【摘要】 本研究探讨了采用工业型光谱仪和实验型光谱仪建立近红外模型用于快速预测木片材性的可行性，分析对比不同光谱仪的建模效果。针对不同材性指标分析特点，通过光谱信号校正和特征波长筛选算法优化模型预测性能，建立适宜的建模方法。结果表明，基于工业型光谱仪建立的近红外模型对木片水分、基本密度、纤维形态等物理性能指标表现出更高的预测精度，而化学组分含量的预测精度与实验型光谱仪无显著差异。工业型光谱仪木片理化材性近红外模型适用于制浆原料品质评价和工业过程分析。更多还原

【Abstract】 In this study, the feasibility of near-infrared(NIR) modeling using an industrial near infrared spectrometer for rapid prediction of wood chips properties was explored and compared with the modeling results of experimental spectrometer. According to the characteristics of different wood properties, the model performance was optimized by spectral signal correction and wavelength screening algorithms, and a suitable modeling method was established. The results showed that the NIR model based on an industrial spectrometer exhibited higher prediction accuracy for physical properties such as moisture, basic density, and fiber length of wood chips, while the prediction accuracy of chemical component content was not significantly different from that of the experimental spectrometer. NIR model of wood chip properties based on industrial spectrometer was suitable for raw material quality evaluation and industrial process analysis.更多还原