Postprint version. Published in International Journal of Non-Linear Mechanics, Volume 39, Issue 10, March 24, 2004, pages 1678-1697.
At the time of publication, the author Mohammad N.Noori was affiliated with North Carolina State University. Currently, July 2008, he is the Dean of the College of Engineering at California Polytechnic State University - San Luis Obispo.
The definitive version is available at https://doi.org/10.1016/j.ijnonlinmec.2004.03.001.
Most structural health monitoring and damage detection strategies utilize dynamic response information to identify the existence, location, and magnitude of damage. Traditional model-based techniques seek to identify parametric changes in a linear dynamic model, while non-model-based techniques focus on changes in the temporal and frequency characteristics of the system response. Because restoring forces in base-excited structures can exhibit highly non-linear characteristics, non-linear model-based approaches may be better suited for reliable health monitoring and damage detection. This paper presents the application of a novel intelligent parameter varying (IPV) modeling and system identification technique, developed by the authors, to detect damage in base-excited structures. This IPV technique overcomes specific limitations of traditional model-based and non-model-based approaches, as demonstrated through comparative simulations with wavelet analysis methods. These simulations confirm the effectiveness of the IPV technique, and show that performance is not compromised by the introduction of realistic structural non-linearities and ground excitation characteristics.
Civil and Environmental Engineering