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推进大型关键结构的非接触式结构与预后健康评估。

Advancing a Non-Contact Structural and Prognostic Health Assessment of Large Critical Structures.

作者信息

Chiu Wing Kong, Kuen Thomas, Vien Benjamin Steven, Aitken Hugh, Rose Louis Raymond Francis, Buderath Matthias

机构信息

Department of Mechanical and Aerospace Engineering, Monash University, Wellington Rd, Clayton, VIC 3800, Australia.

Melbourne Water Corporation, 990 La Trobe Street, Docklands, VIC 3008, Australia.

出版信息

Sensors (Basel). 2024 May 22;24(11):3297. doi: 10.3390/s24113297.

Abstract

This paper presents an overview of integrating new research outcomes into the development of a structural health monitoring strategy for the floating cover at the Western Treatment Plant (WTP) in Melbourne, Australia. The size of this floating cover, which covers an area of approximately 470 m × 200 m, combined with the hazardous environment and its exposure to extreme weather conditions, only allows for monitoring techniques based on remote sensing. The floating cover is deformed by the accumulation of sewage matter beneath it. Our research has shown that the only reliable data for constructing a predictive model to support the structural health monitoring of this critical asset is obtained directly from the actual floating cover at the sewage treatment plant. Our recent research outcomes lead us towards conceptualising an advanced engineering analysis tool designed to support the future creation of a digital twin for the floating cover at the WTP. Foundational work demonstrates the effectiveness of an unmanned aerial vehicle (UAV)-based photogrammetry methodology in generating a digital elevation model of the large floating cover. A substantial set of data has been acquired through regular UAV flights, presenting opportunities to leverage this information for a deeper understanding of the interactions between operational conditions and the structural response of the floating cover. This paper discusses the current findings and their implications, clarifying how these outcomes contribute to the ongoing development of an advanced digital twin for the floating cover.

摘要

本文概述了将新的研究成果整合到澳大利亚墨尔本西部污水处理厂(WTP)浮动盖结构健康监测策略的制定过程中。该浮动盖面积约为470米×200米,其规模、恶劣的环境以及暴露于极端天气条件下,使得只能采用基于遥感的监测技术。浮动盖会因下方污水物质的堆积而变形。我们的研究表明,构建预测模型以支持对这一关键资产进行结构健康监测的唯一可靠数据,是直接从污水处理厂的实际浮动盖上获取的。我们最近的研究成果促使我们构思一种先进的工程分析工具,旨在支持未来为WTP的浮动盖创建数字孪生模型。基础工作证明了基于无人机(UAV)的摄影测量方法在生成大型浮动盖数字高程模型方面的有效性。通过定期的无人机飞行已经获取了大量数据,这为利用这些信息更深入地了解运行条件与浮动盖结构响应之间的相互作用提供了机会。本文讨论了当前的研究结果及其影响,阐明了这些成果如何有助于为浮动盖持续开发先进的数字孪生模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8e/11174557/6e18774aae8c/sensors-24-03297-g001.jpg

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