Enhanced adaptive sequential Monte Carlo method for Bayesian model class selection by quantifying data fit and information gain

JH Yang, WY Liu, YH An, HF Lam - Mechanical Systems and Signal …, 2024 - Elsevier
For complex engineering structures, it is important to systematically select a model class
among various choices and search the complicated parameter space, while also quantifying …

A novel Metropolis-within-Gibbs sampler for Bayesian model updating using modal data based on dynamic reduction

A Das, RP Kiran, S Bansal - … Engineering and Mechanics, An Int'l …, 2023 - dbpia.co.kr
The paper presents a Bayesian Finite element (FE) model updating methodology by utilizing
modal data. The dynamic condensation technique is adopted in this work to reduce the full …

Defect Detection of Conductive Materials Based on Real Part Slope of Sweep-Frequency Inductance

W Wang, Z Zhang, W Yin, Y Zhang - Available at SSRN 4674652 - papers.ssrn.com
This paper aims to solve the problem of defect identification (grooves of different depths or
widths) of conductive materials. In this method, eddy current sensors are used to stimulate …

[引用][C] A Structural Damage Localization Method Based on Empirical Probability Mass Function of ARMAX Model Residual and Kullback–Leibler Divergence

L Ma, F Wang, X Ma, Y Xiao, Q Deng, X Li… - International Journal of …, 2023 - World Scientific
Damage localization is very significant in engineering applications. The existing method
based on the chi-square distribution of an autoregressive moving average with exogenous …

[引用][C] Overlapping Group Sparse Regularization Technique for Vibration-Based Regional Damage Detection of Structures

Z Luo, H Liu, Z Ouyang - International Journal of Structural Stability …, 2024 - World Scientific
In structural damage detection (SDD) studies, regularization techniques have shown
potential for improving the ill-posedness. However, existing methods based on …