光谱学与光谱分析, 2012, 32 (11): 3010, 网络出版: 2012-11-22
小波分解重建算法提高近红外煤质水分检测精度
Improving Precision in Coal Moisture Detection Using Wavelet Transform
近红外光谱 小波分解重建 偏最小二乘法 Near-infrared spectroscopy Wavelet decomposition and reconstruction Partial least square (PLS) modeling
摘要
水分是煤质经济价值的基本指标, 会造成煤质利用率下降和能源浪费。 因此, 近红外光谱法实现煤质水分快速、 无损、 低成本检测具有重要意义。 针对目前近红外煤质水分检测精度普遍在1%, 且鲜有关于精度提高系统性研究的现状, 从光谱预处理及波长选择进行比较, 提出了提高煤质水分检测精度的可行性方法。 实验结果表明, 采用小波分解重建算法对1 300~2 400 nm光谱区间进行降噪及去基线预处理, 对重建光谱进行偏最小二乘建模, 其建模结果明显优于其他方法, RMSEC达到0.06%, RMSEP达到0.27%, 相关性系数R-square达到0.995, 且证明模型稳定性较好, 显著提高了近红外煤质水分的检测精度。
Abstract
Moisture, as a core determination of the economic value of coal, can result in the utilization and energy inefficiency. Near-infrared (NIR) spectroscopy, with advantages of high accuracy and low cost, provides significant solution to the quick and non-invasive detection of coal moisture. In the present paper, the improvement of the coal moisture analysis was conducted based on the precision of 1% and insufficient comparisons in recent experiments, and aspects of spectrum pretreatment and wavelength selection were mainly discussed. The optimized result with R-square of 0.995, RMSEC of 0.06% and RMSEP of 0.27% indicates the priority of wavelet decomposition and reconstruction, compared with other methods, in the noise reduction and baseline removing of original spectra (1 300~2 400 nm) before PLS modeling, and the stability experiment validates its robust potential in improving precision of coal moisture detection based on the NIR spectroscopy.
贾浩, 付强, 韩婵娟, 邹德宝, 陈文亮, 徐可欣. 小波分解重建算法提高近红外煤质水分检测精度[J]. 光谱学与光谱分析, 2012, 32(11): 3010. JIA Hao, FU Qiang, HAN Chan-juan, ZOU De-bao, CHEN Wen-liang, XU Ke-xin. Improving Precision in Coal Moisture Detection Using Wavelet Transform[J]. Spectroscopy and Spectral Analysis, 2012, 32(11): 3010.