结构健康监测中的贝叶斯网络:理论背景和应用审查
Qi-Ang Wang1,2, Ao-Wen Lu2, Yi-Qing Ni3,4
1State Key Laboratory for Geomechanics & Deep Underground Engineering, China University of Mining and Technology, Xuzhou 221116, China.
Sensors (Basel, Switzerland)
|June 27, 2025
概括
贝叶斯网络通过整合各种数据来更好地预测损害和评估风险,增强对老化基础设施的结构健康监测 (SHM). 这种方法提高了安全性,并降低了土木结构的维护成本.
科学领域:
- 土木工程 土木工程是指土木工程.
- 计算机科学 计算机科学
- 数据科学数据科学数据科学
背景情况:
- 加快的城市化和老化的基础设施给土木工程结构带来了重大挑战.
- 结构健康监测 (SHM) 对于确保这些结构的安全性和耐用性至关重要.
- 现有的SHM方法在处理不确定性和整合多源数据方面面临挑战.
研究的目的:
- 系统地审查贝叶斯网络 (BNs) 在SHM中的应用.
- 探索BN如何解决不确定性,并将多源数据合并到SHM中.
- 将BN的理论框架与基础设施管理的实际SHM应用统一起来.
主要方法:
- 对贝叶斯网络应用在SHM中的系统文献综述.
- 分析BN在损害预测,数据融合,不确定性建模和决策支持方面的能力.
- 概率推理与多源传感器数据的整合.
主要成果:
- 贝叶斯网络为SHM提供了一个强大的概率推理工具.
- 通过数据融合和不确定性处理,BN提高了监控系统的准确性和可靠性.
- 该研究为损害识别,风险预警和维护优化提供了理论基础.
结论:
- 贝叶斯网络代表了一条新的技术途径,用于推进SHM.
- 这项研究弥合了概率推理和现实世界基础设施管理之间的差距.
- 这些结果对降低成本和确保公共基础设施安全具有重大影响.
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