Executable Digital Twin - Prevent the Early Failure of a Truck Anchorage Using Smart Virtual Sensors

Abstract

<div class="section abstract"><div class="htmlview paragraph">Executable Digital Twins (xDT) are starting a revolution in the industry, where high fidelity simulation models extend their usage from the design and validation phases to in-operation and service phase. Two critical technology blocks in this revolution are Model Order Reduction and Smart Virtual Sensing. The former allows the high-fidelity models to be represented in compact forms and the latter allows to extend the limits of physical sensors and provide full field data combining simulation models and test data in a real-time estimator framework.</div><div class="htmlview paragraph">The smart virtual sensing technology leverages a state-of-the-art Kalman filtering approach to combine the simulation and physical testing. This allows to virtually measure locations that are not accessible with physical sensors due to e.g. physical constrains or high temperatures. In case of large sensors setups, the instrumentation time, and hence the cost, can be greatly reduced by using a combination of physical and smart virtual sensors. Moreover, the estimation is performed in a non-deterministic framework in order to compensate for the modelling inaccuracies and measurement uncertainties.</div><div class="htmlview paragraph">Throughout this paper, the smart virtual sensing technology is initially described and successively applied to virtually measure the stress hotspot locations of the anchorage of a truck axle to prevent its early failure. In this application, the morphology of the components does not allow the placement of any physical sensor at the stress hotspots due to the lack of physical space. In order to provide reliable virtual measurements, an xDT is first authored in Simcenter™ 3D using the Smart Virtual Sensing technology and it is successively imported in Simcenter Testlab™ to directly link the physical sensors to the xDT. This allows to quickly estimate the virtual measurements and process the results.</div></div>