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P-wave arrival time pickup method based on long and short time windows and AR model variance surge effect

An AR model and technology of long and short time windows, applied in the field of signal processing, can solve problems such as poor recognition effect, poor anti-noise, low signal-to-noise ratio, etc., and achieve the effect of high picking accuracy, good stability, and strong applicability

Pending Publication Date: 2021-03-19
CHONGQING UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] When the P wave arrives, it is initially picked up manually. Although the accuracy of the pick-up is guaranteed, the efficiency is too low.
Therefore, scholars at home and abroad have successively proposed a series of P-wave arrival time automatic picking methods to improve the picking efficiency, but they all have their own limitations: the length of the long and short time windows and the selection of the threshold in the STA / LTA algorithm directly affect the Recognition effect, and when the signal-to-noise ratio is low or the initial movement is not obvious, the recognition effect is poor; wavelet transform is easy to fall into the limitation of Fourier analysis spectrum leakage; high-order statistical methods have higher requirements for waveform clarity; PAI-S / K method introduces The function of kurtosis and skewness of microseismic waveform is simple and fast to calculate, but the anti-noise is not good; the calculation of fractal dimension method and neural network method takes a long time
The AR-AIC algorithm method based on the autoregressive model (AR model) has high picking accuracy, but the dual-sequence AR model leads to low picking efficiency, and the picking effect is unstable for low signal-to-noise ratio and spike signals

Method used

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  • P-wave arrival time pickup method based on long and short time windows and AR model variance surge effect
  • P-wave arrival time pickup method based on long and short time windows and AR model variance surge effect
  • P-wave arrival time pickup method based on long and short time windows and AR model variance surge effect

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Embodiment 1

[0040] see figure 1 , the present embodiment discloses a P-wave arrival picking method based on the long-short time window and the AR model variance surge effect, including the following steps:

[0041] 1) Intercept the signal waveform data x(n) to be picked up from the microseismic signal. where n=1, 2, . . . , N. N is the number of sampling points of the microseismic signal. N=1000~2000.

[0042] 2) The STA / LTA (short term averaging / long term averaging, energy ratio of long and short time windows) method is used to locate the interval X' including the arrival time of the P wave (primary wave).

[0043] 2.1) Given a sliding long time window, take a short time window within the long time window. The end points of the long and short time windows coincide. The length of the short time window is ST, usually 8-15, and the length of the long time window is LT, usually (5-10) ST. The change of the signal amplitude is reflected by the ratio of the short-time window signal avera...

Embodiment 2

[0067] This embodiment discloses a P-wave arrival time picking method based on long and short time windows and the variance surge effect of the AR model, including the following steps:

[0068] 1) Intercept the signal waveform data x(n) to be picked up from the microseismic signal. Wherein, n=1, 2, . . . , N. N is the number of sampling points of the microseismic signal. N=1000~2000.

[0069] 2) Use the STA / LTA (short term averaging / long term averaging, long and short time window energy ratio) method to locate the interval X' including the arrival time of the P wave (primary wave).

[0070] 3) Pick the VIC autocorrelation minimum point of X' as the arrival time of P wave.

Embodiment 3

[0072] This embodiment discloses a P-wave arrival pickup device including:

[0073] The message exchange module is used for receiving and intercepting microseismic signals.

[0074] Memory, used to store computer programs.

[0075] The processor is configured to execute the computer program stored in the memory to implement the P-wave arrival time picking method as described in any one of Embodiment 1 or 2.

[0076] The data sharing module is used to report the arrival time of the P wave.

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Abstract

The invention provides a P-wave arrival time pickup method based on long and short time windows and an AR model variance surge effect. The method comprises the steps of extracting micro-seismic signalwaveform data, preliminarily judging the interval of P wave arrival time, picking up the P wave arrival time and the like. According to the method, the interval where the P wave arrives and the auto-regression model variance surge effect caused by the difference between the signal and the noise level are preliminarily judged by means of the STA / LTA method, the pickup error rate is greatly reduced, the pickup efficiency is improved, and meanwhile the P wave pickup stability is also enhanced. The method has the advantages of being high in picking precision, high in speed, good in stability, high in applicability and the like.

Description

technical field [0001] The invention relates to the technical field of signal processing, in particular to a method for picking up the arrival time of a P wave based on a long and short time window and the variance surge effect of an AR model. Background technique [0002] With the rapid development of my country's economic construction, energy mining and storage projects, tunnel projects, and deep burial of nuclear waste projects are being built continuously, and ground pressure disasters such as mine earthquakes and rock bursts have increased sharply, which has seriously threatened the safety of people's lives and properties. Disasters such as explosions have become an urgent research topic. As an effective monitoring technology, microseismic monitoring has been widely used in the early warning of mine earthquakes, rock bursts and other disasters. Microseismic monitoring mainly includes waveform identification, phase picking, source location, focal mechanism analysis, and ...

Claims

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Application Information

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IPC IPC(8): G01V1/28G01V1/36
CPCG01V1/282G01V1/36
Inventor 王桂林梁锋孙帆张亮吴曙光文海家陈建功谢强许明周小平杨海清
Owner CHONGQING UNIV
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