Determination of complex permittivity of thin dielectric samples Cheek for based on high-q microstrip resonance sensor

被引:12
|
作者
Sun, Haoran [1 ,2 ]
Li, Rongqiang [2 ]
Tian, Gui Yun [1 ,3 ]
Tang, Tao [1 ,2 ]
Du, Guohong [2 ]
Wang, Bin [2 ]
机构
[1] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 611731, Sichuan, Peoples R China
[2] Chengdu Univ Informat Technol Chengdu, Sch Elect Engn, Chengdu 610225, Sichuan, Peoples R China
[3] Newcastle Univ, Sch Elect & Elect Engn, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England
基金
英国工程与自然科学研究理事会;
关键词
High quality factor; Fractal structure; Complex permittivity; Neural network; MICROWAVE; THICKNESS;
D O I
10.1016/j.sna.2019.07.001
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, a high quality factor microstrip resonator based on modified Minkowski fractal structure sensor is presented for determining the dielectric sample's complex permittivity. A high loaded quality factor value has been achieved by utilizing fractal structure, which is far greater than that of a typical rectangle microstrip antenna. Besides, the modified fractal radiation patch and the feeding section of the sensor result in a highly sensitive area to the tested materials. The sensing principle is implemented by detecting the electric fields perturbation of the resonator when different tested materials are placed over it. The complex permittivity change of the tested materials can be forecasted by transferring the acquired experimental relative resonant frequency shifts (Delta f) and loaded Q(perpendicular to) values of the proposed sensor to a well-developed neural network system. To validate the proposed method, various standard dielectric samples including Teflon, PVC, and others are tested and analyzed. The experimental results are compared with published values with the maximum error of 4.9%. (C) 2019 Published by Elsevier B.V.
引用
收藏
页码:31 / 37
页数:7
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