Abstract: Visualized measurement of oil-water two-phase flow is of vital importance in multi-phase flow measurement and process industry. Ultrasonic tomography (UT) is widely applied in two-phase flow measurement due to its non-invasive, non-radiative, safe, and portable advantages. Aiming at UT reconstruction of oil-water two-phase medium with low acoustic impedance, we propose a high-resolution reconstruction algorithm based on Gaussian regression prediction. The iteratively simultaneously algebraic reconstruction technique is modified with high pass filter, and the truncated singular value decomposition is used to reduce dimensionality of the coefficient matrix. Gaussian process regression is applied to gain high-resolution image. Simulation results indicate that the proposed algorithm provides high accuracy and high-resolution reconstruction with fast computing speed.

Key words: oil-water two-phase flow, ultrasonic tomography, truncated singular value decomposition, Gaussian process regression, simultaneous algebraic reconstruction technique