Based on element geochemical studies of the main Permian exploitable coal measure strata in Western Guizhou, the element geochemical distribution characteristics of the main exploitable coal measures were revealed in ...Based on element geochemical studies of the main Permian exploitable coal measure strata in Western Guizhou, the element geochemical distribution characteristics of the main exploitable coal measures were revealed in the regions of Dafang, Qianxi, Weining, Hezhang, Zhijin, etc., of Guizhou Province, and the results show that their element contents are mainly affected by terrestrial material supply. Coal measures formed in the delta plain environment where sufficient terrestrial materials are supplied contain relatively abundant trace elements and rare-earth elements, whereas those formed in the tidal-fiat environment influenced greatly by seawater have relatively low contents of trace elements and rare-earth elements, mainly con- trolled by the geological fact that basalts the parent rocks from source regions contain high trace elements and rare-earth elements. In addition, coal measures affected by later hydrothermal activities and fault tectonics contain a large amount of harmful elements. According to the rules of distribution of elements in coal measures, a new idea was put forward to classify coal-forming environments by using the geochemical composition characteristics, which is of great significance in dissolving the problem of whether coal measures were fbrmed either in delta environments or in tidal-flat environments in Western Gui- zhou. At the same time, the rules of distribution of elements in the main exploitable coal measures in Western Guizhou were fully understood, which is of direct significance in utilizing coal resources on the basis of classification of coals, as well as in developing the coal chemical industry.展开更多
This study was performed to investigate the spectral characteristics of micro-seismic signals observed during the rupture of coal. Coal rupture micro-seismic observations were obtained on a test system that included a...This study was performed to investigate the spectral characteristics of micro-seismic signals observed during the rupture of coal. Coal rupture micro-seismic observations were obtained on a test system that included an electro-hydraulic servo pressure tester controlled by a YAW microcomputer, a micro-seismic sensor, a loading system, and a signal collection system. The results show that the micro-seismic signal increases with increasing compressive stress at the beginning of coal rupture. The signal remains stable for a period at this stage. A large number of micro-seismic signals appear immediately before the main rupture event. The frequency of micro-seismic events reaches a maximum immediately after the coal ruptures. Micro-seismic signals were decomposed into several Intrinsic Mode Functions (IMF's) by the empirical mode decomposition (EMD) method using a Hilbert-Huang transform (HHT). The main fre- quency band of the micro-seismic signals was found to range from 10 to 100 Hz in the Hilbert energy spectrum and from marginal spectrum calculations. The advantage of applying an HHT is that this can extract the main features of the signal. This fact was confirmed by an HHT analysis of the coal micro-seis- mic signals that shows the technique is useful in the field of coal rupture.展开更多
This paper discussed the petrological characteristics and coal facies of No.6 coal seam from the Haerwusu Mine, Jungar Coalfield, Inner Mongolia by using of coal petrology and geochemistry. No.6 coal facies can be div...This paper discussed the petrological characteristics and coal facies of No.6 coal seam from the Haerwusu Mine, Jungar Coalfield, Inner Mongolia by using of coal petrology and geochemistry. No.6 coal facies can be divided into 3 types, arid forest peat swamp （including two subfacies） and reed peat swamp, respectively. From bottom to top, the development of peat swamps present wavy changes, and three coal facies types appear alternately, with obvious thyme. According to the parameters, 11 secondary sequences were identified of the peat swamps of No.6 coal seam. The results indicate that the mire formed in brackish water-fresh water weak regression environment, changed in excess oxygen and poor oxygen, and reflected the characteristics of transition phase.展开更多
Using research results on physical properties of primary coal and rock mass, in this paper, response characteristic function y（t）, amplitude frequency characteristic H（ω） and phase-frequency characteristic φ（ω...Using research results on physical properties of primary coal and rock mass, in this paper, response characteristic function y（t）, amplitude frequency characteristic H（ω） and phase-frequency characteristic φ（ω） were used to describe dynamic response of stress impulse signal. At the same time, with the help of computer simulation analogue technique, applying these characteristic parameters to research the rock-burst forecasting, this paper deduced response characteristic function model. This function model is valuable for rockburst tendency test. According to these researches, develops monitoring recording system to acquire rockburst precursor signals. This system can monitor stress impulse signal dynamically and continuously. By applying the forecast information systems can forecast rockburst successfully.展开更多
In this study,analyses are conducted on the information features of a construction site,a cornfield and subsidence seeper land in a coal mining area with a synthetic aperture radar (SAR) image of medium resolution. Ba...In this study,analyses are conducted on the information features of a construction site,a cornfield and subsidence seeper land in a coal mining area with a synthetic aperture radar (SAR) image of medium resolution. Based on features of land cover of the coal mining area,on texture feature extraction and a selection method of a gray-level co-occurrence matrix (GLCM) of the SAR image,we propose in this study that the optimum window size for computing the GLCM is an appropriate sized window that can effectively distinguish different types of land cover. Next,a band combination was carried out over the text feature images and the band-filtered SAR image to secure a new multi-band image. After the transformation of the new image with principal component analysis,a classification is conducted selectively on three principal component bands with the most information. Finally,through training and experimenting with the samples,a better three-layered BP neural network was established to classify the SAR image. The results show that,assisted by texture information,the neural network classification improved the accuracy of SAR image classification by 14.6%,compared with a classification by maximum likelihood estimation without texture information.展开更多
文摘Based on element geochemical studies of the main Permian exploitable coal measure strata in Western Guizhou, the element geochemical distribution characteristics of the main exploitable coal measures were revealed in the regions of Dafang, Qianxi, Weining, Hezhang, Zhijin, etc., of Guizhou Province, and the results show that their element contents are mainly affected by terrestrial material supply. Coal measures formed in the delta plain environment where sufficient terrestrial materials are supplied contain relatively abundant trace elements and rare-earth elements, whereas those formed in the tidal-fiat environment influenced greatly by seawater have relatively low contents of trace elements and rare-earth elements, mainly con- trolled by the geological fact that basalts the parent rocks from source regions contain high trace elements and rare-earth elements. In addition, coal measures affected by later hydrothermal activities and fault tectonics contain a large amount of harmful elements. According to the rules of distribution of elements in coal measures, a new idea was put forward to classify coal-forming environments by using the geochemical composition characteristics, which is of great significance in dissolving the problem of whether coal measures were fbrmed either in delta environments or in tidal-flat environments in Western Gui- zhou. At the same time, the rules of distribution of elements in the main exploitable coal measures in Western Guizhou were fully understood, which is of direct significance in utilizing coal resources on the basis of classification of coals, as well as in developing the coal chemical industry.
