Title :
Prediction of further Operation based on vehicle Tribo data
Author :
Valis, D. ; Zak, L. ; Chaloupka, J.
Author_Institution :
Dept. of Combat & Special Vehicles, Univ. of Defence, Brno, Czech Republic
Abstract :
The paper deals with application of selected analytical methods for analysing field data from heavy off-road military vehicles. The information from the engine oil are interpreted in form of polluting particles like particles from wear process (e.g. Fe, Pb, Cu, etc.) and particles from oil deterioration itself (like Mn, Si, Zn, etc.). These pieces of information have good technical and analytical potential which has not been explored well yet. There is available reasonable set of vehicles and their oil data from in-field-operation. Based on the data we assume it will be possible to determine some changes in the system. This may help to change e.g. the system maintenance policy, may estimate system operation and help in mission planning.
Keywords :
maintenance engineering; military vehicles; off-road vehicles; wear; engine oil; heavy off-road military vehicles; oil deterioration; polluting particles; system maintenance policy; system operation estimation; vehicle tribo data; wear process; Educational institutions; Engines; Fuzzy logic; Iron; Maintenance engineering; Regression analysis; Vehicles; Field data assessment; maintenance optimization; off-line diagnostics; residual life;
Conference_Titel :
Industrial Engineering and Engineering Management (IEEM), 2013 IEEE International Conference on
Conference_Location :
Bangkok
DOI :
10.1109/IEEM.2013.6962644