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Entropy-Based Optimal Sensor Location for Structural Model Updating

Papadimitriou, Costas and Beck, James L. and Au, Siu-Kui (2000) Entropy-Based Optimal Sensor Location for Structural Model Updating. Journal of Vibration and Control, 6 (5). pp. 781-800. ISSN 1741-2986. https://resolver.caltech.edu/CaltechAUTHORS:20120809-153753425

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Abstract

A statistical methodology is presented for optimally locating the sensors in a structure for the purpose of extracting from the measured data the most information about the parameters of the model used to represent structural behavior. The methodology can be used in model updating and in damage detection and localization applications. It properly handles the unavoidable uncertainties in the measured data as well as the model uncertainties. The optimality criterion for the sensor locations is based on information entropy, which is a unique measure of the uncertainty in the model parameters. The uncertainty in these parameters is computed by a Bayesian statistical methodology, and then the entropy measure is minimized over the set of possible sensor configurations using a genetic algorithm. The information entropy measure is also extended to handle large uncertainties expected in the pretest nominal model of a structure. In experimental design, the proposed entropy-based measure of uncertainty is also well-suited for making quantitative evaluations and comparisons of the quality of the parameter estimates that can be achieved using sensor configurations with different numbers of sensors in each configuration. Simplified models for a shear building and a truss structure are used to illustrate the methodology.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://jvc.sagepub.com/content/6/5/781.shortPublisherUNSPECIFIED
http://dx.doi.org/10.1177/107754630000600508DOIUNSPECIFIED
ORCID:
AuthorORCID
Papadimitriou, Costas0000-0002-9792-0481
Additional Information:?f 2000 Sage Publications, Inc. Received 3 June 1998; accepted 17 December 1999. The paper is based on work partly supported by the National Science Foundation under subcontract to grant CMS-9503370. This support is gratefully acknowledged.
Funders:
Funding AgencyGrant Number
NSFCMS-9503370
Subject Keywords:System identification, information entropy, sensors, model updating, structural health monitoring
Issue or Number:5
Record Number:CaltechAUTHORS:20120809-153753425
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20120809-153753425
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:33067
Collection:CaltechAUTHORS
Deposited By: Sydney Garstang
Deposited On:13 Aug 2012 23:08
Last Modified:03 Oct 2019 04:06

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