吉林大学学报(工学版) ›› 2020, Vol. 50 ›› Issue (1): 382-388.doi: 10.13229/j.cnki.jdxbgxb20181069

• 农业工程·仿生工程 • 上一篇    

基于仿生鼻腔优化的油气检测方法与实验新技术

翁小辉1,2,3(),孙友宏4,张书军1,2,5,谢军1,2,常志勇1,2,4()   

  1. 1. 吉林大学 工程仿生教育部重点实验室, 长春 130022
    2. 吉林大学 生物与农业工程学院, 长春 130022
    3. 吉林大学 机械与航空航天工程学院, 长春 130022
    4. 吉林大学 油页岩地下原位转化与钻采技术国家地方联合工程实验室, 长春 130021
    5. 格罗斯特郡大学 计算机与技术学院, 公园区, 切尔滕纳姆 GL50 2RH, 英国
  • 收稿日期:2018-10-09 出版日期:2020-01-01 发布日期:2020-02-06
  • 通讯作者: 常志勇 E-mail:wengxiaohui@jlu.edu.cn;zychang@jlu.edu.cn
  • 作者简介:翁小辉（1986-），男，工程师，博士研究生. 研究方向：仿生气体检测.E-mail:wengxiaohui@jlu.edu.cn
  • 基金资助:
    国家自然科学基金项目(51875245);吉林省科技发展计划项目(20180201038GX);吉林省教育厅“十三五”科学技术项目(JJKH20180083KJ);吉林省产业技术研究与开发专项项目(2019C039-5)

Oil and gas detection method and experimental new technology based on bionic nasal chamber optimization

Xiao-hui WENG1,2,3(),You-hong SUN4,Shu-jun ZHANG1,2,5,Jun XIE1,2,Zhi-yong CHANG1,2,4()   

  1. 1. Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China
    2. College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
    3. College of Mechanical and Aerospace Engineering, Jilin University, Changchun 130022, China
    4. National?Local Joint Engineering Laboratory of In?situ Conversion, Drilling and Exploitation Technology for Oil Shale, Jilin University, Changchun 130021, China
    5. School of Computing and Technology, University of Gloucestershire, The Park, Cheltenham GL50 2RH, UK
  • Received:2018-10-09 Online:2020-01-01 Published:2020-02-06
  • Contact: Zhi-yong CHANG E-mail:wengxiaohui@jlu.edu.cn;zychang@jlu.edu.cn

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摘要：

设计了一种适用于油气检测的小型仿生电子鼻系统。通过分析狗鼻腔鼻流道内部的结构特征及流场分布情况，提出了模拟狗鼻腔的仿生电子鼻腔室，解决油气检测装置尺寸臃肿、操作不灵活等问题。使用3D打印腔室样件进行烃类混合气体检测对比试验，采用十折交叉验证法比较随机森林、朴素贝叶斯、极限学习机和支持向量机算法识别效果。结果表明，优化检测腔室后的电子鼻系统灵敏度较普通腔室电子鼻系统有明显提高，识别率提高5.5%，构建的三维仿真腔室CFD分析结果也验证了本文仿生腔室的有效性。

关键词: 仪器仪表技术, 电子鼻, 狗鼻腔, 仿生设计, 油气检测, 传感器

Abstract:

A small bionic electronic nose system for oil and gas detection was designed. By analyzing the structural characteristics and flow field distribution inside the nasal passage of the dog's nasal chamber, an optimized bionic electronic nasal chamber simulating the nasal chamber of the dog was proposed, which effectively solved the problems of bloated and inflexible operation of the oil and gas detection device. The 3-D printed chamber sample was used to evaluate the detection effect of hydrocarbon mixed gas. The 10-fold cross-validation method was used to compare the recognition effects of random forest, naive Bayes, extreme learning machine and support vector machine algorithms. The results show that the sensitivity of the electronic nose system after optimizing the detection chamber is obviously higher than that of the ordinary chamber electronic nose system, and the recognition rate is increased by 5.5%. The CFD analysis results of the 3D simulation chamber also verify the validity of the bionic nasal chamber.

Key words: technology of instruments and meter, electronic nose, dog nasal chamber, bionic design, oil and gas detection, sensor

中图分类号: 

  • TH763

表1

普通腔室设计的因素水平表"

水 平 因 素
A/mm B/mm C/（m?s-1） D/s
1 20 75 0.5 60
2 30 85 0.8 90
3 40 95 1.2 120
离差平方和 0.183 0.052 0.101 0.001
均方 0.115 0.061 0.072 0.021
F 4.241 1.034 3.124 0.021

图1

普通电子鼻腔室a结构示意图"

图2

狗鼻腔Fluent模型吸气和呼气流体动力学显示图"

图3

仿生电子鼻腔室b结构示意图"

表2

仿生腔室设计因素水平表"

水平 因素
E F G H I
1 30 10 10 20 10
2 40 15 15 30 15
3 50 20 20 40 20
离差平方和 0.002 0.073 0.192 0.012 0.051
均方 0.005 0.063 0.131 0.011 0.026
F 0.014 2.245 4.713 0.021 1.134

图4

3D打印电子鼻"

表3

样本气体各组分浓度配比"

种 类 体积浓度/%
甲烷 乙烷 二氧化碳 氮气
1 1 1 8 90
2 2 1.5 6.5 90
3 3 2 5 90

图5

电子鼻系统工作流程图"

图6

电子鼻系统组成图"

图7

同一传感器在不同腔室中的响应图"

图8

不同算法识别率结果比较柱状图"

图9

传感器表面的漩涡强度比较图"

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