不同探测距离与角度下典型煤岩近红外光谱特征与定性分析

Near Infrared Spectral Characteristics and Qualitative Analysis of Typical Coal-Rock Under Different Detection Distances and Angles

近红外波段的反射光谱测量较方便,不需对试样进行预处理,同时也适用于在线分析。为利用近红外光谱实现综放开采自动化放煤技术中的煤岩识别,从某矿井的综放工作面收集了炭质泥岩、砂质泥岩、砂岩、气煤4种典型的块状煤岩试样,综合考虑工作面后部刮板输送机的堆煤情况,在实验室利用光谱仪采集了常见探测距离(1.3, 1.4和1.5 m)与探测角度(10°, 20°, 30°, 40°和90°)下的4种典型煤岩的近红外漫反射光谱。通过对4种典型煤岩光谱特征分析,发现探测角度与距离对光谱曲线波形和吸收谷位置无明显影响,但明显影响光谱曲线的反射率。炭质泥岩、砂质泥岩、砂岩这3种岩样,均在1 400, 1 900和2 200 nm波段附近出现较明显的吸收谷,此外,砂岩与炭质泥岩在2 200 nm波段附近出现双吸收谷,气煤在近红外波段内的漫反射光谱曲线整体呈水平趋势,无明显的吸收谷。在1.3 m探测距离下,光谱曲线反射率随着探测角度的增大而增大;在1.4和1.5 m探测距离下,光谱曲线反射率随着探测角度的增大而减小。在10°, 20°和30°探测角度下,光谱曲线的反射率随着探测距离的增大而增大;在40°和90°探测角度下,光谱曲线的反射率随着探测距离的增大而降低。使用一阶微分(FD)、 Savitzky-Golay卷积平滑(S-G卷积平滑)、标准正态变量变换(SNV)这三种方法来增强光谱曲线吸收特征以及消除探测条件对煤岩漫反射光谱的影响,发现S-G卷积平滑在增强光谱吸收特征的前提下,还有效的消除了探测角度与高度对光谱曲线的影响。利用余弦相似度与皮尔逊相关系数两种模型分别进行煤岩定性分析,结果发现,基于S-G卷积平滑预处理后的余弦相似度模型分类效果最优,其正确分类率为100%。最佳预处理方法与定性分析模型的获得可以为在不同探测距离与探测角度下直接利用反射光谱的波形进行快速、定性地识别煤岩提供参考意义。

The reflection spectrum of the near-infrared band was convenient to measure. It was not necessary to pretreat the sample, but also suitable for on-line analysis. In order to realize the identification of coal-rock in the automatic coal caving technology of fully mechanized caving mining based on the near-infrared spectroscopy, the fully mechanized caving work from a mine four kinds of typical massive coal-rock samples such as carbonaceous mudstone, sandy mudstone, sandstone and gas coal were collected, and the coal pile condition of the rear scraper conveyor was considered comprehensively. Near infrared diffuse reflectance spectra of four typical coal-rock with common detection distances(1.3, 1.4, 1.5 m) and detection angles(10, 20, 30, 40 and 90 degrees) were collected in the laboratory by the spectrometer. By analyzing the spectral characteristics of four typical coal-rock, it was found that the detection angle and distance have no significant influence on the spectral curve and the position of the absorption valley, but obviously affected the reflectivity of the spectral curve. Carbonaceous mudstone, sandy mudstone and sandstone all have obvious absorption valleys near the 1 400, 1 900 and 2 200 nm bands. In addition, sandstone and carbonaceous mudstones have double absorption valleys near the 2 200 nm band. The diffuse reflectance spectral curve of coal in the near-infrared region is generally horizontal, with no obvious absorption valley. At the detection distance of 1.3 m, the reflectance of the spectral curve increased with the increased of the detection angle;at the detection distance of 1.4 and 1.5 m, the reflectance of the spectral curve decreased with the increased of the detection angle. At the detection angles of 10°, 20° and 30°, the reflectivity of the spectral curve increased with the increased of the detection distance;at the detection angle of 40° and 90°, the reflectivity of the spectral curve increased with the detection distance. Three methods of first-order differential(FD), Savitzky-Golay convolution smoothing(SG convolution smoothing), and standard normal enthalpy switching(SNV) were used to enhanced spectral absorption characteristics and eliminated detection conditions for coal-rock diffuse reflection spectra. The effect of SG convolution smoothing on the premise of enhancing spectral absorption characteristics also effectively eliminated the influence of detection angle and height on the spectral curve. The qualitative analysis of coal-rock was carried out by using two models of cosine similarity and Pearson correlation coefficient. The results showed that the cosine similarity model based on S-G convolution smoothing was the best, and the correct classification rate was 100%. Obtaining the best pre-processing method and qualitative analysis model can provide reference for the rapid and qualitative identification of coal-rock by directly using the waveform of the reflection spectrum at different detection distances and detection angles.