A method, device, terminal and storage medium for detecting epicenter position

Abstract

The present invention discloses a method, device, terminal and storage medium for detecting epicenter position, including: obtaining the time series of seismic signals, and extracting the P wave first arrival in the time series of seismic signals according to the long and short time window algorithm; selecting the time window, and accurately picking up the extracted P wave first arrival according to the selected time window and according to the AIC criterion to obtain the accurate P wave first arrival; analyzing the accurately picked up P wave first arrival according to the principal component analysis algorithm to determine the epicenter azimuth of the seismic signal; determining the epicenter position of the time series of seismic signals according to the epicenter azimuth and seismic records of multiple stations, and outputting the determined epicenter position. The present invention accurately extracts the P wave arrival time based on the improved STA / LTA and AIC criterion method, and applies the PCA method to determine the epicenter azimuth, so as to accurately detect the epicenter position within a small range.

Description

Technical Field

[0001] The present invention relates to the field of microseismic detection technology, and in particular to an epicenter position detection method, device, terminal and storage medium. Background Art

[0002] The rapid determination of the epicenter azimuth is of great significance for earthquake early warning, earthquake rapid reporting, strong earthquake observation, underwater target positioning and other fields. The calculation of the epicenter azimuth was first performed using the amplitude ratio, and then the moving average method was proposed on this basis. The principal component analysis (PCA) method is currently the most widely used. However, in the estimation of the azimuth, whether it is the moving average method or the polarization analysis method, the calculation results of the existing methods have large errors, which are difficult to meet the needs of some application scenarios (such as high-speed railway early warning).

[0003] In addition, before applying the principal component analysis method, a reasonable time window needs to be determined. This time window usually starts from the first arrival of the P wave. Therefore, it is crucial to automatically and accurately identify the P-wave phase from the actual seismic record. The commonly used STA / LTA (short-term average to long-term average, i.e., the ratio of the short-term average value of the signal to the long-term average value of the signal) method for extracting the first arrival of the P wave, its recognition results are heavily dependent on the selection of characteristic functions, moving time window length and trigger threshold, and to a certain extent, it is impossible to achieve automatic recognition of the P-wave phase.

[0004] At the same time, the existing methods are limited to the determination of the epicenter azimuth, and the estimation of the epicenter position is only for natural earthquakes (using longitude and latitude to represent its position). No specific calculation formula is given for the epicenter position within a small scale range or the horizontal projection position of an underwater target (i.e., the epicenter position).

[0005] Therefore, the prior art needs to be improved. Summary of the invention

[0006] The technical problem to be solved by the present invention is that, in view of the defects of the prior art, the present invention provides a method, device, terminal and storage medium for detecting the epicenter position to solve the technical problem that the existing microseismic detection technology cannot detect the specific epicenter position.

[0007] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0008] In a first aspect, the present invention provides a method for detecting an epicenter position, comprising:

[0009] Acquire a time series of seismic signals, and extract the first arrival of a P wave in the time series of the seismic signals according to a long-short time window algorithm;

[0010] Select a time window, and accurately pick the extracted P wave first arrival according to the selected time window and the AIC criterion to obtain the accurate P wave first arrival;

[0011] Analyze the accurately picked P wave first arrival according to the principal component analysis algorithm to determine the epicenter azimuth of the seismic signal;

[0012] The epicenter position of the time series of the seismic signal is determined according to the epicenter azimuth and the seismic records of multiple stations, and the determined epicenter position is output.

[0013] In one implementation, the step of acquiring a time series of seismic signals and extracting the first arrival of a P wave in the time series of seismic signals according to a long-short time window algorithm includes:

[0014] Acquiring a time series of the seismic signal;

[0015] Improving the long and short time window algorithm according to a recursive algorithm to obtain an improved long and short time window algorithm;

[0016] According to the improved long-short time window algorithm, the first arrival of the P wave in the time series of the seismic signal is extracted.

[0017] In one implementation, the improving the long and short time window algorithm according to the recursive algorithm to obtain the improved long and short time window algorithm includes:

[0018] Obtaining a characteristic function for reflecting the change of the amplitude and frequency of the original signal;

[0019] The short-time window average value and the long-time window average value are calculated by the recursive algorithm according to the characteristic function to obtain the improved short- and long-time window algorithm.

[0020] In one implementation, the step of calculating the short-time window average value and the long-time window average value by using the recursive algorithm according to the characteristic function may then include:

[0021] The amplification factor is determined according to the short-time window average value.

[0022] In one implementation, extracting the first arrival of a P wave in the time series of the seismic signal according to the improved long-short time window algorithm includes:

[0023] Calculate the ratio of the long time window to the short time window according to the short time window average value, the long time window average value and the amplification factor;

[0024] Determining the detection domain of the seismic signal according to the ratio of the long to short time windows;

[0025] Screening the long-short time window ratios exceeding the detection domain, and selecting the first extreme value point from the obtained long-short time window ratios;

[0026] The first extreme point is taken as the extracted P wave first arrival.

