岩石破裂过程中的微震及声发射监测技术已广泛应用于岩石工程领域。P波到时自动拾取是进行岩石破裂源定位和矩张量反演等声发射(AE)技术研究的基础与关键,为提高到时拾取精度,分析Allen拾取法、Baer-Kradolfer改进拾取法、高阶统计量拾取法以及AR-AIC拾取法对模拟正弦信号振幅、频率与相位突变识别的敏感性。基于加拿大原子能公司地下实验室(URL)的隧道密封试验现场监测数据,对比分析几种拾取方法对不同信噪比(SNR)水平的信号拾取结果,研究表明。Allen拾取法、Baer-Kradolfer拾取法和高阶统计量拾取法具有更广的信噪比识别范围,特别对低信噪比水平的信号具有较强识别能力,进而提出对AR-AIC拾取法的改进思路。利用改进AR-AIC拾取法对真实声发射信号进行到时拾取,得到影响拾取精度的关键因素以及适用于工程尺度的局部范围的声发射信号的合理参量,进而成功对信噪比水平小于10的声发射信号进行自动到时拾取,研究认为高阶统计量法中的峰度拾取法是应用改进AR-AIC法初拾阶段的最优方法,其自动拾取与人工识别结果时差小于5μs的准确率为94%,表明提出的改进AR-AIC拾取法在实际应用中,特别是对低信噪比水平信号进行到时拾取具有良好的适用性。 Microseismic and acoustic emission monitoring techniques during rock failure have been widely used in rock engineering. P wave pick-up time is the basis and key to study the acoustic emission (AE) technique such as the location of rock rupture source and the inversion of moment tensor. In order to improve the time-to-pick accuracy, we analyze the Allen Pickup, Baer-Kradolfer Improved Pickup, Sensitivity of high-order statistics pick-up and AR-AIC pick-up to the identification of sinusoidal signal amplitude, frequency and phase mutations. Based on field monitoring data from the tunnel seal test conducted by the Canadian Atomic Energy Corporation’s Underground Laboratory (URL), the signal pick-up results of several pick-up methods for different signal-to-noise ratio (SNR) levels are compared and analyzed. Allen pick-up method, Baer-Kradolfer pick-up method and high-order statistic pick-up method have a wider range of signal-to-noise ratio recognition, especially for low signal-to-noise ratio signals. Improve thinking. By using the improved AR-AIC pick-up method to pick up the real acoustic emission signal on time, the key factors affecting the pick-up accuracy and the reasonable parameters of the acoustic emission signal suitable for the local range of the engineering scale are obtained, and the signal to noise ratio of less than 10 It is considered that the kurtosis picking method in high-order statistics method is the best method to improve the initial stage of AR-AIC method. The accuracy of the time-difference of automatic picking-up and manual recognition is less than 5μs Is 94%, which shows that the proposed improved AR-AIC pick-up method has good applicability in practical application, especially for picking up the signal with low signal-to-noise ratio.