基于RBF人工神经网络的SAW气体传感器检测系统的实验分析-临床检验诊断学专业论文.docxVIP

第三军医大学硕士学位论文  PAGE 10 缩略语表 英文缩写 ANNs英文全称 Artificial Neural Networks中文全称 人工神经网络ANOVAanalysis of variance方差分析BPerror-Back Propagation net work误差反向传播神经网络CIcredibility interval可信区间cmcentimeter厘米dBdecibel分贝FE-SEMField Emission Scanning Electron Microscopes场发射扫描电子显微镜FT-IRFourier Transform Infrared Spectroscopy傅里叶变换红外光谱仪GCGas Chromatography气相色谱法GHzgigahertz千兆赫g/Lgram per litre克每升hhour小时hEAThuman Exhaled Air Test人体呼出气体试验HPMChydroxypropyl methylcellulose羟丙基甲基纤维素IDTInter Digital Transducer叉指换能器kVkilovolt千伏L/minlitre per minute升/分钟L-BLangmuir-Blodgett朗缪尔-布洛杰特Mmole per litre摩尔每升MHzmegahertz兆赫mlmilliliter毫升mMmilli mole per litre毫摩尔每升MSMass Spectrography质谱法m/smeters per second米每秒NINational Instruments美国国家仪器公司nmnanometer纳米 PaPascal帕斯卡PAApolyacrylic acid聚丙烯酸PCAPrincipal Component Analysis主成分分析PLSPartial Least Squares偏最小二乘法P4VPpoly(4-vinylphenol)聚 4 乙基苯酚均聚物PAN1-(2-pyridylazo)-2-naphthol1-(2-吡啶基偶氮)-2-萘酚PANIpolyaniline聚苯胺ppmpart per million百万分之RBF-ANNRadial Basis Function-Artificial Neural Networks径向基函数-人工神经网络 Experimental study of SAW gas sensor system based on Radial Basis Function- Artificial Neural Networks Abstract Background： Human exhaled air test (hEAT) is a new field in clinical laboratory medicine, due to its scathelessness, painlessness and easy acceptability for the patients. Surface Acoustic Wave (SAW) gas sensors will be an ideal candidate method for hEAT, for their outstanding capability of high sensitivity and real-time detection. Objective： To establish a SAW gas sensor array for hEAT, and explore the ability of the sensors for ammonia and acetone gases identification with Radial Basis Function-Artificial Neural Networks (RBF-ANN) arithmetic. Methods： Multiple channel dual-resonance SAW transducers were developed. Several organic polymer, conductive polymer and metal-oxide materials were selected and prepared as gas sensitive