected vehicle's box information. And it is tracked by vehicle's box information on the continuous images. The proposed algorithm has evaluated for performance of detection and cost in real time using day and night images captured by CCTV on the road.

• Journal of Advanced Navigation Technology
• /
• v.16 no.4
• /
• pp.619-626
• /
• 2012

One-way Network-RTK(Real Time Kinematics) is considered as a method which can satisfy moving vehicle's recently-required high accuracy and mobility. When we use one-way Network RTK for vehicle navigation, multiple cells-based system is required to provide the service continuously in wide area. The rover which moves through various cells inevitably experiences a correction discontinuity, which is not eliminated by the DD(Double Difference) method and to cause 13cm(horizontal) and 48cm(vertical) position error. We suggest three solutions to reduce this discontinuity, which are identification of master RS with neighbor networks, duplication of communication module to receive corrections from other cells, and ambiguity adjustment between neighbor cells. All of our suggestions reduce the error to 1/4 wavelength in measurement and 3cm in position-domain, and we suggest the ambiguity adjustment is the best when we consider the extendibility of service area and the cost of rover device.

• Journal of Sensor Science and Technology
• /
• v.28 no.6
• /
• pp.414-419
• /
• 2019

An ultrasonic based magnetostrictive position sensor (MPS) provides an indication of real target position. It determines the real target position by multiplying the propagation speed of ultrasonic wave and the time-of-flight between the receiving signals; one is the initial signal by an excitation current and the other is the reflection signal by the ultrasonic wave. The propagation speed of the ultrasonic wave depends on the temperature of the waveguide. Hence, the change of the propagation speed in various environments is a critical factor in terms of the positioning accuracy in the MPS. This means that the influence of the changes in the waveguide temperature needs to be compensated. In this paper, we presents a novel way to improve the positioning accuracy of MPSs using temperature compensation for waveguide. The proposed method used the inherent measurement blind area for the structure of the MPS, which can simultaneously measure the position of the moving target and the temperature of the waveguide without any additional devices. The average positional error was approximately -23.9 mm and -1.9 mm before and after compensation, respectively. It was confirmed that the positioning accuracy was improved by approximately 93%.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.6 no.1
• /
• pp.90-98
• /
• 1998

A Dual Mass Flywheel(D.M.F.) system is an evolution to the reduction of torsional vibration and impact noise occurring in powertrain when a vehicle is either moving or idling. The D.M.F. system has two flywh-eels, which is different from the conventional clutch system. One section belongs to the mass moment of in-ertia of the engine-side. The other section increases the mass moment of inertia of the transmission-side. These two masses are connected via a spring/damping system. This reduces the speed at which the dreaded resonance occurs to below idle speed. Since 1984m D.M.F. system has been developed. However, the processes of development of D.M.F. system don't have any difference from the trial and error method of conventional clutch system. This paper present the method for systematical design of D.M.F. system with dimensionless design varia-bles of D.M.F. system, mass ratio between two flywheels, natural frequency rate of two flywheels, and visc-osity coefficient. And expermental results are used to prove these theoretical results.

• International Journal of Aeronautical and Space Sciences
• /
• v.15 no.3
• /
• pp.241-257
• /
• 2014

The modern development in design of airships and aerostats has led to unconventional configurations quite different from the classical ellipsoidal and spherical ones. This new class of air-vehicles presents a mass-to-volume ratio that can be considered very similar to the density of the fluid displaced by the vehicle itself, and as a consequence, modeling and simulation should consider the added masses in the equations of motion. The concept of added masses deals with the inertia added to a system, since an accelerating or decelerating body moving into a fluid displaces a volume of the neighboring fluid. The aim of this paper is to provide designers with the added masses matrix for more than twenty Lighter Than Air vehicles with unconventional shapes. Starting from a CAD model of a given shape, by applying a panel-like method, its external surface is properly meshed, using triangular elements. The methodology has been validated by comparing results obtained with data available in literature for a known benchmark shape, and the inaccuracies of predictions agree with the typical precision required in conceptual design. For each configuration, a CAD model and a related added masses matrix are provided, with the purpose of assisting the practitioner in the design and flight simulation of modern airships and scientific balloons.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2002.11a
• /
• pp.163-170
• /
• 2002

Terrain surfaces have to be modeled in very detail and wheel-surface contacting geometry must be well defined in order to obtain proper ground-reaction and friction forces for realistic simulation of off-road vehicles. Delaunay triangulation is one of the most widely used methods in modeling 3-dimensional terrain surfaces, and T-search is a relevant algorithm for searching resulting triangular polygons. The T-search method searches polygons in successive order and may not allow real-time computation of off-road vehicle dynamics if the terrain is modeled with many polygons, depending on the computer performance used in the simulation. In order to accelerate the searching speed of T-search, a terrain database of triangular polygons is modeled in multi-levels by adopting the LOD (Level of Detail) method used in realtime computer graphics. Simulation results show that the new LOD search is effective in shortening the required computing time. The LOD search can be even further accelerated by introducing an NN (Neural Network) algorithm, in the cases where a appropriate range of moving paths can be predicted by cultual information of the simulated terrain, such as lakes, houses, etc.. Numerical tests show that LOD-NN search almost double the speed of the original T-search.

