Hydro-steel structure digital twins: Application in structural health monitoring and maintenance of large-scale reservoir

IF 8 1区工程技术 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Advanced Engineering Informatics Pub Date : 2024-10-01 DOI:10.1016/j.aei.2024.102922

Helin Li , Shufeng Zheng , Yonghao Shen , Minghai Han , Rui Zhang , Huadong Zhao

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引用次数: 0

Abstract

In the context of frequent accidents during hydro-steel structures (HSS) operations due to harsh environments and extended service conditions, a novel approach is proposed to reduce the frequency of structural failure incidents and ensure safe and reliable operation. The approach begins with introducing a comprehensive DT modeling framework. Subsequently, detailed DT modeling and DT-based SHM methods are developed. Finally, a platform with perception, interaction, analysis, and decision-making for intelligent health monitoring and maintenance of HSS is constructed and validated in China’s large-scale reservoir project, Luhun Reservoir. The platform includes functions of condition monitoring, fault feature recognition, health status assessment, and maintenance strategies optimization. The integration of DT technology has led to significant improvements in health monitoring and maintenance quality, which includes data collection, model optimization, comprehensive evaluation, and decision-making. This approach has also demonstrated its effectiveness by reducing the operation and maintenance response time and enhancing the overall efficiency and reliability.

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水工钢结构数字双胞胎：在大型水库结构健康监测和维护中的应用

在水工钢结构（HSS）运行过程中，由于恶劣的环境和长时间的使用条件，事故频发，在此背景下，提出了一种新的方法，以减少结构失效事故的发生频率，确保安全、可靠的运行。该方法首先引入了一个全面的 DT 建模框架。随后，开发了详细的 DT 建模和基于 DT 的 SHM 方法。最后，构建了集感知、交互、分析和决策于一体的 HSS 智能健康监测和维护平台，并在中国大型水库项目--鲁浑水库中进行了验证。该平台包括状态监测、故障特征识别、健康状况评估和维护策略优化等功能。DT 技术的集成显著提高了健康监测和维护质量，包括数据收集、模型优化、综合评估和决策。这种方法还缩短了运行和维护响应时间，提高了整体效率和可靠性，从而证明了其有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Advanced Engineering Informatics 工程技术-工程：综合

CiteScore

12.40

自引率

18.20%

发文量

292

审稿时长

45 days

期刊介绍： Advanced Engineering Informatics is an international Journal that solicits research papers with an emphasis on 'knowledge' and 'engineering applications'. The Journal seeks original papers that report progress in applying methods of engineering informatics. These papers should have engineering relevance and help provide a scientific base for more reliable, spontaneous, and creative engineering decision-making. Additionally, papers should demonstrate the science of supporting knowledge-intensive engineering tasks and validate the generality, power, and scalability of new methods through rigorous evaluation, preferably both qualitatively and quantitatively. Abstracting and indexing for Advanced Engineering Informatics include Science Citation Index Expanded, Scopus and INSPEC.