预制叠合板构件智能化识别与检测方法
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TU741.2

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国家重点研发计划(2019YFD1101005、2016YFC0701909);中央高校基本科研业务费(2020CDJQY-A067)


Intelligent identification and detection method of prefabricated laminated slab
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    摘要:

    预制叠合板构件质量问题是导致施工现场预制构件不能顺利安装的重要因素之一。提出了一种基于机器视觉的智能化检测预制叠合板构件的方法。首先通过预制构件生产线上的摄像系统进行图像采集,然后通过滤除噪声对图像进行预处理,通过Canny算子对边缘特征进行提取,通过Harris角点检测算法对图像内部特征进行提取,并将提取出的信息与已储存信息进行对比。利用该方法对三块预制叠合板试件进行特征识别及分析,结果表明:该检测方法可以识别预制叠合板尺寸信息,识别预留孔洞及预埋件的数量、尺寸及位置信息,对预制叠合板特征信息进行检测,并判断构件是否合格,提高了出厂构件的合格率,从而减少了施工成本,降低了工期延误风险。

    Abstract:

    The quality problem of prefabricated laminated slab (PLS) is one of the important factors that lead to the failure of prefabricated components in construction.A method of intelligent detection of PLS based on machine vision is presented in this paper. First, the image is collected through the camera system on the production line of PLS, and then the image is preprocessed through noise removal. The Canny algorithm is used to extract the edge features, and Harris corner detection algorithm is used to extract the internal features of the image.The extracted information is compared with the stored information.This method is used to identify and analyze the features of three PLS. The results prove that intelligent detection method can be used for image acquisition and image preprocessing of PLS, and the characteristics of the statistics, the size of PLS, the number, size and location information of reserved holes and embedded parts.Intelligent detection method can quickly detect and judge whether the PLS is qualified. It can improve the pass rate of factory components and reduce the return rate of components, and hence reduce the construction cost and the risk of project delay.

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杨阳,李青泽,姚刚.预制叠合板构件智能化识别与检测方法[J].土木与环境工程学报(中英文),2022,44(1):87-93. YANG Yang, LI Qingze, YAO Gang. Intelligent identification and detection method of prefabricated laminated slab[J]. JOURNAL OF CIVIL AND ENVIRONMENTAL ENGINEERING,2022,44(1):87-93.10.11835/j. issn.2096-6717.2020.187

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  • 收稿日期:2020-07-10
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  • 在线发布日期: 2021-11-25
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