Liquid Film Thickness Estimation using Electrical Capacitance Tomography

Abstract

In air/oil lubrication systems, the flow parameters, e.g., flow pattern, liquid film thickness, and air/oil flow rate, are of great importance to the transportation efficiency. In most cases, the on-going two-phase flow is annular flow with the oil moving along the tube wall and the air travelling at high speed in the center. This usually results in the formation of a thin oil film, the thickness of which is a key parameter determining the efficiency of the lubrication system. As the oil film thickness of the on-going air/oil flow varies dynamically, there is actually no applicable method for a non-intrusive test. In this paper, the use of electrical capacitance tomography (ECT) to investigate the air/oil flow has been studied. Capacitance measurements are made from an externally mounted electrode array in a non-invasive and non-intrusive manner. Both average and distributed oil film thicknesses can be calculated from the reconstructed ECT images. Simulation and experimental results show that the ECT technique can provide satisfactory results of online oil film thickness estimation.

Research on Lubrication Properties of Selected Raw Plant and Animal Materials

“…Liquid film occurs very often in industrial applications with thicknesses that may range from below 10 μm to above 5 mm (Cui et al 2014). Engine tribology has been always an important subject of study in the automotive industry (Macián et al 2016).…”

Transportation characteristics of gas–solid two-phase flow in a long-distance pipeline

“…The distance between the two sensors was 600 m. Each ECT sensor was powered using a dedicated data acquisition system. The data acquisition systems were field-programmable gate array (FPGA) based and communicated with the host PC via a USB link, with a data acquisition rate of 800 frames per second (fps) (Cui, Wang, Chen, Xu, & Yang, 2011;Cui, Yang, Sun, & Wang, 2014). To avoid possible mutual interference between the two data acquisition systems, through the metal pipeline, different excitation frequencies were assigned to the two systems.…”

A Benchmark Dataset and Deep Learning-Based Image Reconstruction for Electrical Capacitance Tomography

“…With the change of the medium’s permittivity from a low value to a high value in the ECT imaging area, the capacitance values among the different electrode pairs behave totally differently in terms of their properties and nonlinearities. Cui et al [ 43 ] and Yang et al [ 44 ] reported and preliminarily analyzed the effect of the nonlinearity of capacitances between different electrode pairs on ECT image reconstruction. This issue may need to be investigated more deeply in future studies on ECT image reconstruction, particularly while the permittivity distribution inside the sensor has a relatively high contrast variation.…”