Determining the status of diesel engines using neural network and analyzing the results of oil analysis

It should be noted that in the process of analyzing and interpreting the results of oil analysis, issues such as research and study of engine erosion performance and evaluation and analysis of the relationship between the final state of the engine and the status of components analyzed in oil analysis, are addressed. The analysis examines the components that are effective in analyzing the condition of the engine, what they are and how effective they are. Indicators studied in oil analysis are: Erosive metals such as iron, aluminum, lead, copper, tin, chromium, PQ, viscosity, silicon. Perceptron predicted the final condition of the engine, then according to the results of oil analysis, obtained expert analysis and diagnosis for each sample, and after opening the engine and observing the final condition of the engine, it was concluded that the results of expert analysis and forecast Significantly corresponds to the final state of the engine.