Structural Deformation Warning Method for Coal Mine Roadway Surrounding Rock Based on Evidential Reasoning

被引:0
|
作者
Zhang, Zehui [1 ]
Liu, Hanfeng [1 ]
Xu, Xiaobin [1 ]
Xie, Zhemin [1 ]
Huo, Huining [1 ]
Chang, Leilei [1 ]
Tao, Zhigang [2 ]
机构
[1] Hangzhou Dianzi Univ, China Austria Belt & Rd Joint Lab Artificial Intel, Hangzhou 310018, Peoples R China
[2] China Univ Min & Technol Beijing, State Key Lab Tunnel Engn, Beijing 100083, Peoples R China
基金
中国国家自然科学基金;
关键词
Deformation; Rocks; Optimization; Monitoring; Predictive models; Cognition; Reliability; Linear programming; Deformable models; Coal mining; Coal mine roadway surrounding rock; deformation prediction; early warning; evidential reasoning; optimization algorithm;
D O I
10.1109/TIM.2025.3553893
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The structural deformation measuring of coal mine roadways is an effective method to prevent dynamic disasters and avoid loss of civilian life and property. Previous studies on structural deformation early warning, however, failed on multisource uncertain data integration, dynamic adaptability, and limiting the updating ability of models. To address the above issues, this article proposes a structural deformation warning method for coal mine roadway surrounding rock based on evidential reasoning. The evidential reasoning theory is used to construct the models for predicting the deformation value and evaluating the stability level of the surrounding rock through multiple-source data fusion. Moreover, the online optimization mechanism is proposed to improve the performance of the evidence reasoning (ER)-based models. The proposed deformation warning method is evaluated on real coal mine roadway surrounding rock data. Experiment results demonstrate that the proposed method model performs well in deformation prediction with the advantage of dynamic updating and the roadway surrounding stability evaluation.
引用
收藏
页数:12
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