On predicting monitoring system effectiveness

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

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

1 Scopus citations

Abstract

While the objective of structural design is to achieve stability with an appropriate level of reliability, the design of systems for structural health monitoring is performed to identify a configuration that enables acquisition of data with an appropriate level of accuracy in order to understand the performance of a structure or its condition state. However, a rational standardized approach for monitoring system design is not fully available. Hence, when engineers design a monitoring system, their approach is often heuristic with performance evaluation based on experience, rather than on quantitative analysis. In this contribution, we propose a probabilistic model for the estimation of monitoring system effectiveness based on information available in prior condition, i.e. before acquiring empirical data. The presented model is developed considering the analogy between structural design and monitoring system design. We assume that the effectiveness can be evaluated based on the prediction of the posterior variance or covariance matrix of the state parameters, which we assume to be defined in a continuous space. Since the empirical measurements are not available in prior condition, the estimation of the posterior variance or covariance matrix is performed considering the measurements as a stochastic variable. Moreover, the model takes into account the effects of nuisance parameters, which are stochastic parameters that affect the observations but cannot be estimated using monitoring data. Finally, we present an application of the proposed model to a real structure. The results show how the model enables engineers to predict whether a sensor configuration satisfies the required performance.

Original languageEnglish (US)
Title of host publicationSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2015
EditorsHoon Sohn, Kon-Well Wang, Jerome P. Lynch
PublisherSPIE
ISBN (Electronic)9781628415384
DOIs
StatePublished - Jan 1 2015
EventSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2015 - San Diego, United States
Duration: Mar 9 2015Mar 12 2015

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9435
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

OtherSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2015
CountryUnited States
CitySan Diego
Period3/9/153/12/15

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Keywords

  • Bayesian statistics
  • Fiber optic sensors
  • Monitoring design
  • Optimal sensor configuration
  • Structural health monitoring
  • Uncertainty estimation

Fingerprint Dive into the research topics of 'On predicting monitoring system effectiveness'. Together they form a unique fingerprint.

  • Cite this

    Cappello, C., Sigurdardottir, D., Glisic, B., Zonta, D., & Pozzi, M. (2015). On predicting monitoring system effectiveness. In H. Sohn, K-W. Wang, & J. P. Lynch (Eds.), Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2015 [94352M] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9435). SPIE. https://doi.org/10.1117/12.2086365