基金support for this work provided by the National Science and Technology Planning Project (No. 2009BAK54B03)the National Natural Science Foundation of China (No. 50834005)
文摘This study was performed to investigate the spectral characteristics of micro-seismic signals observed during the rupture of coal. Coal rupture micro-seismic observations were obtained on a test system that included an electro-hydraulic servo pressure tester controlled by a YAW microcomputer, a micro-seismic sensor, a loading system, and a signal collection system. The results show that the micro-seismic signal increases with increasing compressive stress at the beginning of coal rupture. The signal remains stable for a period at this stage. A large number of micro-seismic signals appear immediately before the main rupture event. The frequency of micro-seismic events reaches a maximum immediately after the coal ruptures. Micro-seismic signals were decomposed into several Intrinsic Mode Functions (IMF's) by the empirical mode decomposition (EMD) method using a Hilbert-Huang transform (HHT). The main fre- quency band of the micro-seismic signals was found to range from 10 to 100 Hz in the Hilbert energy spectrum and from marginal spectrum calculations. The advantage of applying an HHT is that this can extract the main features of the signal. This fact was confirmed by an HHT analysis of the coal micro-seis- mic signals that shows the technique is useful in the field of coal rupture.
基金Supported by the Natural Science Foundation of Hebei Province （D2012402025, D2009000832）
文摘This paper discussed the petrological characteristics and coal facies of No.6 coal seam from the Haerwusu Mine, Jungar Coalfield, Inner Mongolia by using of coal petrology and geochemistry. No.6 coal facies can be divided into 3 types, arid forest peat swamp （including two subfacies） and reed peat swamp, respectively. From bottom to top, the development of peat swamps present wavy changes, and three coal facies types appear alternately, with obvious thyme. According to the parameters, 11 secondary sequences were identified of the peat swamps of No.6 coal seam. The results indicate that the mire formed in brackish water-fresh water weak regression environment, changed in excess oxygen and poor oxygen, and reflected the characteristics of transition phase.
文摘Using research results on physical properties of primary coal and rock mass, in this paper, response characteristic function y（t）, amplitude frequency characteristic H（ω） and phase-frequency characteristic φ（ω） were used to describe dynamic response of stress impulse signal. At the same time, with the help of computer simulation analogue technique, applying these characteristic parameters to research the rock-burst forecasting, this paper deduced response characteristic function model. This function model is valuable for rockburst tendency test. According to these researches, develops monitoring recording system to acquire rockburst precursor signals. This system can monitor stress impulse signal dynamically and continuously. By applying the forecast information systems can forecast rockburst successfully.
基金Projects 40771143 supported by the National Natural Science Foundation of China2007AA12Z162 by the Hi-tech Research and Development Program of China
文摘In this study,analyses are conducted on the information features of a construction site,a cornfield and subsidence seeper land in a coal mining area with a synthetic aperture radar (SAR) image of medium resolution. Based on features of land cover of the coal mining area,on texture feature extraction and a selection method of a gray-level co-occurrence matrix (GLCM) of the SAR image,we propose in this study that the optimum window size for computing the GLCM is an appropriate sized window that can effectively distinguish different types of land cover. Next,a band combination was carried out over the text feature images and the band-filtered SAR image to secure a new multi-band image. After the transformation of the new image with principal component analysis,a classification is conducted selectively on three principal component bands with the most information. Finally,through training and experimenting with the samples,a better three-layered BP neural network was established to classify the SAR image. The results show that,assisted by texture information,the neural network classification improved the accuracy of SAR image classification by 14.6%,compared with a classification by maximum likelihood estimation without texture information.
