Transitional markov chain monte carlo method for bayesian model updating
In this paper, three different strategies are proposed to identify general hysteretic behavior of a typical shear structure subjected to external excitations. Different case studies are presented to analyze the dynamic responses of a time varying shear structural system with the early version of Bouc-Wen-Baber-Noori (BWBN) hysteresis model. An adaptive extended Kalman filter for structural damage identification. Hysteresis can be described as the hereditary and memory nature of a non-linear or inelastic system behavior where the restoring force is dependent on both instantaneous as well as past history of deformations. doi: 10.1016/j.ymssp.20 Cross Ref Full Text | Google Scholar Wu, M., and Smyth, A. In general, under cyclic loading, mechanical and structural systems are capable of dissipating considerable energy and they exhibit appreciable hysteretic behavior with hysteresis loops. A Bayesian probabilistic framework was proposed to detect damage of continuous monitored structures by incorporating load-dependent Ritz vectors as an alternative to modal vectors (Sohn, 1998). Structural system identification and damage detection using the intelligent parameter varying technique: an experimental study. A large body of work was conducted to track, estimate and identify structural parameters, system status and hysteretic and degrading behavior of structures using Kalman filters, extended Kalman filters and unscented Kalman filters (Jeen-Shang and Yigong, 1994; Yang et al., 2006; Wu and Smyth, 2007, 2008; Chatzi and Smyth, 2009; Chatzi et al., 2010; Lei and Jiang, 2011; Mu et al., 2013; Kontoroupi and Smyth, 2017; Erazo and Nagarajaiah, 2018).
The schematic diagram of system identification process is depicted in Figure 1. Application of the unscented Kalman filter for real-time nonlinear structural system identification. The results showed that neural networks were found more promising for the prediction of slightly pinched, hardening hysteresis, strongly pinched, hardening hysteresis, and classical quasi-linear softening hysteresis (Brewick et al., 2016).