Publications

@conference{Houiji2016229,

title = {Fault detection performances analysis for stochastic systems based on adaptive threshold},

author = {M. Houiji and R. Hamdaoui and M. Aoun},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84974575297\&doi=10.1109%2fSSD.2016.7473701\&partnerID=40\&md5=0f9cdd28ba3852316e53997164690401},

doi = {10.1109/SSD.2016.7473701},

isbn = {9781509012916},

year  = {2016},

date = {2016-01-01},

journal = {13th International Multi-Conference on Systems, Signals and Devices, SSD 2016},

pages = {229-234},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {This paper investigates the problem of fault detection for discrete linear systems subjected to unknown disturbances, actuator and sensor faults. A bank of Augmented Robust Three stage Kalman filters is adapted to estimate both the state and the fault as well as to generate the residuals. Besides, this paper presents the evaluation of the residuals with Bayes test of binary hypothesis test for fault detection to adaptive threshold compared with fixed threshold. This test allow the detection of low magnitude faults as fast as possible with a minimum risk of errors, the increase of detection probability and the reduction of false alarm probability. © 2016 IEEE.},

note = {cited By 2},

keywords = {Actuator and sensor faults; Adaptive thresholds; Binary hypothesis tests; Detection delays; Detection performance; Detection probabilities; Discrete linear systems; False alarm probability, Fault detection, Linear systems; Signal detection; Stochastic systems},

pubstate = {published},

tppubtype = {conference}

}