Flight Path Reconstruction for Sensor Failure Detection and Health Monitoring

Girija, G and Zorn, Christopher (2004) Flight Path Reconstruction for Sensor Failure Detection and Health Monitoring. Technical Report. National Aerospace Laboratories, Bangalore, India.

[img] PDF
Restricted to Repository staff only

Download (792kB)
[img] Indexer Terms (Generate index codes conversion from application/pdf to indexcodes)
Restricted to Repository staff only

Download (8kB)


Model based sensor failure detection and health monitoring requires a model of the system which utilizes the redundancies present among the various measured variables. In this report, the flight path reconstruction model of a flying vehicle is used for health monitoring of a magnetometer using ARTIS (Autonomous Rotorcraft Test bed for Intelligent Systems) developed at DLR Institute of Flight systems as the test bed. ARTIS is equipped with a miniaturized avionics system which is realized with Commercial-Off-The-Shelf (COTS) components. The use of low quality micro sensors in such miniaturized vehicles makes intelligent data fusion a mandatory requirement for purposes of compensating for bias and scale factor errors in sensors as well as for health monitoring of the sensors. Using the measurements from the Inertial Measurement Unit (IMU), a three axis magnetometer and DGPS on ARTIS, a model for flight path reconstruction has been developed. The positions, velocities and attitudes as well as bias errors in sensors are estimated using an Extended Kalman Filter. The entire scheme has been realized on a MATLAB/SIMULINK platform using simulated data of ARTIS. Commonly encountered sensor failures like no output, constant output and drift are simulated for the magnetometer and failure detection has been achieved by residual monitoring. The algorithm has also been used for state estimation of the fight test data from recently conducted flight tests on ARTIS.

Item Type: Monograph (Technical Report)
Uncontrolled Keywords: Health monitoring;Multi sensor data fusion;Sensor failure detection and isolation (SFDI);Flight path reconstruction; Extended Kalman filter;Autonomous rotorcraft
Subjects: ENGINEERING > Electronics and Electrical Engineering
Depositing User: Ms Indrani V
Date Deposited: 03 Feb 2009
Last Modified: 13 Oct 2015 07:31
URI: http://nal-ir.nal.res.in/id/eprint/794

Actions (login required)

View Item View Item