[0027] In one implementation, the selecting of the time window and accurately picking the extracted P wave first arrival according to the selected time window and the AIC criterion to obtain an accurate P wave first arrival includes:

[0028] Taking the extracted P wave first arrival as the center, a preset time width is selected before and after as the time window;

[0029] Acquire historical earthquake records to which the AIC criterion is applied, and determine a function value of the AIC criterion according to the historical earthquake records;

[0030] Accurate picking is performed according to the function value and the time window to obtain an accurately picked P wave first arrival.

[0031] In one implementation, analyzing the accurately picked P wave first arrival according to the principal component analysis algorithm to determine the epicenter azimuth of the seismic signal includes:

[0032] Converting the accurately picked P wave first arrival into a spatial rectangular coordinate system and a spatial polar coordinate system according to the principal component analysis algorithm;

[0033] The epicenter azimuth of the seismic signal is determined based on the P-wave characteristics.

[0034] In one implementation, the converting of the accurately picked P wave first arrivals between a spatial rectangular coordinate system and a spatial polar coordinate system according to the principal component analysis algorithm includes:

[0035] According to the accurately picked P wave first arrival, the recorded seismic data is constructed into a matrix A in the order of vertical direction, north-south direction and east-west direction, and the covariance matrix of the matrix A is determined.

[0036] In one implementation, determining the epicenter azimuth of the seismic signal according to the P-wave characteristics includes:

[0037] Calculating eigenvalues ​​of the covariance matrix;

[0038] Sort the obtained eigenvalues ​​in descending order, and determine the corresponding eigenvectors according to the sorting;

[0039] The epicenter azimuth of the seismic signal is determined according to the determined eigenvector and the set angle parameter.

[0040] In one implementation, determining the epicenter position of the time series of the seismic signal according to the epicenter azimuth and seismic records of multiple stations, and outputting the determined epicenter position, includes:

[0041] Select any two stations from a plurality of stations and determine the epicenter azimuth and horizontal position of the corresponding records of the two stations;

[0042] Calculating the coordinates of the epicenter positions detected by the two stations based on the epicenter azimuths and horizontal positions recorded by the two stations;

[0043] The coordinates of all calculated epicenter positions are averaged to obtain a final epicenter position, and the final epicenter position is output.

[0044] In a second aspect, the present invention provides an epicenter position detection device, comprising:

[0045] A P wave first arrival extraction module is used to obtain the time series of seismic signals and extract the P wave first arrival in the time series of seismic signals according to a long and short time window algorithm;

[0046] The accurate picking module is used to select a time window and accurately pick the extracted P wave first arrival according to the selected time window and the AIC criterion to obtain an accurate P wave first arrival;

[0047] A principal component analysis module, used to analyze the accurately picked P wave first arrival according to the principal component analysis algorithm to determine the epicenter azimuth of the seismic signal;

[0048] The epicenter position output module is used to determine the epicenter position of the time series of the seismic signal according to the epicenter azimuth and the seismic records of multiple stations, and output the determined epicenter position.

[0049] In a third aspect, the present invention provides a terminal, comprising: a processor and a memory, wherein the memory stores an epicenter position detection program, and when the epicenter position detection program is executed by the processor, it is used to implement the operation of the epicenter position detection method as described in the first aspect.

[0050] In a fourth aspect, the present invention further provides a storage medium, which is a computer-readable storage medium, and which stores an epicenter position detection program. When the epicenter position detection program is executed by a processor, it is used to implement the operation of the epicenter position detection method as described in the first aspect.

[0051] The present invention adopts the above technical solution to achieve the following effects:

[0052] The present invention can flexibly set the STA / LTA absolute value of the processed signal according to the improved STA / LTA algorithm, so as to adapt to the quality of the signal or the signal-to-noise ratio, and is not likely to cause misjudgment or missed judgment of the first arrival of the seismic signal; and when searching for the first arrival of the P wave according to the detection threshold, the robustness of the algorithm is improved by searching for the first extreme point after exceeding the detection threshold; and the first arrival of the P wave determined based on the improved STA / LTA and AIC two-step method makes the time window length with a smaller azimuth calculation error for the seismic record used; the present invention accurately extracts the P wave arrival time based on the improved STA / LTA and AIC criterion method, and uses the PCA method to determine the epicenter azimuth, so as to accurately detect the epicenter position within a small range. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0054] Figure 1 It is a flow chart of a method for detecting an epicenter position in one implementation of the present invention.

[0055] Figure 2 This is a schematic diagram of the simulated natural earthquake record of station A.

