The difficulty in quantifying the benefit of Structural Health Monitoring (SHM) for decision support is one of the bottlenecks to an extensive adoption of SHM on real-world structures. In this paper, we present a framework for such a quantification of the value of vibration-based SHM, which can be flexibly applied to different use cases. These cover SHM-based decisions at different time scales, from near-real time diagnostics to the prognosis of slowly evolving deterioration processes over the lifetime of a structure. The framework includes an advanced model of the SHM system. It employs a Bayesian filter for the tasks of sequential joint deterioration state-parameter estimation and structural reliability updating, using continuously identified modal and intermittent visual inspection data. It also includes a realistic model of the inspection and maintenance decisions throughout the structural life-cycle. On this basis, the Value of SHM is quantified by the difference in expected total life-cycle costs with and without the SHM. We investigate the framework through application on a numerical model of a two-span bridge system, subjected to gradual and shock deterioration, as well as to changing environmental conditions, over its lifetime. The results show that this framework can be used as an a-priori decision support tool to inform the decision on whether or not to install a vibration-based SHM system on a structure, for a wide range of SHM use cases.
翻译:很难量化结构健康监测(SHM)对决策支持的好处,这是在现实世界结构上广泛采用SHM的瓶颈之一。在本文件中,我们提出了一个框架,用于量化基于振动的SHM的价值,可以灵活地应用于不同的使用案例,包括基于SHM的决定在不同的时间尺度上,从近实时诊断到在一个结构存在期间缓慢变化的恶化过程的预测,包括SHM系统的先进模型。这个框架包括SHM系统的先进模型。它使用巴伊西亚过滤器来完成连续联合恶化状态-参数估计和结构可靠性更新的任务,使用不断查明的模式和间歇性视觉检查数据。它还包括在整个结构生命周期内进行检查和维护决定的现实模式。在此基础上,SHM的价值以预期总寿命周期费用的差异为基础,不使用SHM。我们通过应用基于二层桥梁系统的数字模型来调查该框架,在逐渐和冲击性恶化的情况下,以及在其整个生命周期内改变环境条件。结果显示,是否可使用一个广泛的SHM系统决定范围,用于SHM决定系统的系统。