Abstract

Accurate, computationally efficient simulations enable engineers to design high-performing, cost-efficient, lightweight machines that can leverage models of predictive controls and digital twin predictive maintenance schedules. This study demonstrates a new speed-dependent eigenmode method for accurately and efficiently simulating shaft transverse vibrations. The method involves first independently computing shaft eigenmodes over a range of operating speeds, then correlating the eigenmodes across the different speeds during compilation, and finally adjusting modal properties gradually in accordance with a lookup method during simulation. The new method offers several distinct advantages over the traditional static eigenmodes and Craig-Bampton methods. The new method maintains accuracy over a large range of shaft rotation speeds whereas the static eigenmodes method does not. The new method typically requires fewer modal degrees of freedom than the Craig-Bampton method. Whereas the Craig-Bampton method is limited to modeling changes at the boundaries, the new method is suitable for modeling changing body properties as well as boundary-based changes. For this paper, a fluid-bearing-supported 10 MW direct-drive wind turbine drive shaft is tested virtually in a simulation model developed in Simscape™ Driveline™. Using the simulation statistics, this study compares the accuracy and computational efficiency of the speed-dependent eigenmode method to the traditional finite lumped element, static eigenmode, and Craig–Bampton methods. This paper shows that the new method simulates the chosen system 5 times faster than the traditional lumped mass method and 2.4 times faster than the Craig-Bampton method.

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