The processing and interpretation of microseismic (MS) signals are the basis for obtaining source information of MS events in rock engineering. However, MS signal processing is subjective and time-consuming, in which different strategies have to be empirically adopted to cope with different issues. To facilitate MS signal analysis, this study proposes an entirely data-driven method based on local mean decomposition (LMD), which has been applied in various signal processing fields. Through some numerical experiments, the superiorities (e.g., smaller reconstruction errors and fewer sifting iterations) of the proposed method over other methods are demonstrated, and the proposed method is identified as an effective filtering and frequency analysis tool to process recorded MS signals. Our analysis results show that the proposed method can effectively remove interfering noise existing in MS signals collected from the Lianghekou hydropower station during underground rock excavation. Moreover, the proposed method can be employed to analyze the frequency revolution features of MS signals before and after rock mass failure. In addition, it is found that MS signal frequency migrates to a low-frequency range when approaching rock failure, which can be regarded as an early warning indicator of rock instability. The proposed method is believed to facilitate MS monitoring and offer a new clue to conduct MS signal processing and interpretation.

微震信号的处理和解释是岩石工程中获取微震事件震源信息的基础。然而，MS 信号处理是主观且耗时的，其中必须根据经验采用不同的策略来应对不同的问题。为了促进 MS 信号分析，本研究提出了一种基于局部均值分解 (LMD) 的完全数据驱动的方法，该方法已应用于各种信号处理领域。通过一些数值实验，证明了所提出的方法相对于其他方法的优越性（例如，较小的重建误差和更少的筛选迭代），并且所提出的方法被认为是处理记录的MS信号的有效滤波和频率分析工具。分析结果表明，该方法能有效去除地下岩石开挖过程中两河口水电站采集的MS信号中存在的干扰噪声。此外，该方法可用于分析岩体破坏前后MS信号的频率旋转特征。此外，发现MS信号频率在接近岩石破坏时向低频范围迁移，可作为岩石失稳的预警指标。所提出的方法被认为有助于 MS 监测，并为进行 MS 信号处理和解释提供了新线索。该方法可用于分析岩体破坏前后MS信号的频率旋转特征。此外，发现MS信号频率在接近岩石破坏时向低频范围迁移，可作为岩石失稳的预警指标。所提出的方法被认为有助于 MS 监测，并为进行 MS 信号处理和解释提供了新线索。该方法可用于分析岩体破坏前后MS信号的频率旋转特征。此外，发现MS信号频率在接近岩石破坏时向低频范围迁移，可作为岩石失稳的预警指标。所提出的方法被认为有助于 MS 监测，并为进行 MS 信号处理和解释提供了新线索。