首页> 外文期刊>Wireless personal communications: An Internaional Journal >Detection, Localization and Analysis of Oil Spills in Water Through Wireless Thermal Imaging and Spectrometer Based Intelligent System
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Detection, Localization and Analysis of Oil Spills in Water Through Wireless Thermal Imaging and Spectrometer Based Intelligent System

机译:无线热成像和基于光谱仪的智能系统在水中溢油的检测,定位和分析

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摘要

In this study, a marine robotic system is designed to locate and to quantify the surface water pollution in lakes and ponds with the consideration of the influences of neighboring buildings and trees. The proposed system consists of an aerial robot and a marine robot, which are actuated by pattern recognition at the base station with safe path planning. In the designed system,on quadrotor a Forward Looking Infra Red (FLIR) thermal imaging camera is employed to spot oil spills following a neural network method, while a wireless digital camera is used to identify the apropos path by imparting edge detection techniques. The surrounding buildings and trees dysfunction the digital camera's reflectivity, thereby disparate from optimal path planning. To dwindle the experimental impediment, the Voronoi algorithm is employed by fractionating the experiment's domain into small sub-sections. After that, Dijkstra's algorithm is considered to assure the optimal path planning from the starting point to the target. Fuzzy logic is introduced to direct boats towards the target. Global positioning system (GPS), sonar and navigation sensors based boat follow the trajectory defined by the aerial robot towards target point and take samples for quantification test through the spectrometer. These results then sent to the base station for pattern recognition using neural networks. Such systems can efficiently and effectively navigate the water pollution problems as disaster response.
机译:在这项研究中,船舶机器人系统旨在定位和量化邻近建筑物和树木影响的湖泊和池塘的地表水污染。所提出的系统由空中机器人和海洋机器人组成,该船用机器人通过具有安全路径规划的基站的模式识别来致动。在设计的系统中,在正版上看的红外线(FLIR)上的前进的红外线(FLIR)热成像相机在神经网络方法之后采用漏油泄漏,而无线数字相机用于通过赋予边缘检测技术来识别APPOS路径。周围的建筑物和树木功能障碍数码相机的反射率,从而不同于最佳路径规划。为了DWindle实验障碍,通过将实验域分解成小子部分来使用Voronoi算法。之后,Dijkstra的算法被认为是将最佳路径规划从起点到目标。引入模糊逻辑以指向目标的船只。基于全球定位系统(GPS),声纳和导航传感器的船遵循由空中机器人朝向目标点定义的轨迹,并通过光谱仪采取样品进行定量测试。然后,这些结果将由神经网络发送到基站以进行模式识别。这种系统可以有效地,有效地将水污染问题导航为灾害响应。

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