ATTRN: Acoustic Information Encoder and Temperature Field Reconstruction Decoder Network for Boiler Temperature Field...

Area of Science:

• Engineering
• Thermal Science
• Acoustics

Background:

• Accurate boiler furnace temperature evaluation is crucial for energy efficiency and operational safety.
• Traditional temperature field reconstruction methods face challenges like accumulated errors and poor generalization.

Purpose of the Study:

• To develop an advanced method for temperature field reconstruction in boiler furnaces.
• To overcome the limitations of existing traditional algorithms using a novel network architecture.

Main Methods:

• A Temperature Field Reconstruction Network (ATTRN) was proposed, integrating an acoustic information encoder (AIE) and a temperature field reconstruction decoder (TFRD).
• The ATTRN directly uses acoustic measurement data for temperature prediction, balancing global and local feature capture.
• This approach bypasses complex mathematical processing and empirical parameter selection.

Main Results:

• The ATTRN demonstrated effective temperature field prediction using acoustic data.
• The method showed improved accuracy and generalization capabilities compared to traditional approaches.
• Simulation and engineering validation confirmed the network's performance and industrial applicability.

Conclusions:

• The proposed ATTRN offers an accurate and efficient solution for boiler furnace temperature field reconstruction.
• This acoustic-based method enhances energy efficiency and operational safety in industrial applications.
• ATTRN provides a robust alternative to traditional methods, simplifying processing and improving reliability.