Perspective approach in using anti-oxidation and anti-wear particles from oil to estimate residual technical life of a system

Indirect diagnostic measures have big potential for estimating a system condition. One of these are oil data. Since the oil is in direct contact with the observed system, oil data are of great importance and value. Usually the authors analyse its physio-chemical properties, or the concentration of selected wear particles. In our article, however, we take into account a completely novel attitude towards anti-oxidation and anti-wear particles (AOWP). Their great importance lies in the fact that the AOWP concentration depends on both an operation time and a calendar time. Due to the extensive oil field data the dependence on an operation time and a calendar time is available. The development of the AOWP particles concentration is modelled stochastically with the use of the Wiener process with drift, or generally with a diffusion process. The aim is to set the trajectory of oil or engine degradation, and set the probability of an engine soft failure. In order to compare our results obtained by using the diffusion process of Wiener type we apply the Fuzzy Inference System (FIS). The results are expected to help us to estimate the residual technical life of a system, optimize the maintenance and make life cycle costs more effective. The system is meant to be the oil itself and the combustion engine where the oil is used.