A High Resolution Reconstruction Method of Temperature Distribution in Acoustic Tomography

Authors

Lifeng Zhang, Department of Automation, North China Electric Power University, Baoding 071003, China;Follow
Yu Miao, Department of Automation, North China Electric Power University, Baoding 071003, China;

Abstract

Abstract: Accurate measurement temperature distribution is important for industrial production. In order to solve the number of mesh divisions will impact reconstruction accuracy in acoustic tomography, the TR-RBF (Tikhonov regularization-radial basis function) reconstruction algorithm is rebuilt to reconstruct the temperature field with high resolution. The Tikhonov regularization is used to reconstruct the ultrasound time of flight (TOF) to obtain a temperature distribution on coarse grids, and use local weighted regression method to smooth processing; use RBF neural networks to predict the temperature distribution on fine grids. Through numerical simulation with and without noise, compared with ART,SVD and Tikhonov, the proposed algorithm improves the reconstruction accuracy greatly and has the best anti-noise performance in the case of typical peak temperature.

Recommended Citation

Zhang, Lifeng and Miao, Yu (2022) "A High Resolution Reconstruction Method of Temperature Distribution in Acoustic Tomography," Journal of System Simulation: Vol. 34: Iss. 9, Article 16.
DOI: 10.16182/j.issn1004731x.joss.21-0447
Available at: https://dc-china-simulation.researchcommons.org/journal/vol34/iss9/16

First Page

2065

Revised Date

2021-08-10

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.21-0447

Last Page

2073

CLC

TP391.9

Recommended Citation

Lifeng Zhang, Yu Miao. A High Resolution Reconstruction Method of Temperature Distribution in Acoustic Tomography[J]. Journal of System Simulation, 2022, 34(09): 2065-2073.

DOI

10.16182/j.issn1004731x.joss.21-0447