Identification of structural parameters based on symbolic time series analysis and differential evolution strategy

Rongshuai Li; Akira Mita; Jin Zhou

doi:10.1117/12.1000146

19 April 2013 Identification of structural parameters based on symbolic time series analysis and differential evolution strategy

Rongshuai Li, Akira Mita, Jin Zhou

Author Affiliations +

Proceedings Volume 8692, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013; 86923F (2013) https://doi.org/10.1117/12.1000146
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2013, San Diego, California, United States

Abstract

A novel symbolization strategy, "dynamic" strategy, of symbolization state series analysis (STSA) is employed in symbolization-based differential evolution strategy (SDES) to alleviate the effects of harmful noise. Procedure of "dynamic" strategy is described, effect of parameters in "dynamic" is verified, cases of partial output are considered. Performance of the proposed methodology was numerically compared with other symbolization strategies. Particle swarm optimization (PSO) and differential evolution (DE) on raw acceleration data are used as comparison to show the good noise immunity of our proposed methodology. These simulations revealed that our proposed methodology is a powerful tool for identifying the unknown parameters of structural systems even when the data is contaminated with relatively large amounts of noise.

Citation Download Citation

Rongshuai Li, Akira Mita, and Jin Zhou "Identification of structural parameters based on symbolic time series analysis and differential evolution strategy", Proc. SPIE 8692, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013, 86923F (19 April 2013); https://doi.org/10.1117/12.1000146

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