UAV flight test and its endurance degradation modelling by considering the energy efficiency and flight stability factors
This study presents a novel method for UAV degradation modeling based on real-world flight data, emphasizing the introduced factors of flight energy efficiency and flight operating stability. The approach adopts a dual-modeling framework. Firstly, an LSTNet (Long Short-Term Memory Network) model int...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/172714 |
| _version_ | 1811687351476289536 |
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| author | Wang, Jinlong Govind, Siddesh Hu, Xinting Feroskhan, Mir |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Wang, Jinlong Govind, Siddesh Hu, Xinting Feroskhan, Mir |
| author_sort | Wang, Jinlong |
| collection | NTU |
| description | This study presents a novel method for UAV degradation modeling based on real-world flight data, emphasizing the introduced factors of flight energy efficiency and flight operating stability. The approach adopts a dual-modeling framework. Firstly, an LSTNet (Long Short-Term Memory Network) model interprets a vast time series dataset from flight logs, focusing on the individual rotator's instantaneous rotation speeds, to forecast a flight efficiency indicator in a many-to-one manner. This predicted efficiency marker, 'FE_KPCA', when combined with other metadata parameters, aids regression models in the estimation of the UAV's flight endurance for the second modelling objective. The experimental design for this study, which produced over 40 hours of manual flight data, serves as a notable contribution and foundation for our findings. |
| first_indexed | 2024-10-01T05:14:56Z |
| format | Conference Paper |
| id | ntu-10356/172714 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:14:56Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1727142023-12-29T07:25:43Z UAV flight test and its endurance degradation modelling by considering the energy efficiency and flight stability factors Wang, Jinlong Govind, Siddesh Hu, Xinting Feroskhan, Mir School of Mechanical and Aerospace Engineering 2023 IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC) Air Traffic Management Research Institute Engineering::Aeronautical engineering::Accidents and air safety Unmanned Aerial Vehicle Performance Degradation Test This study presents a novel method for UAV degradation modeling based on real-world flight data, emphasizing the introduced factors of flight energy efficiency and flight operating stability. The approach adopts a dual-modeling framework. Firstly, an LSTNet (Long Short-Term Memory Network) model interprets a vast time series dataset from flight logs, focusing on the individual rotator's instantaneous rotation speeds, to forecast a flight efficiency indicator in a many-to-one manner. This predicted efficiency marker, 'FE_KPCA', when combined with other metadata parameters, aids regression models in the estimation of the UAV's flight endurance for the second modelling objective. The experimental design for this study, which produced over 40 hours of manual flight data, serves as a notable contribution and foundation for our findings. Civil Aviation Authority of Singapore (CAAS) This research is supported by the National Research Foundation, Singapore, and the Civil Aviation Authority of Singapore, under the Aviation Transformation Programme. 2023-12-29T07:25:43Z 2023-12-29T07:25:43Z 2023 Conference Paper Wang, J., Govind, S., Hu, X. & Feroskhan, M. (2023). UAV flight test and its endurance degradation modelling by considering the energy efficiency and flight stability factors. 2023 IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC). https://dx.doi.org/10.1109/DASC58513.2023.10311139 https://hdl.handle.net/10356/172714 10.1109/DASC58513.2023.10311139 en © 2023 IEEE. All rights reserved. |
| spellingShingle | Engineering::Aeronautical engineering::Accidents and air safety Unmanned Aerial Vehicle Performance Degradation Test Wang, Jinlong Govind, Siddesh Hu, Xinting Feroskhan, Mir UAV flight test and its endurance degradation modelling by considering the energy efficiency and flight stability factors |
| title | UAV flight test and its endurance degradation modelling by considering the energy efficiency and flight stability factors |
| title_full | UAV flight test and its endurance degradation modelling by considering the energy efficiency and flight stability factors |
| title_fullStr | UAV flight test and its endurance degradation modelling by considering the energy efficiency and flight stability factors |
| title_full_unstemmed | UAV flight test and its endurance degradation modelling by considering the energy efficiency and flight stability factors |
| title_short | UAV flight test and its endurance degradation modelling by considering the energy efficiency and flight stability factors |
| title_sort | uav flight test and its endurance degradation modelling by considering the energy efficiency and flight stability factors |
| topic | Engineering::Aeronautical engineering::Accidents and air safety Unmanned Aerial Vehicle Performance Degradation Test |
| url | https://hdl.handle.net/10356/172714 |
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