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Temperature Distribution Reconstruction of Acoustic Tomography Based on Improved Sparse Reconstruction Model |
DONG Xianghu,ZHANG Lifeng |
Department of Automation, North China Electric Power University, Baoding, Hebei 071003, China |
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Abstract In order to further improve the reconstruction accuracy of temperature distribution based on acoustic tomography, an error function (ERF) with small deviation is introduced to improve the sparse reconstruction model, and the iterative reweighting algorithm is used to further optimize the model. Finally, the alternating direction multiplier algorithm (ADMM) is used to solve the model, so as to complete the reconstruction of temperature distribution. Simulation and experimental tests are carried out and compared with LASSO, ART and Landweber algorithms. In the simulation experiment, the reconstruction quality of temperature distribution based on ERF model is the best, with the average relative error and root mean square error of 0.1% and 0.14% respectively. In the experimental testing, the average absolute value of the reconstruction temperature error at the set temperature point is the smallest, 0.043%, which is significantly smaller than the other three algorithms.
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Received: 25 May 2023
Published: 06 June 2024
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