Title :
Linguistic model for axle fatigue
Author :
Grantner, Janos ; Bazuin, Bradley ; Liang Dong ; Al-shawawreh, Jumana ; Hathaway, Richard ; Fajardo, Claudia ; Castanier, Matthew P. ; Hussain, Shiraz
Author_Institution :
Dept. of Electr. & Comput. Eng., WMU, Kalamazoo, MI, USA
Abstract :
Army ground vehicles often operate in extremely severe environmental and battlefield conditions. Condition Based Maintenance (CBM) allows maintenance to be performed based on evidence of need provided by reliability modeling and/or other enabling technologies, thus reducing maintenance costs and increasing vehicle availability. A fuzzy model is developed to diagnose the axle fatigue of light trucks. The extraction of the fuzzy rules is based upon expert knowledge and a linear damage model. Training data will be used to modify the membership functions and the fuzzy If-Then rules to improve the quality of the fuzzy model for fault diagnostics. The improvement of the fuzzy model will be carried out using re-clustering operation and membership function optimization.
Keywords :
axles; condition monitoring; fault diagnosis; fuzzy set theory; knowledge based systems; maintenance engineering; mechanical engineering computing; military computing; military vehicles; optimisation; CBM; army ground vehicles; axle fatigue; condition based maintenance; fault diagnostics; fuzzy If-Then rules; fuzzy model; fuzzy rule extraction; linear damage model; linguistic model; maintenance costs reduction; membership function optimization; reclustering operation; reliability modeling; Axles; Computational modeling; Fatigue; Maintenance engineering; Stress; Training data; Vehicles; Condition Based Maintenance; Rainflow algorithm; axle fatigue; fuzzy model; intelligent diagnostics;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1507-4
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZ-IEEE.2012.6251197
