基于气致变色气体传感器的数据采集与图像处理研究
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摘要
可视嗅觉的气致变色传感系统是新一代的电子鼻领域发展上的突破,近年来发展迅速。气致变色传感器有两个模块组成,即前端的敏感单元模块与后端的气敏图像采集与识别模块。早在上个世纪80年代,英国科学家就提出了可以通过气体对敏感材料有光谱响应的显色性来进行混合气体的分类鉴别。2000年,伊利诺大学的Kenneth S. Suslick教授等人发明了利用金属卟啉类配合物合成的敏感单元,对气体进行显色实验,并获得了良好的气体检测效果;2006年,我国西北工业大学的郭冬敏等人在对卟啉基敏感单元进行了大量的气敏实验的基础上,也对后端的图像采集与处理进行了开拓性的研究。近几年,电子科技大学电子薄膜与集成器件国家重点实验室也建立了气致变色传感器研究项目组,分别对前端与后端进行了系统的研究,并取得了一些成果,对某些气体得到了很好的检测效果。
本文在对前端四苯基金属卟啉与钛菁锌材料的敏感单元进行大量气体检测实验的基础上,重点对后端的图像采集与处理模块进行了开发与研究,主要工作如下:
1在气敏显色实验与原有16种气体数据库的基础上,通过气敏单元的制备、气敏显色的实验,以及嵌入式图像采集模块的开发,采集并扩充了14种气体检测数据库,实现了更多气体的定性检测效果,14种新扩充气体的检测率达100%,使系统总的可识别气体达到30种。
2基于ARM-Linux,体积小、效率高、价格低廉,能够很好的适应特定检测环境的限制的优点,采用从嵌入式Linux内核的移植入手,通过内核配置,按键驱动设计,按键响应控制程序的实现,LCD显示应用程序配置的方法,实现了具有实时图像采集与显示功能的嵌入式图像采集系统。
3将基于MATLAB的气敏图像数据库更新为VC++的OpenCV图像处理类库,改善并优化了图像识别的开发平台,使其对嵌入式系统具有了更好的可移植性;对采集到气敏特征图像进行了预处理、边缘检测以及特征提取与对比的图像识别模块,实现了数据库中所有扩充气体的定性识别。
4通过对1ml,2ml,3ml挥发性甲基丙烯酸甲酯气体进行气敏实验,对甲基丙烯酸甲酯的有机挥发物的定量显色实验做了试探性的研究,进一步的图像识别需要在以后的工作中继续完善。
With rapid development, visible gas-induced smelling sensor system, which is a breakthrough of new generation electronic nose region, is composed of two modules, which are front sensitive color-changing arrays and back image-collecting and recognition system. In last century, gas recognition theory based on gas-induced color-changing effect was proposed by British scientists. In 2000, an invention that sensor arrays of metal porphyris by Professor Kenneth S. Suslick and their work-team was made to apply to recognizing gases and the result is favorable. In 2006, Guo Dongmin et al of Northwestern Polytechnical University did a pioneering research on back sensitive image-collecting and recgnition on the basis of a massive color-changing experiments. In recently years, a gas-induced color-changing sensor project team was gradually established in our national key laboratory. Some systematic researches were carried out on both front and back-end systems. There are some very good testing results on some gases. The recognition rate is 100%.
In this paper, focusing on back-end image acquisition and processing based on massive experiments of front gas detection unit of tetraphenyl porphyrin zinc and titanium material Jing. Main tasks are as follow:
1 14 types of gases database were expanded on the basis of the original color of 16 gas database and gas experiments, by sensing element through the preparation, sensing the color of the experiments, and development of embedded image acquisition module. Recognition rate of the newly added 14 types of gases is 100%. Identifiable gases of the system are totally 30.
2 ARM-Linux, having the advantage of small size, high efficiency, low prices, can well adapt to specific testing surroundings with good performance. Adopting embedded Linux kernel configuration, button driver design, button-response programming and LCD display configuration method, a real-time image acquisition and display system was realized.
3 The OpenCV VC + + based preprocessing gas sensing characteristics of the collected images, edge detection, feature extraction and comparison of image recognition realized all the qualitative expanding database of the gas recognition, recognition rate is 100%.
