2010
DOI: 10.3182/20100906-3-it-2019.00084
|View full text |Cite
|
Sign up to set email alerts
|

Diagnosis of UAV Pitot Tube Defects Using Statistical Change Detection

Abstract: Unmanned Aerial Vehicles need a large degree of tolerance to faults. One of the most important steps towards this is the ability to detect and isolate faults in sensors and actuators in real time and make remedial actions to avoid that faults develop to failure. This paper analyses the possibilities of detecting faults in the pitot tube of a small unmanned aerial vehicle, a fault that easily causes a crash if not diagnosed and handled in time. Using as redundant information the velocity measured from an onboar… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
14
0

Year Published

2013
2013
2023
2023

Publication Types

Select...
5
2

Relationship

3
4

Authors

Journals

citations
Cited by 17 publications
(14 citation statements)
references
References 11 publications
0
14
0
Order By: Relevance
“…The residual has been prewhitened and is uncorrelated with past samples as seen in the figure. The histogram shows that as in [21] the noise on the residual follows a Cauchy distribution with a general form of…”
Section: Estimatesmentioning
confidence: 98%
See 3 more Smart Citations
“…The residual has been prewhitened and is uncorrelated with past samples as seen in the figure. The histogram shows that as in [21] the noise on the residual follows a Cauchy distribution with a general form of…”
Section: Estimatesmentioning
confidence: 98%
“…This gives rise to the parity relations shown in Table II, which were also used in [21]. A "1" in Table II means the residual TABLE II MEASUREMENTS AND VOTING SCHEME RESIDUALS.…”
Section: Possibilities For Diagnosismentioning
confidence: 99%
See 2 more Smart Citations
“…This overview paper draws upon results from airspeed sensor system diagnosis (initial results in (Hansen et al, 2010) and a detailed scrutiny in (Hansen and Blanke, 2014)) and diagnosis of control surface defects (with different approaches presented in (Hansen and Blanke, 2012), and ).…”
Section: Introductionmentioning
confidence: 99%