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Automatic Crack Recognition System for Concrete Structures Using Image Processing Approach

机译:基于图像处理的混凝土结构裂缝自动识别系统

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Recently, digital image processing technologies have been widely applied in different industries, because computerized technologies were widely utilized. In performance evaluation of deteriorating concrete bridges, the defect recognition such as crack pattern, crack width, crack depth, etc. On concrete surface is a significant advance and may lead to automation of the existing concrete bridge inspection at primary stage of the diagnosis. This study describes a novel approach for developing a system that extracts a crack pattern from digital images. A characteristic feature of the system is the use of an interactive genetic algorithm to optimize some parameters involved in the digital image processing. The algorithm prevents the system user from adjusting the parameters by trial and error. The user only evaluates some images produced by the system. The effectiveness of the system is verified by comparison of the results processed by trial and error and those obtained by using the proposed system. Once the above mentioned crack pattern on the concrete surface can be recognized, this study also introduces, in addition to an automatic measuring method of the maximum crack width, a practical recognition expert system which performs automatically with a certain level of accuracy.
机译:近年来,由于计算机技术被广泛利用,因此数字图像处理技术已广泛应用于不同行业。在劣化混凝土桥梁的性能评估中,在混凝土表面上的缺陷识别(例如裂缝模式,裂缝宽度,裂缝深度等)是一项重大进步,并可能在诊断的初期阶段使现有混凝土桥梁检查自动化。这项研究描述了一种开发系统的新颖方法,该系统可以从数字图像中提取裂纹图案。该系统的一个特征是使用交互式遗传算法来优化数字图像处理中涉及的某些参数。该算法可防止系统用户通过反复试验来调整参数。用户仅评估系统产生的一些图像。通过将试验和错误处理的结果与使用建议的系统获得的结果进行比较,可以验证该系统的有效性。一旦可以识别出混凝土表面上的上述裂缝图案,除了自动测量最大裂缝宽度的方法外,本研究还介绍了一种实用的识别专家系统,该系统以一定的精度自动执行。

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