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The Technique Research about Prediction of Sulfide Ores Spontaneous Combustion Based on Network

Author: YangJuanJuan
Tutor: LiShuGang
School: Xi'an University of Science and Technology
Course: Safety Technology and Engineering
Keywords: Sulfur ore Spontaneous Combustion Neural Networks Forecast Prevention
CLC: TD752.2
Type: Master's thesis
Year: 2008
Downloads: 100
Quote: 6
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Abstract


Incidents of spontaneous combustion of sulfur ore the sulfur mine one of major disasters , often caused by the damage of injury to personnel and equipment , facilities , and seriously affected the normal production of the mine . Therefore , strengthening sulfur ores spontaneous combustion risk prediction technology , has a positive role to improve the sulfur mine safety production situation . Based on the analysis of sulfur ore bio - oxidation mechanism , electrochemical mechanism , chemical thermodynamic mechanism and the basis of the physical mechanism proposed mine oxygen compound mechanism . Temperature four aspects of the mechanism from physical adsorption , chemisorption , chemical reaction , and heat accumulation , a systematic analysis of the reasons for the spontaneous combustion of the sulfur-containing ore , spontaneous combustion dangerous laid a theoretical foundation for predicting sulfur ore . And sulfur ore Spontaneous combustion characteristics and spontaneous combustion influencing factors studied , fault tree analysis diagram , draw out the basic event to identify the impact of sulfur ore spontaneous combustion , spontaneous combustion of sulfur-containing ore prediction, prevention work basis . Application of highly nonlinear relationship between BP network neural network , the geological conditions of the influencing factors , the three aspects of the spontaneous combustion tendency temperature selected from the spontaneous combustion of sulfur-containing ore seam thickness , seam inclination , the oxidation rate of weight gain , and the ignition temperature of 4 risk level as indicators as sample input to spontaneous combustion of sulfur ore output , and establish a BP neural network model , predicted spontaneous combustion risk level of sulfur ore , and sulfur ore spontaneous combustion risk prediction , a systematic study of the techniques and methods of prevention of spontaneous combustion of sulfur-containing ore appropriate precautions and applied engineering examples .

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CLC: > Industrial Technology > Mining Engineering > Mine safety and labor protection > Mine fire > Mine Fire > Internal fire and prevention
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