1. Background and significance
With the rapid development of China's economy, the demand for energy will continue to rise rapidly for a long time in the foreseeable future. Although the proportion of coal use has declined, it will not change as the first major energy source, and the proportion of coal consumption in China will still reach about 55% by 2030. Because 90% of China's coal is underground, and 50% of the buried depth is more than 1,000 meters, the incidence of geological disasters such as deep coal seam gas, rock collapse, and water inrush is high and accidental. In view of the development needs of the coal energy technology revolution, the mining mode with high rate and low efficiency can no longer meet the needs of modern mining, and unmanned and intelligent mining is an urgent demand and effective way for coal mines around the world to achieve safe, efficient and green goals.
As a common but unsolved frontier technology in the field of international coal mining, coal and rock identification has always been a major problem hindering the research and application of unmanned coal mining.
It is of great significance to study the characteristics and differences of high-resolution reflectance spectra in coal and rock, and to efficiently distinguish coal and rock based on reflectance spectra. Therefore, mastering the basic principles and effective identification methods of coal and rock identification based on reflectance spectroscopy technology will provide an important theoretical basis and technical guidance for the global problem of coal and rock identification.
2. Reflectance spectral characteristics of coal
The application of reflectance spectroscopy technology in the field of remote sensing in coal mines and rocks provides a new idea for the study of coal and rock identification methods, and obtaining the reflectance spectral characteristics of coal and rock is the basis for studying the coal and rock identification methods based on reflection spectroscopy, and a few scholars have studied the visible-near-infrared reflection and absorption spectral characteristics of some coal and rocks. However, there has not been a systematic study on the reflectance spectral characteristics of typical coal and coal measure rocks in China, and the study of the reflectance spectral characteristics of typical coal and coal measure rocks not only provides a basis for the low-cost and rapid identification of coal and coal measure rock types by using spectral waveforms, but also provides a premise for studying the differences and identification methods of coal and rock reflectance spectra. The characteristics of the reflectance spectrum of coal and coal measure rocks are the basis for the analysis of the difference of the reflectance spectrum of coal and rock, and the difference of the reflection spectrum of coal and rock is the direct basis for the distinction of coal and rock.
Therefore, this chapter analyzes the characteristics of visible-near-infrared reflectance spectra of various typical coals and coal measure rocks, and studies the material composition mechanism corresponding to the reflectance spectral characteristics of coal and rock.
2.1 Spectral reflectance curves of typical coal types
In the international standard for coal classification ISO 11760 classification of coals and the Chinese national standard GB T5751 "China Coal Classification", the same definition of coal is given for coal, that is, coal is a carbon-rich solid combustible organic sedimentary rock mainly converted from plant remains through coalification, containing a certain amount of minerals, and its ash yield is less than or equal to 50%. Both standards divide coal into three categories: anthracite, bituminous coal, and lignite according to the degree of its metamorphosis. From the above criteria, it can be seen that coal is a sedimentary rock, but due to the high degree of coalification and metamorphism of anthracite, some monographs classify some anthracite as metamorphic rock types. In this paper, sub-categories were sampled according to GB T 5751, and 12 typical coal types were selected as the research objects, covering three major coal types: anthracite, bituminous coal and lignite, as shown in Table 1. The 12 coal samples in Table 1 are arranged from top to bottom in order of coal rank reduction, including the origin and coal mine of each type of coal.
Table 1 Typical coal samples
This paper utilizes coal 0The surface reflectance spectrum of the 5 mm particle size powder sample was simulated to simulate the surface reflectance spectrum of the massive in-situ coal rock sample. The 12 types of coal in Table 1 collected at close range are 0The reflectance spectra of the smoothed surface of a 5 mm powder are shown in Figure 1, Figure 2, Figure 3.
