TY - JOUR
T1 - A framework for quantifying the value of vibration-based structural health monitoring
AU - Kamariotis, Antonios
AU - Chatzi, Eleni
AU - Straub, Daniel
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2023/2/1
Y1 - 2023/2/1
N2 - 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.
AB - 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.
KW - Bayesian decision analysis
KW - Bayesian filtering
KW - Environmental variability
KW - Sequential decision making
KW - Structural reliability
KW - Vibration-based structural health monitoring
KW - Visual inspections
UR - http://www.scopus.com/inward/record.url?scp=85137169451&partnerID=8YFLogxK
U2 - 10.1016/j.ymssp.2022.109708
DO - 10.1016/j.ymssp.2022.109708
M3 - Article
AN - SCOPUS:85137169451
SN - 0888-3270
VL - 184
JO - Mechanical Systems and Signal Processing
JF - Mechanical Systems and Signal Processing
M1 - 109708
ER -