霉变小麦的电子鼻区分及其传感器阵列选择优化
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摘要
采用电子鼻区分不同霉变程度的扬麦23号样品,连续检测不同霉变程度小麦样品,并记录检测数据。将检测数据耦合到双稳态随机共振系统,调解系统参数诱发产生共振,依据系统输出信噪比特征值建立小麦霉变程度预测模型。为了提高电子鼻对霉变小麦样品区分效果,进行了电子鼻传感器负荷加载分析,对电子鼻传感器阵列进行了优化研究,结果表明传感器阵列优化可有效提高电子鼻检测小麦霉变程度的准确度。采用华麦6号样品构建验证实验,结果证明所建立的方法具有较好的应用意义,并具有普遍意义上的适用性。
Electronic nose technique was utilized to discriminate Yangmai23 wheat samples in different mildew status. The experiments were continuously measured,and measurement data was recorded. The data was coupled into bistable stochastic resonance. Resonance status was achieved by adjusting system parameters. Output signal-to-noise ratio eigen value was selected to build wheat mildew status predicting model. In order to improve discriminating accuracy,electronic nose sensor array loadings analysis was conducted. Electronic nose gas sensor array optimization effectively improved the detecting accuracy of mildew wheat status prediction. Huamai6 samples were used as validation experiments,and results demonstrated that the developed method presented good application value. This method also has universal applicability.
Electronic nose technique was utilized to discriminate Yangmai23 wheat samples in different mildew status. The experiments were continuously measured,and measurement data was recorded. The data was coupled into bistable stochastic resonance. Resonance status was achieved by adjusting system parameters. Output signal-to-noise ratio eigen value was selected to build wheat mildew status predicting model. In order to improve discriminating accuracy,electronic nose sensor array loadings analysis was conducted. Electronic nose gas sensor array optimization effectively improved the detecting accuracy of mildew wheat status prediction. Huamai6 samples were used as validation experiments,and results demonstrated that the developed method presented good application value. This method also has universal applicability.
引文
[1] Persand K,Dodd G H.Analysis of Discrimination Mechanisms in the Mammalian Olfactory System Using a Model Nose[J].Nature,1982,299(5881):352-355.
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[3] 张红梅,何玉静.电子鼻技术在粮食质量检测中的应用[J].农机化研究,2009,3:181-182.
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[8] 胡卫军,许改霞,王平.电子鼻和电子舌在航天医学检测中的应用[J].国外医学生物医学工程分册,2005,28(4):213-217.
[9] 张红梅,何玉静.电子鼻技术在粮食质量检测中的应用[J].农机化研究,2009(3):181-182.
[10] 徐亚丹,王俊,赵国军.基于电子鼻的对掺假的“伊利”牛奶的检测[J].中国食品学报,2006,6(5):111-118.
[11] Gardner J W,Bartlett P N.A Brief History of Electronic Nose[J].Sensors and Actuators B:Chemical,1994,18(1-3):211-220.
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[13] Magan N,Evans P.Volatiles as an Indicator of Fungal Activity and Differentiation between Species,and the Potential Use of Electronic Nose Technology for Early Detection of Grain Spoilage[J].Journal of Stored Products Research,2000,36(4):319-340.
[14] Balasubramanian S,Panigrahi S,Kottapalli B,et al.Evaluation of an Artifical Oflactrory System for Grain Quality Discrimination[J].LWT-Food Science and Technology,2007,40(10):1815-1825.
[15] 潘天红,陈山,赵德安.电子鼻技术在谷物霉变识别中的应用[J].仪表技术与传感器,2005(3):51-52.
[16] 张红梅,王俊,叶盛,等.电子鼻传感器阵列优化与谷物霉变程度的检测[J].传感技术学报,2007,20(6):1207-1210.
[17] Paolesse R,Alimelli A,Martinlli E,et al.Detection of Fungal Contamination of Cereal Grain Samples by an Electronic Nose[J].Sensors and Actuators B:Chemical,2006,119(2):425-430.
[18] Evans P,Persaud K C,McNeish A S,et al.Evaluation of a Radial Basis Function Neural Networks for the Determination of Wheat Quality from Electronic Nose Data[J].Sensors and Actuators B:Chemical,2000,69(3):348-358.
[19] Abramson D,Hulasare R,York R K,et al.Mycotoxins,Ergosterol,and Odor Volatiles in Durum Wheat During Granary Stroage at 16% and 20% Moisture Content[J].Journal of Storaged Products Research,2005,41(1):61-76.
