基于声发射法的煤与瓦斯突出预测研究

发布时间：2018-06-29 03:29

本文选题：煤与瓦斯突出 + AE声发射　；参考：《辽宁工程技术大学》2013年硕士论文

【摘要】：目前煤矿产业急需解决的首要问题是煤矿安全性问题，其中煤与瓦斯突出是煤矿安全生产最主要的自然灾害之一，是造成人员伤亡、影响生产效率的主要因素。在发生煤与瓦斯突出之前一般都具有前兆显现，其中煤岩声发射信号是瓦斯突出之前明显的预兆信息之一，本文通过对瓦斯突出机理的研究，提出了一种新的方法—温度判断法，，用以辅助判断瓦斯突出，其次根据AE声发射在煤层中传播特征规律及与煤层突出的危险性关系指标，提出相对能率和相对事件率指标。针对矿井信号复杂，对信号提取是重中之重，根据声发射信号的特点，引入小波分析理论，作为一种数学工具来提取和处理非平稳信号，考虑到声发射信号通常混有噪声并且相当微弱，而且现今消噪技术也不能很好的让声发射监测得以精确预报，因此本论文提出基于小波分析的声发射信号消噪方法，系统设计了一种以小波函数为基底函数的新型BP神经网络，并通过试验计算和计算机仿真证明了此思想的优越性，将其应用于煤与瓦斯突出危险性预测上。在前面几章研究的基础上，文章最后设计一个声发射信号处理分析工具—集成化声发射信号处理平台，主要介绍信号处理平台的开发工作和模块功能的实现。
[Abstract]:At present, coal mine safety is the most important problem in coal mine industry, in which coal and gas outburst is one of the most important natural disasters in coal mine production safety, and it is the main factor that causes casualties and affects production efficiency. Usually there are precursors before coal and gas outburst, among which the acoustic emission signal of coal and rock is one of the obvious precursory information before gas outburst. In this paper, the mechanism of gas outburst is studied. A new method, temperature judgment method, is put forward to judge gas outburst. Secondly, according to the characteristics of AE propagation in coal seam and the dangerous relation index between AE and coal seam outburst, the relative energy rate and relative event rate index are put forward. According to the characteristics of acoustic emission signals, wavelet analysis theory is introduced to extract and process non-stationary signals as a mathematical tool. Considering that acoustic emission signals are usually mixed with noise and very weak, and the current de-noising technology is not able to accurately predict acoustic emission monitoring, this paper proposes a method of acoustic emission signal de-noising based on wavelet analysis. A new BP neural network based on wavelet function is designed in this paper. The superiority of this idea is proved by experimental calculation and computer simulation. It is applied to predict the danger of coal and gas outburst. On the basis of the research in the previous chapters, an integrated acoustic emission signal processing platform is designed in the end of this paper. The development of the signal processing platform and the realization of the module function are mainly introduced.
【学位授予单位】：辽宁工程技术大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TD713.2

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