Bearing Damage Detection of a Reinforced Concrete Plate Based on Sensitivity Analysis and Chaotic Moth-Flame-Invasive Weed Optimization

Abstract

This article proposes a novel damage detection method based on the sensitivity analysis and chaotic moth-flame-invasive weed optimization (CMF-IWO), which is utilized to simultaneously identify the damage of structural elements and bearings. First, the sensitivity coefficients of eigenvalues to the damage factors of structural elements and bearings are deduced, the regularization technology is used to solve the problem of equation undetermined, meanwhile, the modal strain energy-based index is utilized to detect the damage locations, and the regularization objective function is constructed to quantify the damage severity. Then, for the subsequent procedure of damage detection, CMF-IWO is proposed based on moth-flame optimization and invasive weed optimization as well as chaos theory, reverse learning, and evolutional strategy. The optimization effectiveness of the hybrid algorithm is verified by five benchmark functions and a damage identification numerical example of a simply supported beam; the results demonstrate it is of great global search ability and higher convergence efficiency. After that, a numerical example of an 8-span continuous beam and an experimental reinforced concrete plate are both adopted to evaluate the proposed damage identification method. The results of the numerical example indicate that the proposed method can locate and quantify the damage of structural elements and bearings with high accuracy. Furthermore, the outcomes of the experimental example show that despite the existence of some errors and uncertain factors, the method still obtains an acceptable result. Generally speaking, the proposed method is proved that it is of good feasibility.

Bearing Damage Detection of a Bridge under the Uncertain Conditions Based on the Bayesian Framework and Matrix Perturbation Method

“…Aiming to every damage case, the modal test number is 50, and the first five-order natural frequencies and modal shapes are adopted; and the iterative number is determined as 5000 for case 1 and 10,000 for cases 2-7. Meanwhile, another method in the paper [13] is also adopted to make a comparison, namely, the identification method using optimization algorithm and sensitivity analysis (OASA), which can make a comparison with the proposed method. As far as OASA is concerned, herein, some parameters of CMF-IWO algorithm except for the iterative number and population size are the same as in [13].…”

“…where K s means the global stiffness matrix of a structure; nele denotes the total number of structural elements; and k e i and θ i are i-th element stiffness matrix and i-th stiffness reduction factor, respectively. Meanwhile, the boundary condition change, namely, the damage of bearings, can be represented as the boundary condition matrix, and it can be defined as follows [13,30]:…”

“…Regarding the present research, there are few studies that have focused on the bearing damage identification, even less to consider the uncertainties of bearing damage detection; thus, in this paper, a bearing damage detection method with good potential has been developed to identify the damage of structural elements and bearings simultaneously; compared to the previous research [13], the proposed one shows high accuracy.…”

“…Ni et al [12] adopted correlation and sensitivity analysis to put forward a damage identification indicator of the bridge pot rubber bearing and then combined with the support vector machine to form a safety-level discriminant model to assess the health state of the bridge pot rubber bearing. However, because the influence severities of modal parameters to structural elements and bearings are discrepant and nonlinear, Huang et al [13] conducted the modal parameter sensitivity analysis on the damage of structural elements and bridge bearings and deduced the sensitivity coefficients of eigenvalue to the damage factors of structural elements and bearings; then, the regularization method and chaotic mothflame-invasive weed optimization were used to identify the structural element and bearing damage simultaneously. e outcomes indicate that the accuracy still desires to be improved.…”

Chaos in metaheuristic based artificial intelligence algorithms: a short review

“…The optimization effectiveness of the hybrid algorithm was tested and verified via five benchmark functions and damage identification numerical example of a simply supported beam. The results revealed its excellent global search ability and better convergence effectiveness [52].…”