Application of Multiple Regression Analysis in Coal Spontaneous Combustion Prediction
Spontaneous combustion( sponcom) of coal is an important problem in mining and storage, in terms of both safety and economics. In order to take suitable measures to prevent coal fire, the spontaneous combustion stage( SCS) should be known at first. Through the proximate analysis of the composition which determines SCS most in different coal samples, and the SCS that is measured by experiment, by means of the mathematical model of multiple regression analysis, we set up a regression equation which is to predict the SCS. The significance of the equation and its coefficient are tested in addition, and residual analysis is carried out to identify the appropriateness of the equation. The equation reflects the relationship between coal self-ignition duration and ash, volatilization, sulphur and oxygen directly. And the SCS can be predicted by the equation.
coal spontaneous combustion multiple regression analysis prediction heat
DENG Jun XING Zhen MA Li
Xian University of Science and Technology, Xian 710054, China Key Laboratory of Western Mine and Hazard Prevention, Ministry of Education of China, Xian 710054, China
国际会议
The 2nd International Conference on Mine Safety and Environment Protection(第二届采矿、安全与环境保护国际会议)
西安
英文
105-109
2011-10-10（万方平台首次上网日期，不代表论文的发表时间）