4 Tentative quantitative identification of volatile organic compounds of methyl methacrylate was made by 1ml, 2ml, 3ml MMA volatile gas sensing experiments. But quantitative Image identification needs for further work in the future to improve.
本文在对前端四苯基金属卟啉与钛菁锌材料的敏感单元进行大量气体检测实验的基础上,重点对后端的图像采集与处理模块进行了开发与研究,主要工作如下:
1在气敏显色实验与原有16种气体数据库的基础上,通过气敏单元的制备、气敏显色的实验,以及嵌入式图像采集模块的开发,采集并扩充了14种气体检测数据库,实现了更多气体的定性检测效果,14种新扩充气体的检测率达100%,使系统总的可识别气体达到30种。
2基于ARM-Linux,体积小、效率高、价格低廉,能够很好的适应特定检测环境的限制的优点,采用从嵌入式Linux内核的移植入手,通过内核配置,按键驱动设计,按键响应控制程序的实现,LCD显示应用程序配置的方法,实现了具有实时图像采集与显示功能的嵌入式图像采集系统。
3将基于MATLAB的气敏图像数据库更新为VC++的OpenCV图像处理类库,改善并优化了图像识别的开发平台,使其对嵌入式系统具有了更好的可移植性;对采集到气敏特征图像进行了预处理、边缘检测以及特征提取与对比的图像识别模块,实现了数据库中所有扩充气体的定性识别。
4通过对1ml,2ml,3ml挥发性甲基丙烯酸甲酯气体进行气敏实验,对甲基丙烯酸甲酯的有机挥发物的定量显色实验做了试探性的研究,进一步的图像识别需要在以后的工作中继续完善。
With rapid development, visible gas-induced smelling sensor system, which is a breakthrough of new generation electronic nose region, is composed of two modules, which are front sensitive color-changing arrays and back image-collecting and recognition system. In last century, gas recognition theory based on gas-induced color-changing effect was proposed by British scientists. In 2000, an invention that sensor arrays of metal porphyris by Professor Kenneth S. Suslick and their work-team was made to apply to recognizing gases and the result is favorable. In 2006, Guo Dongmin et al of Northwestern Polytechnical University did a pioneering research on back sensitive image-collecting and recgnition on the basis of a massive color-changing experiments. In recently years, a gas-induced color-changing sensor project team was gradually established in our national key laboratory. Some systematic researches were carried out on both front and back-end systems. There are some very good testing results on some gases. The recognition rate is 100%.
In this paper, focusing on back-end image acquisition and processing based on massive experiments of front gas detection unit of tetraphenyl porphyrin zinc and titanium material Jing. Main tasks are as follow:
1 14 types of gases database were expanded on the basis of the original color of 16 gas database and gas experiments, by sensing element through the preparation, sensing the color of the experiments, and development of embedded image acquisition module. Recognition rate of the newly added 14 types of gases is 100%. Identifiable gases of the system are totally 30.
2 ARM-Linux, having the advantage of small size, high efficiency, low prices, can well adapt to specific testing surroundings with good performance. Adopting embedded Linux kernel configuration, button driver design, button-response programming and LCD display configuration method, a real-time image acquisition and display system was realized.
3 The OpenCV VC + + based preprocessing gas sensing characteristics of the collected images, edge detection, feature extraction and comparison of image recognition realized all the qualitative expanding database of the gas recognition, recognition rate is 100%.
4 Tentative quantitative identification of volatile organic compounds of methyl methacrylate was made by 1ml, 2ml, 3ml MMA volatile gas sensing experiments. But quantitative Image identification needs for further work in the future to improve.
