Air data system fault modeling and detection

Freeman, Paul K.; Seiler, Peter; Balas, Gary J.

doi:10.1016/j.conengprac.2013.05.007

Cited by 58 publications

(26 citation statements)

References 12 publications

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“…The main challenge in anomaly detection algorithm development is that sensor networks are highly application and domain dependent. Two domainspecific techniques are proposed by Yin et al [34] who model wind turbine data and Freeman et al [35] who model aircraft pilot-static probe data. Both of these examples propose anomaly detection techniques for data with a nonlinear and unknown distribution and significant measurement noise.…”

Section: Detection Of Corrupted Datamentioning

confidence: 99%

A Survey of Research on Data Corruption in Cyber–Physical Critical Infrastructure Systems

Woodard

Sarvestani

Hurson

2015

Advances in Computers

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Section: Detection Of Corrupted Datamentioning

confidence: 99%

A Survey of Research on Data Corruption in Cyber–Physical Critical Infrastructure Systems

Woodard

Sarvestani

Hurson

2015

Advances in Computers

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“…4,5,6 IMU and ADS FDD are both studied by a lot of researchers. 7,8,9 Most researchers use the aerodynamic model of the aircraft. However, the calculation of the aerodynamic forces and moments may contain uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Active Fault-Tolerant Control System using Incremental Backstepping Approach

Kampen

2015

AIAA Guidance, Navigation, and Control Conference

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This paper proposes an Active Fault-Tolerant Control System (AFTCS) using the Incremental Backstepping (IBS) approach. The AFTCS contains a sensor Fault Detection and Diagnosis (FDD) system and a Fault-Tolerant Control (FTC) system and it is able to cope with Inertial Measurement Unit (IMU) sensor and Air Data Sensors (ADS) faults, as well as actuator faults and process faults. IMU faults are detected and estimated by an Iterative Optimal Two-Stage Extended Kalman Filter whereas ADS faults are detected and diagnosed by designing an Iterative Three-Step Extended Kalman Filter. The FTC system uses an IBS controller in order to cope with actuator and process faults. The FDD system provides more reliable information for the FTC system which guarantees that the IBS can maintain the flight. The performance of the complete AFTCS is validated using a Cessna Citation II aircraft model with the objective of attitude control. The simulation results demonstrate that the AFTCS is able to maintain the flight in the presence of sensor and actuator faults.Nomenclature A x , A y , A z = specific forces along the body axis, m/s 2 p, q, r = roll, pitch and yaw rate along the body axis, rad/s u a , v a , w a = air speed components along the body axis, m/s u B GS , v B GS , w B GS = ground speed components along the body axis, m/s V t = true airspeed, m/s α, β = angle of attack, sideslip angle, rad φ, θ, ψ = roll, pitch and yaw angles along the body axis, rad δ e , δ a , δ r

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“…At this time, the incorrect measurements should be detected, identified and isolated to avoid its continuous propagation by using the previous faults self-detection methodology [8][9]. Further, some detailed faults information such as the type of faults is very needed, which can benefit the further device maintenance and can also be ready for latter data recovery under faults.…”

Section: Figure 1 Construction Models Of Svads Systemmentioning

confidence: 99%

“…Complete the signal decomposition of sample X by using EEMD and obtain seven IMFs called as IMF 1 , IMF 2 ,…, IMF 7 and a residual called as IMF 8 .…”

Section: Faults Features Extraction Based On Sensitive Imf Selectionmentioning

confidence: 99%

Faults Diagnosis of Self-validating Air Data Sensing System Based on Ensemble EMD and Multiclass RVM

Fu¹,

Shen²,

Han³

et al. 2017

IJCA

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Air data system fault modeling and detection

Cited by 58 publications

References 12 publications

A Survey of Research on Data Corruption in Cyber–Physical Critical Infrastructure Systems

A Survey of Research on Data Corruption in Cyber–Physical Critical Infrastructure Systems

Active Fault-Tolerant Control System using Incremental Backstepping Approach

Faults Diagnosis of Self-validating Air Data Sensing System Based on Ensemble EMD and Multiclass RVM

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