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题名

Rapid Gas Sensing Based on Pulse Heating and Deep Learning

作者
DOI
发表日期
2021-01-25
会议名称
34th IEEE International Conference on Micro Electro Mechanical Systems (MEMS)
ISSN
1084-6999
ISBN
978-1-6654-3024-1
会议录名称
卷号
2021-January
页码
438-441
会议日期
JAN 25-29, 2021
会议地点
Gainesville, FL, USA
出版地
345 E 47TH ST, NEW YORK, NY 10017 USA
出版者
摘要
We have reported a rapid sensing method for MEMS gas sensors based on the combination of pulse heating and deep learning. Pulse heating is used to reduce the power consumption of MEMS gas sensor and to realize the rapid gas sensing process. The output signals of the gas sensor are extracted and assigned with different weights according to their importance by deep learning algorithm during data processing. Afterwards, we have used two prediction methods to verify the accuracy of this method. One is to randomly select part of the measurement data as the test sets, which results in an average relative error of 4%. The other method is using the data of the first two days as the training sets to build the model, which could be used to predict the test sets of the third day and the best average relative error of 3.2% is achieved.
关键词
学校署名
第一
语种
英语
相关链接[Scopus记录]
收录类别
资助项目
Shenzhen Science and Technology Innovation Committee[JCYJ20170412154426330]
WOS研究方向
Engineering ; Science & Technology - Other Topics
WOS类目
Engineering, Electrical & Electronic ; Engineering, Mechanical ; Nanoscience & Nanotechnology
WOS记录号
WOS:000667731600106
EI入藏号
20211410171494
EI主题词
Chemical detection ; Chemical sensors ; Data handling ; Gas detectors ; Gases ; Learning algorithms ; Mechanics ; MEMS
EI分类号
Electric Equipment:704.2 ; Data Processing and Image Processing:723.2 ; Chemistry:801 ; Accidents and Accident Prevention:914.1 ; Mechanics:931.1
Scopus记录号
2-s2.0-85103466158
来源库
Scopus
全文链接https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9375312
引用统计
被引频次[WOS]:6
成果类型会议论文
条目标识符http://sustech.caswiz.com/handle/2SGJ60CL/222725
专题工学院_深港微电子学院
作者单位
Southern University of Science and Technology,School of Microelectronics,Shenzhen,China
第一作者单位深港微电子学院
第一作者的第一单位深港微电子学院
推荐引用方式
GB/T 7714
Hu,Yushen,Tian,Ye,Zhuang,Yi,et al. Rapid Gas Sensing Based on Pulse Heating and Deep Learning[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2021:438-441.
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