A multi-fractal spectrum analysis for online structural health monitoring Conference Paper

abstract

• IEOM Society International. The nonlinear and nonstationary nature of structural damage brings a great challenge to structural health monitoring (SHM). Chaos theory and nonlinear time-series analysis domain suggests many effective candidates to capture system dynamic and measure the complexity of dynamical system. From different candidates, this paper focuses on multi-fractal spectrum analysis for online structural health monitoring. Results show that the quasi recessive correlation dimension (QRCD) is not only the best fractal dimension for detecting different defect levels, but also it has less computational complexity than the singularity spectrum used for extracting multi-fractal spectrum. On the other hand, the multi-fractal spectrum analysis is an effective damage quantifier for analyzing data which exhibit multi-fractal behavior and it has a better diagnosis capability for monitoring non-stationary process and those attractors which exhibit phase-transition.

authors

• Bukkapatnam, Satish

published proceedings

• Proceedings of the International Conference on Industrial Engineering and Operations Management

author list (cited authors)

• Mistarihi, M. Z., Kong, Z., & Bukkapatnam, S.

complete list of authors

• Mistarihi, MZ||Kong, Z||Bukkapatnam, STS

publication date

• January 2017

published in

• Proceedings of the International Conference on Industrial Engineering and Operations Management  Journal

start page

• 711

end page

• 721

volume

• 2017

issue

• OCT