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Structural Health Monitoring in Smart Structures Through Time Series Analysis

Department of Mechanical Design, Faculty of Mechanical Engineering State University of Campinas - UNICAMP Rua Mendeleiev s/n Cidade Universitária, P.O. Box 6122, 13083-970, Campinas, SP, Brazil, samsilva{at}fem.unicamp.br

Milton Dias Júnior

Department of Mechanical Design, Faculty of Mechanical Engineering State University of Campinas - UNICAMP Rua Mendeleiev s/n Cidade Universitária, P.O. Box 6122, 13083-970, Campinas, SP, Brazil

Vicente Lopes Junior

Department of Mechanical Engineering, Grupo de Materiais e Sistemas Inteligentes, Universidade Estadual Paulista - UNESP, Av. Brasil n.56, Centro, 15385-000, Ilha Solteira, SP, Brazil

This paper describes the application of a structural health monitoring technique based on electrical measurements obtained by piezoceramics (PZT) patches bonded in lightweight structures. The goal is to detect and locate imminent structural change occurrence with statistical confidence through a nondestructive evaluation test. Though the major focus in damage detection is given by monitoring electrical impedance in frequency-domain, the current research work applies a novel approach based on time-series. In such case, auto-regressive moving average with exogenous input (ARMAX) system identification models and statistical process control (SPC) charts are used for linear prediction to detect and locate damages. In order to compare the results, the classical damage metric chart obtained by frequency response from input—output data is described. The efficacy of the proposed approach is demonstrated through experimental tests.

Key Words: damage detection • damage metric • PZT patches • electrical impedance • statistical process control

This version was published on September 1, 2008

Structural Health Monitoring, Vol. 7, No. 3, 231-244 (2008)
DOI: 10.1177/1475921708090561


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