High temperature dielectric properties measurement system at 915 MHz based on deep learning

2019 ◽  
Vol 29 (11) ◽  
Author(s):  
Qian Tan ◽  
Huacheng Zhu ◽  
Weiquan Ma ◽  
Yang Yang ◽  
Kama Huang
Keyword(s):  
Deep Learning ◽  
High Temperature ◽  
Dielectric Properties ◽  
Measurement System

scholarly journals Development of a Cryogen-Free Compact 3 T Superconducting Magnet for an Electromagnetic Property Measurement System

2021 ◽  
Vol 11 (7) ◽  
pp. 3074
Author(s):  
Jae Young Jang ◽  
Myung Su Kim ◽  
Young Jin Hwang ◽  
Seunghyun Song ◽  
Yojong Choi ◽  
...  
Keyword(s):  
High Temperature ◽  
Measurement System ◽  
Electromagnetic Property ◽  
Superconducting Magnet ◽  
Optimized Design ◽  
Magnet System ◽  
Superconducting Tape ◽  
High Temperature Superconducting ◽  
Target Field ◽  
Property Measurement

A cryogen-free portable 3 T high-temperature superconducting magnet for an electromagnetic property measurement system has been developed to serve as a user facility at the Korea Basic Science Institute. The metallic insulation method was adopted to reduce the charging delay without sacrificing the self-protecting feature. A genetic-algorithm-aided optimized design was carried out to minimize the superconducting tape consumption while satisfying several design constraints. After the design, the compact high-temperature superconducting magnet composed of eight double-pancake coil modules was wound with high-temperature superconducting tape and stainless steel tape, and integrated with a two-stage cryo-cooler. The 3 T magnet was successfully cooled to approximately 20 K with a cryo-cooler and reached the target field of 3 T without any problems. Long-term measurements and a range of other tests were also implemented to verity the performance of the magnet. Test results demonstrated the feasibility of a cryogen-free portable high-temperature superconducting magnet system for electromagnetic property measurement experiments.

Ferroelectric, piezoelectric, and dielectric properties of BiScO3-PbTiO3-Pb(Cd1/3Nb2/3)O3 ternary high temperature piezoelectric ceramics

2013 ◽  
Vol 114 (2) ◽  
pp. 027014 ◽  
Author(s):  
Tian-Long Zhao ◽  
Jianguo Chen ◽  
Chun-Ming Wang ◽  
Yang Yu ◽  
Shuxiang Dong
Keyword(s):  
High Temperature ◽  
Dielectric Properties ◽  
Piezoelectric Ceramics

Dielectric Properties of Solid Solutions of BiFeO3 with Pb(Ti, Zr)O3 at High Temperature and High Frequency

1968 ◽  
Vol 39 (1) ◽  
pp. 70-74 ◽  
Author(s):  
Robert T. Smith ◽  
Gary D. Achenbach ◽  
Robert Gerson ◽  
W. J. James
Keyword(s):  
High Temperature ◽  
Dielectric Properties ◽  
Solid Solutions ◽  
High Frequency

An Update High-Temperature Superconducting Maglev Measurement System

2007 ◽  
Vol 17 (2) ◽  
pp. 2067-2070 ◽  
Author(s):  
Suyu Wang ◽  
Jiasu Wang ◽  
Changyan Deng ◽  
Yiyu Lu ◽  
Youwen Zeng ◽  
...  
Keyword(s):  
High Temperature ◽  
Measurement System ◽  
High Temperature Superconducting ◽  
High Temperature Superconducting Maglev

scholarly journals Defect Detection in CK45 Steel Structures through C-scan Images Using Deep Learning Method

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Navid Moshtaghi Yazdani
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Measurement System ◽  
Processing System ◽  
Steel Structures ◽  
Learning Method ◽  
Metallic Structures ◽  
Defect Profile ◽  
Network Methods ◽  
Deep Convolution Neural Network

In the present paper, a method for reliable estimation of defect profile in CK45 steel structures is presented using an eddy current testing based measurement system and post-processing system based on deep learning technique. So a deep learning method is used to determine the defect characteristics in metallic structures by magnetic field C-scan images obtained by an anisotropic magneto-resistive sensor. Having designed and adjusting the deep convolution neural network and applied it to C-scan images obtained from the measurement system, the performance of deep learning method proposed is compared with conventional artificial neural network methods such as multilayer perceptron and radial basis function on a number of metallic specimens with different defects. The results confirm the superiority of the proposed method for characterizing defects compared to other classical training-oriented methods.

Rapid Prediction of High Temperature Properties of Furnace Tube Alloys Using Deep Learning Approaches

2021 ◽  
Author(s):  
Shulin Xiang ◽  
Tao Chen ◽  
Zhichao Fan ◽  
Xuedong Chen ◽  
Zhigang Wu ◽  
...  
Keyword(s):  
Deep Learning ◽  
High Temperature ◽  
Learning Approaches ◽  
High Temperature Properties ◽  
Rapid Prediction ◽  
Furnace Tube

Improvement of Dielectric Performance of a Prototype AlN High Temperature Chip-level Package

2011 ◽  
Vol 2011 (HITEN) ◽  
pp. 000052-000057 ◽  
Author(s):  
Liang-Yu Chen
Keyword(s):  
High Temperature ◽  
Dielectric Properties ◽  
High Temperatures ◽  
Substrate Surface ◽  
Substrate Material ◽  
Glass Coating ◽  
Temperature Dependent ◽  
High Temperature Electronics ◽  
Dielectric Performance ◽  
Parasitic Parameters

Aluminum nitride (AlN) has been proposed as a packaging substrate material for reliable high temperature electronics operating in a wide temperature range. However, it was discovered in a recent study that the dielectric properties of some commercial polycrystalline AlN materials change quite significantly with temperature at high temperatures. These material properties resulted in undesired large and temperature-dependent parasitic parameters for a prototype chip-level package based on an AlN substrate with the yttrium oxide dopant. This paper reports a method using a coating layer of a commercial thick-film glass on the AlN substrate surface to significantly reduce both the parasitic capacitances and parasitic conductances between neighboring inputs/outputs (I/Os) of a prototype AlN chip-level package. The parasitic parameters of 8-I/Os low power chip-level packages with the insulating glass coating were characterized at frequencies from 120 Hz to 1 MHz between room temperature and 500°C. These results were compared with the parameters of AlN packages without the glass coating. The results indicate that the parasitic capacitances and conductances between I/Os of the improved prototype AlN packages are significantly reduced and stable at high temperatures. The method using a glass coating provides a feasible way to mitigate the temperature dependence of dielectric properties of AlN and further utilize AlN as a reliable packaging substrate material for high temperature applications.

scholarly journals Characterization of AlN-based ceramic composites for use as millimeter-wave susceptor materials at high temperature: Dielectric properties of AlN:Mo with 0.25 vol% to 4.0 vol% Mo from 25 to 550 °C

2019 ◽  
Vol 34 (15) ◽  
pp. 2573-2581 ◽  
Author(s):  
Brad W. Hoff ◽  
Steven C. Hayden ◽  
Martin S. Hilario ◽  
Rachael O. Grudt ◽  
Frederick W. Dynys ◽  
...  
Keyword(s):  
High Temperature ◽  
Dielectric Properties ◽  
Millimeter Wave ◽  
Ceramic Composites ◽  
Image Position

Abstract

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