Xiao Deng

Dr. Xiao Deng

Taiyuan University of Technology
+1
orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2020 in Measurement
Verified
Journal Article
Closed access
Xiao DengXiao Deng
Xiao Deng
HGHuinan Gu
Huinan Gu
LYLei Yang
Lei Yang
HLHuafang Lyu
Huafang Lyu
YCYuanguo Cheng
Yuanguo Cheng
LZLi Zhang
Li Zhang

22 April 2022 in IEEE Sensors Journal
Verified
Journal Article
Closed access
DZDongsheng Zheng
Dongsheng Zheng
ZLZiyin Li
Ziyin Li
ZDZhenyu Du
Zhenyu Du
YMYue Ma
Yue Ma
LZLin Zhang
Lin Zhang
Xiao DengXiao Deng
Xiao Deng
An ice types recognition and ice thickness detection system was designed based on capacitance and impedance double parameters. By studying the influence of electrode structure on sensor performance based on finite element simulation, the finger electrode was selected with better performance, and a planar electrode sensor was designed suitable for wing thin ice detection. After the thin ice (2.5 mm) making experiment, the capacitance and impedance spectra of three ice types (glaze ice, rime ice and mixed ice) were obtained. Among them, capacitance can reflect the growth of ice well, and the impedance spectra of different ice types are significantly different. Therefore, a capacitance-based regression model and an impedance-based classification model were built. The results of regression model show that about 90% of the calculation error of thin ice thickness is concentrated in the range of [−0.2 mm, 0.2 mm]. Finally, a field test was conducted in the ice wind tunnel to preliminarily determine the system effectiveness.

12 February 2023 in Optical Fiber Technology
Verified
Journal Article
Closed access
SZShuang Zhao
Shuang Zhao
CDChao Du
Chao Du
QWQiuyu Wang
Qiuyu Wang
BJBin Jia
Bin Jia
LZLi Zhang
Li Zhang
SCShizhe Chen
Shizhe Chen

10 December 2014 in Journal of Materials Science
Verified
Journal Article
Closed access
PDF file
JHJie Hu
Jie Hu
FGFanqin Gao
Fanqin Gao
Shengbo SangShengbo Sang
Shengbo Sang
PLPengwei Li
Pengwei Li
Xiao DengXiao Deng
Xiao Deng
KLKun Lian
Kun Lian

1 July 2017 in Optical Fiber Technology
Verified
Journal Article
Closed access
YYYi Yang
Yi Yang
LYLingzhen Yang
Lingzhen Yang
ZZZongwei Zhang
Zongwei Zhang
JYJianjun Yang
Jianjun Yang
JWJuanfen Wang
Juanfen Wang
ZZZhaoxia Zhang
Zhaoxia Zhang

29 March 2023 in IEEE Sensors Journal
Verified
Journal Article
Closed access
BJBin Jia
Bin Jia
CDChao Du
Chao Du
Xiao DengXiao Deng
Xiao Deng
MZMiangjiang Zhang
Miangjiang Zhang
YYYibiao Yang
Yibiao Yang
Three-dimensional strain (3D strain) and the principal strain in ice are very important for glacier movement research and glacier-related disaster prediction. The internal 3D strain of ice is sensitive to temperature, and it is very complex during the whole freezing and melting process including phase transformation. In this study, we present a 3D strain sensor (3D-S Sensor) based on fiber Bragg grating (FBG) and long period fiber grating (LPFG) that can measure the 3D strain in ice. The LPFG (the temperature sensitivity coefficient is 56.3 pm/°C) was fabricated by the laser etching method, which was used for the temperature compensation of FBGs to improve the accuracy of strain measurement. The 3D principal strain can be calculated by the value of 6 direction strains from FBGs. A freeze-melt experiment is designed to verify the performance of 3D-S Sensor. The experimental results show that the sensor can measure the complex 3D deformation of ice from a more precise angle. Among the 6 directions of strain measured by the sensor, the strain value in the Z direction is the largest (ε z = 6232.9 με). The first principal strain in ice is close to the negative direction of the Z axis (θ 1 Z = 160.7°), and the maximum value is 6638.2 με. The measured results are consistent with the actual deformation of ice, indicating that the sensor can effectively measure the 3D strain and principal strain inside the ice.