[20] Gammaitoni L,Hanggi P.Stochastic Resonance[J].Reviews of Modern Physics,1998,71(1):223-287.郑豪男(1998-),男,浙江温州人,主要从事计算机与物联网领域的科研学习工作,zx874561@126.com;李剑(1981-),男,浙江瑞安人,副教授,主要研究方向为智能检测、机器学习。先后承担浙江省自然科学基金、浙江省公益项目等多项科研项目,已发表论文十余篇,多为SCI、EI收录。lijian0120@foxmail.com。
[2] 王肇慈,孙明.国内外粮食储藏品质评价与技术状况[J].南京经济学院学报,1997(4):64-66.
[3] 张红梅,何玉静.电子鼻技术在粮食质量检测中的应用[J].农机化研究,2009,3:181-182.
[4] 赵玉霞.粮食储藏中粮堆温度与大气温度之关系[J].粮油食品科技,2002,10(6):1-5.
[5] 任如杉,万艳芬,胡雅丽,等.粮情测控系统在粮食储藏中的应用[J].粮食流通技术,2002(4):36-39.
[6] 杜锋,雷鸣.电子鼻及其在食品工业中的应用[J].食品科学,2003,24(5):161-163.
[7] Julian W Gardner,Hyun Woo Shin,Evor L Hines.An Electronic Nose System to Diagnose Illness[J].Sensors and Actuators B,2000,70(1-3):19-24.
[8] 胡卫军,许改霞,王平.电子鼻和电子舌在航天医学检测中的应用[J].国外医学生物医学工程分册,2005,28(4):213-217.
[9] 张红梅,何玉静.电子鼻技术在粮食质量检测中的应用[J].农机化研究,2009(3):181-182.
[10] 徐亚丹,王俊,赵国军.基于电子鼻的对掺假的“伊利”牛奶的检测[J].中国食品学报,2006,6(5):111-118.
[11] Gardner J W,Bartlett P N.A Brief History of Electronic Nose[J].Sensors and Actuators B:Chemical,1994,18(1-3):211-220.
[12] Jonsson A,Winquist F,Schnurer J,et al.Electronic Nose for Microbial Quality Classification of Grains[J].International Journal of Food Microbiology,1997,35:187-193.
[13] Magan N,Evans P.Volatiles as an Indicator of Fungal Activity and Differentiation between Species,and the Potential Use of Electronic Nose Technology for Early Detection of Grain Spoilage[J].Journal of Stored Products Research,2000,36(4):319-340.
[14] Balasubramanian S,Panigrahi S,Kottapalli B,et al.Evaluation of an Artifical Oflactrory System for Grain Quality Discrimination[J].LWT-Food Science and Technology,2007,40(10):1815-1825.
[15] 潘天红,陈山,赵德安.电子鼻技术在谷物霉变识别中的应用[J].仪表技术与传感器,2005(3):51-52.
[16] 张红梅,王俊,叶盛,等.电子鼻传感器阵列优化与谷物霉变程度的检测[J].传感技术学报,2007,20(6):1207-1210.
[17] Paolesse R,Alimelli A,Martinlli E,et al.Detection of Fungal Contamination of Cereal Grain Samples by an Electronic Nose[J].Sensors and Actuators B:Chemical,2006,119(2):425-430.
[18] Evans P,Persaud K C,McNeish A S,et al.Evaluation of a Radial Basis Function Neural Networks for the Determination of Wheat Quality from Electronic Nose Data[J].Sensors and Actuators B:Chemical,2000,69(3):348-358.
[19] Abramson D,Hulasare R,York R K,et al.Mycotoxins,Ergosterol,and Odor Volatiles in Durum Wheat During Granary Stroage at 16% and 20% Moisture Content[J].Journal of Storaged Products Research,2005,41(1):61-76.
[20] Gammaitoni L,Hanggi P.Stochastic Resonance[J].Reviews of Modern Physics,1998,71(1):223-287.郑豪男(1998-),男,浙江温州人,主要从事计算机与物联网领域的科研学习工作,zx874561@126.com;李剑(1981-),男,浙江瑞安人,副教授,主要研究方向为智能检测、机器学习。先后承担浙江省自然科学基金、浙江省公益项目等多项科研项目,已发表论文十余篇,多为SCI、EI收录。lijian0120@foxmail.com。