煤质的近红外光谱定量分析研究

Quantitative Analysis and Research on Coal Quality Based on Near Infrared Spectrum

实验中首先采用多元散射校正(MSC)的方法对煤粉样品的漫反射光谱进行了预处理,然后分别通过偏最小二乘法(PLS)和主成分分析(PCR)的方法建立煤粉样品的近红外光谱的全水分、挥发分和灰分的定量分析模型,通过预测集对建立的模型进行验证,发现利用偏最小二乘法建立的煤粉全水分模型最优,r=0.975,RMSEC=0.166,RMSEP=0.169,RPD=3.22,通过主成分分析方法建立的挥发分和灰分的模型最优,最后通过选取验证集样本对建立的模型进行了验证,得出利用近红外光谱分析技术间接对煤质进行定量分析是可行的。

In the experiment, firstly, quantitative analysis models of the total moisture, volatile matter and ash content of the near infrared spectral of the pulverized coal samples are respectively established by adopting the method ofpartia~ least squares. As the model has high predicted precision and good stability, we can see that is feasible to conduct nondestructive testing to the pulverized coal indirectly using the NIR analysis method. Then a further study is made on the correlation of the total moisture, volatile matter and ash content in pulverized coal samples respectively, through which we found that the ash content and volatile matter in the pulverized coal sample have a high linear correlation. Finally, by comparing the ash content value obtained from the correlation function between the ash content and volatile matter with that obtained from partial least squares model, we can find that the ash content value obtained from the linear correlation between ash content and volatile matter in the pulverized coal ash is more accurate and orecise.