Input forces estimation of a cantilever beam

Abstract

This work presents an application of the Kalman filter with a recursive estimator to determine the excitation forces of linear dynamic systems. The forces were estimated from the measured dynamic responses through an inverse method. The estimator employed a least squares algorithm to compute the magnitudes and, therefore, the onset time histories of the forces. The practicability and accuracy of the proposed method were verified with laboratory tests from which the input forces of a cantilever beam were estimated from the measured dynamic responses. In the experimental study, the beam was subjected to periodic forces and random forces. The estimation results of the input forces are qualitatively and quantitatively good in all cases tested.

Input Forces Estimation of Beam Structures by an Inverse Method

“…To illustrate the practicability and accuracy of the present approach in estimating unknown input forces, numerical experiments of a cantilever beam [15] are investigated here. The finite element model of the cantilever beam with a lumped mass on the free end is shown in Figure 1.…”

“…The simulation results indicate that the method can accurately estimate unknown impulsive loads. In addition, we have developed an experimental apparatus and conducted a series of experiments on a physical cantilever beam to identify the excitation forces [15]. The estimation results have demonstrated the validity of the estimation method.…”

Adaptive weighting input estimation for nonlinear systems

“…The algorithm proposed in these works is based on the Kalman filter (KF; Kalman 1960) and a recursive least-squares estimator (RLSE). Simulation (Ma et al 1998 and experimental results (Ma and Lin 2000) reveal that the proposed algorithm accurately estimates the values of inputs. Moreover, this work estimates loads in a highly reliable, adaptive and robust manner and uses an adaptive weighting inverse method .…”

“…An experimental apparatus has been used to conduct a series of experiments on a physical cantilever beam to determine the excitation forces (Ma and Lin 2000). The algorithm proposed in these works is based on the Kalman filter (KF; Kalman 1960) and a recursive least-squares estimator (RLSE).…”

Input estimation for nonlinear systems

“…In previous studies, the authors developed an inverse method for estimating impulsive loads on lumped-mass structural systems [10]; we utilized experimental apparatus and conducted a series of experiments on a physical cantilever beam to identify excitation forces [11]. The algorithm is based on the KF and a recursive least-squares approach.…”