受载煤岩破裂多参数监测系统研究与实现
发布时间：2019-02-17 12:04
【摘要】：煤矿井下环境复杂且地质结构多样,受采挖过程及自然状况的影响,煤矿井下的煤岩动力灾害时有发生,对财产和人身安全带来严重威胁。因此寻找有效的预测预警手段是十分必要的。煤岩动力灾害的发生具有突发性和多向性,煤岩体因灾害破裂变形的过程中会释放多种前兆物理信息。这些前兆信息各有特点但都复合一定规律,为灾害的预防提供了新方法。对此,本文选取受载煤岩破裂过程释放的电荷感应信号、电磁辐射信号、红外温度信号作为预测物理信息,详细论述了三种信号在煤岩受载破裂时的产生机理,并针对信号的固有特征设计制作信号采集模块,搭建了基于DSP电荷感应、电磁辐射和红外辐射温度的多参数监测系统,通过串口通信与上位机LabVIEW进行人机交流。针对微弱信号的采集及优化,改进了传统小波阈值算法,并通过MATLAB对新的改进小波阈值算法进行验证。进行煤岩受载破裂实验,使用自主研制的煤岩多参数信号监测系统全程监测整个实验过程。实验结果显示,煤岩多参数监测系统可有效检测到煤岩破裂变形时释放的电荷感应信号、电测辐射信号、红外温度信号。改进的小波阈值算法对电荷感应信号和电磁辐射信号均有良好的去噪效果,为煤岩动力灾害的预警开辟新的途径。
[Abstract]:The underground environment of coal mine is complex and the geological structure is diverse, which is influenced by the process of mining and the natural condition. The coal and rock dynamic disasters in the coal mine occur from time to time, which bring serious threat to the property and personal safety. Therefore, it is necessary to find effective means of forecasting and warning. The occurrence of coal and rock dynamic disasters is sudden and multi-directional, and many kinds of precursor physical information will be released in the process of coal and rock mass rupture and deformation. These precursory information have their own characteristics but all compound certain laws, which provides a new method for disaster prevention. In this paper, the charge-induced signal, electromagnetic radiation signal and infrared temperature signal are selected as the prediction physical information, and the generation mechanism of the three signals during the coal rock rupture is discussed in detail. A multi-parameter monitoring system based on DSP charge induction, electromagnetic radiation and infrared radiation temperature is built for signal acquisition module according to the inherent characteristics of the signal. The system communicates with the host computer LabVIEW through serial port communication. Aiming at the acquisition and optimization of weak signals, the traditional wavelet threshold algorithm is improved, and the new improved wavelet threshold algorithm is verified by MATLAB. The experiment of coal rock failure under load was carried out and the whole process of the experiment was monitored by using the self-developed multi-parameter signal monitoring system. The experimental results show that the multi-parameter monitoring system of coal and rock can effectively detect the charge-induced signal, the electric radiation signal and the infrared temperature signal when the coal and rock break and deform. The improved wavelet threshold algorithm has good denoising effect on both charge-induced signals and electromagnetic radiation signals, which opens a new way for early warning of coal and rock dynamic disasters.
【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】：2017
【分类号】：TD326
本文编号：2425143
[Abstract]:The underground environment of coal mine is complex and the geological structure is diverse, which is influenced by the process of mining and the natural condition. The coal and rock dynamic disasters in the coal mine occur from time to time, which bring serious threat to the property and personal safety. Therefore, it is necessary to find effective means of forecasting and warning. The occurrence of coal and rock dynamic disasters is sudden and multi-directional, and many kinds of precursor physical information will be released in the process of coal and rock mass rupture and deformation. These precursory information have their own characteristics but all compound certain laws, which provides a new method for disaster prevention. In this paper, the charge-induced signal, electromagnetic radiation signal and infrared temperature signal are selected as the prediction physical information, and the generation mechanism of the three signals during the coal rock rupture is discussed in detail. A multi-parameter monitoring system based on DSP charge induction, electromagnetic radiation and infrared radiation temperature is built for signal acquisition module according to the inherent characteristics of the signal. The system communicates with the host computer LabVIEW through serial port communication. Aiming at the acquisition and optimization of weak signals, the traditional wavelet threshold algorithm is improved, and the new improved wavelet threshold algorithm is verified by MATLAB. The experiment of coal rock failure under load was carried out and the whole process of the experiment was monitored by using the self-developed multi-parameter signal monitoring system. The experimental results show that the multi-parameter monitoring system of coal and rock can effectively detect the charge-induced signal, the electric radiation signal and the infrared temperature signal when the coal and rock break and deform. The improved wavelet threshold algorithm has good denoising effect on both charge-induced signals and electromagnetic radiation signals, which opens a new way for early warning of coal and rock dynamic disasters.
【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】：2017
【分类号】：TD326
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