發(fā)布時(shí)間：2018-05-01 19:38

  本文選題：開(kāi)采擾動(dòng) + 動(dòng)力災(zāi)害��； 參考：《武漢科技大學(xué)》2015年碩士論文

【摘要】：地下礦山的采礦作業(yè)正逐漸進(jìn)入深部開(kāi)采階段，此時(shí)因開(kāi)采擾動(dòng)引起的動(dòng)力災(zāi)害也慢慢增多，，其中包括巖爆和流變等高應(yīng)力問(wèn)題就非常突出，它是影響礦山安全生產(chǎn)非常重要的動(dòng)力災(zāi)害表現(xiàn)形式，會(huì)導(dǎo)致井下作業(yè)人員的傷亡和財(cái)產(chǎn)損失進(jìn)一步加大。 首先，對(duì)地下礦山開(kāi)采擾動(dòng)動(dòng)力災(zāi)害的典型表現(xiàn)形式和破壞機(jī)制進(jìn)行了理論研究，比較了不同動(dòng)力災(zāi)害監(jiān)測(cè)方法的優(yōu)缺點(diǎn)，選取了微震監(jiān)測(cè)技術(shù)作為動(dòng)力災(zāi)害監(jiān)測(cè)的手段并說(shuō)明了其工作的原理。然后，結(jié)合地下礦山實(shí)際開(kāi)采作業(yè)的情況，在對(duì)不同系統(tǒng)比較的基礎(chǔ)上，選擇分布式與集中式相結(jié)合的微震監(jiān)測(cè)系統(tǒng)，完成系統(tǒng)的總體設(shè)計(jì)方案；運(yùn)用模塊化和層次化思想對(duì)系統(tǒng)軟件進(jìn)行設(shè)計(jì)與開(kāi)發(fā)，從而讓微震監(jiān)測(cè)系統(tǒng)能夠進(jìn)行實(shí)時(shí)在線的微震數(shù)據(jù)采集、處理和分析的功能。 其次，運(yùn)用小波包分析原理將微震監(jiān)測(cè)系統(tǒng)采集到的微震信號(hào)進(jìn)行一系列的波形分析、波形變換、波形綜合、波形識(shí)別的加工處理，從中獲取時(shí)頻特征信息，就能對(duì)該事件震源類型進(jìn)行區(qū)分和判斷。 最后，借助支持向量機(jī)的方法建立微震事件分類器模型和微震預(yù)測(cè)模型，不斷優(yōu)化微震事件的自動(dòng)識(shí)別學(xué)習(xí)能力，為后期微震數(shù)據(jù)庫(kù)的完善提供更多有效數(shù)據(jù)，通過(guò)該數(shù)據(jù)庫(kù)進(jìn)行微震事件的實(shí)時(shí)回歸預(yù)測(cè)，為開(kāi)采擾動(dòng)動(dòng)力災(zāi)害的實(shí)時(shí)預(yù)測(cè)提供科學(xué)依據(jù)。
[Abstract]:Mining operations in underground mines are gradually entering the stage of deep mining. At this time, the dynamic disasters caused by mining disturbances are gradually increasing, including the problems of high stress such as rock burst and rheology. It is a very important form of dynamic disaster affecting mine safety, which will cause casualties and property losses to further increase. Firstly, the typical manifestation and failure mechanism of disturbance dynamic disaster in underground mining are studied theoretically, and the advantages and disadvantages of different dynamic disaster monitoring methods are compared. The microseismic monitoring technology is selected as the means of dynamic disaster monitoring and the principle of its work is explained. Then, combined with the actual mining operation of underground mines, on the basis of comparison of different systems, the microseismic monitoring system combined with distributed and centralized is selected to complete the overall design of the system. The system software is designed and developed by modularization and hierarchy, so that the microseismic monitoring system can collect, process and analyze the microseismic data in real time and online. Secondly, a series of waveform analysis, waveform transformation, waveform synthesis, waveform recognition processing are carried out by using wavelet packet analysis principle to obtain time-frequency characteristic information from the microseismic signal collected by the microseismic monitoring system. The source type of the event can be distinguished and judged. Finally, the support vector machine (SVM) method is used to establish the microseismic event classifier model and the microseismic prediction model, and to continuously optimize the learning ability of automatic recognition of microseismic events, so as to provide more effective data for the improvement of microseismic database in the later period. The real-time regression prediction of microseismic events can provide scientific basis for real-time prediction of mining disturbance dynamic disasters.
【學(xué)位授予單位】：武漢科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TD326

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