Design, Modelling, and Experimental Validation of a Glass U-Tube Mass Sensing Cantilever for Particulate Direct-on-Line Emissions Measurement

Abstract

The requirement to monitor and control industrial processes has increased over recent years, therefore innovative techniques are required to meet the demand for alternative methods of particulate measurement. Resonant mass sensors are now strong candidates for accurate mass measurement and are frequently used in many diverse fields of science and engineering. This paper presents the design, modelling, and optimal geometry selection for sensitivity improvement of a U-shaped glass tube as a resonant mass sensing cantilever with a view to becoming a component of particulate measurement equipment. Finite Element Analysis (FEA) was used to develop the system which was validated experimentally using a physical model. This paper focuses on both the proof of concept and the geometry selection of the sensor using analysis of the system sensitivity for best selection. Modal and harmonic analysis were undertaken across a range of commercially available glass tube sizes from 6 mm to 10 mm diameter, to determine the optimal geometry selection, validated with practical experimental data. Results show a consistent difference of 3–5% between the simulation and experimental results, showing strong correlation. This research provides a methodology on the development of using a U-shaped glass tube for accurate mass measurement with a view to exploring the design as a component of particulate emissions equipment. The experimental and simulation results confirm that the highest sensitivity is achieved when the geometry dimensions, and therefore the vacant mass of the tube, is reduced. The 6 mm diameter tube with the smallest bend radius was the most suitable design to meet the design criteria. The calibration curve was plotted to allow an unknown mass to be calculated, which gave an R2 value of 0.9984. All experimental work was repeated three times with results giving an average of 0.44% between the minimum and maximum showing strong linearity and suggesting the potential for implementation of the methodology in its intended application. The design provides possible solutions to some of the issues currently seen with particulate measurement from stationary sources.