Acoustic Tomography of Temperature Field by Finite Element Method and Improved Singular Value Decomposition-Based Tikhonov Regularization

The reconstruction algorithms play an important role in acoustic thermometry and are a research hotspot. This paper proposes a novel reconstruction method to improve the accuracy of temperature field reconstruction methods based on acoustic tomography. First, three mesh models are constructed by using the finite element method, which overcomes the defects of oversimplified classical discretization models. Secondly, the coefficient matrix A of the acoustic thermometry forward problem is calculated offline, and then the temperature values of several points in the measurement are obtained by solving the inverse problem using the improved regularization method based on singular value decomposition. Finally, the temperature profile of the entire region is obtained through interpolation. The correctness and feasibility of the proposed method are validated through simulations and experimental testing with three different temperature fields. Results show that the proposed method has satisfactory reconstruction accuracy and provides a different solution for reconstructing the ultrasound temperature field.