Combustion Field Prediction and Diagnosis via Spatiotemporal Discrete U-ConvLSTM Model
Considering the importance of combustion diagnosis in industrial manufacturing and many fields, efficient, quick, and real-time multidimensional reconstruction is necessary and indispensable. Hence, focusing on the combustion field dynamic and multi-dimensional reconstruction, a modified U-ConvLSTM...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Photonics Journal |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10457001/ |
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| Summary: | Considering the importance of combustion diagnosis in industrial manufacturing and many fields, efficient, quick, and real-time multidimensional reconstruction is necessary and indispensable. Hence, focusing on the combustion field dynamic and multi-dimensional reconstruction, a modified U-ConvLSTM model was proposed to combine with the TDLAS method to resolve the real-time reconstruction and short prediction. By dividing the combustion field into space and time slices, we used discretized spatiotemporal slices to complete the 2-D distribution reconstruction and then expanded them into higher dimensions. The simulation results demonstrate that our design can effectively reconstruct different 2-D distributions, achieving a reconstruction error of less than 5%. Three-step predictions also performed well, a PSNR no less than 30 dB, and an SSIM no less than 0.75. In general, our multidimensional combustion field reconstruction method, based on the spatiotemporal discretization U-ConvLSTM model, can enhance the accuracy of combustion field reconstruction and provide short-term predictions. This work will contribute to closed-loop control in industrial fields. |
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| ISSN: | 1943-0655 |