Dynamic Load Identification and Displacement Prediction Based on FBG for a Cantilever Beam

Abstract

To identify load and predict displacement of the cantilever beam, a dynamic strain measurement method based on distributed fiber Bragg grating (FBG) sensor network is proposed. The applied inverse algorithm contains two parts: Kalman filter (KF) without input items and a load estimator. Firstly, structure’s state equations are established using finite element method (FEM). Secondly, noise is suppressed and the displacement of cantilever beam is predicted through KF. Finally, the load is identified through the corresponding matrixes generated by KF. For the simulations of the sinusoidal load, rectangular load and triangular load, the mean errors of load identification are less than 0.058%, 0.273%, and 0.09%, respectively. The RMSE values of load identification are less than 0.283, 0.781 and 1.374, respectively. Under the above conditions, the mean errors of displacement prediction at the end node are less than 0.003%, 0.00012%, and 0.00016%, respectively. The RMSE values of displacement prediction at the end node are less than 0.025, 0.00034 and 0.00018, respectively. Both the results of simulation and experiment indicate that the method is feasible, and its performance is excellent.