S-wave arrival time identification method based on wavelet transform covariance model

Abstract

The invention provides an S-wave arrival time identification method based on a wavelet transform covariance model. According to the method, noise reduction processing is firstly carried out on an input wave signal, then continuous wavelet transformation is carried out on the signal after noise reduction, then covariance analysis, improved Rectilinity function processing and secondary filtering are sequentially carried out on data after continuous wavelet transformation, and finally, the arrival time of an S wave is determined according to a set threshold value. The system comprises the following modules: a micro-seismic signal excitation module, a micro-seismic signal receiving module and an upper computer. According to the S-wave arrival time identification method and system based on the wavelet transform covariance model, the process of the method is clear and easy to understand, the method can be used for S-wave arrival time identification of a single-component sensor signal, and the S-wave arrival time identification precision is high; the system is simple in structure, can be used for engineering field application, and solves the problem that the S wave arrival time of a single-component sensor is difficult to identify in mine practical application.

Description

technical field [0001] This patent belongs to the technical field of microseismic monitoring, and in particular relates to an S-wave arrival time recognition method based on a wavelet transform covariance model. Background technique [0002] Microseismic monitoring technology is a technical method to monitor the stability of engineering rock mass by using the elastic waves (P wave and S wave) released during the stress deformation and failure process of rock mass. Because of its advantages of real-time uninterrupted, three-dimensional monitoring, and accurate spatial prediction, it is widely used in mine microseismic, oil and gas field exploitation, tunnel engineering, water conservancy and hydropower engineering and other fields. The general process of microseismic monitoring technology research is the optimal layout of station network, microseismic waveform identification, P wave and S wave arrival time picking, source location, source mechanism analysis, mine microseismic...

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Problems solved by technology

However, it should be pointed out that although scholars at home and abroad have achieved more research results in S-wave picking, there are still the following problems to be solved urgently: First, most methods still use three-component mine seismic signals for S-wave automatic picking, However, in the actual application of mines, there are many single-component sensors installed, so these methods are difficult to apply; second, compared with natural earthquakes, mine microseisms have a shorter duration, a smaller distribution range, and are mostly in shallow areas, and are less affected by surface inhomogeneity. Large, resulting in the separation of P wave and S wave is not obvious, and it is more difficult to identify

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