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IoT-powered remote sensing system and portable tools for real-time evaluation of strain imaging sheets affixed to old outdoor structures

机译:IOT供电的遥感系统和便携式工具,用于实时评估粘贴到旧室外结构的应变成像板

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Photonic crystal-based strain visualization film is promising for detecting the age-related deterioration of large man-made structures and public infrastructures.1 However, as the number of target structures increases, monitoring them all will become a major problem. We propose two solutions: (1) a portable solar-battery-powered automated monitoring station to monitor the color of photonic coatings, and (2) the application of real-time image analysis using mobile phones to record color changes. Both solutions make use of the power of small computers, while the former assists us with efficient data collection, and the latter helps non-experts to inspect structures without using expensive spectroscopes.The portable monitoring station consists of a micro-computer connected to a 3G mobile network, a USB camera and a solar battery system installed in a waterproof box. Photographs of the strain visualization film are taken once every hour and, at all other times, the computer disconnects the camera to save electricity. We placed four monitoring stations in the shade of a bridge or a tree and ran them continuously for more than a year.The application displays a real-time image in which only the strain-free area of the film is extracted. As a result, the region under strain and the background appear in white. This software runs on many mobile computers with built-in cameras and with OSs including Android, iOS, Windows and Linux. This is possible due to the versatility of the computer vision library we used, namely OpenCV, which widely used in robotics and automatic car-driving.
机译:基于光子晶体的应变可视化胶片是有希望检测大型人造结构和公共基础设施的年龄相关的恶化。然而,随着目标结构的数量增加,监测它们将成为一个主要问题。我们提出了两个解决方案:(1)便携式太阳能电池供电的自动化监控站,用于监控光子涂层的颜色,并使用移动电话进行实时图像分析的应用来记录颜色变化。这两种解决方案都利用了小型计算机的力量,而前者有助于我们有效的数据收集,后者有助于非专家在不使用昂贵的光谱的情况下检查结构。便携式监控站包括连接到3G移动网络的微型计算机,USB相机和安装在防水​​盒中的太阳能电池系统。每小时应变可视化膜的照片每小时一次,并且在所有其他时间都将电脑断开相机节省电力。我们在桥梁或树荫下放置了四个监测站,并连续跑了一年多。应用程序显示实时图像,其中仅提取膜的无应变区域。结果,在应变和背景下的区域出现在白色。该软件在许多移动计算机上运行内置摄像机,同时具有Android,iOS,Windows和Linux。这可能是由于我们使用的计算机视觉库的多功能性,即OpenCV,它广泛用于机器人和自动车辆驾驶。

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