Image reconstruction technique via ultrasonic tomography system for metal pipe

Abstract

Detection of concentration of the gas/liquid mixture inside the pipe with Ultrasonic Tomography (UT) has been investigated seriously with various researchers in the recent decade. To date, most of the researches of ut focus on Acrylic or PVC as pipe material. This research investigates the usage of metal pipe for ut application. The attenuation problem of metal pipe is due to high acoustic impedance mismatch between liquid and metal pipe. Based on the problems of metal pipe for application in the UT system, various alternatives are presented in this research. Modelling of the UT using COMSOL software is studied to visualize the real UT system. Various frequencies are tested to determine the optimum frequency of the UT system. The hardware of UT system is developed after selection of the suitable transceiver. The structures of the transmitter and receiver circuits are developed in order to improve the Signal to Noise Ratio (SNR) and functionality of circuits. The sampled signals are preceded to the computer via Data Acquisition (DAQ) system. Various algorithms are investigated to produce the best image reconstruction of the UT system. As the basic and convenient algorithm, Linear Back Projection (LBP) is used for reconstructing the primary image. Median Filter Back Projection (MFBP) and Disk Filter Back Projection (DFBP) are applied to improve the image quality of LBP algorithm. Additionally, the Circular Thresholding Segmentation (CTS) algorithm is applied to produce the segmented thresholding images. Based on the simulation results, 40 kHz is determined as the optimum frequency of UT system. The designed UT system for the metal pipe is experimentally tested and cross-sectional images are extracted from metal pipe. Additionally, this thesis presents the static and dynamic results of UT system from metal pipe. Based on the comparison between the performances of applied algorithms, the CTS algorithm has the best results due the minimum errors between original images and reconstructed images. The obtained results corroborate the.