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A Practical Fog Detection and Dissipating System for the Preventing Fog Hazards of the Long-Span Bridge

机译:一种实用的雾检测和散热系统,用于防止长跨度桥梁的雾气危害

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A transportation development in recent years is quite remarkable. The occurrence and prediction of fog have been significant operational issues for quite some time, particularly with regard to transportation. A poor visibility arose from heavy fog and high vehicle speeds often causes terrible accidents such as Seohae grand bridge’s case at 2006 in Korea. Therefore, It is very important to quickly detect a fog occurrence, to notify users, and to practically be able to dissipate fog. In this study, we have proposed intelligent system to be aware of fog-occurrence, to deliver high intensity fog area and to operate fog-dissipating system at the long-span bridge. Well-tailored fog potential index can be provided to the two types of mobile application for the bridge’s manager and users. In the case of forecasting high intensity fog through calculated fog potential index, fiber net of farinfrared radiation is unfolded to hinder approaching fog and dissipate fog inside the bridge, which results in increasing more than 300m visibility distance capable to ordinarily drive. We expect this practical system to effectively respond fog hazards in the long span bridge, and have a plan to strengthen forecasting method through probabilistic analysis in the future.
机译:近年来的交通发展是非常显着的。雾的发生和预测是一段时间内的重大操作问题,特别是在运输方面。从雾气和高车速产生的可见性差,往往会导致韩国2006年Seohae Grand Bridge案例等可怕事故。因此,快速检测到雾化,通知用户非常重要,并且实际上能够消散雾。在这项研究中,我们提出了智能系统来了解雾化,以提供高强度雾面积,并在长跨度桥接运行雾化系统。可以为桥梁经理和用户提供良好定制的雾势指数。在通过计算出的雾势指数预测高强度雾的情况下,Farinfrad辐射的纤维网展开妨碍接近雾并在桥内消散雾,这导致往上沿往常驱动的300m的可见度距离。我们预计这一实际系统会在长跨度桥梁中有效地应对雾危害,并通过将来通过概率分析加强预测方法。

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