Remaining Useful Life Prediction for Aircraft Engines using LSTM
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866917567791104000 |
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| author | Peringal, Anees Mohiuddin, Mohammed Basheer Hassan, Ahmed |
| author_facet | Peringal, Anees Mohiuddin, Mohammed Basheer Hassan, Ahmed |
| contents | This study uses a Long Short-Term Memory (LSTM) network to predict the remaining useful life (RUL) of jet engines from time-series data, crucial for aircraft maintenance and safety. The LSTM model's performance is compared with a Multilayer Perceptron (MLP) on the C-MAPSS dataset from NASA, which contains jet engine run-to-failure events. The LSTM learns from temporal sequences of sensor data, while the MLP learns from static data snapshots. The LSTM model consistently outperforms the MLP in prediction accuracy, demonstrating its superior ability to capture temporal dependencies in jet engine degradation patterns. The software for this project is in https://github.com/AneesPeringal/rul-prediction.git. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_07590 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Remaining Useful Life Prediction for Aircraft Engines using LSTM Peringal, Anees Mohiuddin, Mohammed Basheer Hassan, Ahmed Signal Processing This study uses a Long Short-Term Memory (LSTM) network to predict the remaining useful life (RUL) of jet engines from time-series data, crucial for aircraft maintenance and safety. The LSTM model's performance is compared with a Multilayer Perceptron (MLP) on the C-MAPSS dataset from NASA, which contains jet engine run-to-failure events. The LSTM learns from temporal sequences of sensor data, while the MLP learns from static data snapshots. The LSTM model consistently outperforms the MLP in prediction accuracy, demonstrating its superior ability to capture temporal dependencies in jet engine degradation patterns. The software for this project is in https://github.com/AneesPeringal/rul-prediction.git. |
| title | Remaining Useful Life Prediction for Aircraft Engines using LSTM |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2401.07590 |