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Application of Near-infrared Spectroscopy to Predict Paper Properties of Acacia

机译:近红外光谱法预测金合欢纸质性质的应用

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First attempt to predicting physical properties of paper by Near Infrared Spectroscopy(abbreviated as NIRS) mathematical model, Acacia is a kind of fast-growing tree which is a potential resource in pulp and paper industry. The mathematical models of physical properties of Acacia unbleached kraft paper were established by software OPUS6.5 of Near Infrared Spectroscopy. Spectral data of Acacia unbleached kraft paper were acquired by Near-Infrared. Physical properties, which include quality, whiteness, tensile index, burst index and tear index, of the paper were measured by GB methods. NIRS mathematical models between the spectral data and the laboratory reference values were established and optimized by software OPUS6.5 partial least squares (abbreviated as PLS). The NIRS mathematical models were evaluated by its parameters, and used to predict the physical properties of unknown samples rapidly and accurately. Compared with NIRS mathematical model of physical properties of Acacia unbleached kraft pulp, the NIRS mathematical models of paper have a better prediction on unknown samples;;Compared with traditional laboratory methods, predicting properties of paper by the NIRS mathematical models of paper is rapid, accurate and non-destructive.
机译:首先尝试通过近红外光谱(缩写为NIRS)数学模型来预测纸张的物理性质,金合欢是一种快速生长的树,是纸浆和造纸工业中的潜在资源。通过近红外光谱的软件OPUS6.5建立了金合欢未漂白牛皮纸的物理性质的数学模型。通过近红外线获得金合欢未漂白牛皮纸的光谱数据。通过GB方法测量纸张的物理性质,包括质量,白度,拉伸指数,爆破指数和撕裂指数。频谱数据和实验室参考值之间的NIRS数学模型是由软件OPUS6.5部分最小二乘(缩写为PLS)的制定和优化的。 NIRS数学模型由其参数评估,并且用于预测快速且准确地预测未知样品的物理性质。与纳瑞斯的丙酰亚橡胶的物理性质的数学模型相比,纸张的数学模型对未知样品有更好的预测;与传统的实验室方法相比,通过纳里斯的纸张的数学模型预测纸张的性质快速,准确和非破坏性的。

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