Dynamic input estimation and shape sensing for a nonlinear beam based on distributed fiber bragg grating sensor network

摘要

In the area of structural health monitoring, input estimation and shape sensing play an important role. This paper proposes a method to estimate dynamic input and reconstruct dynamic shape at the same time for a nonlinear beam system based on strain measurement by distributed fiber bragg grating(FBG) sensor network. In the process of estimating the magnitude and location of input, shape can be monitored at the same time. For a nonlinear beam system, the proposed method is based on cubature Kalman filter (CKF) and a nonlinear estimator. There are three steps to fulfill task. First, the state equations of structures are constructed and discretized. Second, CKF is used to suppress noise and reconstruct dynamic shape. Finally, the residual innovation sequences, priori state estimate, gain matrix and innovation covariance generated by CKF are used to estimate input. To verify the novel method, experiment of a nonlinear beam is employed and results show that the method has an excellent performance to estimate dynamic input and reconstruct dynamic shape. (C) 2017 Elsevier GmbH. All rights reserved.