Research on Forecasting of the Compressor Geometric Variable System Based on the MAE Model
The compressor geometric variable system is vital for aeroengines, as it affects their performance and design. To monitor the compressor geometric variable system states and detect anomalies in real time, a t-step forecasting method based on the MAE (masked autoencoders) model was proposed in this a...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2023/9082587 |
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| _version_ | 1832547948036096000 |
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| author | Cunjiang Xia Yuyou Zhan Yan Tan Wenqing Wu |
| author_facet | Cunjiang Xia Yuyou Zhan Yan Tan Wenqing Wu |
| author_sort | Cunjiang Xia |
| collection | DOAJ |
| description | The compressor geometric variable system is vital for aeroengines, as it affects their performance and design. To monitor the compressor geometric variable system states and detect anomalies in real time, a t-step forecasting method based on the MAE (masked autoencoders) model was proposed in this article. Unlike previous studies that used simulated or lab-generated data, we use actual flight data recorded by the aircraft data acquisition system to make our results more realistic. Through our experimental efforts, the feasibility of forecasting the compressor geometric variable system based on the MAE model is verified. That is not only the first application of transformer models with a masked pretraining mechanism in time series forecasts but also taking the lead in exploring the possibility of this key system forecast. We also test the generalizability of our method across different types of aeroengines. Finally, to make our theories more reasonable and convincing, experiments on different aeroengine states, including the transition state and the steady state, are carried out. |
| format | Article |
| id | doaj-art-cbf18089122e4d2f9162a4d051fcdde1 |
| institution | Kabale University |
| issn | 1687-5974 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-cbf18089122e4d2f9162a4d051fcdde12025-02-03T06:42:49ZengWileyInternational Journal of Aerospace Engineering1687-59742023-01-01202310.1155/2023/9082587Research on Forecasting of the Compressor Geometric Variable System Based on the MAE ModelCunjiang Xia0Yuyou Zhan1Yan Tan2Wenqing Wu3Civil Aviation Flight University of ChinaCivil Aviation Flight University of ChinaCivil Aviation Flight University of ChinaCivil Aviation Flight University of ChinaThe compressor geometric variable system is vital for aeroengines, as it affects their performance and design. To monitor the compressor geometric variable system states and detect anomalies in real time, a t-step forecasting method based on the MAE (masked autoencoders) model was proposed in this article. Unlike previous studies that used simulated or lab-generated data, we use actual flight data recorded by the aircraft data acquisition system to make our results more realistic. Through our experimental efforts, the feasibility of forecasting the compressor geometric variable system based on the MAE model is verified. That is not only the first application of transformer models with a masked pretraining mechanism in time series forecasts but also taking the lead in exploring the possibility of this key system forecast. We also test the generalizability of our method across different types of aeroengines. Finally, to make our theories more reasonable and convincing, experiments on different aeroengine states, including the transition state and the steady state, are carried out.http://dx.doi.org/10.1155/2023/9082587 |
| spellingShingle | Cunjiang Xia Yuyou Zhan Yan Tan Wenqing Wu Research on Forecasting of the Compressor Geometric Variable System Based on the MAE Model International Journal of Aerospace Engineering |
| title | Research on Forecasting of the Compressor Geometric Variable System Based on the MAE Model |
| title_full | Research on Forecasting of the Compressor Geometric Variable System Based on the MAE Model |
| title_fullStr | Research on Forecasting of the Compressor Geometric Variable System Based on the MAE Model |
| title_full_unstemmed | Research on Forecasting of the Compressor Geometric Variable System Based on the MAE Model |
| title_short | Research on Forecasting of the Compressor Geometric Variable System Based on the MAE Model |
| title_sort | research on forecasting of the compressor geometric variable system based on the mae model |
| url | http://dx.doi.org/10.1155/2023/9082587 |
| work_keys_str_mv | AT cunjiangxia researchonforecastingofthecompressorgeometricvariablesystembasedonthemaemodel AT yuyouzhan researchonforecastingofthecompressorgeometricvariablesystembasedonthemaemodel AT yantan researchonforecastingofthecompressorgeometricvariablesystembasedonthemaemodel AT wenqingwu researchonforecastingofthecompressorgeometricvariablesystembasedonthemaemodel |