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Rapid and non-destructive measurement of biofuel pellet quality indices based on two-dimensional near infrared spectroscopic imaging

机译：基于二维近红外光谱成像技术的生物燃料颗粒质量指标的快速无损测量

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摘要

Rapid measurements for characterizing biomass pellets and monitoring the production process are needed due to increasing use of biofuel pellets in the context of renewable energy. The objective of this study was to assess the accuracy and reliability of hyperspectral imaging combined with chemometrics to predict biofuel pellet properties for automatic online application. First, a successive projections algorithm (SPA) was applied to hyperspectral image analysis to select the important variables. Subsequently, prediction models established using partial least-squares regression (PLSR) and a least-squares support vector machine (LSSVM) based on whole wavelengths and important wavelengths were compared. The optimized prediction models constructed by SPA-LSSVM showed excellent performance for measuring moisture content, ash content, volatile matter, and calorific value, with the coefficients of determination being 0.94, 0.92, 0.94, and 0.90 respectively. Finally, all the quality indices were quantitatively visualized on prediction maps by transferring each optimal model to each pixel in the hyperspectral images. The results show that calibration models for biofuel pellets quality indices are successful developed, which would enable pellet producers to improve the operation of the pelletizing process for high-throughput applications.
机译：由于在可再生能源的背景下越来越多地使用生物燃料颗粒，因此需要快速测量以表征生物质颗粒并监测生产过程。这项研究的目的是评估与化学计量学相结合的高光谱成像的准确性和可靠性，以预测生物燃料颗粒的性能，以便自动在线应用。首先，将连续投影算法（SPA）应用于高光谱图像分析以选择重要变量。随后，比较了使用偏最小二乘回归（PLSR）和基于整个波长和重要波长的最小二乘支持向量机（LSSVM）建立的预测模型。由SPA-LSSVM构建的优化预测模型在测量水分，灰分，挥发性物质和热值方面表现出优异的性能，测定系数分别为0.94、0.92、0.94和0.90。最后，通过将每个最佳模型转移到高光谱图像中的每个像素，在预测图上定量显示所有质量指标。结果表明，成功开发了生物燃料颗粒质量指标的校准模型，这将使​​颗粒生产商能够改善用于高通量应用的制粒过程的操作。

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  • 来源
    《Fuel》 |2018年第15期|197-205|共9页
  • 作者

    Feng Xuping; Yu Chenliang; Shu Zhenyu; Liu Xiaodan; Yan Wei; Zheng Qishuai; Sheng Kuichuan; He Yong;

  • 作者单位

    Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou 310058, Zhejiang, Peoples R China;

    Zhejiang Acad Agr Sci, Vegetable Res Inst, Hangzhou 310021, Zhejiang, Peoples R China;

    Zhejiang Univ, Ningbo Inst Technol, Sch Comp & Data Engn, Ningbo 315100, Zhejiang, Peoples R China;

    Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou 310058, Zhejiang, Peoples R China;

    Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou 310058, Zhejiang, Peoples R China;

    Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou 310058, Zhejiang, Peoples R China;

    Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou 310058, Zhejiang, Peoples R China;

    Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou 310058, Zhejiang, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Biomass; Two-dimensional near infrared spectroscopic; imaging; Chemometrics analysis; Non-destructive measurement;

    机译：生物质二维近红外光谱成像化学计量分析无损检测;

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