Introducing tribo-data map as a novel analysis for a detailed correlation between friction data and wear surface features

The results of wear tests are conventionally regarded as a type of time-series data. Consequently, various signal processing methods are employed for the analysis, with the aim of investigating wear behaviors and mechanisms. However, in addition to temporal dependencies, the wear behavior is also influenced by surface topography which varies with the position inside a wear track. Hence, the spatial distribution characteristics of force data are of equal significance in the study of wear mechanisms. In this work, we propose a novel data analysis method, tribo-data map, which offers a more immediate and concurrent visualization of the force distribution over both temporal and spatial dimensions. Dry sliding wear tests of two different materials displaying different wear mechanisms (316L stainless steel and Ti6Al4V alloy) were performed using a reciprocating tribometer. The worn surfaces were investigated, with scanning-electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and confocal microscopy , in detail. The results show that tribo-data map can detect a significant wear mechanism transformation (oxidation reaction) during the wear process. Furthermore, it was also found that the spatial distribution of force data is related to surface topography . Inside a single wear path, the loading state still varies with positions.