Capacitance Based Virtual Instrument Mass Flow Measuring System

Lingard, Paul (2009) Capacitance Based Virtual Instrument Mass Flow Measuring System. Masters by Research thesis (MSc), Manchester Metropolitan University.

Preview

Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (5MB) | Preview

Abstract

The research program conducted at the MMU into the design and development of a Virtual Instrument ECT Imaging System is a continuation from preceding investigations conducted by the MMU into tomographic imaging. The rationale behind the MMU tomographic imaging system is a response to the need for a robust and flexible proprietary tomographic imaging system appropriate for large industrial systems. The MMU Virtual Instrument ECT Imaging System consists of capacitance sensor(s), capacitance measuring hardware and the National Instruments (NI) PXI modular data acquisition system on which runs NI’s LabVIEW graphical programming environment. The MMU tomographic imaging system is capable of high tomographic speed imaging from single and dual plane sensing arrays. The purpose of this MSc project is, by utilising the MMU Virtual Instrument ECT Imaging System, to design and develop a virtual instrument measurement system for the purpose of measuring mass flow and flow velocity. Evaluation of the virtual instrument measurement system is achieved by measuring the flow of polypropylene pellets through a vertical, hopper fed, gravity-conveyed flow system fitted with two axially spaced 8 electrode transducers. Pellet mass flow is determined from the averaged volumetric concentration of pellet materials present in the capacitance sensor placed in the upstream path of the pellet flow. Pellet velocity is determined by the cross correlation of the two random noise patterns generated by the pellets as it passes through the two capacitance sensors placed in the upstream and downstream path of the pellet flow. Results are presented which show the relationship between the actual measured mass flow and the mean volumetric concentration taken from the upstream sensor compared to the number of independent normalised capacitance measurements taken from the upstream sensor. Also presented are results which relate the accuracy of the measured flow velocity to the number of independent normalised capacitance measurements taken from the upstream and downstream sensors. The results presented show that as the number of independent normalised capacitance measurements taken from both the capacitance sensors are reduced, the electrostatic field distribution within the sensors becomes more inhomogeneous which has an adverse affect v on the measurement accuracy of mass flow. Conversely, by increasing the number of independent normalised capacitance measurements taken from both the capacitance sensors has a detrimental affect on the accuracy of flow velocity measurement. The results shown prove that the MMU Virtual Instrument ECT Imaging System is capable of individual accurate measurement of either mass flow or flow velocity. But, due to the limitations encountered with the current available hardware, simultaneous and accurate measurement of mass flow and flow velocity is impractical.