Ultrasonic tomography based temperature distribution measurement method

The temperature distribution information plays an important role in industrial applications. Owing to the advantages such as non-intrusive sensing and low cost, the ultrasonic tomography (UT) is considered to be a promising method for temperature field visualization. The ultrasonic time-of-flight (TOF) measurement and the reconstruction algorithm are crucial for practical applications of the UT measurement. In this paper, a dual-threshold measurement method is proposed to ensure a high-quality TOF measurement. In view of the inaccurate nature of the reconstruction model and TOF data, a new reconstruction method that integrates the advantages of the Tikhonov regularization method and the least squares support vector machine (LSSVM) is proposed to improve the reconstruction quality. The experimental results were compared against thermocouple measurements and the results show that the temperature distribution can be reconstructed with the error of 1.3%, which validates the feasibility and effectiveness of the proposed Tikhonov-LSSVM reconstruction algorithm.