发电技术2025，Vol.46Issue(2)：361-369,9.DOI:10.12096/j.2096-4528.pgt.23115
基于鲁棒正则化极限学习机的声学层析温度分布重建
Reconstruction of Temperature Distribution in Acoustic Tomography Based on Robust Regularized Extreme Learning Machine
摘要
Abstract
[Objectives]Acoustic tomography,as a non-invasive temperature detection technology,holds significant value in industrial process monitoring.However,it is constrained by insufficient spatial resolution caused by ill-posed inversion and sensitivity to noise.To address these issues,a acoustic tomography temperature distribution based on robust regularized extreme learning machine(ELM)is proposed.[Methods]A two-stage reconstruction framework is established.In the first stage,the network is trained using acoustic time of flight data and low-resolution temperature data to obtain a low-resolution temperature distribution on a coarse grid.In the second stage,the network is further trained using low-resolution and high-resolution temperature distribution,enabling high-resolution temperature reconstruction on a fine grid.Numerical simulations are conducted on typical temperature field models,and the proposed method is compared with traditional algorithms,including Tikhonov regularization,Landweber algorithm,algebraic reconstruction technique(ART),and ELM algorithm.[Results]The robust regularized ELM algorithm achieves an average relative error of 0.28%and a root mean square error of 0.38%,significantly outperforming the other algorithms in reconstruction quality.[Conclusions]The acoustic tomography temperature distribution based on robust regularized ELM balances computational efficiency and reconstruction accuracy,providing a new solution for high-resolution temperature monitoring in power plant boilers and similar equipment.It demonstrates significant engineering application value,particularly under harsh conditions such as high temperature and strong interference.关键词
发电厂/电站锅炉/声学层析成像/温度分布/高分辨率重建/鲁棒正则化/极限学习机/数值模拟/重建算法Key words
power plant/power station boiler/acoustic tomography/temperature distribution/high-resolution reconstruction/robust regularized/extreme learning machine/numerical simulation/reconstruction algorithm分类
能源科技引用本文复制引用
张立峰,董祥虎..基于鲁棒正则化极限学习机的声学层析温度分布重建[J].发电技术,2025,46(2):361-369,9.基金项目
国家自然科学基金项目(61973115).Project Supported by National Natural Science Foundation of China(61973115). （61973115）
