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Sensors and Materials, Volume 36, Number 6(5) (2024)
Copyright(C) MYU K.K.
pp. 2655-2668
S&M3693 Research Paper of Special Issue
Published: June 28, 2024

Enhancing Reliability of Inertial Measurement Unit Sensors in Quadrotor Drones [PDF]

Yau-Ren Shiau and Wei-Cheng Chang

(Received February 22, 2024; Accepted June 7, 2024)

Keywords: inertial measurement unit (IMU) sensor, prognostics health management (PHM), UKF-SVM

In unmanned aerial vehicles (UAVs), an inertial measurement unit (IMU) sensor is essential for maintaining stability and navigational accuracy during flight. It becomes exceptionally crucial when UAVs undertake complex tasks, such as flying near wind turbines for inspections or maintaining precise formations alongside other UAVs. The main challenge stems from the nonlinear nature of IMU sensor readings, especially in situations requiring meticulous control. In this article, the authors suggest integrating an unscented Kalman filter (UKF) with a support vector machine (SVM) to predict defects for effective fault prediction in UAVs. The efficacy of this method is validated through comparative experiments with standard prediction algorithms, demonstrating its accuracy in various simulated faulty scenarios. As a result of this research, the proposed method can serve as a trend predictor for monitoring IMU failures as well as a method of enhancing the reliability of drones.

Corresponding author: Wei-Cheng Chang

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Cite this article
Yau-Ren Shiau and Wei-Cheng Chang, Enhancing Reliability of Inertial Measurement Unit Sensors in Quadrotor Drones, Sens. Mater., Vol. 36, No. 6, 2024, p. 2655-2668.

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