Model-based virtual sensing approaches for the estimation of forces in guiding systems

摘要

The assessment of the contact and friction forces acting on guiding rails is of high importance in the design and maintenance of mechanical systems. The direct measurement of these forces is however difficult as the use of a dedicated sensor is impractical and in some cases unfeasible. The use of model-based virtual sensing approaches is an attractive option to estimate these forces using off-the-shelf sensors. In this paper a nonlinear model that includes the lateral dynamics of a vertical transportation system is developed. The model is then combined with simulated measurements by means of an Extended Kalman Filter to estimate the forces in the guiding system. Special attention is given to reducing the modeling effort while keeping a highly accurate model. With that purpose the model is developed in Modelica and combined with the estimation filters by means of the Functional Mock-up Interface. The effect of the uncertainties in the characteristics of the contact model is also assessed. The estimated forces will be analyzed to monitor the condition of the guiding rails.