摘要
施工现场数据收集错误率大、迟缓,难以为管理人员提供准确及时的现场数据作为质量管理依据,因此需要更新数据采集和记录设备,高效获取数据,同时依靠图像识别技术开发施工质量自动化检查工具,有助于施工现场的质量管理,保证施工安全。
It is difficult for the management to timely obtain accurate data on-site due to errors and delay of data collection on-site.Therefore,equipment for data collection and recording need to be updated so that data can be acquired efficiently.Besides,tools capable of automatically assessing the construction quality should be developed by using image recognition technology to ensure the construction safety.
作者
杨森
刘子圣
霍冬梅
刘占省
裴亮
周航
YANG Sen;LIU Zi-sheng;HUO Dong-mei;LIU Zhan-sheng;PEI Liang;ZHOU Hang(China Power Construction Group Co.,Ltd.,100120,Beijing,China;Beijing University of Technology,100124,Beijing,China)
出处
《建筑技术》
2023年第2期138-141,共4页
Architecture Technology
关键词
钢结构
施工质量管理
质量评估
深度神经网络(DNN)
steel structure
management of construction quality
quality evaluation
deep neural network
