Title :
Embedded Capacitive Pressure Sensing for Electrically Assisted Microrolling
Author :
Zhaoyan Fan ; Xiyue Zou ; Gao, Robert X. ; Man-Kwan Ng ; Jian Cao ; Smith, Edward F.
Author_Institution :
Univ. of Connecticut, Storrs, CT, USA
fDate :
6/1/2015 12:00:00 AM
Abstract :
This paper presents the design, characterization, and experimental evaluation of a wireless capacitive pressure sensor embedded within a rotating workroll of a microrolling machine for monitoring the production of micrometer-scaled texture on thin metallic workpiece. The sensor converts the spatial and temporal variations of pressure across the interface between the roll and workpiece into capacitance values, thereby experimentally establishing a quantitative correlation between the online measurement and the geometric features being formed on the workpiece, in real time. Analytical and numerical models have been developed to guide the design of the sensor to maximize the capacitance output while satisfying the space constraint. A sensitivity matrix linking the measured capacitance with pressure distribution has been established through numerical analysis. Simulation and experiments confirmed the effectiveness of the embedded sensor in enabling intelligent microrolling.
Keywords :
capacitive sensors; intelligent sensors; micromechanics; numerical analysis; pressure sensors; process monitoring; rolling; sheet metal processing; analytical models; capacitance values; electrically assisted microrolling; embedded capacitive pressure sensing; embedded sensor; geometric features; intelligent microrolling; micrometer-scaled texture; microrolling machine; numerical analysis; numerical models; online measurement; pressure distribution; production monitoring; quantitative correlation; rotating workroll; sensitivity matrix; sensor design; space constraint; spatial variations; temporal variations; thin metallic workpiece; thin sheet metals; wireless capacitive pressure sensor; Capacitance; Capacitance measurement; Electrodes; Numerical models; Pressure measurement; Sensitivity; Sensors; Electrically assisted microrolling; embedded sensing; modeling; online monitoring;
Journal_Title :
Mechatronics, IEEE/ASME Transactions on
DOI :
10.1109/TMECH.2014.2365512