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Developing and Laboratory Testing a Smart System for Automated Falsework Inspection in Construction

机译:开发和实验室测试智能系统,以进行施工中的自动虚假检查

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The procedure of falsework inspection has the potential for improvements in accuracy and time efficiency. The current process of inspection is often time-consuming and there is a potential for human error that could lead to undesirable outcomes. This paper presents an innovative smart system with the purpose of achieving an automation in falsework inspection. The system is basically a combination of radio frequency identification (RFID) with a virtual three-dimensional (3D) model that is represented by the AutoCAD 360 drawing viewer on a mobile device. Member identification is to be addressed by the RFID component, while the virtual model is expected to enable more accurate positional identification of members within the entire falsework configuration. A mock-up formwork structure was assembled in order to test this developed system. RFID was found to identify members significantly faster (5.6s as an average) than by inspecting manually (33.2s as an average) during 20 demonstrations. Simultaneously, higher inspection accuracy of 96.2% compared to 91.5% was achieved by inspecting manually. However, the smart technology option for component positioning did not have expected results and was less efficient than the currently practiced method. This shows that there is a potential in implementing one of the previous technologies while the other still requires further development before it would be applied to the inspection process. The primary contribution of the research lies in demonstrating the true value of the tangible smart system in an actual situation. In short, it enabled showing its effectiveness during the quantification, but still needs more work in its positioning. (C) 2017 American Society of Civil Engineers.
机译:脚手架检查程序可能会提高准确性和时间效率。当前的检查过程通常很耗时,并且可能存在人为错误,可能导致不良后果。本文提出了一种创新的智能系统,旨在实现自动检查虚假信息。该系统基本上是射频识别(RFID)与虚拟三维(3D)模型的组合,该模型由移动设备上的AutoCAD 360图形查看器表示。成员标识将由RFID组件处理,而虚拟模型有望在整个脚手架配置内实现对成员的更准确的位置标识。组装了一个模型模板结构,以测试此开发的系统。发现RFID在20个演示中比通过手动检查(平均33.2s)明显更快地识别成员(平均5.6s)。同时,通过手动检查实现了96.2%的更高检查精度(相比91.5%)。但是,用于零件定位的智能技术选项没有得到预期的结果,并且效率不如当前实践的方法。这表明有可能实施先前的一种技术,而另一种仍需要进一步开发才能应用到检查过程中。该研究的主要贡献在于在实际情况中证明了有形智能系统的真实价值。简而言之,它可以在定量过程中显示其有效性,但在定位上还需要做更多的工作。 (C)2017年美国土木工程师学会。

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