Open AccessContact‐free dielectric response measurement based on limit fitting by neural network
Author(s) -
Shen Zhongyi,
Yang Lijun,
Tang Hanwei,
Lai Yijun
Publication year - 2021
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/smt2.12050
Subject(s) - repeatability , frequency domain , dielectric , artificial neural network , materials science , limit (mathematics) , distortion (music) , sample (material) , time domain , test method , acoustics , computer science , mathematics , artificial intelligence , optoelectronics , mathematical analysis , statistics , computer vision , amplifier , chemistry , physics , cmos , chromatography
Frequency domain spectroscopy (FDS) is widely used in analysis of insulation condition of dielectric material. The traditional contact method is susceptible to the impact of the contact state between the test sample and the electrode, which is also difficult to ensure the accuracy and repeatability of the test results. Using the method of sputtering gold on the surface of the sample is an effective way to avoid this problem though, this processing method is time‐consuming and high‐cost. This paper presents a method based on limit fitting by neural network to realize contact‐free dielectric response measurement, which can eliminate the distortion effect of the air gap introduced by the uneven surface of dielectric material. Cross linked polyethylene (XLPE) is chosen as the test object to verify this method: in the domain of frequency = 1–1000 Hz, comparing with the test results of sample treatment by gold sputtering, the average error of frequency domain spectroscopy data in traditional method is 10%, while the new method is only 1%. Meanwhile, this paper analyses the cause of the errors in each method.