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采空区岩体声发射信号的多重分形分析及响应特征研究

Study on Multiple Fractal Analysis and Response Characteristics of Acoustic Emission Signals from Goaf Rock Bodies.

作者信息

Xie Xuebin, Li Shaoqian, Guo Jiang

机构信息

School of Resources and Safety Engineering, Central South University, Changsha 410083, China.

出版信息

Sensors (Basel). 2022 Apr 2;22(7):2746. doi: 10.3390/s22072746.

Abstract

Based on the actual monitoring data of the acoustic emission (AE) ground pressure monitoring and positioning system, this paper introduces fractal theory and the multifractal detrended fluctuation analysis (MF-DFA) method to estimate the waveform multifractal spectrum of goaf rock acoustic emission signals and investigate multifractal time-varying response characteristics. The research results show that the wavelet hard thresholding method has the best noise reduction effect on the original signal, and the box counting dimension has a strong waveform identification effect. Before deformation damage occurs, fractal spectral width Δ shows an increase and then decrease and the fluctuation scale factor Δ() decreases and then increases. When damage occurs, fractal spectral width Δ decreases and then stabilizes and concentrates. Simultaneously, the fluctuation scale factor Δ() keeps decreasing until the lowest point, and then shows an increasing trend until it reaches a stable state. This study is of great significance to the stability evaluation and disaster early warning of mine goaf.

摘要

基于声发射(AE)地压监测与定位系统的实际监测数据,本文引入分形理论和多重分形去趋势波动分析(MF-DFA)方法,以估计采空区岩石声发射信号的波形多重分形谱,并研究多重分形时变响应特征。研究结果表明,小波硬阈值法对原始信号的降噪效果最佳,盒维数具有较强的波形识别效果。在变形破坏发生前,分形谱宽度Δ呈先增大后减小的趋势,波动尺度因子Δ()呈先减小后增大的趋势。当破坏发生时,分形谱宽度Δ先减小后稳定并集中。同时,波动尺度因子Δ()持续减小至最低点,然后呈上升趋势直至达到稳定状态。本研究对矿山采空区的稳定性评价和灾害预警具有重要意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f7ef/9002906/ed7e8b7b53de/sensors-22-02746-g001.jpg

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