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Two-Stage Damage Identification Based on Modal Strain Energy and Revised Particle Swarm Optimization

Auteur(s):


Médium: article de revue
Langue(s): anglais
Publié dans: International Journal of Structural Stability and Dynamics, , n. 5, v. 14
Page(s): 1440005
DOI: 10.1142/s0219455414400057
Abstrait:

This paper presents a novel two-stage damage detection method by integrating modal strain energy and revised particle swarm optimization (RPSO). In the first stage, the modal strain energy change ratio (MSECR) is used to roughly identify the locations of damaged elements via an appropriate MSECR threshold which is determined through parameter estimation. In the second stage, RPSO that integrates evolutionary theory with general PSO is used to precisely locate and quantify the damage with the gravity position of the selected excellent particles in the current entire population taken into consideration. Two numerical simulations and a seven-story steel frame experiment in laboratory conditions are performed to validate the proposed method, and a comparison is made between the proposed approach and existing methods. The results show that: (1) the proposed method can not only effectively locate damage, but also accurately evaluate the extent of damage. Meanwhile, it also enjoys good noise-tolerance and adaptability; (2) the damage threshold of the MSECR presented in this paper can be determined by the parameter estimation and reliability index, and then used to reduce the number of elements to be analyzed and to improve the computation efficiency in the second stage; and (3) compared with general PSO algorithm, RPSO is more efficient and robust for damage detection with a better noise-tolerance. This study shows that the proposed method can provide a reliable and fast tool to accurately identify, locate and quantify single- and multi-damage of complex engineering structures.

Structurae ne peut pas vous offrir cette publication en texte intégral pour l'instant. Le texte intégral est accessible chez l'éditeur. DOI: 10.1142/s0219455414400057.
  • Informations
    sur cette fiche
  • Reference-ID
    10352737
  • Publié(e) le:
    14.08.2019
  • Modifié(e) le:
    14.08.2019
 
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