Frequency controlled intelligent standalone RF sensor system for dispersive material testing

Abstract

An artificial neural network (ANN) based frequency controlled automated RF sensor system for the characterization of dispersive liquids is presented. The frequency of the designed structure is electronically controlled by varying the applied reverse-biased voltage to the complementary split ring resonator (CSRR) attached varactor diode. A hybrid modelling approach has mainly been devised to account for the effects of biasing circuitry and the parasitic elements. The designed RF sensor can provide a relatively higher tuning bandwidth (800 MHz) for applied DC biasing voltage of 0–25 V. The proposed sensor system employs an artificially intelligent feed-forward neural network architecture, which is trained by the Levenberg–Marquardt training algorithm for the complex permittivity estimation in the designated frequency band with reasonable accuracy. It employs the Bayesian Regularization for better input–output correlation and system performance. The ANN based characterization algorithm is integrated with a graphical user interface (GUI) and implemented using MATLAB.

KEYWORDS:

• Artificial neural network
• CSRR
• dielectric constant
• electronic tunability
• and frequency controlled varactor diode

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

# NA denotes that these sensors do not have tuning arrangement. Sensitivity is estimated here as the percentage change in resonant frequency for unit change in dielectric constant (ε_r= 2) relative to the unloaded condition (ε_r= 1), i.e. $\text{Sensitivity }(\mathrm{\%})=\frac{{f_s}_{({\epsilon }_{rs}=2)}-{f_0}_{({\epsilon }_{r0}=1)}}{{f_0}_{({\epsilon }_{r0}=1)}\times ({\epsilon }_{rs}-{\epsilon }_{r0})}\times 100=\frac{f_s-f_0}{f_0\times (2-1)}\times 100$.

^a Depicts the designed single unit cell based VLCSRR structure.

^b Corresponding to single cell (identically half than that of the reported dual cell) with applied DC voltage 0–25 V.

# MUT depicts the material under test.

^a Measured data corresponding to maximum error scenario over the operating tuning range (0–25 V) ∼ ${\epsilon }_{err}=|{\epsilon }_m-{\epsilon }_r|$ ∼ $\tan {\delta }_{err}=|\tan {\delta }_m-\tan {\delta }_r|$.

^b 1:1 mixture of chloroform and toluene.

^c Reference values of dielectric constant ${\epsilon }_r$ and loss tangent $\tan {\delta }_r$ [34].

Additional information

Notes on contributors

Sachin Seth

Sachin Seth received his B-Tech in Electronics and Communication Engineering from Maulana Abul Kalam Azad University of Technology, Kolkata (2017) and an M-Tech in Electrical Engineering from Indian Institute of Technology Kanpur, Kanpur (2019). His research interests include artificial Intelligence based electrical system optimizations, machine learning, metamaterial inspired RF sensors, digital design, computer vision and digital image processing.

Apala Banerjee

Apala Banerjee is presently a PhD Research Scholar at Indian Institute of Technology, Kanpur in RF and Microwaves specialization. Her present area of interest includes Integrated RF planar sensors, active circuit, active RF sensors and high sensitive passive sensors. She has completed her Master's Degree (Gold Medalist) from The University of Burdwan, West Bengal with specialization in Microwaves (2018). She was associated with SAC, ISRO, Ahmedabad, India where she has worked as a project Trainee for her MTech Thesis Project (2017–2018). She has received her BTech Degree in Electronics and Communications from West Bengal University of Technology in the year 2016. She is presently the IEEE MTT chapter Secretary, Up Section, IIT Kanpur.

Nilesh K. Tiwari

Dr Nilesh K. Tiwari completed his PhD in RF and Microwaves from Indian Institute of Technology, Kanpur (2020). He completed his Master's degree from Indian institute of Technology, Kanpur and his BTech from Government Engineering College JEC, Jabalpur (2007). He has authored and co-authored more than 50 journal and conference papers, 2 book chapters and 1 patent. He has guided and mentored more than 10 masters and Phd students. He has obtained the best thesis award for his Phd thesis work. His main area of research includes RF sensors, integrated RF planar sensors, biomedical applications of RF sensors.

M. Jaleel Akhtar

M. Jaleel Akhtar (S'99–M'03–SM'09) received the PhD/Dr Ing degrees in electrical engineering from the Otto-von-Guericke University of Magdeburg, Magdeburg, Germany, in 2003. He was a Scientist with the Central Electronics Engineering Research Institute, Pilani, India, from 1994 to 1997, where he was involved in the design and development of high-power microwave tubes. From 2003 to 2009, he was a Post-Doctoral Research Scientist and a Project Leader with the Institute for Pulsed Power and Microwave Technology, Karlsruhe Institute of Technology, Karlsruhe, Germany, where he was involved with a number of projects in the field of microwave material processing. In 2009, he joined the Department of Electrical Engineering, Indian Institute of Technology Kanpur, India, where he is currently a Professor. He has authored two books, two book chapters, and has authored or coauthored over 250 papers in various peer-reviewed international journals and conference proceedings. He also holds one patent on coplanar-based RF Sensors. His current research interests include microwave imaging and nondestructive testing, RF sensors, electromagnetic modeling and testing of artificial dielectrics and metamaterials, UWB antennas for imaging, and design of RF filters and components using the electromagnetic inverse scattering. Dr Akhtar is a Fellow of the Institution of Electronics and Telecommunication Engineers, New Delhi, India, and a Life Member of the Indian Physics Association and the Indo-French Technical Association. He was a recipient of the CST University Publication Award 2009 from the CST AG, Germany.