【摘要】：煤礦井下環(huán)境復雜且地質(zhì)結(jié)構多樣,受采挖過程及自然狀況的影響,煤礦井下的煤巖動力災害時有發(fā)生,對財產(chǎn)和人身安全帶來嚴重威脅。因此尋找有效的預測預警手段是十分必要的。煤巖動力災害的發(fā)生具有突發(fā)性和多向性,煤巖體因災害破裂變形的過程中會釋放多種前兆物理信息。這些前兆信息各有特點但都復合一定規(guī)律,為災害的預防提供了新方法。對此,本文選取受載煤巖破裂過程釋放的電荷感應信號、電磁輻射信號、紅外溫度信號作為預測物理信息,詳細論述了三種信號在煤巖受載破裂時的產(chǎn)生機理,并針對信號的固有特征設計制作信號采集模塊,搭建了基于DSP電荷感應、電磁輻射和紅外輻射溫度的多參數(shù)監(jiān)測系統(tǒng),通過串口通信與上位機LabVIEW進行人機交流。針對微弱信號的采集及優(yōu)化,改進了傳統(tǒng)小波閾值算法,并通過MATLAB對新的改進小波閾值算法進行驗證。進行煤巖受載破裂實驗,使用自主研制的煤巖多參數(shù)信號監(jiān)測系統(tǒng)全程監(jiān)測整個實驗過程。實驗結(jié)果顯示,煤巖多參數(shù)監(jiān)測系統(tǒng)可有效檢測到煤巖破裂變形時釋放的電荷感應信號、電測輻射信號、紅外溫度信號。改進的小波閾值算法對電荷感應信號和電磁輻射信號均有良好的去噪效果,為煤巖動力災害的預警開辟新的途徑。
[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.
【學位授予單位】：遼寧工程技術大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TD326

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