Engineering of lightweight and robust structures is significant in mechanical engineering. Nevertheless, weight optimization of such structures leads to undesirable vibrations. Modal analysis is a common technique used in industry to investigate vibration behaviour. The classification of the mode shapes resulting from the analysis is conducted through human visual inspection, which can be time-consuming and susceptible to error. This paper presents an exploratory study investigating the potential of ML methods to classify three-dimensional vibration modes of truck frame structures. The aim is to evaluate the potential of such an approach to automate the modal analysis process to streamline the development process. As a result, the developed ML model can classify the vibration modes with high performance and additionally demonstrates flexibility regarding changes in geometry topology.
