Stable force identification in structural dynamics using Kalman filtering and dummy-measurements. (January 2015) - Naets, F.; Cuadrado, J.; Desmet, W.
Abstract: Many engineering applications require the knowledge of input forces to mechanical systems. However, in practice, it is quite difficult to measure these forces directly. In order to obtain an estimate of the input forces to structural systems, Kalman filtering based techniques have recently been introduced. These state-estimation techniques allow estimating the forces concurrent with the states of a system, based on a limited number of measurements. In practice, acceleration measurements are most convenient to use in structural dynamics applications. This paper proposes an analytical analysis of the stability of the Kalman based force estimation techniques and shows that only using acceleration measurements inherently leads to unreliable results. In order to circumvent this issue, the addition of dummy-measurements on a position level is proposed. These fictitious measurements dictate the estimator to return to an undeformed state and lead to a stable estimation approach. The proposed method is validated through both a numerical and a practical experiment. Both experiments show the inadequacy of the augmented Kalman filter based on only acceleration measurements to provide stable results. The estimator with dummy measurements on the other hand provides good results in the case of an unbiased external load. Abstract : Highlights: An online time-domain method for input force estimation is developed. A structural dynamics model is coupled with accelerometers through a Kalman filter. Using on only acceleration measurements is not sufficient for stable estimates. A dummy-measurement approach on a position level is proposed for stabilization. The proposed methods are validated numerically and experimentally.