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| Equipment Residual Life Prediction and Evaluation with Transformer Small Sample Multi-source Data Fusion |
| Received:July 15, 2024 Revised:August 01, 2024 |
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| DOI：10.7643/issn.1672-9242.2024.11.009 |
| KeyWord:life extension engineering residual life transformer multi-source data fusion transfer learning source domain target domain |
| Author | Institution |
| CHEN Kainuo |
Naval Aviation University, Shandong Yantai , China |
| ZHANG Fuguang |
Naval Aviation University, Shandong Yantai , China |
| HAN Jianli |
Naval Aviation University, Shandong Yantai , China |
| YIN Yantao |
Naval Aviation University, Shandong Yantai , China |
| DU Guangchuan |
Naval Aviation University, Shandong Yantai , China |
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| Abstract: |
| The work aims to address the low accuracy in residual life assessments caused by the scarcity of failure data and the small sample size in storage life extension of certain high-reliability aviation equipment. A method utilizing Transformer architecture for transfer learning and multi-source data fusion was proposed. This method effectively integrated sensor data from various stages (such as storage, use and life extension) and types of equipment tests using a multi-head attention mechanism, to explore the internal relation of data and improve the level of comprehensive utilization of information. On this basis, the transfer learning strategy was introduced to mitigate the distribution difference between the source domain and the target domain by pre-training the model on relevant domain data and using feature alignment and semantic alignment techniques, so as to improve the adaptability and discrimination ability of the model on target tasks. Compared with traditional methods, this method significantly improved the accuracy and practicability of the residual life prediction, which proved that the model had ideal prediction accuracy and robustness in the case of small-sample scenarios. This method provides an effective solution for predicting the residual life of high reliability equipment and has important values for practical application. |
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