Abstract
Abstract This paper presents a model-based approach for the condition monitoring of guiding rails in vertical transportation systems. A physics-based model of the system is used to estimate friction forces by means of an augmented Extended Kalman Filter (EKF). This estimation is compared to the friction forces predicted by a more detailed model of the system. This comparison, provides quantitative knowledge of the condition of the system. The difference between the estimated and the expected friction is continuously tracked, allowing an early assessment of the system’s degradation. The method is validated using an scaled test bench of a vertical transportation system. It is shown that, using only off-the-shelf sensors, a model-based approach could simplify the condition monitoring of guiding rails, which generally requires costly and complex devices.
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