Fig.1. Spectral reflectance curve of anthracite
Fig. 1, Fig. 2 and Fig. 3 remove the spectral curves of the 350-399 nm and 2451-2500 nm bands, and only the spectral curves of the 400-2450 nm bands are retained. It can be seen from Figure 1 that the waveforms of the overall spectral curves of the two anthracites are horizontal, the overall spectral curves of anthracite No. 1 have a slight downward trend, and the overall reflectivity of anthracite No. 2 and anthracite No. 2 spectral curves is slightly higher than that of anthracite No. 1. In the 400-1000 nm band, the two spectral curves showed frequent absorption valley characteristics, and in the 1000-2450 nm band, there were basically no obvious absorption valley characteristics.
Fig.2. Spectral reflectance curve of bituminous coal
The overall spectral reflectance of the eight bituminous coals in Fig. 2 showed an upward trend with the decrease of coal rank, and the lower the coal rank, the more obvious the upward trend. With the decrease of coal rank, the absorption characteristics in the 2100-2400nm band become more and more obvious. When the coal rank is low, such as 1 3 coking coal, gas fertilizer coal, and gas coal, the spectral curves stop the overall upward trend with the increase of wavelength from about 2200nm. In the 400-1000 nm band, most of the reflectance spectral curves show frequent absorption valley characteristics, and in the 1000-2450 nm band, the absorption valley characteristics not only increase, but also become more obvious.
Fig.3. Spectral reflectance curve of lignite
The reflectance spectral curves of the two types of lignite in Figure 3 first increased with the increase of wavelength, and then an obvious absorption valley began to appear from about 1800nm, and the overall waveform began to decrease, and the overall reflectance of the Lignite No. 2 spectral curve was slightly higher than that of Lignite No. 1. In the 400-1000 nm band, the reflectance spectra of the two types of lignite showed frequent absorption valley characteristics, and in the 1000-2450 nm band, the two types of lignite showed obvious absorption valley characteristics near 1900 nm, and lignite No. 2 was the most obvious. The overall variation of the reflectance spectra of the 12 kinds of coal in the 400-2450nm band and the obvious wavelength position of the absorption valley are shown in Figure 4.
Fig.4 Visible and near-infrared band reflectance spectra of 12 typical coal types show the location of the obvious absorption valleys
35: Anthracite No. 1; 59: Anthracite No. 2; 36: lean coal; 37: lean coal; 38: lean coal; 39: coking coal; 40: Fertile coal; 41:1 3 Coking coal; 42: gas-fertilized coal; 43: gas coal; 44: Lignite No. 1; 45: Lignite No. 2
It can be seen from Figure 4 that the overall reflectance spectrum curves of the 12 coals show that with the decrease of coal rank, the curve increases, that is, the overall reflectance increases, the waveform gradually increases from near horizontal to positive inclination, and the overall waveform of the second half of the near-infrared band spectral reflectance curve of low-rank coal changes horizontally to negative tilt.
2.2 Parameterization and regularity of coal reflectance spectrum curves
The parameterization of spectral curve features is to transform spectral curve features into a form suitable for computer calculation and analysis. Therefore, the characteristics of the reflectance spectrum curve are quantitatively expressed, and the law of reflectance change is expressed in a parametric way. Through the feature parameterization and parameter extraction of the reflectance spectrum curve, the analysis feature parameter set was constructed, which laid the foundation for the subsequent spectral matching, classification, identification and inversion. As mentioned above, the overall slope of the reflection spectral curve of 12 kinds of coal in the near-infrared band (780-2450nm) has obvious regularity, so the spectral slope of the coal reflectance spectrum curve is calculated from the wavelength point of 780nm. In Fig. 5, the reflectance spectra of 4 representative coal rocks in the above 12 coal samples are selected, including: coal type of coal rank-anthracite No. 1 (35), coal rank bituminous coal-lean coal (36), coal rank bituminous coal-gas coal (43), and coal rank lignite-lignite No. 2 (45).
