跟踪主要资源,用于施工活动的自动化进度监控:砖石工程案例

G. Guven, E. Ergen
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引用次数: 10

摘要

本研究的目的是通过使用基于传感器的技术来跟踪建筑施工中使用的多种资源,以自动化的方式监测建筑活动的进度。设计/方法/方法提出了一种自动化现场进度监测方法,并开发了概念验证原型,随后在高层建筑施工现场进行了现场实验研究。所开发的方法用于整合从活动不同步骤中使用的多个资源收集的传感器数据。它结合了与站点布局条件和活动方法相关的领域特定启发式。该原型对整体进度的估计准确率为95%。与人工方法相比,实现了更准确和最新的进度测量,并且消除了从现场进行目视检查和手动收集数据的需要。总体而言,现场实验表明,如果在设备上使用现成的或嵌入式传感器,低成本实施是可能的。原创性/价值以前的研究要么监测一个特定的设备,要么开发的方法只适用于有限的活动类型。该研究表明,在建筑上部结构施工过程中,通过融合从多个资源收集的传感器数据来确定现场进度在技术上是可行的。基于规则的推理算法是根据起重机和起重机的典型工作实践开发的,可以适用于涉及转移散装物料和使用起重机和/或起重机进行物料搬运的其他活动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tracking major resources for automated progress monitoring of construction activities: masonry work case
Purpose The purpose of this study is to monitor the progress of construction activities in an automated way by using sensor-based technologies for tracking multiple resources that are used in building construction. Design/methodology/approach An automated on-site progress monitoring approach was proposed and a proof-of-concept prototype was developed, followed by a field experimentation study at a high-rise building construction site. The developed approach was used to integrate sensor data collected from multiple resources used in different steps of an activity. It incorporated the domain-specific heuristics that were related to the site layout conditions and method of activity. Findings The prototype estimated the overall progress with 95% accuracy. More accurate and up-to-date progress measurement was achieved compared to the manual approach, and the need for visual inspections and manual data collection from the field was eliminated. Overall, the field experiments demonstrated that low-cost implementation is possible, if readily available or embedded sensors on equipment are used. Originality/value Previous studies either monitored one particular piece of equipment or the developed approaches were only applicable to limited activity types. This study demonstrated that it is technically feasible to determine progress at the site by fusing sensor data that are collected from multiple resources during the construction of building superstructure. The rule-based reasoning algorithms, which were developed based on a typical work practice of cranes and hoists, can be adapted to other activities that involve transferring bulk materials and use cranes and/or hoists for material handling.
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