摘要
钢筋是各项建设工程都离不开的一种材料,每年的钢筋使用量巨大,其在建设工程的重要程度不言而喻。在工程建设的各个环节中,钢筋检测是一项必不可少的工作。随着近年来神经网络的快速发展,社会各领域均向着智慧化方向发展,神经网络也已逐步应用于钢筋检测方面,重点阐述了神经网络在钢筋检测中的研究与应用,包括钢筋数量检测、钢筋尺寸检测、既有结构钢筋检测和钢筋锈蚀检测等几个方面,神经网络在钢筋检测中的研究与应用对于提高工程建设的质量和效率具有重要意义。通过充分利用神经网络的优势,可以实现自动化、高效、准确的钢筋检测,为工程师和建设项目的成功实施提供有力支持。
Rebars are an indispensable material for various construction projects,and the annual use of rebars is enormous,making it self-evident that they are of great importance in construction projects.In various stages of engineering construction,rebar inspection is an essential task.With the rapid development of neural networks in recent years,various fields in society have moved towards intelligence.Neural networks have also been gradually applied to rebar detection,with a focus on the research and application of neural networks in rebar detection,including rebar quantity detection,rebar size detection,existing structural rebar detection,and rebar corrosion detection.The research and application of neural networks in rebar detection is of great significance for improving the quality and efficiency of engineering construction.By fully utilizing the advantages of neural networks,automated,efficient,and accurate rebar detection can be achieved,providing strong support for the successful implementation of engineers and construction projects.
作者
唐仕尧
曾令勇
蒋军
付相林
Tang Shiyao;Zeng Lingyong;Jiang Jun;Fu Xianglin(Hunan Hengzhou Construction Co.,Ltd.,Hengyang Hunan 421001,China;School of Civil Engineering,Changsha University of Science&Technology,Changsha Hunan 410114,China)
出处
《山西建筑》
2024年第12期42-45,69,共5页
Shanxi Architecture
基金
国家自然科学基金(51408063,51808054)
湖南省教育厅优秀青年项目(20B031)。
关键词
神经网络
钢筋检测
钢筋数量检测
钢筋尺寸检测
既有结构钢筋检测
钢筋锈蚀检测
neural networks
rebar detection
rebar quantity detection
rebar dimension detection
detection of existing structure reinforcement
rebar corrosion detection
