Structural damage identification using adaptive immune clonal selection algorithm and acceleration data

R. Li, A. Mita

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

4 Citations (Scopus)

Abstract

In order to identify damage of civil engineering structures precisely and efficiently, an approach for damage identification by employing Adaptive Immune Clonal Selection Algorithm (AICSA) is proposed. By utilizing secondary response, adaptive mutation regulation and vaccination operator, AICSA achieves the dynamic control of evolution process, which realizes global optimal computing combined with the local searching. Compared with basic clonal selection algorithm, AICSA improves convergence rate and global optimum searching ability. The experimental results show that AICSA can efficiently and precisely identify single and multiple damages of civil engineering structures respect to different damage location, extent and measurement noise.

Original languageEnglish
Title of host publicationSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2011
DOIs
Publication statusPublished - 2011 May 26
EventSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2011 - San Diego, CA, United States
Duration: 2011 Mar 72011 Mar 10

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7981
ISSN (Print)0277-786X

Other

OtherSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2011
CountryUnited States
CitySan Diego, CA
Period11/3/711/3/10

Keywords

  • AICSA
  • SHM
  • damage identification
  • immune

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'Structural damage identification using adaptive immune clonal selection algorithm and acceleration data'. Together they form a unique fingerprint.

  • Cite this

    Li, R., & Mita, A. (2011). Structural damage identification using adaptive immune clonal selection algorithm and acceleration data. In Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2011 [79815A] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 7981). https://doi.org/10.1117/12.879782