DocumentCode
519400
Title
Engine Condition Monitoring Based on Grey AR Combination Model
Author
Wang, Qiang ; Dai, Hui Sheng
Volume
1
fYear
2010
fDate
6-7 March 2010
Firstpage
215
Lastpage
218
Abstract
Aiming at the problems of the wear condition monitoring, grey theory and auto-regressive combination forecasting model was put forward, and the combination model was build. The rough trend of the wear particle content change can be reflected through grey theory, and the detail of the change can be reflected through auto-regressive model. By testing and comparing a set of Ferro graphic data, the result shows that the combination model has a better forecasting result.
Keywords
Abrasives; Condition monitoring; Engines; Graphics; Least squares approximation; Linear regression; Predictive models; Technology forecasting; Testing; Time series analysis; auto-regressive; condition monitoring; grey theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Challenges in Environmental Science and Computer Engineering (CESCE), 2010 International Conference on
Conference_Location
Wuhan, China
Print_ISBN
978-0-7695-3972-0
Electronic_ISBN
978-1-4244-5924-7
Type
conf
DOI
10.1109/CESCE.2010.19
Filename
5493095
Link To Document