The exact measurement of multiphase flow is an important and essential task in the oil and petrochemical related industries. Several methods have already been proposed in this field. In the existing methods, flow rate measurement depends on the fluid flow pattern. Flow pattern recognition requiring calibration has created instability in such systems. In this paper, a imple and reliable method is proposed which is based on ultrasonic tomography. It is free from calibration and instability problems that existing methods have. The obtained data from a 32-digit array of ultrasonic sensors have been used and the two-phase flow rate including liquid and gas phases have been calculated through a simple algebraic algorithm. Simulation results show that while applying this method the measurement technique is independent from the fluid flow pattern and the system error is decreased. For the proposed algorithm, the average amount of the spatial imaging error (SIE) for a bubble at different positions inside the pipe is about 5%.

The paper describes an innovative ultrasound imaging method called Doppler Tomography (DT), otherwise known as Continuous Wave Ultrasonic Tomography (CWUT). Thanks to this method, it is possible to image the tissue cross-section in vivo using a simple two-transducer ultrasonic probe and using the Doppler effect. It should be noted that DT significantly differs from the conventional ultrasound Doppler method of measuring blood flow velocity. The main difference is that when measuring blood flow, we receive information with an image of the velocity distribution in a given blood vessel (Nowicki, 1995), while DT allows us to obtain a cross-sectional image of stationary tissue structure. In the conventional method, the probe remains stationary, while in the DT method, the probe moves and the examined tissue remains stationary.

This paper presents a method of image reconstruction using the DT method. First, the basic principle of correlation of generated Doppler frequencies with the location of inclusions from which they originate is explained. Then the exact process and algorithm in this method are presented. Finally, the impact of several key parameters on imaging quality is examined. As a result, the conclusions of the research allow to improve the image reconstruction process using the DT method.