ATTRN: Acoustic Information Encoder and Temperature Field Reconstruction Decoder Network for Boiler Temperature Field Reconstruction
Accurate and swift evaluation of the temperature distribution in boiler furnaces is essential for maximizing energy efficiency and ensuring operational safety. Traditional temperature field reconstruction algorithms, while effective, often suffer from accumulated errors, difficulty in solving ill-posed problems, low accuracy, and poor generalization. To overcome these limitations, a Temperature Field Reconstruction Network based on an acoustic information encoder (AIE) and a temperature field reconstruction decoder (TFRD) is proposed (ATTRN). This method directly utilizes acoustic measurement data for temperature field prediction, effectively balancing global semantic capture and local detail preservation. The proposed approach avoids complex traditional mathematical processing and empirical parameter selection, enhancing both accuracy and generalization. Simulation studies and engineering validations demonstrate the performance and industrial applicability of the proposed method.
Authors
- Kunyu Wu
- Junqiao Wang (ORCID: https://orcid.org/0009-0005-4298-5885)
- Xinzhi Zhou (ORCID: https://orcid.org/0000-0003-2007-2493)
- Hengyuan Xu
- Liwei Chen (ORCID: https://orcid.org/0000-0002-3689-6529)
- Jingyi Zhou (ORCID: https://orcid.org/0009-0004-8049-115X)
- Keqi Ni
Institutions
- National University of Singapore (SG)
- Sichuan University (CN)
Publication Details
- Journal
- Sensors
- Published
- 2025-04-18
- DOI
- https://doi.org/10.3390/s25082567
- Primary Topic
- Flow Measurement and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Key Research and Development Program of China