Characterization and Identification of Coal and Carbonaceous Shale Using Visible and Near-Infrared Reflectance Spectroscopy
Because of the high organic carbon concentration in carbonaceous shale, a large proportion of carbonaceous shales are often misclassified into coals using visible and near-infrared (VIS-NIR) reflectance spectroscopy in the field of coal-gangue identification of hyperspectral remote sensing of coal m...
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Wiley
2018-01-01
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| Series: | Journal of Spectroscopy |
| Online Access: | http://dx.doi.org/10.1155/2018/2754908 |
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| author | En Yang Shirong Ge Shibo Wang |
| author_facet | En Yang Shirong Ge Shibo Wang |
| author_sort | En Yang |
| collection | DOAJ |
| description | Because of the high organic carbon concentration in carbonaceous shale, a large proportion of carbonaceous shales are often misclassified into coals using visible and near-infrared (VIS-NIR) reflectance spectroscopy in the field of coal-gangue identification of hyperspectral remote sensing of coal mine. In order to study spectral characterization of coal and carbonaceous shale, three bituminite samples and three carbonaceous shales were collected from a coal mine of China, and their spectral reflectance curves were obtained by a field spectrometer in the wavelength range of 350–2500 nm. Only one carbonaceous shale could be easily identified from the three bituminite samples according to obvious absorption valleys near 1400 nm, 1900 nm, and 2200 nm of its reflectance curve while the other two carbonaceous shales have similar reflectance curves to the three bituminite samples. The effect of carbon concentration on reflectance curve was simulated by the mixed powder of ultralow ash bituminite and clay in 0.5 mm grain size under various mixing ratios. It was found that absorption valleys near 1400 nm, 1900 nm, and 2200 nm of the mixed powder become not obvious when the bituminite content is more than 30%. In order to establish an effective identification method of coal and carbonaceous shale, 250 other samples collected from the same coal mine were divided into 150 training samples and 100 prediction samples. Principal component analysis (PCA) and Gauss radial basis kernel principal component analysis (GRB-KPCA) were employed to extract principal components (PCs) of continuum removed (CR) spectra of the training samples in eight selected wavelength regions which are related to the main mineral and organic compositions. Two support vector machine- (SVM-) based models PCA-SVM and GRB-KPCA-SVM were established. The results showed that the GRB-KPCA-SVM model had better identification accuracies of 94% and 92% for powder and nature block prediction samples, respectively. |
| format | Article |
| id | doaj-art-3e604f83fb3a4e87aaebb2fc6b20d7db |
| institution | Kabale University |
| issn | 2314-4920 2314-4939 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
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| series | Journal of Spectroscopy |
| spelling | doaj-art-3e604f83fb3a4e87aaebb2fc6b20d7db2025-02-03T07:24:53ZengWileyJournal of Spectroscopy2314-49202314-49392018-01-01201810.1155/2018/27549082754908Characterization and Identification of Coal and Carbonaceous Shale Using Visible and Near-Infrared Reflectance SpectroscopyEn Yang0Shirong Ge1Shibo Wang2School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaBecause of the high organic carbon concentration in carbonaceous shale, a large proportion of carbonaceous shales are often misclassified into coals using visible and near-infrared (VIS-NIR) reflectance spectroscopy in the field of coal-gangue identification of hyperspectral remote sensing of coal mine. In order to study spectral characterization of coal and carbonaceous shale, three bituminite samples and three carbonaceous shales were collected from a coal mine of China, and their spectral reflectance curves were obtained by a field spectrometer in the wavelength range of 350–2500 nm. Only one carbonaceous shale could be easily identified from the three bituminite samples according to obvious absorption valleys near 1400 nm, 1900 nm, and 2200 nm of its reflectance curve while the other two carbonaceous shales have similar reflectance curves to the three bituminite samples. The effect of carbon concentration on reflectance curve was simulated by the mixed powder of ultralow ash bituminite and clay in 0.5 mm grain size under various mixing ratios. It was found that absorption valleys near 1400 nm, 1900 nm, and 2200 nm of the mixed powder become not obvious when the bituminite content is more than 30%. In order to establish an effective identification method of coal and carbonaceous shale, 250 other samples collected from the same coal mine were divided into 150 training samples and 100 prediction samples. Principal component analysis (PCA) and Gauss radial basis kernel principal component analysis (GRB-KPCA) were employed to extract principal components (PCs) of continuum removed (CR) spectra of the training samples in eight selected wavelength regions which are related to the main mineral and organic compositions. Two support vector machine- (SVM-) based models PCA-SVM and GRB-KPCA-SVM were established. The results showed that the GRB-KPCA-SVM model had better identification accuracies of 94% and 92% for powder and nature block prediction samples, respectively.http://dx.doi.org/10.1155/2018/2754908 |
| spellingShingle | En Yang Shirong Ge Shibo Wang Characterization and Identification of Coal and Carbonaceous Shale Using Visible and Near-Infrared Reflectance Spectroscopy Journal of Spectroscopy |
| title | Characterization and Identification of Coal and Carbonaceous Shale Using Visible and Near-Infrared Reflectance Spectroscopy |
| title_full | Characterization and Identification of Coal and Carbonaceous Shale Using Visible and Near-Infrared Reflectance Spectroscopy |
| title_fullStr | Characterization and Identification of Coal and Carbonaceous Shale Using Visible and Near-Infrared Reflectance Spectroscopy |
| title_full_unstemmed | Characterization and Identification of Coal and Carbonaceous Shale Using Visible and Near-Infrared Reflectance Spectroscopy |
| title_short | Characterization and Identification of Coal and Carbonaceous Shale Using Visible and Near-Infrared Reflectance Spectroscopy |
| title_sort | characterization and identification of coal and carbonaceous shale using visible and near infrared reflectance spectroscopy |
| url | http://dx.doi.org/10.1155/2018/2754908 |
| work_keys_str_mv | AT enyang characterizationandidentificationofcoalandcarbonaceousshaleusingvisibleandnearinfraredreflectancespectroscopy AT shirongge characterizationandidentificationofcoalandcarbonaceousshaleusingvisibleandnearinfraredreflectancespectroscopy AT shibowang characterizationandidentificationofcoalandcarbonaceousshaleusingvisibleandnearinfraredreflectancespectroscopy |