DocumentCode :
3442924
Title :
Regression based complex equipment Prognostic and Health Management
Author :
Guoshun Chen ; Gefang Wang ; Wenbin Cao
Author_Institution :
Inst. of Ordnance Technol., Shijiazhuang, China
fYear :
2013
fDate :
15-18 July 2013
Firstpage :
1893
Lastpage :
1896
Abstract :
A novel Prognostic and Health Management (PHM) method for an Unmanned Air Vehicle (UAV) is proposed. The method uses trend analysis with regression to build the reference indicator, through probability-based techniques, and produce a degradation model to health monitoring UAV system. This method is concerned with trend analysis and regression techniques for estimation of the future condition of the system and prediction of the time-to-failure. The simulation results show that the proposed method can give the health index of UAV visually and is proved to be practical and easy to implement in engineering.
Keywords :
autonomous aerial vehicles; condition monitoring; failure analysis; regression analysis; PHM; health index; health monitoring UAV system; probability-based techniques; regression based complex equipment prognostic and health management; time-to-failure prediction; unmanned air vehicle; Analytical models; Degradation; Fuels; Maintenance engineering; Market research; Prognostics and health management; Reliability; Prognostic and Health Management(PHM); Unmanned Aerial Vehicle(UAV); equipment health management; regression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE), 2013 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-1014-4
Type :
conf
DOI :
10.1109/QR2MSE.2013.6625949
Filename :
6625949
Link To Document :
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