[2018-Vol.15-Issue 3]Bionic Optimization Design of Electronic Nose Chamber for Oil and Gas Detection
Time: 2018-05-12 21:43  Click:326
Journal of Bionic Engineering
 
Volume 15, Issue 3, May 2018, Pages  533-544.
 
Zhiyong Chang1,2,3, Youhong Sun3,4*, Yuchen Zhang1,2, Yanli Gao5, Xiaohui Weng2,6, Donghui Chen1,2, Liewe David7, Jun Xie1,2,8
1. Key Lab of Advanced Technologies of Materials, Ministry of Education, School of Materials Science and Engineering, Southwest Jiaotong University, Chengdu 610031, China
2. Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China
3. National-Local Joint Engineering Laboratory of In-situ Conversion, Drilling and Exploitation Technology for Oil Shale, Jilin University, Changchun 130021, China
4. College of Construction Engineering, Jilin University, Changchun 130022, China
5. Clinical Medicine, Bethune First Hospital of Jilin University, Changchun 130021,China
6. College of Mechanical Science and Engineering, Jilin University, Changchun 130022, China
7. School of Computing and Technology, the University of Gloucestershire, The Park, Cheltenham GL50 2RH, UK
8. Air Combat Service Academy, Air Force Aviation University, Changchun 130021, China
 
Abstract  In this paper, a miniaturized bionic electronic nose system is developed in order to solve the problems arising in oil and gas detection for large size and inflexible operation in downhole. The bionic electronic nose chamber is designed by mimicking human nasal turbinate structure, V-groove structure on shark skin surface and flow field distribution around skin surface. The sensitivity of the bionic electronic nose system is investigated through experimentation. Radial Basis Function (RBF) and Support Vector Machines (SVM) of 10-fold cross validation are used to compare the recognition performance of the bionic electronic nose system and common one. The results show that the sensitivity of the bionic electronic nose system with bionic composite chamber (chamber B) is significantly improved compared with that with common chamber (chamber A). The recognition rate of chamber B is 4.27% higher than that of chamber A for the RBF algorithm, while for the SVM algorithm, the recognition rate of chamber B is 5.69% higher than that of chamber A. The three-dimensional simulation model of the chamber is built and verified by Computational Fluid Dynamics (CFD) simulation analysis. The number of vortices in chamber B is fewer than that in chamber A. The airflow velocity near the sensors inside chamber B is slower than that inside chamber A. The vortex intensity near the sensors in chamber B is 2.27 times as much as that in chamber A, which facilitates gas molecules to fully contact with the sensor surface and increases the intensity of sensor signal, and the contact strength and time between odorant molecules and sensor surface. Based on the theoretical investigation and test validation, it is believed that the proposed bionic electronic nose system with bionic composite chamber has potential for oil and gas detection in downhole.
 
Key words: electronic nose      bionic chamber      sensors      oil gas detection     

Full text is available at   https://link.springer.com/article/10.1007/s42235-018-0044-6

Home| News| Research Progress| Events & Meetings| Resources| Membership| Contact Privacy Policy Terms of use

Address: 1201 Administrative Building, Jilin University, 2699 Qianjin Street, Changchun 130012, P. R. China

Copyright © 2018 International Society of Bionic Engineering All Rights Reserved