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含水砂岩在破坏过程中的频谱特性分析 被引量:25

Spectral character analysis of sandstone under saturation condition in rupture procedure
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摘要 通过对含水砂岩进行单轴加载声发射试验,获取声发射信号。对整个加载过程声发射信号进行FFT变换,发现随着加载地进行,声发射信号的峰值频率由60 kHz下降到40 kHz,平均主频比自然状态下的砂岩平均主频降低了1 kHz;通过分析能量和岩石声发射事件数之间的关系,发现能量与对应声发射事件数之间的比值越大,说明能量是由较大的破裂导致的,而能量值与对应声发射事件数之间的比值越小(数量级在104以下),说明能量是由多个小破裂同时产生积聚而成的;用Welch法做功率谱估计,发现得到的声发射信号其功率谱大致分为A、B两种,B类功率谱对应信号的相位突变性强。选取一些较大能量信号,计算这些信号出现之前的B类型功率谱出现的几率,发现越接近破裂出现B类型功率谱的几率越大。研究结果为分析岩石破裂全过程的声发射特性提供了一条新的思路,也为声发射应用于岩石破裂失稳预报奠定了一定的工作基础。 The acoustic emission(AE) signals are obtained through uniaxial load tests on sandstones. Performing the fast Fourier transform(FFT) on AE signals, the analysis result shows that the peak frequency of AE signals reduces from 60 kHz to 40 kHz as load process proceeding, and the average peak frequency is 1 kHz lower than that of in natural situation. By analyzing the relationship between energy and acoustic emission events of rock, it is found that the bigger ratio of energy to acoustic emission events means the energy comes from the deeper degree rock fracture, the smaller ratio(order of magnitude 〈104 ) means that energy is accumulated by some lighter degree rock fractures. The power spectral density (PSD) of AE signals is done with Welch method; it is found that the power spectrum of AE signals can be divided generally into two classes(Type A and Type B), the phase of Type B has obvious discontinuity. Some larger-energy signals are chosen, probability of Type B power spectrum before these larger-energy signals is computed; it is found that the closer to the rupture time, the greater the probability of the type B. The research results provide a new way to analyze the AE properties of the whole rupture procedure of rock, and lay a certain working foundation for the application of acoustic emission in the prediction of rupture and instability.
出处 《岩土力学》 EI CAS CSCD 北大核心 2013年第6期1574-1578,共5页 Rock and Soil Mechanics
基金 国家自然科学基金资助项目(No.51174071) 河北省自然科学基金资助项目(No.E2012209047)
关键词 声发射信号 主频 破裂 能量 Welch功率谱 acoustic emission signal dominant frequency fracture energy Welch power spectrum
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