Two Dimensional Free Interface Reconstruction Based on Ultrasound and EIT Fusion Imaging
Guanghui Liang, Shangjie Ren and Feng Dong
Tianjin Key Laboratory of Process Measurement and Control
School of Electrical Engineering and Automation, Tianjin University, Tianjin, China firstname.lastname@example.org
Layered medium distribution is normal seen in the industrial production process. Detection of the interface between these mediums is important for the optimization and control of the industrial processes. Electrical impedance tomography (EIT) is a noninvasive technique to image the conductivity distributions inside a closed pipe from the electrical measurements on its boundary. Due to its advantages of high-speed and low cost, EIT has been widely researched and is promising for solving many industrial measurements problems. However, the image reconstruction in EIT is an ill- posed and nonlinear inverse problem, which always leads to a resolution solution. To deal with the problem, an ultrasound-EIT dual-modality tomography is proposed to reconstruct the 2D free-interface between the layered distributed mediums. The ultrasound sensor is mounted at the bottom of the sensing domain. The narrow field ultrasonic pulse echo is used to detect the height of the interface. Then, the ultrasound measurements are used as a prior constraint to improve the ill-posedness of EIT. In order to obtain a quantitative result, the shape-based method is used to solve the inverse problem of EIT. The unknown interface is parameterized by front points method, and then estimated within a constrain least square framework. The Lagrange Multiplier method and Levenberg–Marquardt method is used to solve the constrained least square problem. The numerical tests show that the proposed dual-modality free-interface reconstruction is more accurate than the single modality method.
Keywords Boundary element method, Electrical impedance tomography, Levenberg–Marquardt method, Lagrange Multiplier method, Narrow field ultrasonic pulse echo, Shape reconstruction.
Copyright © International Society for Industrial Process Tomography, 2016. All rights reserved.