Work

Three-Dimensional Temperature Field Reconstruction Based on Tucker Decomposition and Acoustic Thermometry

Year: 2025

Type: article

Abstract: Accurate temperature measurement in coal-fired power plants is crucial for optimizing combustion and achieving deep load regulation. While acoustic temperature measurement is an efficient and stable method, its practical application is limited to two-dimensional (2D) temperature fields, leading to poor reconstruction of complex 3D temperature fields due to limited measurement points. In this work, we propose a novel 3D temperature field reconstruction algorithm based on Tucker decomposition and acoustic thermometry. The key innovation lies in the use of Tucker decomposition to extract essential features from 3D time-of-flight (TOF) data, enabling efficient reconstruction of 3D temperature fields from a small number of single-layer TOF measurements. Our method achieves faster reconstruction speeds (approximately 4 s) and higher accuracy, reducing reconstruction errors by over 10% compared to traditional acoustic thermometry. Additionally, the algorithm demonstrates strong anti-noise capabilities and applicability to temperature fields beyond the a priori conditions, making it a valuable tool for combustion optimization and load adjustment in coal-fired power plants.

Source: Applied Sciences

DOI: 10.3390/app15073716

Authors: Jidong Yan, Liansuo An, Pengbo Yao, Guoqing Shen, Shiping Zhang

Institution: North China Electric Power University

Language: English

Topic: Tensor decomposition and applications

Subfield: Computational Mathematics

Field: Mathematics

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: gold

Estimated APC paid: $2,896