The value of monitoring a structural health monitoring system

Structural Health Monitoring (SHM) systems are adopted to acquire timely and continuous data on the state of civil structures, aerospace vehicles, and industrial machines, which deteriorate due to slow processes, such as corrosion and fatigue, and shock events, including natural and man-made disasters. The components of SHM systems themselves are exposed to deterioration after their installation; thereby, they might provide altered information to decision-makers. To account for this issue, Sensor Validation Tools (SVTs) have been developed to give insight into the actual condition of the SHM systems. In the last decade, researchers have exploited the Value of Information (VoI) from Bayesian decision theory to quantify the benefit of the information provided by an SHM system, implicitly assuming that it is working correctly when interrogated. The benefit of the information provided by SVTs on the state of an SHM system has never been investigated. This paper addresses this topic and extends the classical VoI framework to quantify the additional benefit brought by the information on the state of the SHM system to the decision problems it is meant to support. A numerical analysis, as well as a methodology demonstration on a real bridge, are presented to discuss the framework.