Partition airflow varying features of chaos-theory-based coalmine ventilation system and related safety forecasting and forewarning system

作     者：Zhang Xiaoqiang Cheng Weimin Zhang Qin Yang Xinxiang Du Wenzhou 

作者机构：Key Laboratory of Ministry of Education for Mine Disaster Prevention and ControlShandong University of Sdence and TechnologyQingdao 266590China College of Mining and Safety Engineering Shandong University of Science and TechnologyQingdao 266590China 

出 版 物：《International Journal of Mining Science and Technology》 (矿业科学技术学报（英文版）)

年 卷 期：2017年第27卷第2期

页      面：269-275页

核心收录：

学科分类：0709[理学-地质学] 0819[工学-矿业工程] 0808[工学-电气工程] 081903[工学-安全技术及工程] 08[工学] 0818[工学-地质资源与地质工程] 0708[理学-地球物理学] 0807[工学-动力工程及工程热物理] 0815[工学-水利工程] 0813[工学-建筑学] 0814[工学-土木工程] 

基　　金：supported by the National Natural Science Foundation of China(Nos.51304128 and 51674158) the Natural Science Foundation of Shandong Province(No.ZR2013EEQ015) 

主　　题：Mine ventilation system Safety partition Reconstructed phase space Maximum Lyapunov exponent Chaos forecasting and forewarning 

摘      要：To realize real-time monitoring and short-term forecasting and forewarning of coalmine ventilation systems(CVS), in this paper, we first established a joint surface and underground CVS safety management system consisting of main ventilation fan, safety-partition linked passageways, and air-required locations. We then applied chaos theory to identify the air quantity and gas concentration of underground partition boundaries, and adopted a fixed data quantity, multi-step progressive, weighted first-order local-domain method to setup a chaos prediction model and a CVS safety forecasting and forewarning system formed by the normal change level, orange forewarning level, and red alarm level. We next conduct the on-field application of the system in a coalmine in Jining, Shandong, China. The results showed that (1) in the statistical scale of 5 min, the changes in both air quantity and gas concentration along CVS partition airflow boundaries were characteristic of chaos and could be used for short-term chaos prediction, and the latter was more chaotic than the former;(2) the setup chaos prediction model had a higher prediction precision and the established safety prediction system could not only predict the variation in CVS stability but also reflect the rationality of underground mining intensity. Thus, this CVS safety forecasting and forewarning system is of better application value.