煤粉发热量近红外光谱检测的预处理方法研究  

Research on Preprocessing Method of Near-Infrared Spectroscopy Detection of Coal Ash Calorific Value

作　　者：张林[1] 陆辉山[1] 闫宏伟[1] 高强[1] 王福杰[1] 宋海燕[2] 

机构地区：[1]中北大学机械与动力工程学院,山西太原030051 [2]山西农业大学工程技术学院,山西太原030801

出　　处：《光谱学与光谱分析》2013年第12期3212-3215,共4页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(41201294);山西省青年科技基金项目(2009021019-3);江苏省农产品物理加工重点实验室开放基金项目(JAPP2012-2)资助

摘　　要：煤炭的发热量是评价煤炭品质的重要指标。首先对比分析了平滑处理、微分处理、多元散射校正(MSC)以及标准归一化(SNV)等光谱与处理方法在改善煤粉近红外漫反射光谱信噪比的效果,然后利用偏最小二乘法(PLS)和主成分分析方法(PCR)分别对采用每种预处理方法处理后的光谱建立煤粉发热量模型,发现采用5点平滑处理、多元散射校正和标准归一化处理可使模型的性能有较明显的改观,5点平滑效果最好,相关系数、校正标准差和预测标准差分别为:0.989 9,0.0004 9和0.0005 2,采用25点平滑处理产生了过平滑现象,导致模型的性能变坏,采用微分预处理后的光谱建立的模型没有明显变化,对模型的性能影响不大。The calorific value of coal ash is an important indicator to evaluate the coal quality. In the experiment, the effect of spectrum and processing methods such as smoothing, differential processing, multiplicative scatter correction （MS（;） and stand- ard normal variate （SNV） in improving the near-infrared diffuse reflection spectrum signal-noise ratio was analyzed first, then partial least squares （PLS） and principal component analysis （PCR） were used to establish the calorific value model of coal ash for the spectrums processed with each preprocessing method respectively. It was found that the model performance can be obvi- ously improved with 5-point smoothing processing, MS（; and SNV, in which 5-point smoothing processing has the best effect, the coefficient of association, correction standard deviation and forecast standard deviation are respectively 0. 989 9, 0. 000 49 and 0. 000 52, and when 25-point smoothing processing is adopted, over-smoothing occurs, which worsens the model perform- ance, while the model established with the spectrum after differential preprocessing has no obvious change and the influence on the model is not large.

关 键 词：近红外光谱 漫反射 发热量 预处理 

分 类 号：O657.3[理学—分析化学]