Title :
SVM Classifier Based Fault Diagnosis of the Satellite Attitude Control System
Author :
Zhao, Shi-lei ; Zhang, Ying-chun
Author_Institution :
Res. Center of Satellite Technol., Harbin Inst. of Technol., Harbin
Abstract :
A fault detection and diagnosis scheme using SVM classifier is explored in this paper, First, NPCA method is applied to generate residual for classification. Second, one-against-one SVM classifiers and DS theory are combined to a kind of new multi-classifier, which is used for sensors or actuators faults of satellite attitude control system (ACS). The combination method we proposed not only effectively lighten the computing burden but also could keep the classification accuracy. Research result shows that this method for detection and diagnosis of the ACS faults is feasible.
Keywords :
artificial satellites; attitude control; fault diagnosis; pattern classification; support vector machines; DS theory; NPCA method; SVM classifier based fault diagnosis; fault detection; satellite attitude control system; Actuators; Automation; Electronic mail; Fault detection; Fault diagnosis; Neural networks; Satellites; Sensor systems; Support vector machine classification; Support vector machines; ACS; DS theory; SVM;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
DOI :
10.1109/ICICTA.2008.409