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机构地区:[1]辽宁工程技术大学电气与控制工程学院,辽宁葫芦岛125105
出 处:《计算机工程与应用》2014年第23期215-219,228,共6页Computer Engineering and Applications
基 金:辽宁省创新团队项目(No.LT2010047)
摘 要:分析即将失稳的煤岩的声发射信号,可以确定煤岩体的状态。鉴于小波较好滤波特性,而传统时延估计对声发射源定位精度受噪声影响较大。为了准确地定位声发射源,提出了Coif5小波分析和TDE相结合的方法,既解决了传统时延相关估计方法易受噪声的影响,又解决了定位精度低的问题。在实验室建立监测系统,并对煤岩体样品进行单轴压缩的实验。实验结果表明,通过基于Coif5小波的TDE算法在能实现声发射源定位的同时,也大大减小了声发射源定位的误差。将其应用到即将失稳的煤岩体的预测预报中去,将为煤矿的安全生产保驾护航。The state of coal and rock can be determined through analyzing coal rock acoustic emission signal of forthcoming instability. Wavelet has the advantage of better filter characteristic, and traditional Time Delay Estimation(TDE)has an influence on Acoustic Emission(AE) source location precision. In order to accurate location of acoustic emission source, it presents a method in this paper, which combines Coif5 wavelet analysis with TDE, the method not only resolves traditional TDE’s shortcomings, which is susceptible to noise, but also resolves low position accuracy. It establishes a monitoring system in the laboratory, and the coal and rock samples are subjected to uniaxial compression test. The test results show that the system can realize acoustic emission source positioning based on Coif5 wavelet and TDE algorithm, at the same time, it also greatly reduces the acoustic emission source localization error. It can be applied to the forecasting for upcoming instability coal-rock, it will escort for coal safety production.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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