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An efficient image-based damage detection for cable surface in cable-stayed bridges

机译:对斜拉桥中的电缆表面进行基于图像的有效损伤检测

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Since cable members are the major structural components of cable bridges, they should be properly inspected for surface damage and inside defects such as corrosion and/or breakage of wires. This study introduces an efficient image-based damage detection system that can automatically identify damages to the cable surface through image processing techniques and pattern recognition. The damage detection algorithm combines image enhancement techniques with principal component analysis (PCA) algorithm. Images from three cameras attached to a cable climbing robot are wirelessly transmitted to a server computer located on a stationary cable support. To improve the overall quality of the images, this study utilizes an image enhancement method together with a noise removal technique. Next the input images are projected into PCA sub-space, the Mahalanobis square distance is used to determine the distances between the input images and sample patterns. The smallest distance is found to be a match for an input image. The proposed damage detection algorithm was verified through laboratory tests on three types of cables. Results of the tests showed that the proposed system could be used to detect damage to bridge cables.
机译:由于电缆构件是电缆桥架的主要结构部件,因此应适当检查它们的表面损伤和内部缺陷,例如腐蚀和/或电线断裂。这项研究引入了一种有效的基于图像的损坏检测系统,该系统可以通过图像处理技术和模式识别来自动识别电缆表面的损坏。损伤检测算法将图像增强技术与主成分分析(PCA)算法结合在一起。来自连接到攀岩机器人的三个摄像机的图像被无线传输到位于固定电缆支架上的服务器计算机。为了提高图像的整体质量,本研究利用图像增强方法和噪声消除技术。接下来,将输入图像投影到PCA子空间中,使用Mahalanobis平方距离来确定输入图像与样本图案之间的距离。发现最小距离是输入图像的匹配。通过对三种类型的电缆进行实验室测试,验证了所提出的损伤检测算法。测试结果表明,所提出的系统可用于检测桥梁电缆的损坏。

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