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

TL;DR

This paper introduces a flexible framework to quantify the economic value of vibration-based Structural Health Monitoring (SHM) across different decision-making scenarios, aiding in the decision to install SHM systems.

Contribution

It presents a comprehensive Bayesian-based framework that models SHM system performance, deterioration, and maintenance decisions to evaluate SHM's value over a structure's lifetime.

Findings

Framework effectively estimates SHM value for various use cases.

Application on a bridge model demonstrates practical decision support.

Quantifies cost savings and risk reduction from SHM implementation.

Abstract

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.