Biomass fuel identification using flame spectroscopy and tree model algorithms
Biomass fuel identification using flame spectroscopy and tree model algorithms
复制标题
使用火焰光谱和树模型算法识别生物质燃料
DOI：
10.1080/00102202.2019.1680654
复制
发表时间：
2019-10
影响因子：
1.9
通讯作者：
Yong Yan
中科院分区：
文献类型：
--
作者：
Hong Ge;Xinli Li;Gang Lu;Yong Yan
摘要本文提出了一种结合火焰光谱监测和树模型算法的生物质等燃料类型识别方法。提取火焰光谱特征，包括火焰自由基的光谱强度[OH* (310.85 nm)、CN* (390.00 nm)、CH* (430.57 nm)和C2* (515.23 nm、545.59 nm)]、火焰辐射强度和火焰辐射能量（光谱强度积分）。采用决策树、随机森林、极度随机树和梯度提升决策树四种树模型算法建立识别模型。将不同类型的生物质和燃烧火焰的光谱特征组成样本对来训练识别模型。实验在实验室规模的生物质-空气燃烧实验台上进行。燃烧四种不同的生物质燃料，包括玉米芯、柳树、花生壳和麦秆。结果表明，所提出的识别模型能够正确识别生物质燃料的类型，10次试验的平均识别成功率为98%。
ABSTRACT This paper presents an identification method for types of fuel such as biomass by combining flame spectroscopic monitoring and tree model algorithms. The features of the flame spectra are extracted, including the spectral intensity of flame radicals [OH* (310.85 nm), CN* (390.00 nm), CH* (430.57 nm) and C2* (515.23 nm, 545.59 nm)], flame radiation intensity and flame radiation energy (integration of spectral intensity). The identification models are built using four tree model algorithms, i.e., decision tree, random forest, extremely randomized trees, and gradient boost decision tree. The different type of biomass and spectra features of combustion flames are composed of sample pairs to train identification models. Experiments are carried out on a laboratory-scale biomass-air combustion test rig. Four different biomass fuels, including corncob, willow, peanut shell, and wheat straw are burnt. The results demonstrate that the identification models proposed is capable of identifying types of biomass fuels correctly with the average identification success rate of 98% in 10 trials.
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影响因子：
64.8
作者：
Xinli Li;Yijiao Li;G. Lu;Yong Yan
通讯作者：
Xinli Li;Yijiao Li;G. Lu;Yong Yan
DOI：
10.4028/www.scientific.net/amr.317-319.1237
发表时间：
2011-08
期刊：
Advanced Materials Research
影响因子：
--
作者：
Y. Huang;Shi Liu;Jie Li;Lei Jia;Z. Li
通讯作者：
Y. Huang;Shi Liu;Jie Li;Lei Jia;Z. Li
DOI：
10.1631/jzus.a1500306
发表时间：
2017-02
期刊：
Journal of Zhejiang University-Science A(Applied Physics & Engineering)
影响因子：
--
作者：
Yin Feng;Luo Zhi-hao;Li Yuan;Zhou Ming-xi;Zhou Hao;Yin Feng;Luo Zhi-hao
通讯作者：
Luo Zhi-hao
影响因子：
5.6
作者：
Lijun Xu;Yong Yan;S. Cornwell;G. Riley
通讯作者：
Lijun Xu;Yong Yan;S. Cornwell;G. Riley
DOI：
10.1088/0031-9112/22/3/032
发表时间：
1971-03
期刊：
Physics Bulletin
影响因子：
--
作者：
P. Padley
通讯作者：
P. Padley