Title :
A fault diagnosis approach for autonomous spacecraft based on transition-system model
Author :
Jin, Yang ; Wang, Rixin ; Xu, Minqiang
Author_Institution :
Deep Space Exploration Res. Center, Harbin Inst. of Technol., Harbin, China
Abstract :
For autonomous spacecraft, anomaly detection and fault diagnosis systems play a very important role. To meet the requirement of real-time diagnosis performance for the fault diagnosis system of an autonomous spacecraft, a new method based on transition system model is proposed. In order to improve the efficiency of fault diagnosis, we introduce the separation strategy to separate this process into two stages: the off-line stage at which to finish most computation works of conflict recognition, and the on-line stage at which to generate the fault candidate sets with the minimum matching space. In order to reduce the matching space effectively and avoid enumerating all the fault modes, we build a Conflict-Net to record the relation between the fault modes and the key variables. We have applied this method on a primary power subsystem of a certain satellite, and the result shows it can work more effectively.
Keywords :
data mining; fault diagnosis; learning (artificial intelligence); space vehicles; anomaly detection; autonomous spacecraft; conflict-net; data mining; fault candidate sets; fault diagnosis approach; fault modes; machine learning; minimum matching space; off-line stage; on-line stage; primary power subsystem; real-time diagnosis performance; separation strategy; transition-system model; Artificial intelligence; Cognition; Fault diagnosis; Flywheels; Sensors; Space vehicles; Valves; conflict-net; fault diagnosis; separation strategy; transition system model;
Conference_Titel :
Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2012 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4673-0786-4
DOI :
10.1109/ICQR2MSE.2012.6246304