Modified genetic algorithm strategy for structural identification

• Published in: Computers & structures Vol. 84; no. 8; pp. 529 - 540
• Main Authors: Perry, M.J., Koh, C.G., Choo, Y.S.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.03.2006; Elsevier Science
• Subjects: Computational techniques; Exact sciences and technology; Fundamental areas of phenomenology (including applications); Genetic algorithm; Mathematical methods in physics; Measurement and testing methods; Optimisation; Physics; Solid mechanics; Structural and continuum mechanics; Structural dynamics system identification; Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...); Optimisation; Genetic algorithm; Structural dynamics system identification; Engineering design; System with n degrees of freedom; Vibration; Error estimation; System identification; Reliability; Structural analysis
• ISSN: 0045-7949; 1879-2243
• DOI: 10.1016/j.compstruc.2005.11.008

Genetic algorithms (GA) have proved to be a robust, efficient search technique for many problems. As the number of variables involved increases, classical GA will often have difficulty and/or require long computational time in obtaining acceptable results. In this paper, a modified GA strategy is proposed to improve the accuracy and computational time for parameter identification of multiple degree-of-freedom (DOF) structural systems. The strategy includes multiple populations or ‘species’, a search space reduction procedure and new operators designed to provide a robust and reliable identification. Average absolute error in the estimated stiffness values of 1.4% is achieved for a 20-DOF unknown mass system with 5% noise, and even more importantly the maximum error is reduced to only 3.8%.