Statistical signal processing for the diagnostics of gas bubbles

An advanced diagnostics feature for magnetic flowmeter is presented. Gas bubbles in the liquid do not only falsify the measurement of the flow rate but are an important indicator for the process quality. Based on electric field simulations and measurements in the flow laboratory a physical device model has been developed. Different signal processing algorithms for bubbles or solid particle detection have been designed. They have been analyzed and verified based on statistical signal processing in the laboratory and in the field. This served as the basis for a successful implementation of the diagnostics function in an embedded microcontroller based flowmeter platform.