Process force determination in machine tools is an important topic for both optimization of manufacturing processes as well as predictive maintenance purposes. This work aims at providing a short overview of existing methods, motivating the integration of sensors into a linear guide, and then showing the results of an implemented new method for capturing the load on a rolling element linear guide by measuring the stresses resulting from the rolling element contact at the side of the runner block. The implementation of the approach is based on the piezoresistive diamond like carbon (DLC) coating DiaForce® provided by the Fraunhofer Institute for Surface Engineering and Thin Films (IST), Braunschweig, Germany. Good agreement of measurements with analytical and finite element method simulation results promises a stable modeling and load estimation process. Nevertheless, non-idealities due to high temperature dependency and cross-sensitivity to non rolling element contact related stresses could be shown, but also an efficient approach to diminish these effects is included.
Measuring the mechanical load on linear guides provides many possibilities regarding predictive maintenance and process monitoring. In this contribution, we provide an in depth evaluation of a Diamond Like Carbon (DLC) based sensor system integrated into the runner block’s raceway that is capable of directly measuring the load on individual rolling elements. An efficient algorithm based on an Extended Kalman Filter (EKF) for local sensor fusion and load estimation is presented and proven to reliably retrieve the load regardless of the rolling element’s position. Afterwards, we compare locally measured loads to results from a theoretical load distribution model, providing valuable insight into modeling parameters and a verification of the sensor measurement principle. In a final step, an algorithm to invert the load distribution model is derived and used for an evaluation of the sensor system, achieving Root-Mean-Square (RMS) estimation errors of equivalently 1.4 kN in the preload range and 2.75 kN overall for one dimensional loads. Load mode distinction was equally successful with a suppression RMS error of 0.7 kN in the preload range and 2.87 kN in total.
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