Active Fault Diagnosis for Hybrid Systems Based on Sensitivity Analysis and EKF

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5 Citationer (Scopus)

Resumé

An active fault diagnosis approach for different
kinds of faults is proposed. The input of the approach is
designed off-line based on sensitivity analysis such that the
maximum sensitivity for each individual system parameter is
obtained. Using maximum sensitivity, results in a better
precision in the estimation of the corresponding parameter. The
fault detection and isolation is done by comparing the nominal
parameters with those estimated by Extended Kalman Filter
(EKF). In study, Gaussian noise is used as the input disturbance
as well as the measurement noise for simulation. The method is
implemented on the large scale livestock hybrid ventilation
model which was obtained during previous research
OriginalsprogEngelsk
TidsskriftAmerican Control Conference. Proceedings
Sider (fra-til)244-249
Antal sider6
ISSN0743-1619
StatusUdgivet - 2 jul. 2011

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Extended Kalman filters
Hybrid systems
Agriculture
Sensitivity analysis
Failure analysis

Citer dette

@inproceedings{cf00f536799948a5b69c9a275ce321c9,
title = "Active Fault Diagnosis for Hybrid Systems Based on Sensitivity Analysis and EKF",
abstract = "An active fault diagnosis approach for differentkinds of faults is proposed. The input of the approach isdesigned off-line based on sensitivity analysis such that themaximum sensitivity for each individual system parameter isobtained. Using maximum sensitivity, results in a betterprecision in the estimation of the corresponding parameter. Thefault detection and isolation is done by comparing the nominalparameters with those estimated by Extended Kalman Filter(EKF). In study, Gaussian noise is used as the input disturbanceas well as the measurement noise for simulation. The method isimplemented on the large scale livestock hybrid ventilationmodel which was obtained during previous research",
keywords = "Active fault diagnosis, sensitivity analysis, hybrid systems, EKF",
author = "Mehdi Gholami and Henrik Schi{\o}ler and Thomas Bak",
year = "2011",
month = "7",
day = "2",
language = "English",
pages = "244--249",
journal = "American Control Conference",
issn = "0743-1619",
publisher = "American Automatic Control Council",

}

Active Fault Diagnosis for Hybrid Systems Based on Sensitivity Analysis and EKF. / Gholami, Mehdi; Schiøler, Henrik; Bak, Thomas.

I: American Control Conference. Proceedings, 02.07.2011, s. 244-249.

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

TY - GEN

T1 - Active Fault Diagnosis for Hybrid Systems Based on Sensitivity Analysis and EKF

AU - Gholami, Mehdi

AU - Schiøler, Henrik

AU - Bak, Thomas

PY - 2011/7/2

Y1 - 2011/7/2

N2 - An active fault diagnosis approach for differentkinds of faults is proposed. The input of the approach isdesigned off-line based on sensitivity analysis such that themaximum sensitivity for each individual system parameter isobtained. Using maximum sensitivity, results in a betterprecision in the estimation of the corresponding parameter. Thefault detection and isolation is done by comparing the nominalparameters with those estimated by Extended Kalman Filter(EKF). In study, Gaussian noise is used as the input disturbanceas well as the measurement noise for simulation. The method isimplemented on the large scale livestock hybrid ventilationmodel which was obtained during previous research

AB - An active fault diagnosis approach for differentkinds of faults is proposed. The input of the approach isdesigned off-line based on sensitivity analysis such that themaximum sensitivity for each individual system parameter isobtained. Using maximum sensitivity, results in a betterprecision in the estimation of the corresponding parameter. Thefault detection and isolation is done by comparing the nominalparameters with those estimated by Extended Kalman Filter(EKF). In study, Gaussian noise is used as the input disturbanceas well as the measurement noise for simulation. The method isimplemented on the large scale livestock hybrid ventilationmodel which was obtained during previous research

KW - Active fault diagnosis, sensitivity analysis, hybrid systems, EKF

M3 - Conference article in Journal

SP - 244

EP - 249

JO - American Control Conference

JF - American Control Conference

SN - 0743-1619

ER -