DocumentCode
3501751
Title
Data mining-based fault detection and prediction methods for in-orbit satellite
Author
Tianshe Yang ; Bin Chen ; Yu Gao ; Junhua Feng ; Hailong Zhang ; Xiaole Wang
Author_Institution
State Key Lab. of Astronaut. Dynamics, Xi´an Satellite Control Center, Xi´an, China
Volume
02
fYear
2013
fDate
16-18 Aug. 2013
Firstpage
805
Lastpage
808
Abstract
Fault detection and prediction is one of the key technologies for health monitoring of in-orbit satellites. The fault detection and prediction methods for in-orbit satellites is studied by the data mining technology. The deep mining method for telemetry of the in-orbit satellite is studied. Then, several fault detection and prediction methods are proposed, which have been developed and used in fault detection and prediction of actual in-orbit satellites. The results show that the proposed methods are effective and feasible.
Keywords
data mining; fault diagnosis; telemetry; data mining-based fault detection and prediction methods; deep mining method; health monitoring; in-orbit satellite; satellite telemetry data; Estimation theory; Satellite broadcasting; Satellites; Telemetry; data mining; fault detection; fault prediction; in-orbit satellite; telemetry data;
fLanguage
English
Publisher
ieee
Conference_Titel
Measurement, Information and Control (ICMIC), 2013 International Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4799-1390-9
Type
conf
DOI
10.1109/MIC.2013.6758085
Filename
6758085
Link To Document