Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods
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 fitn...
| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
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Institute of Electrical and Electronics Engineers Inc.
2024
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| Online Access: | http://umpir.ump.edu.my/id/eprint/41738/1/Detecting%20problematic%20vibration%20on%20unmanned%20aerial%20vehicles.pdf http://umpir.ump.edu.my/id/eprint/41738/2/Detecting%20problematic%20vibration%20on%20unmanned%20aerial%20vehicles%20via%20genetic-algorithm%20methods_ABS.pdf |
| _version_ | 1825815745789952000 |
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| author | Mohd Sharif, Zakaria Mohammad Fadhil, Abas Fatimah, Dg Jamil Norhafidzah, Mohd Saad Addie, Irawan Pebrianti, Dwi |
| author_facet | Mohd Sharif, Zakaria Mohammad Fadhil, Abas Fatimah, Dg Jamil Norhafidzah, Mohd Saad Addie, Irawan Pebrianti, Dwi |
| author_sort | Mohd Sharif, Zakaria |
| collection | UMP |
| description | 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. |
| first_indexed | 2024-09-25T03:50:53Z |
| format | Conference or Workshop Item |
| id | UMPir41738 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-09-25T03:50:53Z |
| publishDate | 2024 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| record_format | dspace |
| spelling | UMPir417382024-07-31T03:31:14Z http://umpir.ump.edu.my/id/eprint/41738/ Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods Mohd Sharif, Zakaria Mohammad Fadhil, Abas Fatimah, Dg Jamil Norhafidzah, Mohd Saad Addie, Irawan Pebrianti, Dwi T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering 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. Institute of Electrical and Electronics Engineers Inc. 2024 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/41738/1/Detecting%20problematic%20vibration%20on%20unmanned%20aerial%20vehicles.pdf pdf en http://umpir.ump.edu.my/id/eprint/41738/2/Detecting%20problematic%20vibration%20on%20unmanned%20aerial%20vehicles%20via%20genetic-algorithm%20methods_ABS.pdf 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) https://doi.org/979-835038231-0 |
| spellingShingle | T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Mohd Sharif, Zakaria Mohammad Fadhil, Abas Fatimah, Dg Jamil Norhafidzah, Mohd Saad Addie, Irawan Pebrianti, Dwi Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods |
| title | Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods |
| title_full | Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods |
| title_fullStr | Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods |
| title_full_unstemmed | Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods |
| title_short | Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods |
| title_sort | detecting problematic vibration on unmanned aerial vehicles via genetic algorithm methods |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/41738/1/Detecting%20problematic%20vibration%20on%20unmanned%20aerial%20vehicles.pdf http://umpir.ump.edu.my/id/eprint/41738/2/Detecting%20problematic%20vibration%20on%20unmanned%20aerial%20vehicles%20via%20genetic-algorithm%20methods_ABS.pdf |
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