TY - JOUR
T1 - 新型冠状病毒样本查杀一体化系统关键技术
AU - Zhang, Dongheyu
AU - Guo, Yuntao
AU - Zhang, Liyang
AU - Li, Shenwei
AU - Wang, Yao
AU - Liu, Peipei
AU - Wang, Hongqiu
AU - Wu, Yue
AU - He, Yuping
AU - Zhou, Qun
AU - Luo, Haiyun
N1 - Publisher Copyright:
© 2022 Chin. Soc. for Elec. Eng.
PY - 2022/6/20
Y1 - 2022/6/20
N2 - Coronavirus Disease 2019 is an acute respiratory infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2, which has posed a major threat to world economic development and people's health and security. In view of the emergence of virus variants, the difficulty of prevention and control is constantly escalating, and rapid, simple and large-scale detection methods play a key role in epidemic control. Based on Fourier transform infrared spectroscopy detection technology, pattern recognition and plasma disinfection technology, this paper developed a new integrated system for the detection and disinfection of pathogens, and preliminarily tested the effectiveness of the system. In terms of 'detection', the data scale was expanded from 115 to 857 cases. Recognition algorithms including partial least squares classification and convolutional neural network were used to establish classification models for the positive, health control and interference samples, and the prediction accuracy could reach 91.97% and 98.29% respectively. In terms of 'disinfection',to reduce the safety risk of the operation safety, a sample drying and disinfection module and a flexible disinfection film were developed based on the plasma disinfection technology, which was used to protect the key positions of the instruments. The disinfection rate of E. coli in both modules could be higher than 99.9%, in line with the relevant provisions. In summary, the two parts of the spectroscopy detection process of Coronavirus Disease 2019 samples have been innovated. For the first time, the combination of 'detection' and 'disinfection' has been realized, which is conducive to the application and promotion of spectroscopy detection methods.
AB - Coronavirus Disease 2019 is an acute respiratory infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2, which has posed a major threat to world economic development and people's health and security. In view of the emergence of virus variants, the difficulty of prevention and control is constantly escalating, and rapid, simple and large-scale detection methods play a key role in epidemic control. Based on Fourier transform infrared spectroscopy detection technology, pattern recognition and plasma disinfection technology, this paper developed a new integrated system for the detection and disinfection of pathogens, and preliminarily tested the effectiveness of the system. In terms of 'detection', the data scale was expanded from 115 to 857 cases. Recognition algorithms including partial least squares classification and convolutional neural network were used to establish classification models for the positive, health control and interference samples, and the prediction accuracy could reach 91.97% and 98.29% respectively. In terms of 'disinfection',to reduce the safety risk of the operation safety, a sample drying and disinfection module and a flexible disinfection film were developed based on the plasma disinfection technology, which was used to protect the key positions of the instruments. The disinfection rate of E. coli in both modules could be higher than 99.9%, in line with the relevant provisions. In summary, the two parts of the spectroscopy detection process of Coronavirus Disease 2019 samples have been innovated. For the first time, the combination of 'detection' and 'disinfection' has been realized, which is conducive to the application and promotion of spectroscopy detection methods.
KW - Coronavirus Disease 2019
KW - Disinfection
KW - Fourier transform- infrared spectroscopy
KW - Pattern recognition
KW - Surface dielectric barrier discharge
UR - http://www.scopus.com/inward/record.url?scp=85132518046&partnerID=8YFLogxK
U2 - 10.13334/j.0258-8013.pcsee.220321
DO - 10.13334/j.0258-8013.pcsee.220321
M3 - 文章
AN - SCOPUS:85132518046
SN - 0258-8013
VL - 42
SP - 4623
EP - 4632
JO - Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering
JF - Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering
IS - 12
ER -