Prediction of self-heating process of sulfide ore heap using trend and chaos prediction model

被引：1
|
作者：
Pan, Wei [1 ,2 ]
Wu, Chao [1 ]
Li, Zijun [1 ]
Li, Ming [1 ]
机构：
[1] School of Resources and Safety Engineering, Central South University, Changsha,410083, China
[2] Key Laboratory of Mine Thermo-Motive Disaster and Prevention of Ministry of Education, Liaoning Technical University, Fuxin,123000, China
来源：
Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) | 2015年 / 46卷 / 03期
关键词：
Temperature distribution - Sulfur compounds - Spontaneous combustion - Ores;
D O I：
10.11817/j.issn.1672-7207.2015.03.019
中图分类号：
学科分类号：
摘要：
In order to precisely predict the temperature variations of sulfide ore heap during the self-heating process, the trend model for temperature prediction was established according to the temperature rising characteristics of sulfide ore heap. The chaos prediction model for difference series of trend prediction was established by means of the adding-weight one-rank local-region method after chaotic identification. Then, the trend and chaos prediction model was established by the superposition of these two models and the temperature of simulated ore heap was predicted. The results show that the relationship between temperature of sulfide ore heap and time accords with characteristics of exponential model. The exponential model can be used to predict temperature variation trend of the ore heap. The correlation dimension of difference series of trend prediction is fraction and its Kolmogorov entropy is greater than 0, which means that there are chaos in series of difference trend predictions, therefore, chaos can be predicted by using chaos prediction model. The result of prediction shows that the trend and chaos prediction model is very precise. As a result, it can be used to predict spontaneous combustion of sulfide ore heap during early stages. ©, 2015, Central South University of Technology. All right reserved.
引用
收藏
页码：901 / 907
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