Elements of artificial neural networks
Elements of artificial neural networks
Active Noise Control Systems: Algorithms and DSP Implementations
Active Noise Control Systems: Algorithms and DSP Implementations
Damage detection of truss bridge joints using Artificial Neural Networks
Expert Systems with Applications: An International Journal
Differential evolution strategy for structural system identification
Computers and Structures
Modified genetic algorithm strategy for structural identification
Computers and Structures
Direct identification of structural parameters from dynamic responses with neural networks
Engineering Applications of Artificial Intelligence
Fuzzified data based neural network modeling for health assessment of multistorey shear buildings
Advances in Artificial Neural Systems
| Hi-index | 12.05 |
In this research, two novel methods for simultaneous identification of mass-damping-stiffness of shear buildings are proposed. The first method presents a procedure to estimate the natural frequencies, modal damping ratios, and modal shapes of shear buildings from their forced vibration responses. To estimate the coefficient matrices of a state-space model, an auto-regressive exogenous excitation (ARX) model cooperating with a neural network concept is employed. The modal parameters of the structure are then evaluated from the eigenparameters of the coefficient matrix of the model. Finally, modal parameters are used to identify the physical/structural (i.e., mass, damping, and stiffness) matrices of the structure. In the second method, a direct strategy of physical/structural identification is developed from the dynamic responses of the structure without any eigenvalue analysis or optimization processes that are usually necessary in inverse problems. This method modifies the governing equations of motion based on relative responses of consecutive stories such that the new set of equations can be implemented in a cluster of artificial neural networks. The number of neural networks is equal to the number of degree-of-freedom of the structure. It is shown the noise effects may partially be eliminated by using high-order finite impulse response (FIR) filters in both methods. Finally, the feasibility and accuracy of the presented model updating methods are examined through numerical studies on multistory shear buildings using the simulated records with various noise levels. The excellent agreement of the obtained results with those of the finite element models shows the feasibility of the proposed methods.