秸秆和煤混燃物中秸秆含量近红外光谱测定  

Quantitative Analysis of Straw Content in Co-firing Biomass-coal Blends by Near Infrared Spectroscopy

作　　者：贺城[1] 杨增玲[1] 黄光群[1] 廖娜[1] 韩鲁佳[1] 

机构地区：[1]中国农业大学工学院,北京100083

出　　处：《农业机械学报》2011年第10期125-128,104,共5页Transactions of the Chinese Society for Agricultural Machinery

基　　金：公益性行业(农业)科研专项经费资助项目(201003063)

摘　　要：实现秸秆和煤混燃物中秸秆含量快速检测对制定生物质混燃发电补贴方法具有重要意义。收集我国不同地区、不同品种秸秆样品81个,煤样品9个,样品粉碎后,按不同秸秆质量分数(1%～30%)制备样品90个,其中60个为校正集3,0个为独立验证集。用傅里叶变换近红外光谱仪进行光谱扫描,分别采用间隔偏最小二乘法(iPLS)和遗传算法(GA)进行波长选择,用偏最小二乘法(PLS)建立定量分析模型。研究结果表明,采用GA-PLS方法,最优模型建模数据点从3 001个减少到33个,独立验证集决定系数为0.89,预测标准差为2.87%,相对分析误差为3.06。近红外光谱技术结合GA-PLS建模用于快速检测秸秆和煤混燃物中秸秆含量具有可行性。It is important to realize rapid detection of straw content in co-firing biomass-coal blends for drawing up reasonable precept about biomass co-firing power generation subsidy.The original samples were consisted of 81 straws and 9 coals collected from different regions and different varieties in China.90 blends samples of coal and straw（1%～30%） were prepared after comminution and separated into a calibration set（60 samples） and an independent validation set（30 samples）.Spectra were scanned by FT-NIR spectrometer.The interval partial least squares（iPLS） and the genetic algorithm（GA） were used for wavelength selection.Quantitative analysis models for straw content were established by partial least squares（PLS）.The results showed that data points for modelling decreased from 3 001 to 33,determination coefficient,standard deviation of prediction（SEP） and ratio of performance to standard deviation（RPD） in validation were 0.89,2.87% and 3.06 by GA-PLS method,respectively.It is concluded that NIRS with GA-PLS was feasible for fast quantitative analysis of the straw content in co-firing biomass-coal blends.

关 键 词：混燃 秸秆 煤 近红外光谱 遗传算法 

分 类 号：S216.2[农业科学—农业机械化工程]