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

Rongshuai Li, Akira Mita, Jin Zhou

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

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.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Volume8692
DOIs
Publication statusPublished - 2013
Event2013 SPIE Conference on Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013 - San Diego, CA, United States
Duration: 2013 Mar 102013 Mar 14

Other

Other2013 SPIE Conference on Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013
CountryUnited States
CitySan Diego, CA
Period13/3/1013/3/14

Fingerprint

Symbolic Analysis
time series analysis
Time series analysis
Evolution Strategies
Structural Parameters
Time Series Analysis
Differential Evolution
Methodology
methodology
Particle swarm optimization (PSO)
Immunity
Unknown Parameters
Particle Swarm Optimization
immunity
Partial
Series
Strategy
Output
optimization
output

Keywords

  • Building structures
  • Differential evolution
  • Dynamic strategy
  • Structural health monitoring
  • Symbolic time series analysis

ASJC Scopus subject areas

  • Applied Mathematics
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

Cite this

Li, R., Mita, A., & Zhou, J. (2013). Identification of structural parameters based on symbolic time series analysis and differential evolution strategy. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 8692). [86923F] https://doi.org/10.1117/12.1000146

Identification of structural parameters based on symbolic time series analysis and differential evolution strategy. / Li, Rongshuai; Mita, Akira; Zhou, Jin.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 8692 2013. 86923F.

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

Li, R, Mita, A & Zhou, J 2013, Identification of structural parameters based on symbolic time series analysis and differential evolution strategy. in Proceedings of SPIE - The International Society for Optical Engineering. vol. 8692, 86923F, 2013 SPIE Conference on Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013, San Diego, CA, United States, 13/3/10. https://doi.org/10.1117/12.1000146
Li R, Mita A, Zhou J. Identification of structural parameters based on symbolic time series analysis and differential evolution strategy. In Proceedings of SPIE - The International Society for Optical Engineering. Vol. 8692. 2013. 86923F https://doi.org/10.1117/12.1000146
Li, Rongshuai ; Mita, Akira ; Zhou, Jin. / Identification of structural parameters based on symbolic time series analysis and differential evolution strategy. Proceedings of SPIE - The International Society for Optical Engineering. Vol. 8692 2013.
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