Principal Component Analysis for Fault Detection and Isolation in a DC-DC Buck Converter

2021 ◽  
Author(s):  
Cheikhna Mahfoudh ◽  
Othman Nasri ◽  
Hajji Omessad ◽  
Jaleleddine Ben Hadj Slama ◽  
Mamoudou Ndongo
Keyword(s):  
Principal Component Analysis ◽  
Fault Detection ◽  
Principal Component ◽  
Component Analysis ◽  
Buck Converter ◽  
Fault Detection And Isolation

scholarly journals Spacecraft Actuator Diagnosis with Principal Component Analysis: Application to the Rendez-Vous Phase of the Mars Sample Return Mission

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Othman Nasri ◽  
Imen Gueddi ◽  
Philippe Dague ◽  
Kamal Benothman
Keyword(s):  
Principal Component Analysis ◽  
Fault Detection ◽  
Principal Component ◽  
Component Analysis ◽  
Fault Detection And Isolation ◽  
Test Results ◽  
Sample Return ◽  
Rotation Rates ◽  
Analysis Application ◽  
Sample Return Mission

This paper presents a fault detection and isolation (FDI) approach in order to detect and isolate actuators (thrusters and reaction wheels) faults of an autonomous spacecraft involved in the rendez-vous phase of the Mars Sample Return (MSR) mission. The principal component analysis (PCA) has been adopted to estimate the relationships between the various variables of the process. To ensure the feasibility of the proposed FDI approach, a set of data provided by the industrial “high-fidelity” simulator of the MSR and representing the opening (resp., the rotation) rates of the spacecraft thrusters (resp., reaction wheels) has been considered. The test results demonstrate that the fault detection and isolation are successfully accomplished.

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