High accuracy dual split ring resonator-defected ground structure based microwave sensor for material characterization

Misran, Mohamad Harris and Meor Said, Maizatul Alice and Othman, Mohd Azlishah and Zabri @ Suhaimi, Siti Normi and Ruslan, Eliyana and Shairi, Noor Azwan and Zakaria, Zahriladha and Babale, Suleiman Aliyu and Idris, Mohd Zahid (2025) High accuracy dual split ring resonator-defected ground structure based microwave sensor for material characterization. Majlesi Journal of Electrical Engineering (MJEE), 19 (3). pp. 1-10. ISSN 2345-3796

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Abstract

Microwave sensors have grown in popularity in recent years because of their contactless sensing capability, real-time detection capability, measurement, accuracy, ease of manufacture and robustness. They have become one of the primary choices in smart sensing applications. However, some of their key limitations, such as accuracy, sensitivity, and selectivity, might be regarded as limiting their utilization and application range. Thus, this project proposed to design and develop a high-accuracy microwave sensor for material characterization. This microwave sensor uses a Defected Ground Structure (DGS) to enhance sensor accuracy in determining the dielectric characteristics of the material under test (MUT). The sensor achieved high accuracy with a percentage error of 0.56% to 1.86% for the tested various MUTs, demonstrating reliable precision. The DGS significantly enhances performance, optimizing efficiency and compactness while reducing transmission losses on cost-effective substrates like FR4. Its high Q-factor of 595 enables detecting small dielectric constant variation

Item Type:	Article
Uncontrolled Keywords:	Microwave sensor, Defected ground structure, High accuracy, Split ring resonator
Divisions:	Faculty Of Electronics And Computer Technology And Engineering
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	05 Dec 2025 03:54
Last Modified:	05 Dec 2025 03:54
URI:	http://eprints.utem.edu.my/id/eprint/29150
Statistic Details:	View Download Statistic

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