Fig.5 Characteristic parameterization of reflectance spectral curves of representative coal samples
3. Reflectance spectral characteristics of coal measure rocks
According to the types and analysis of coal measure rocks collected in the previous chapter, coal measure rocks mainly include three types of sedimentary rocks: shale, sandstone and limestone. Similar to similar sedimentary rocks on the surface, in the near-infrared band, the reflectance spectral characteristics of coal measure rocks mainly depend on the spectral characteristics of the minerals, and the reflectance spectral absorption characteristics of minerals mainly depend on the combined frequency and doubling of the fundamental frequency of the absorption spectrum of the absorption groups in the minerals in the mid-infrared band. Affected by the complex sedimentation in the process of coal formation, the coal measure rocks mostly contain certain organic carbonaceous components, so compared with similar sedimentary rocks on the surface, the spectral reflectivity is relatively low, and the absorption characteristics are also attenuated.
In view of the demand for hyperspectral remote sensing in coal mines, the research on the spectral reflectance of coal measure rocks mostly focuses on the coal gangue accumulated on the surface of the mining area. This section focuses on the analysis of the spectral reflectance curve characteristics of the three types of coal measure sedimentary rocks collected underground in the visible-near-infrared band. The research results not only provide a basis for the study of coal and rock identification, but also provide reference information for understanding the spectral information of coal measure rocks and judging the core of coal seam geological boreholes by using the reflectance spectral waveform characteristics of coal measure rocks. According to the principle of covering three types of coal measure sedimentary rocks, namely shale, sandstone and limestone, 11 representative roof and floor rock samples from four coal mines, namely Shanxi Malan Coal Mine, Shanxi Xinjing Coal Mine, Shandong Dongfeng Coal Mine and Shandong Xinglongzhuang Coal Mine, were selected as the research objects, and the rock type, appearance characteristics, coal seam distribution, and coal mine origin information are shown in Table 4. The 11 coal measure rock samples in Table 4 are listed in order of rock type.
Table 4 Typical coal measure rock samples
Similar to the analysis of coal reflectance spectral characteristics mentioned above, for the coal measure rocks in Table 4, in order to obtain stable spectral reflectance data of homogeneous rock samples, this paper uses coal measure rocks 0The surface reflectance spectrum of the 5mm particle size powder sample was simulated to simulate the surface reflectance spectrum of the massive coal measure rock sample. The 11 coal measure rocks in Table 4 collected at close range in the previous chapter 0The reflectance spectra of the smoothed surface of the 5 mm particle size powder are shown in Figure 6, Figure 7, Figure 8. The spectral reflectance curves of the 12 typical coal types mentioned above are the same, due to the large dark current noise of the 350-399nm and 2451-2500nm spectral curves, only the 400-2450nm band spectral curves are taken, including the 400-780nm visible band, the 780-1100nm short-wave near-infrared band, and the 1100-2450nm long-wave near-infrared band, and the proportion of the ordinates of each sub-plot is the same.
Fig.6. Spectral reflectance curve of shale
Among the five shale spectral reflectance curves in Fig. 6, the carbonaceous mudstone (46) has the least overall reflectance and absorption valley characteristics compared with the spectral curves of the other four samples, the overall waveform of the carbonaceous mudstone (46) spectral curve is concave, and the carbonaceous mudstone (48) and the other three shale types of the same coal mine are convex. In addition, the overall absorption valley characteristics of black shale (58) are also weak. Except for carbonaceous mudstone (46), the other four shale species showed multiple absorption valleys with increasing wavelength in the visible-shortwave near-infrared band from 400 to 1100 nm. These five shale species showed absorption valley characteristics near the wavelength points of 1400 nm, 1900 nm and 2200 nm in the 1100-2450 nm longwave near-infrared band, while the carbonaceous mudstone (46) and black shale (58) were weak, and the spectral curves of the two shales in the 2350-2450 nm band showed a frequent fluctuation trend.
