摘要
含水量是衡量生物质燃烧的一个重要指标,目前还没有快速、高效地测定生物质水分含量的方法。文章利用傅立叶近红外漫反射光谱(NIRS)技术,采用偏最小二乘法(PLS)建立了木质纤维素类生物质水分含量的校正模型。试验结果表明,当主成分数为6时,预测值与实测值之间的相关系数(Corr.Coeff)可达到最大值0.999 74,校正集均方根误差(RMSEC)达到最小值0.179,预测值和实测值之间的预测均方根误差(RMSEP)为0.518。可见,近红外光谱技术对于快速测定生物质水分含量是可行的。
Rapid and accurate determination of moisture content of biomass is crucial to the prediction of its fuel performance.This paper studied the determination of the moisture content of wood biomass by using near-infrared spectroscopy in which the method of partial least squares（PLS） was used to establish the near-infrared calibration model.The results showed that the correlation coefficient（Corr.Coeff） between the predicted values and measured ones reaches the maximum value of 0.999 74 when the factor is 6;the Root-Mean-Square Error of Cross Validation（RMSEC） reaches the minimum value of 0.179 and the Root-Mean-Square Error of Prediction（RMSEP） arrives at 0.518.The reliability of the NIR model indicates that there is potential for utilization of NIR spectroscopy in predicting the biomass moisture content.
出处
《可再生能源》
CAS
北大核心
2011年第3期46-49,共4页
Renewable Energy Resources