引文
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[2] J. R. Stetter, W. R. Penrose. Understanding chemical sensors and chemical sensor arrays (electronic noses) past, present, and future. Sensors Update, 2002, 10, 189-229
[3] R.H. Tredgold, M.C.J. Young, P. Hodge. A. Hoorfar, Institute. Electron. Eng. PartI, 1985, 132,151-156
[4] M. B. Grieve, A.J. Hudson, T. Richardson, R.A.W. Johnstone, A.J.F.N. Sobral and A. M. d’A. Rocha Gonsalves, Thin Solid Films. 1994 243, 581-586
[5]张红梅,何玉静.电子鼻技术的历史,研究现状及发展前景[J].科技信息, 2008, 27, 12-13
[6]李仁杰.酞菁类化合物的设计合成及结构与性质研究: [博士学位论文].济南:山东大学.2008,8-83
[7] J. W. Gardner, P. N. Bartlett. Electronic Noses: Principles and Applications. Oxford University Press: New York, 1999, 30-35
[8] Cyranose 320 for Cyrano Sciences Portable electronic odor detector (Internet)
[9] S. Panigrahi, et al. Neural-network-integrated electronic nose system for identification of spoiled beef[J]. LWT. 2006, 39: 135-145
[10] http : //www.cycnet.com/encyclopedia/exploration/events/00712018.htm
[11]陈长庆,胡明,吴霞宛.气敏传感器的发展.材料导报, 2003, 17, 33-35
[12] K. S. Suslick, N. A. Rakow, A. Sen. Colorimetric artificial nose having an array of dyes and method for artificial olfaction. Shape Selective Sensors U.S. Patent 6,495,102 B1, Dec. 2002
[13]张彤,徐宝琨,董艳等.集成一体化多功能敏感元件的设计与研制术[会议文献].第八届全国敏感元件与传感器学术会议论文集, 2003, 843-845
[14]唐向阳,张勇,丁锐等.电子鼻技术的发展及展望,机电一体化.2006, 4, 11-12
[15]侯长军,段玉娟,霍丹群等.卟啉传感器检测挥发性有机化合物的研究进展,传感器与微系统. 2008, 27(7), 2-3
[16]左国防.卟啉自组装膜电化学: [博士学位论文].兰州:西北师范大学, 2007, 16-18
[17]彭亦如,黄风华.四苯甲氧基酞菁锌配合物的合成与表征.海峡药学, 2003, 15(2), 53
[18]郭冬敏,杨建华,李秉玺.可视嗅觉传感器阵列研究及图像分析.传感技术学报,2005(18), 795-797
[19]龙菁,徐建华,邢亚第等.金属卟啉LB膜的气敏特性研究.材料导报, 2009(11), 3-5
[20] http://baike.baidu.com/view/7671.htm
[21]戴军,符史流,赵韦人. BMP图像数据提取在分析测试中的应用.计算机与应用化学, 2006(3).889-890
[22]何伟.数字图象处理在视频分割技术中的应用研究[硕士论文].成都:电子科技大学, 1994, 110-115
[23]夏德深,傅得胜.现代图像处理技术与应用.南京:东南大学出版社, 2001, 150-157
[24]杨淑莹.图像模式识别-VC++技术实现[M].北京:清华大学出版社, 2005, 235-351
[25] Persaud K,Dodd G.Analysis of discrimination mechanisms in the mammalian olfactory system using a model nose.Nature, 1982,299:352-355
[26]郭冬敏.基于可视嗅觉的电子鼻技术研究与实现[D].西安:西北工业大学, 2006, 23-26
[27]李宗海,陈蜀宇,李海伟.嵌入式Linux系统在ARM平台上的构建.计算机系统应用2010, 19(11): 25-31
[28]韦山东.嵌入式Linux应用开发完全手册.北京:人民邮电出版社, 2008, 50-75
[29]胥静.嵌入式系统设计与开发实例详解(基于ARM的应用).北京:北京航空航天大学出版社, 2005, 107-130
[30]梁泉.嵌入式Linux系统移植及应用开发技术研究[硕士学位论文].成都:电子科技大学, 2006, 45-48
[31]朱雄辉.嵌入式Linux的研究及其设备驱动程序的开发[硕士学位论文].西安:西安电子科技大学. 2002, 31-33
[32]吴菲.基于ARM的嵌入式linux内核裁剪及移植[J].机械管理开发. 2010, 25(6): 183-186
[33]姚娅川.嵌入式图像实时采集系统设计.半导体技术. 2010, 35(7) :720-721
[34]孙琼.嵌入式Linux应用程序开发详解[M].北京:人民邮电出版社. 2006, 14-27
[35]熊茂华,谢建华,熊昕.嵌入式Linux C语言应用程序设计与实践[M].北京:清华大学出版社. 2010, 55-68
[36] http://baike.baidu.com/view/14685.htm
[37]张洪波.模式识别及其在计算机视觉中的实现[硕士学位论文].山东:青岛科技大学. 2009, 60-61
[38] Theodoridis, Koutroumbas. Pattern Recognition.America: Academic Press.2008, 15-25
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