Electrical Resistance Tomography (ERT) is used in process tomography to measure multi-phase fluid flow in pipes. ERT has the advantage of a non-invasive interface, but has challenges such as noise, a relatively low spatial resolution and the ill-posedness of the inverse problem. Many different image reconstruction algorithms have been developed in the medical imaging community, which offer promise to help improve ERT performance. However, no evaluation or methodology for comparison of different algorithms for industrial applications is available. To provide such an evaluation, we tested six ERT reconstruction algorithms for the identification in static and dynamic flow situations. Metrics were developed to evaluate the algorithms in terms of image quality and accuracy, different objects/shapes and coarse solids bed levels were tested statically in a spool piece, and bed levels dynamically in a pipe loop. An algorithm comparison methodology was developed and used to evaluate the different images based on the results obtained. Overall, results show significant variability between reconstruction algorithms, with some giving poor results at the pipe boundary and others poor results at the centre of the image. We identified two high performing algorithms and show that averages of individual algorithm images can achieve improved performance.

Flow Measurement and Instrumentation
Department of Systems and Computer Engineering

Kotzé, R. (R.), Adler, A, Sutherland, A. (A.), & Deba, C.N. (C. N.). (2019). Evaluation of Electrical Resistance Tomography imaging algorithms to monitor settling slurry pipe flow. Flow Measurement and Instrumentation, 68. doi:10.1016/j.flowmeasinst.2019.101572