The construction industry is acutely aware of the need to improve its management process. Currently,construction management is facing four major schools of thoughts. This paper reports the recent study results,the aim...The construction industry is acutely aware of the need to improve its management process. Currently,construction management is facing four major schools of thoughts. This paper reports the recent study results,the aim of which was to compare these approaches. The focus will be on the questions:What is the theory root for this school of thoughts? What is the position of planning? What are the techniques used or recommended by each of these schools of thoughts in managing construction projects? Recommendations are then given through a deep discussion of the capability of each approach in managing today's highly complex construction 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The construction industry is acutely aware of the need to improve its management process. Currently,construction management is facing four major schools of thoughts. This paper reports the recent study results,the aim of which was to compare these approaches. The focus will be on the questions:What is the theory root for this school of thoughts? What is the position of planning? What are the techniques used or recommended by each of these schools of thoughts in managing construction projects? Recommendations are then given through a deep discussion of the capability of each approach in managing today's highly complex construction 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。
文摘为解决工程施工进度管控关键链技术应用中存在的缓冲区计算方法粗略,缓冲区监控方法脱离实际施工的问题,通过引入风险控制系数、资源影响系数、工序复杂系数、工序位置系数以及环境系数五个指标,运用层次分析法和CRITIC(Criteria Importance Through Intercriteria Correlation)客观赋权法构建缓冲区优化模型;将缓冲区消耗率和项目工作链完成进度百分比相关联,建立了缓冲区动态监控机制。运用缓冲区优化模型和动态监控机制改进关键链技术,将改进关键链技术应用于泵站工程施工进度管理。结果表明:该方法所得到的缓冲区尺寸较为合理,可以实现缩短计划工期和实现缓冲区动态监控,为水利工程施工进度管控提供借鉴。