Fig.7. Spectral reflectance curve of sandstone
The overall waveforms of the four sandstone spectral reflectance curves in Fig. 7 are convex, and the two siltstones have high overall spectral reflectivity, with an average of more than 10%, and the absorption valley characteristics are obvious. In the middle and late sections of the 400-1100nm band, the four sandstones show multiple absorption valley characteristics. In the 1100-2450 nm band, the more obvious absorption valleys of medium-grained sandstone and fine sandstone appear near the wavelength points of 1400 nm, 1900 nm and 2200 nm, the more obvious absorption valleys of siltstone (09) appear near the wavelength points of 1400 nm, 1900 nm, 2200 nm and 2350 nm, and the more obvious absorption valleys of siltstone (28) only appear near the 1900 nm wavelength point.
Fig.8. Spectral reflectance curve of limestone
The overall waveforms of the spectral reflectance curves of the two argillaceous limestones in Fig. 8 are convex, and the overall spectral reflectance of the argillaceous limestone (08) is high, and most of the bands are greater than 10%. The two argillaceous limestones showed multiple absorption valleys in the 400-1100 nm band, with strong absorption near 1900 nm and 2350 nm wavelengths, and weak absorption near 1400 nm and 2200 nm. The reflectance spectra of the 11 coal measure rocks in Fig. 6, Fig. 7 and Fig. 8 show that there are multiple absorption valleys in the visible-short-wave near-infrared band, and in the long-wave near-infrared band, the absorption valleys are basically distributed around the four wavelength points of 1400 nm, 1900 nm, 2200 nm and 2350 nm, and the overall waveform is convex. However, the absorption valley of the spectral curve of carbonaceous mudstone (46) is weak, and the waveform of the 2350-2450nm band fluctuates frequently, and the overall waveform is concave, which is similar to the spectral curve of coal. The reflectance spectra of the 11 coal measure rocks are more obvious in the 400-2450nm band, and the wavelength position of the absorption valley is shown in Fig. 9.
Fig.9 Visible and near-infrared band reflectance spectra of 11 typical coal measure rocks show the location of the absorption valleys
46: carbonaceous mudstone; 48: carbonaceous mudstone; 67: black shale; 58: black shale; 69: sandy shale; 68: medium-grained sandstone; 47: fine sandstone; 09: siltstone; 28: siltstone; 08: argillaceous limestone; 04: Argillaceous limestone
In order to facilitate observation, the reflectance spectral curves of 11 coal measure rocks are offset in Figure 16, and the spectral curves of the same large type of rocks are represented by the same color, and the absorption valleys of each absorption valley in the wavelength range of 400-1100 nm and the wavelength range of 2350-2450 nm are labeled as a whole, and the absorption valleys of each wavelength point at 1400 nm, 1900 nm, 2200 nm and 2350 nm are labeled separately.
4. Conclusion
The main findings of this chapter are as follows.
Characteristics of the reflectance spectrum of coal and its material composition mechanism: In the near-infrared band, the spectral reflectance curve of coal increases with the decrease of coal rank, and the waveform of the overall spectral curve changes from near horizontal to positive slope, and the slope gradually increases. In the visible-near-infrared band, there are 13 obvious absorption valleys in the coal band, among which the absorption valleys at 455nm, 514nm, 591nm, 662nm, 770nm, 900nm, 1106nm and 1342nm appear in all coal ranks, and the absorption valleys at 1418nm, 1698nm, 1905nm, 2196nm and 2303nm appear when the coal rank becomes lower, and the lower the coal rank, the more obvious it is. The aromatization trend of coal molecular structure is the reason for the increase of reflectivity and the change of spectral waveform from near horizontal to positive slope when the coal rank is reduced, and the increase of group frequency and frequency doubling in the coal is the reason for the enhancement of the absorption characteristics of the near-infrared band when the coal rank is reduced.
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