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猪舍有害气体NH_3、H_2S的电子鼻定量识别 被引量:15

Quantitative identification of pernicious gases NH_3 and H_2S in piggery using electronic nose
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摘要 为准确、快速地测定南方猪舍的主要有害气体NH3、H2S,建立了电子鼻系统。在实验室中采用静态配气法配制各种浓度的气体,将快速独立成分分析与径向基神经网络两种方法相结合,对6.95~69.53mg/m3浓度范围内的H2S单一气体以及H2S与NH3组成的混合气体进行定量识别,平均识别精度分别达到99.1%和90.97%。结果表明在基于电子鼻的猪舍NH3、H2S气体定量识别中,采用该种方法具有良好的效果。 In order to establish an accurate and rapid method for determination of the main pernicious gases NH3 and H2S in the piggery in South China,an electronic nose system was built.Gas samples were prepared with static volumetric method,and the fast independent component analysis(FICA)and the radial basis function neural networks(RBFNN)were applied to identify H2S gas alone and the mixed gas of H2S and NH3 between the range of 6.95-69.53 mg/m^3.The average identification accuracy of single gas reached 99.1%,while the average identification accuracy of mixed gas was 90.97%.The results show that good effect was obtained by applying FICA and RBFNN methods to quantitative identification of gases NH3 and H2S in piggery based on electronic nose system.
出处 《农业工程学报》 EI CAS CSCD 北大核心 2009年第7期153-157,共5页 Transactions of the Chinese Society of Agricultural Engineering
基金 广东省科技计划攻关项目(2007A020300010-7) 华南农业大学校长基金项目(2007X024)
关键词 气体识别 径向基神经网络 传感器 电子鼻 猪舍 快速独立成分分析 gas identification radial basis function neural networks sensors electronic nose piggery fast independent component analysis
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参考文献14

  • 1GB/T18407.3-2001农产品安全质量无公害畜禽肉产地环境要求[S].2001.
  • 2陈伯华.猪对环境的要求[J].山西农机,2004(2):38-38. 被引量:6
  • 3朱伟兴,刁统山,葛广军.规模化畜禽养殖场气味检测及控制[J].安徽农业科学,2006,34(6):1207-1208. 被引量:6
  • 4Ishida H, Kaneko S, Tsujita W, et al. Improvement of measurement accuracy in environmental monitoring system based on semiconductor gas sensor[J]. Transactions of the Institute of Electrical Engineers of Japan, 2005, 125(6): 245 -52.
  • 5张琳,邵晟宇,杨柳,董晓强,丁学全.红外光谱法气体定量分析研究进展[J].分析仪器,2009(2):6-9. 被引量:18
  • 6Yang Ziyin, Fang Dong, Shimizu K, et al. Identification of coumarin-enriched Japanese green teas and their particular flavor using electronic nose[J]. Journal of Food Engineering, 2009, 92(3): 312-316.
  • 7周亦斌,王俊.基于电子鼻的番茄成熟度及贮藏时间评价的研究[J].农业工程学报,2005,21(4):113-117. 被引量:77
  • 8Tudu Bipan, Jana Arun, Metla Animesh, et al. Electronic nose for black tea quality evaluation by an incremental RBF network[J]. Sensors and Actuators, 2009, 138(1): 90-95.
  • 9Ampuero S, Bosset J O. The electronic nose applied to dairy products: a review[J]. Sensors and Actuators B, 2003: 1-12.
  • 10Pan Leilei, Simon X. Yang. A new intelligent electronic nose system for measuring and analyzing livestock and poultry farm odors[J]. Environ Monit Assess, 2007.

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