In Tribology – the science of interacting surfaces in relative motion, dealing with friction, wear and lubrication – the prediction of wear plays a major role, since it allows to extend lifetime and to avoid failure of tools or systems. Parameters are very numerous and often hard to measure. Furthermore, experimental results usually scatter strongly. In few cases with exact boundary conditions, reliable simulation models are available. Such models are based on results of tribo-experiments performed on special devices (tribometers). In the BAM, several tribometers have been constructed and employed since decades for specific operational and environmental conditions in order to acquire data for model samples with simple shapes. One of the essential tasks of experimental and theoretical work was – and still is – to identify parameters and values, which can describe tribological systems. To this aim, the databank TRIDAS was developed in the BAM.
About 50 new results and ca. 600 data from the databank were analysed in this paper, in order to study the wear coefficient (wear volume per normal force and sliding distance) of 100Cr6 balls against 100Cr6 discs as a function of humidity. A general correlation between humidity and wear coefficient is state of the art. Thanks to the large dataset and statistical analysis, we could generate a map of the wear coefficient, which allows to predict wear in the whole humidity range with great accuracy. Thereby, for the first time, it was recognized that the wear coefficient depends also on the normal force and the sliding distance. Hence, those parameters were included additionally in the analysis. The results have a strong impact on the evaluation of reproducibility and repeatability of tribo-tests and are the basis for simulations and further theoretical studies.
Influence of relative humidity on wear of self-mated 100Cr6 steel
Manuel Reichelt, Brunero Cappella
erschienen in Wear, Vol. 450-451, page 203239
BAM, Division Macrotribology and Wear Protection