Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods

Mohd Sharif, Zakaria and Mohammad Fadhil, Abas and Fatimah, Dg Jamil and Norhafidzah, Mohd Saad and Addie, Irawan and Pebrianti, Dwi (2024) Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods. In: 2024 20th IEEE International Colloquium on Signal Processing and Its Applications, CSPA 2024 - Conference Proceedings. 20th IEEE International Colloquium on Signal Processing and Its Applications, CSPA 2024 , 1-2 March 2024 , Langkawi. pp. 75-78.. ISBN 979-835038231-0 (Published)

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Abstract

Unmanned Aerial Vehicles (UAV) problematic vibration detection as a flaw detection and identification (FDI) method has emerged as a feasible tool for assessing a UAV's health and condition. This paper shows the potential of optimization-based UAV problematic vibration detection. A proposed fitness function based on the frequency domain has been detailed. The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. The test results show promising results with obtained mean RMSE =1407.2303, mean MAPE =0.7135, and mean detection time =2.6129s for a data range of between 3955 to 9057.

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Frequency-Domain; Genetic algorithm; Mean absolute percentage error; Problematic vibration; Root mean square rrror
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	Institute of Postgraduate Studies Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	31 Jul 2024 03:31
Last Modified:	31 Jul 2024 03:31
URI:	http://umpir.ump.edu.my/id/eprint/41738
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