A formal approach to structural health monitoring design

Carlo Cappello, Dorotea Sigurdardottir, Branko Glisic, Daniele Zonta, Matteo Pozzi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

While the objective of structural design is to achieve stability with an appropriate level of safety, the design of structural health monitoring (SHM design) is performed to identify a configuration that enables acquisition of data with an appropriate level of precision in order to understand the condition state of a structure. Nevertheless, a practical and standardized approach for SHM design is not fully available. In this contribution, we address SHM design by proposing a method for the estimation of the effectiveness of SHM (monitoring effectiveness) based on information available a priori-i.e. before the acquisition of data from sensors. The proposed method is developed with the aim of easing SHM design in real-life settings and maintaining an analogy with structural design. The expected monitoring effectiveness relies on the calculation, performed a priori, of the variance that will affect the estimate of a target variable a posteriori. Since no real observations are available a priori, the estimation of variance is carried out by considering the observations as a random variable. With the aid of two real-life applications, we show how the proposed method can be used in order to evaluate a monitoring system.

Original languageEnglish (US)
Title of host publication8th European Workshop on Structural Health Monitoring, EWSHM 2016
PublisherNDT.net
Pages500-509
Number of pages10
ISBN (Electronic)9781510827936
StatePublished - 2016
Event8th European Workshop on Structural Health Monitoring, EWSHM 2016 - Bilbao, Spain
Duration: Jul 5 2016Jul 8 2016

Publication series

Name8th European Workshop on Structural Health Monitoring, EWSHM 2016
Volume1

Other

Other8th European Workshop on Structural Health Monitoring, EWSHM 2016
Country/TerritorySpain
CityBilbao
Period7/5/167/8/16

All Science Journal Classification (ASJC) codes

  • Health Information Management
  • Computer Science Applications

Keywords

  • Bayesian probability
  • COST Action 1402
  • Civil engineering
  • Pre-posterior analysis
  • Structural heath monitoring

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