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Fault Detection and Isolation in Multiple MEMS-IMUs Configurations

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Publication date 2012
Author Guerrier S., Waegli Adrian, Skalud J., Victoria-Feser M.-P.,
Project Robust Prediction and Model Choice in Mixed Linear Models for the Analysis of Social Sciences Data
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Original article (peer-reviewed)

Journal IEEE Transactions on Aerospace and Electronic Systems
Volume (Issue) 48
Page(s) 2015 - 2031
Title of proceedings IEEE Transactions on Aerospace and Electronic Systems


This research presents methods for detecting and isolating faults in multiple MEMS-IMU configurations. First, geometric configurations with n sensor triads are investigated. It is proofed that the relative orientation between sensor triads is irrelevant to system optimality in the absence of failures. Then, the impact of sensor failure or decreased performance is investigated. Three FDI approaches (i.e. the parity space method, Mahalanobis distance method and its direct robustification) are reviewed theoretically and in the context of experiments using reference signals. It is shown that in the presence of multiple outliers the best performing detection algorithm is the robust version of the Mahalanobis distance.