Title :
The wear fault prediction model of aero-engine based on the gray system theory
Author :
Zhenfeng, Wu ; Lin, Guo ; Hongfu, Zuo
Author_Institution :
28th Res. Inst. of the CETC, Nanjing
Abstract :
The prediction of the aero-engine wear fault is one of the major measures that ensure the safe and economical operation of the military and civil aero-crafts. However, in consideration of the specific characteristics of the data sequence of the lubricating oil spectrum analysis and ferro-graph analysis, the traditional application of the time sequence is to some degree limited for the application of modeling prediction. Hence the prediction model based on gray system theory is introduced, aiming at analyzing and comparing the specific modeling prediction test by the methods of time sequence modeling prediction and gray system theory modeling prediction, so as to validate the advantages of the prediction model of gray system theory modeling in the application of the aero-engine wear fault prediction.
Keywords :
aerospace computing; aerospace engines; data analysis; fault diagnosis; grey systems; wear; aero-engine wear fault prediction model; civil aerocraft; data sequence; economical operation; ferro-graph analysis; grey system theory; lubrication oil spectrum analysis; military aerocraft; safe operation; time sequence; Aerodynamics; Economic forecasting; Intelligent systems; Interpolation; Lubricating oils; Military aircraft; Petroleum; Predictive models; Space technology; System testing;
Conference_Titel :
Grey Systems and Intelligent Services, 2007. GSIS 2007. IEEE International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-1294-5
Electronic_ISBN :
978-1-4244-1294-5
DOI :
10.1109/GSIS.2007.4443330