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Research on a dynamic early warning model for gas outbursts using adaptive fractal dimension characterization

Authors: Jie Chen; Wenhao Shi; Yichao Rui; Junsheng Du; Xiaokang Pan; Xiang Peng; Xusheng Zhao; Qingfeng Wang; Deping Guo; Yulin Zou; Dafa Yin; Yuanbin Luo

DOI: 10.1016/j.ijmst.2025.07.004Status: Verified Translated Edition
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Key Findings in This Report

• Proposes an adaptive window fractal analysis method for gas concentration data, improving local feature detection over fixed window methods. • Integrates box-counting dimension and variation metrics to establish a cross-scale dynamic warning model for gas outbursts. • Achieves dynamic threshold partitioning using membership functions and the 3r principle, enabling graded classification of the MGD index. • Validated at Shoushan #1 Coal Mine, achieving 86.9% warning accuracy and demonstrating enhanced fluctuation characteristics.