A model-based approach for the estimation of bearing forces and moments using outer-ring deformation

Abstract

Bearing load estimation would form a valuable addition to the fields of condition monitoring and system control. Despite effort spend on its development by all major bearing manufacturers no product solution has come to market yet. This can be attributed to both the complexity in conditioning of the strain measurement as well as its non-linearity with respect to the bearing loading. To address these issues, this paper proposes a novel approach based on modeling of the physical behavior of the bearing. An Extended Kalman Filter including a novel strain model is applied for signal conditioning whereas an Unscented Kalman Filter including a semi-analytical bearing model is proposed for reconstruction of the bearing load. An experimental study in both laboratory and field conditions shows that the proposed cascaded Kalman filtering approach leads to accurate estimates for all four considered bearings loads in various loading conditions. Besides an improvement on accuracy, the novel approach leads to a reduction in calibration effort.