Diagnosis of Wing Icing Through Lift and Drag Coefficient Change Detection for Small Unmanned Aircraft

Kim Lynge Sørensen; Mogens Blanke; Tor Arne Johansen

doi:10.1016/j.ifacol.2015.09.582

Diagnosis of Wing Icing Through Lift and Drag Coefficient Change Detection for Small Unmanned Aircraft

Kim Lynge Sørensen, Mogens Blanke, Tor Arne Johansen

Norwegian University of Science and Technology

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Abstract

This paper address the issue of structural change, caused by ice accretion, on UAVs by utilising a Neyman Pearson (NP) based statistical change detection approach, for the identification of structural changes of fixed wing UAV airfoils. A structural analysis is performed on the nonlinear aircraft system and residuals are generated, where a generalised likelihood ratio test is applied to detect faults. Numerical simulations demonstrate a robust detection with adequate balance between false alarm rate and sensitivity.

Original language	English
Book series	IFAC-PapersOnLine
Volume	48
Issue number	21
Pages (from-to)	541-546
ISSN	2405-8963
DOIs	https://doi.org/10.1016/j.ifacol.2015.09.582
Publication status	Published - 2015
Event	9th IFAC Symposium on Fault Detection, Supervision andSafety for Technical Processes - Arts et Métiers ParisTech, Paris, France Duration: 2 Sept 2015 → 4 Sept 2015 Conference number: 9 https://www.sciencedirect.com/journal/ifac-papersonline/vol/48/issue/21

Conference

Conference	9th IFAC Symposium on Fault Detection, Supervision andSafety for Technical Processes
Number	9
Location	Arts et Métiers ParisTech
Country/Territory	France
City	Paris
Period	02/09/2015 → 04/09/2015
Internet address	https://www.sciencedirect.com/journal/ifac-papersonline/vol/48/issue/21

Keywords

Structural Change Detection
Aircraft Ice accretion
Aircraft Icing Detection
UAV
Fixed-Wing UAV
Statistical Change Detection

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title = "Diagnosis of Wing Icing Through Lift and Drag Coefficient Change Detection for Small Unmanned Aircraft",

abstract = "This paper address the issue of structural change, caused by ice accretion, on UAVs by utilising a Neyman Pearson (NP) based statistical change detection approach, for the identification of structural changes of fixed wing UAV airfoils. A structural analysis is performed on the nonlinear aircraft system and residuals are generated, where a generalised likelihood ratio test is applied to detect faults. Numerical simulations demonstrate a robust detection with adequate balance between false alarm rate and sensitivity. ",

keywords = "Structural Change Detection, Aircraft Ice accretion, Aircraft Icing Detection, UAV, Fixed-Wing UAV, Statistical Change Detection",

author = "S{\o}rensen, {Kim Lynge} and Mogens Blanke and Johansen, {Tor Arne}",

year = "2015",

doi = "10.1016/j.ifacol.2015.09.582",

language = "English",

volume = "48",

pages = "541--546",

journal = "IFAC-PapersOnLine",

issn = "2405-8963",

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note = "9th IFAC Symposium on Fault Detection, Supervision andSafety for Technical Processes, SAFEPROCESS 2015 ; Conference date: 02-09-2015 Through 04-09-2015",

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AU - Blanke, Mogens

AU - Johansen, Tor Arne

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PY - 2015

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N2 - This paper address the issue of structural change, caused by ice accretion, on UAVs by utilising a Neyman Pearson (NP) based statistical change detection approach, for the identification of structural changes of fixed wing UAV airfoils. A structural analysis is performed on the nonlinear aircraft system and residuals are generated, where a generalised likelihood ratio test is applied to detect faults. Numerical simulations demonstrate a robust detection with adequate balance between false alarm rate and sensitivity.

AB - This paper address the issue of structural change, caused by ice accretion, on UAVs by utilising a Neyman Pearson (NP) based statistical change detection approach, for the identification of structural changes of fixed wing UAV airfoils. A structural analysis is performed on the nonlinear aircraft system and residuals are generated, where a generalised likelihood ratio test is applied to detect faults. Numerical simulations demonstrate a robust detection with adequate balance between false alarm rate and sensitivity.

KW - Structural Change Detection

KW - Aircraft Ice accretion

KW - Aircraft Icing Detection

KW - UAV

KW - Fixed-Wing UAV

KW - Statistical Change Detection

U2 - 10.1016/j.ifacol.2015.09.582

DO - 10.1016/j.ifacol.2015.09.582

M3 - Conference article

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VL - 48

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EP - 546

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

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T2 - 9th IFAC Symposium on Fault Detection, Supervision andSafety for Technical Processes

Y2 - 2 September 2015 through 4 September 2015

ER -

Diagnosis of Wing Icing Through Lift and Drag Coefficient Change Detection for Small Unmanned Aircraft

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