2019年
IoT-powered remote sensing system and portable tools for real-time evaluation of strain imaging sheets affixed to old outdoor structures
NONDESTRUCTIVE CHARACTERIZATION AND MONITORING OF ADVANCED MATERIALS, AEROSPACE, CIVIL INFRASTRUCTURE, AND TRANSPORTATION XIII
- ,
- ,
- 巻
- 10971
- 号
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1117/12.2513829
- 出版者・発行元
- SPIE-INT SOC OPTICAL ENGINEERING
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.
- リンク情報
- ID情報
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- DOI : 10.1117/12.2513829
- ISSN : 0277-786X
- eISSN : 1996-756X
- Web of Science ID : WOS:000485112200023