The degrading performance of actuators in small unmanned aerial Vehicle (UAV) is often left unnoticed because it is masked by autopilot control. The faulty actuator will only be detected when the actuator has been severely damaged. If it occurs during flight, the UAV will be lost, same
goes with the valuable data on the board. Usually, a pre-flight check is performed before each flight to ensure the overall condition of the UAV including the actuators. The actuator health deterioration is difficult to be recognized by visual inspection. This paper presents a method to detect
the health of the actuator through the integration of Built-in Test System (BITE) using offline model estimation method. Least square regression estimation was performed on the healthy actuator for training data using fixed and increasing input signal. The fault is then simulated to test the
training data accuracy in detecting actuator fault. An analysis is performed to show the advantage and disadvantage of each technique used. The estimation technique described was able to detect faulty actuator which could then be integrated with on-board health detection system in order to
increase the reliability of the UAV.
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Document Type: Research Article
Universiti Kuala Lumpur, Malaysian Institute of Aviation Technology, 43800 Dengkil, Selangor, Malaysia
College of Engineering, Universiti Tenaga Nasional, 43000 Kajang, Selangor, Malaysia
Publication date: 01 June 2017
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