Identification of Structural Dynamic Parameters Using Block Pulse Functions and Recursive Least-Squares Algorithm
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System identification in recent years with the development of dynamic testing of structures has become one of the useful methods for structural health monitoring and damage detection and also finite element model updating. Identification of structural dynamic parameters is performed by using excitation–response data and includes physical parameters such as mass, stiffness and damping matrices and/or modal parameters such as natural frequencies, damping ratios and modal shapes. This paper presents a new method to identify the dynamical parameters of shear building based on continuous-time state-space estimation using block pulse functions and least-squares technique. Block pulse functions are a set of orthogonal functions with piecewise constant values and useful tools in analysis, identification and system science. Assuming that the input–outputs data of the original system are known, their block pulse coefficients can be calculated by numerical methods, and using block pulse operational matrix, state-space equations of dynamical system are transformed into block pulse regression equations. Based on these equations, the plant matrix is estimated using least-squares algorithm. Then, the physical and modal parameters of structure are identified based on eigenmode data of the estimated plant matrix. To prove the validity and feasibility of the proposed method, numerical simulation of a shear building which is equipped with sensors on all floors and excited by four different normally distributed random signals and an earthquake is presented. The results reveal the proposed method can be beneficial in structural identification with less computational expenses and high accuracy.
KeywordsSystem identification Block pulse functions Continuous-time state space Least-squares algorithm Eigenmode data
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