• Proceedings of the KSR Conference
• /
• 2009.05a
• /
• pp.905-911
• /
• 2009

The viscosity drive method by the wheel which is widely used in the conventional railway systems needs a large friction force between the wheel and the guide-rail, which brings on a thrust force for a quick acceleration and a high-speed travelling. In addition, the viscosity drive method needs an increase of the vehicle weight for a large friction force. However, a maglev train is possible to be driven by the electro-magnet instead of the wheel, which produces a levitation and thrust force without any contact. In general, low-speed maglev train uses a linear induction motor(LIM) for propulsion that is operated under 300[km/h] due to the power-collecting and end-effect problems of LIM. In case of high-speed maglev train, a linear synchronous motor(LSM) is more suitable than LIM because of a high-efficiency and high-output properties. LSM has a driving principle as same as a conventional rotary synchronous motor(RSM), and the torque of RSM becomes the thrust force of LSM. A conventional LSM has relatively large air-gap compared with a conventional RSM. So, it must be achieved a design that is considered normal force by finite-asymmetric structure, end-effect on the entry and exit part, and support structure of a moving part. Therefore, in this research, authors accomplish a conceptualizing and basic design of a small-scaled LSM, and characteristics analysis using FEM.

• Structural Engineering and Mechanics
• /
• v.55 no.1
• /
• pp.111-135
• /
• 2015

Bridge behavior under passing traffic loads has been studied for the past 50 years. This paper presents how to model congestion on bridges and how the maximum dynamic stress of bridges change during the passing of moving vehicles. Most current research is based on mid-span dynamic effects due to traffic load and most bridge codes define a factor called the dynamic load allowance (DLA), which is applied to the maximum static moment under static loading. This paper presents an algorithm to solve the governing equation of the bridge as well as the equations of motions of two real European trucks with different speeds, simultaneously. It will be shown, considering congestion in eight case studies, the maximum dynamic stress and how far from the mid-span it occurs during the passing of one or two trucks with different speeds. The congestion effect on the maximum dynamic stress of bridges can make a significant difference in the magnitude. By finite difference method, it will be shown that where vehicle speeds are considerably higher, for example in the case of railway bridges which have more than one railway line or in the case of multiple lane highway bridges where congestion is probable, current designing codes may predict dynamic stresses lower than actual stresses; therefore, the consequences of a full length analysis must be used to design safe bridges.

• Smart Structures and Systems
• /
• v.28 no.6
• /
• pp.799-810
• /
• 2021

When monitoring the structural integrity of a bridge using data collected through accelerometers, identifying the profile of the load exerted on the bridge from the vehicles passing over it becomes a crucial task. In this study, the speed and location of vehicles on the deck of a bridge is reconfigured using real-time video to implicitly associate the load applied to the bridge with the response from the bridge sensors to develop an image-based deep learning network model. Instead of directly measuring the load that a moving vehicle exerts on the bridge, the intention in the proposed method is to replace the correlation between the movement of vehicles from CCTV images and the corresponding response by the bridge with a neural network model. Given the framework of an input-output-based system identification, CCTV images secured from the bridge and the acceleration measurements from a cantilevered beam are combined during the process of training the neural network model. Since in reality, structural damage cannot be induced in a bridge, the focus of the study is on identifying local changes in parameters by adding mass to a cantilevered beam in the laboratory. The study successfully identified the change in the material parameters in the beam by using the deep-learning neural network model. Also, the method correctly predicted the acceleration response of the beam. The proposed approach can be extended to the structural health monitoring of actual bridges, and its sensitivity to damage can also be improved through optimization of the network training.

• Smart Structures and Systems
• /
• v.31 no.1
• /
• pp.29-43
• /
• 2023

This study investigates the possibility of damage detection of a real bridge by means of a modal parameter-based finite element (FE) model update. Field moving vehicle experiments were conducted on an actual steel plate girder bridge. In the damage experiment, cracks were applied to the bridge to simulate damage states. A fast Bayesian FFT method was employed to identify and quantify uncertainties of the modal parameters then these modal parameters were used in the Bayesian model update. Material properties and boundary conditions are taken as uncertainties and updated in the model update process. Observations showed that although some differences existed in the results obtained from different model classes, the discrepancy between modal parameters of the FE model and those experimentally obtained was reduced after the model update process, and the updated parameters in the numerical model were indeed affected by the damage. The importance of boundary conditions in the model updating process is also observed. The capability of the MCMC model update method for application to the actual bridge structure is assessed, and the limitation of FE model update in damage detection of bridges using only modal parameters is observed.