Author_Institution :
Achademy of Mech.-Electr. Eng., Beijing Inst. of Technol., Beijing, China
Abstract :
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
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Confronts with the high frequency of coal gas accident in recent years, to apply better evaluation and prediction on gas omission for coal beds, and to supply theory basis and decision making for the safe production and disaster prediction of working underground in coal. Based on the research of existed methods and technique, this paper firstly points out the problems of present prediction ways for gas omission. Then sets up a new dynamic prediction model for the coal gas omission by using the unascertained C-clusters. Takes some coal beds of Dong pang coal mine as example, according to the coal bed characteristic and geology of this mine, refers to related literatures and the accident cards of it, six factors which mainly influence the gas omission of the coal beds are picked up, they are the gas content, the coal embedding depth, the coal thickness, the average output of working face, the geology characteristic and the coal ash content. Also through collecting the actual data of each coal beds in this mine, by applying model analysis, fully taking the relationship between each factors and gas omission into consideration, the center for each classification is given, and the subject degree of each sample belonged to each classification is gotten, at last, the risk degrees of gas omission in this mine coal beds are confirmed, the validity and feasibility of the model are justified, and the improving measures and suggestion are supplied. The study result indicates that the research made in this paper can not only g- eatly simplify the prediction process for coal bed gas omission, but also increase the prediction veracity and boost up the measures pertinence. Thus supplying a new intellectualized method for the coal bed gas omission, also offers important basis for the mine design and gas management.
Keywords :
accidents; coal; disasters; mining industry; occupational safety; risk analysis; Dong pang coal mine; coal ash content; coal beds; coal gas accidents; decision making; disaster prediction; gas omission prediction; risk degrees; safe production; unascertained C clusters; Accidents; Coal; Coal mining; Fuel processing industries; Geology; Geophysics; Predictive models; the gas omission prediction; the influencing factors pick-up; the prediction system research; the unascertained C—clusters model establishment;
