About the author:

1. Ronghua Construction Group Co., Ltd., Qingdao, 266600, China；2. Ronghua Qingdao Construction Technology Co., Ltd., Qingdao, 266000, China；3. Shandong Jianzhu University,Jinan 250000

Abstract:

Prefabricated buildings adopt industrial production and prefabricated construction, which have the characteristics of high construction efficiency, energy conservation and environmental protection, and have received strong support from the country. As prefabricated components with very high prefabrication and assembly rates, the quality of prefabricated concrete composite panels is related to the entire project. There are some problems in the production process of prefabricated composite panels, such as the use of manual inspection for concealed acceptance work before concrete pouring, which results in a large amount of manual input, low quality inspection level and efficiency, and easy omission and misinspection, seriously restricting the production efficiency of concrete composite panels. This article takes prefabricated concrete composite panels as the research object, conducts research on image distortion correction algorithm and data enhancement algorithm, improves YOLOv7 prefabricated composite panel precise recognition algorithm and steel bar layout and spacing recognition method, and develops a machine vision based intelligent detection and control system for prefabricated composite panels. The system can intelligently evaluate the size error, embedded part position and quantity of composite panels, thereby reducing the investment of quality inspectors, improving production efficiency and product qualification rate.