Various industries today rely on the support of electromechanical equipment,expanding its scope of application and leading to an increase in electromechanical installation projects.However,due to the high level of exp...Various industries today rely on the support of electromechanical equipment,expanding its scope of application and leading to an increase in electromechanical installation projects.However,due to the high level of expertise required and the potential risks involved,it is crucial to emphasize safety management during construction.This paper delves into the significance of construction safety management for electromechanical installation projects,identifies common problems encountered during construction,and proposes solutions.This analysis aims to provide relevant personnel with essential guidance and references for managing electromechanical installation projects safely.展开更多
Given the advances in science and technology,rapid development of socialist market economy and continuous advance of urbanization,it is necessary to enlarge the scale of engineering construction.As the form of enginee...Given the advances in science and technology,rapid development of socialist market economy and continuous advance of urbanization,it is necessary to enlarge the scale of engineering construction.As the form of engineering structure becomes more complex,large-scale and high-level projects with deep foundation have appeared in engineering construction.For construction engineering,one of its technologies includes solving the difficulties in construction.It is required to deal with the safety risk of construction in time to guarantee safety construction,timely solve the management difficulties and contradictory problems of the project and ensure both the safety of engineering construction and the rationalization of the institution setting of the safety supervision on the project.展开更多
为解决危大工程中吊装作业安全管理的问题,基于深度学习构建目标检测算法(You Only Look Once version 5,YOLOv5)网络模型,针对进入吊装作业区域内人员的防护装备进行多目标融合检测,并对吊钩在施工过程中的状态进行检测。在原始的检测...为解决危大工程中吊装作业安全管理的问题,基于深度学习构建目标检测算法(You Only Look Once version 5,YOLOv5)网络模型,针对进入吊装作业区域内人员的防护装备进行多目标融合检测,并对吊钩在施工过程中的状态进行检测。在原始的检测网络模型中引入4种注意力机制,并通过5种训练模型的结果对比分析,进而选择卷积块注意力模块(Convolutional Block Attention Module,CBAM)最优模型。优化后的检测模型对安全帽的平均识别精度达86.5%,对反光衣的平均识别精度达83.0%,对吊钩的状态识别精度达92.0%。将训练好的人员检测模型和吊钩检测模型打包成exe执行文件,应用到施工安全管理人员的中控平台,可帮助管理人员更好地判断吊装作业的工作情况,进而及时进行风险管控。展开更多
文摘Various industries today rely on the support of electromechanical equipment,expanding its scope of application and leading to an increase in electromechanical installation projects.However,due to the high level of expertise required and the potential risks involved,it is crucial to emphasize safety management during construction.This paper delves into the significance of construction safety management for electromechanical installation projects,identifies common problems encountered during construction,and proposes solutions.This analysis aims to provide relevant personnel with essential guidance and references for managing electromechanical installation projects safely.
文摘Given the advances in science and technology,rapid development of socialist market economy and continuous advance of urbanization,it is necessary to enlarge the scale of engineering construction.As the form of engineering structure becomes more complex,large-scale and high-level projects with deep foundation have appeared in engineering construction.For construction engineering,one of its technologies includes solving the difficulties in construction.It is required to deal with the safety risk of construction in time to guarantee safety construction,timely solve the management difficulties and contradictory problems of the project and ensure both the safety of engineering construction and the rationalization of the institution setting of the safety supervision on the project.
文摘为解决危大工程中吊装作业安全管理的问题,基于深度学习构建目标检测算法(You Only Look Once version 5,YOLOv5)网络模型,针对进入吊装作业区域内人员的防护装备进行多目标融合检测,并对吊钩在施工过程中的状态进行检测。在原始的检测网络模型中引入4种注意力机制,并通过5种训练模型的结果对比分析,进而选择卷积块注意力模块(Convolutional Block Attention Module,CBAM)最优模型。优化后的检测模型对安全帽的平均识别精度达86.5%,对反光衣的平均识别精度达83.0%,对吊钩的状态识别精度达92.0%。将训练好的人员检测模型和吊钩检测模型打包成exe执行文件,应用到施工安全管理人员的中控平台,可帮助管理人员更好地判断吊装作业的工作情况,进而及时进行风险管控。