3D-Printed Multilayer Sensor Structure for Electrical Capacitance Tomography

Abstract

Presently, Electrical Capacitance Tomography (ECT) is positioned as a relatively mature and inexpensive tool for the diagnosis of non-conductive industrial processes. For most industrial applications, a hand-made approach for an ECT sensor and its 3D extended structure fabrication is used. Moreover, a hand-made procedure is often inaccurate, complicated, and time-consuming. Another drawback is that a hand-made ECT sensor’s geometrical parameters, mounting base profile thickness, and electrode array shape usually depends on the structure of industrial test objects, tanks, and containers available on the market. Most of the traditionally fabricated capacitance tomography sensors offer external measurements only with electrodes localized outside of the test object. Although internal measurement is possible, it is often difficult to implement. This leads to limited in-depth scanning abilities and poor sensitivity distribution of traditionally fabricated ECT sensors. In this work we propose, demonstrate, and validate experimentally a new 3D ECT sensor fabrication process. The proposed solution uses a computational workflow that incorporates both 3D computer modeling and 3D-printing techniques. Such a 3D-printed structure can be of any shape, and the electrode layout can be easily fitted to a broad range of industrial applications. A developed solution offers an internal measurement due to negligible thickness of sensor mount base profile. This paper analyses and compares measurement capabilities of a traditionally fabricated 3D ECT sensor with novel 3D-printed design. The authors compared two types of the 3D ECT sensors using experimental capacitance measurements for a set of low-contrast and high-contrast permittivity distribution phantoms. The comparison demonstrates advantages and benefits of using the new 3D-printed spatial capacitance sensor regarding the significant fabrication time reduction as well as the improvement of overall measurement accuracy and stability.

Towards Big Data Solutions for Industrial Tomography Data Processing

“…As part of further work, proprietary algorithms for automatic acquisition, analysis and interpretation of large data sets [23] will be developed, as well as intelligent decision algorithms supporting effective diagnostics and monitoring of flow processes [14]; including those to be the next step after crowdsourcing data labelling cases impossible to be automatically processed at once [24] [25]. The prepared algorithms will be verified both by simulation and by real experimental data from their own experiments carried out on the basis of unique, semiindustrial research installations.…”

On the Performance of a Capacitively Coupled Electrical Impedance Tomography Sensor with Different Configurations

“…In this work, two shielded configurations, which are widely studied and applied in the ET filed [ 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ], are applied to the CCEIT sensor and compared with the unshielded configuration.…”

“…The use of shielding is required to be applied in practical industrial conditions. Related ET studies have provided general shielding measures for reference and the effectiveness of shielding measures in suspension of internal and external interferences is well known [ 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ]. However, as a new technique, CCEIT is still developing.…”

Analysis of Data From Measuring Sensors for Prediction in Production Process Control Systems

“…1). There are many methods for solving optimisation problems [2,[5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. Autonomy, optimisation and integration of analytical approaches is related to the operation of sensor networks, large amounts of data, analysis and interpretation of information, taking into account security aspects [1,[13][14][15].…”