The purpose of this factsheet is to formulate a basis for a theory of optimal structural health monitoring sensing system topology based on maximising the net value of information the system can yield. The net value of information is calculated using the pre-posterior Bayesian analysis and this requires, inter alia, the prior probabilities of failure and likelihoods of damage detection by a monitoring system. The factsheet thus starts with some basic concepts from the structural reliability theory which point out to the fact that system failure probabilities are functions of local failure probabilities, and the latter can be updated using SHM data. The need and challenge for mapping SHM measurements into features that enable updating of the said probabilities is then discussed. The probabilistic modelling of the monitoring system performance is then introduced using joint probability density functions of the measured and actual features and considering the probabilities of various errors. Finally, the sensing system topology optimisation problem is stated mathematically using a pre-posterior decision tree analysis to minimise the total risk.
|Title of host publication||Proceedings of the 5th Workshop, COST Action TU1402|
|Subtitle of host publication||Quantifying the Value of Structural Health Monitoring|
|Number of pages||9|
|Publication status||Published - 2016|
Omenzetter, P. (2016). Optimal SHM system topology for maximising the value of information: An initial sketch of a theory. In Proceedings of the 5th Workshop, COST Action TU1402: Quantifying the Value of Structural Health Monitoring