We propose linear parameter-varying (LPV) model-based approaches to the synthesis of robust fault detection and diagnosis (FDD) systems for loss of efficiency (LOE) faults of flight actuators. The proposed methods are applicable to several types of parametric (or multiplicative) LOE faults such as actuator disconnection, surface damage, actuator power loss or stall loads. For the detection of these parametric faults, advanced LPV-model detection techniques are proposed, which implicitly provide fault identification information. Fast detection of intermittent stall loads (seen as nuisances, rather than faults) is important in enhancing the performance of various fault detection schemes dealing with large input signals. For this case, a dedicated fast identification algorithm is devised. The developed FDD systems are tested on a nonlinear actuator model which is implemented in a full nonlinear aircraft simulation model. This enables the validation of the FDD system's detection and identification characteristics under realistic conditions.
@article{bwmeta1.element.bwnjournal-article-amcv25i1p53bwm,
author = {Daniel Ossmann and Andreas Varga},
title = {Detection and identification of loss of efficiency faults of flight actuators},
journal = {International Journal of Applied Mathematics and Computer Science},
volume = {25},
year = {2015},
pages = {53-63},
zbl = {1322.93040},
language = {en},
url = {http://dml.mathdoc.fr/item/bwmeta1.element.bwnjournal-article-amcv25i1p53bwm}
}
Daniel Ossmann; Andreas Varga. Detection and identification of loss of efficiency faults of flight actuators. International Journal of Applied Mathematics and Computer Science, Tome 25 (2015) pp. 53-63. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-amcv25i1p53bwm/
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