A framework for quantifying the value of vibration-based structural health monitoring

In this work, led by Antonios Kamariotis (TUM / SMM group), with Eleni Chatzi (SMM group) and Daniel Straub (TUM), we present a framework for quantifying the expected gains that continuous vibration-based SHM-aided maintenance planning can provide when compared against the currently dominant approach of intermittent inspection-based maintenance planning; the Value of SHM (VoSHM) metric is adopted for formally computing this benefit. 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.

Most works to date related to the VoSHM quantification utilize simple idealized models of the information obtained from monitoring. In contrast to these works, the framework presented in this work includes an advanced model of a vibration-based SHM system, considering modal data that is continuously identified via operational modal analysis (OMA) schemes. The analysis further includes the effect of environmental variability on the identified modal data, a key issue in vibration-based SHM. A Bayesian filter is employed for the tasks of sequential joint deterioration state-parameter estimation and structural reliability updating, using continuously identified modal and intermittent visual inspection data. The framework incorporates the full sequence of inspection and maintenance decisions throughout the structural life-cycle rather than just individual decisions, as in most of the literature. On this basis, the VoSHM is quantified by the difference in expected total life-cycle costs with and without the SHM.

This work discusses a novel classification of SHM use cases in terms of the associated time scales for decision making for infrastructure management. In the context of this classification, the framework is investigated on different case studies 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 investing in SHM systems can potentially lead to large benefits.

This is collaborative work between the Engineering Risk Analysis Group of TUM and the SMM group, conducted under the auspices of the TUM-Institute for Advanced Study.

read more in external page Volume 184 of MSSP