Identification of structural parameters based on PZT impedance using genetic algorithms

Y. H. Hu, Y. W. Yang, L. Zhang, Y. Lu

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

Abstract

Electromechanical (EM) impedance method for structural health monitoring (SHM) is based on detecting the changes of the measured signatures of the Lead Zirconate Titanate (PZT) EM admittance (the inverse of the impedance). Although this method has been successfully applied for various engineering structures for damage detection, it is unable to specify the effect of damage on structural properties. The direct indicator of the structural properties is the structural mechanical impedance which can be extracted from the PZT EM admittance signatures. To model the structural impedance, this paper presents a multiple-degrees-of-freedom system consisting of a number of one-degree-of-freedom elements with mass, spring and damper components. Genetic algorithms (GAs) are employed to search for the optimal solution of the unknown dynamic system parameters by minimizing an objective function. Experiment has been carried on a two-storey concrete frame subjected to base vibrations that simulate earthquake. A number of PZT transducers are regularly arrayed and bonded to the frame structure to acquire PZT EM admittance signatures. The changes of the structural parameters in the model system are quantified using GAs. The relation between the distance of the PZT transducer away from the damage and the changes of the structural parameters identified by the PZT transducer is studied. Finally, the sensitivity of the PZT transducers is discussed.

Original languageEnglish (US)
Title of host publication2007 IEEE Congress on Evolutionary Computation, CEC 2007
Pages4170-4177
Number of pages8
DOIs
StatePublished - 2007
Externally publishedYes
Event2007 IEEE Congress on Evolutionary Computation, CEC 2007 - , Singapore
Duration: Sep 25 2007Sep 28 2007

Publication series

Name2007 IEEE Congress on Evolutionary Computation, CEC 2007

Other

Other2007 IEEE Congress on Evolutionary Computation, CEC 2007
Country/TerritorySingapore
Period9/25/079/28/07

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Theoretical Computer Science

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