Aircraft Actuator Performance Analysis Based on Dynamic Neural Network
Monitoring the condition of the aircraft actuators in various operating and environmental circumstances, this paper presents a method for measuring the surface roughness of aircraft actuators. The proposed method starts with the current and vibration signal as failure indicators and a dual-tree comp...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-01-01
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| Series: | Journal of Engineering |
| Online Access: | http://dx.doi.org/10.1155/2023/8237786 |
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| _version_ | 1832547822676738048 |
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| author | Wathiq Rafa Abed |
| author_facet | Wathiq Rafa Abed |
| author_sort | Wathiq Rafa Abed |
| collection | DOAJ |
| description | Monitoring the condition of the aircraft actuators in various operating and environmental circumstances, this paper presents a method for measuring the surface roughness of aircraft actuators. The proposed method starts with the current and vibration signal as failure indicators and a dual-tree complex wavelet transformation (DTCWT) to generate the necessary features. Time-delay neural networks (TDNNs) have been developed for real-time performance monitoring to categorize problems and determine their severity. The simulation results show that the suggested method can accurately identify various faults. |
| format | Article |
| id | doaj-art-03af28e0a63147419e107e7657e5013f |
| institution | Kabale University |
| issn | 2314-4912 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Engineering |
| spelling | doaj-art-03af28e0a63147419e107e7657e5013f2025-02-03T06:43:11ZengWileyJournal of Engineering2314-49122023-01-01202310.1155/2023/8237786Aircraft Actuator Performance Analysis Based on Dynamic Neural NetworkWathiq Rafa Abed0Department of Electrical EngineeringMonitoring the condition of the aircraft actuators in various operating and environmental circumstances, this paper presents a method for measuring the surface roughness of aircraft actuators. The proposed method starts with the current and vibration signal as failure indicators and a dual-tree complex wavelet transformation (DTCWT) to generate the necessary features. Time-delay neural networks (TDNNs) have been developed for real-time performance monitoring to categorize problems and determine their severity. The simulation results show that the suggested method can accurately identify various faults.http://dx.doi.org/10.1155/2023/8237786 |
| spellingShingle | Wathiq Rafa Abed Aircraft Actuator Performance Analysis Based on Dynamic Neural Network Journal of Engineering |
| title | Aircraft Actuator Performance Analysis Based on Dynamic Neural Network |
| title_full | Aircraft Actuator Performance Analysis Based on Dynamic Neural Network |
| title_fullStr | Aircraft Actuator Performance Analysis Based on Dynamic Neural Network |
| title_full_unstemmed | Aircraft Actuator Performance Analysis Based on Dynamic Neural Network |
| title_short | Aircraft Actuator Performance Analysis Based on Dynamic Neural Network |
| title_sort | aircraft actuator performance analysis based on dynamic neural network |
| url | http://dx.doi.org/10.1155/2023/8237786 |
| work_keys_str_mv | AT wathiqrafaabed aircraftactuatorperformanceanalysisbasedondynamicneuralnetwork |