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The acquisition and evaluation of acoustic emissions (AE) in tribology have proven to be a meaningful tool for condition monitoring and offer possibilities to deepen the understanding of tribological processes. The authors used this technology with the aim of expanding existing test methodologies towards increased visualization capability of tribological processes and investigated the correlation between tribological processes and acoustic emissions on a Ring-on-Disc and a close-to-component journal bearing test setting. The results of this study include the description of friction as well as wear processes and prove the usability of several AE evaluation parameters whereby a close correlation between AE and tribological processes can be shown. Consequently, it was possible to expand the visualization and evaluation capabilities of the test settings offering additional insights by making use of AE.

Short fibre reinforced polymers are getting more important for structural applications. Becasue of lightweight actions, components are designed for a specific application and lifetime. The bearable numbers of cycles can be estimated using material data and models for the consideration of influence factors. Further static loadings affect material behaviour, which influences the component lifetime. Commonly used models are not able to capture these effects. Therefore, material tests, with different load sequences, on 40% short glass fibre reinforced polypropylene have been performed. These sequences are combinations of cyclic and static loads at different, defined levels. Our research shows a lifetime elongation or reduction of a polymer, depending on the amount of static load time and quantity. For a certain stress level, the time to failure can be elongated or shortened more than a decade by another stress level, as compared to pure cyclic load. Additionally, the stiffness development of the composite is investigated in order to capture the damage course. Accordingly, these effects needed to be considered in lifetime prediction.