[0056] Figure 3 This is a schematic diagram of the simulated natural earthquake record of station B.

[0057] Figure 4 Yes Figure 2 The results of applying STA / LTA to the three component records of station A in the figure.

[0058] Figure 5 Yes Figure 2 AIC calculation results for a section of the z component in the graph.

[0059] Figure 6 This is an observation diagram of the land hammer experiment.

[0060] Figure 7 is Figure 6 The three-component data of each channel obtained by hammering at the excitation point (10,20).

[0061] Figure 8 The gun point is Figure 6 (10,20) in FIG. 1 is the result of applying STA / LTA to the three-component data received by station 1.

[0062] Fig. 9 The gun point is Figure 6 (10, 20) in FIG. 8 is the result of applying STA / LTA to the three-component data received by station 8.

[0063] Fig.10 The PCA method is applied to the natural earthquake data received by stations A and B to determine the epicenter.

[0064] Fig.11 It is a functional principle diagram of a terminal in one implementation of the present invention.

[0065] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0067] Exemplary Methods

[0068] The commonly used STA / LTA method for extracting the first arrival of P waves has a recognition result that is heavily dependent on the selection of characteristic functions, moving time window length, and trigger threshold, and to a certain extent cannot achieve automatic recognition of P-wave phases. In addition, the existing methods are limited to the determination of the epicenter azimuth, and the estimation of the epicenter position is only for natural earthquakes (using longitude and latitude to represent its position). There is no specific calculation formula for the epicenter position within a small scale range or the horizontal projection position of an underwater target (i.e., the epicenter position).

[0069] In response to the above technical problems, a method for detecting the epicenter position is provided in this embodiment. The method for detecting the epicenter position is based on the improved STA / LTA and AIC (Akaike Information Criteria) criteria to accurately extract the arrival time of the P wave, and uses the PCA method to determine the epicenter azimuth. The epicenter position is determined by the epicenter azimuth determined by the two stations and the station positions, which can accurately detect the epicenter position within a small range.

[0070] like Figure 1 As shown, an embodiment of the present invention provides a method for detecting an epicenter position, comprising the following steps:

[0071] Step S100, obtaining a time series of seismic signals, and extracting the first arrival of P waves in the time series of seismic signals according to a long-short time window algorithm.

[0072] In this embodiment, the epicenter position detection method is applied in a terminal, and the terminal includes but is not limited to: a computer, a mobile terminal and other devices.

[0073] In this embodiment, the epicenter position detection method is a calculation scheme for estimating the epicenter position by combining automatic P-wave phase identification and principal component analysis. Specifically, first, the P-wave first arrival is automatically extracted according to the improved STA / LTA method; then, the AIC method is used to accurately pick up the P-wave arrival time based on the P-wave first arrival extracted in the previous step; then, based on the picked P-wave first arrival, the PCA method is used to determine the azimuth of the epicenter; finally, the above steps are repeated to process the seismic records of multiple stations, and the epicenter position can be determined by the epicenter azimuth and station position determined by two of the stations.

[0074] Specifically, in an implementation of this embodiment, step S100 includes the following steps:

[0075] Step S101, obtaining the time series of the seismic signal;

[0076] Step S102, improving the long and short time window algorithm according to a recursive algorithm to obtain an improved long and short time window algorithm;

[0077] Step S103, extracting the first arrival of the P wave in the time series of the seismic signal according to the improved long-short time window algorithm.

[0078] In this embodiment, with respect to the seismic records of multiple stations, the seismic record of one of the stations is obtained to obtain the seismic data recorded at the station; then, the time series of the seismic signals is obtained by combining the recorded seismic data in chronological order; at the same time, a recursive algorithm is used to improve the existing long-short time window algorithm, and then the improved long-short time window algorithm is used to extract the first arrival of the P wave of the seismic data recorded by the station.

[0079] Specifically, in an implementation of this embodiment, step S102 includes the following steps:

[0080] Step S102a, obtaining a characteristic function for reflecting the change of the amplitude and frequency of the original signal;

[0081] Step S102b, calculating the short-time window average value and the long-time window average value by using the recursive algorithm according to the characteristic function to obtain the improved long-short time window algorithm;

[0082] Step S102c: determining an amplification factor according to the short-time window average value.

[0083] In this embodiment, it is assumed that the time series of a seismic signal is y i(i=1,2,...,N), the time recording interval is Δt, and a characteristic function that can simultaneously reflect the changes in the amplitude and frequency of the original signal is introduced A recursive algorithm is used to calculate STA / LTA, namely:

[0084]

[0085] Among them, S i is the value of STA (Short-term average, short-term window average), L i is the value of LTA (Long-term average, long-term window average), N sta is the number of record points contained in the short-time window, N lta The number of record points included in the long time window.

[0086] In this embodiment, for natural earthquake signals, the short time window can be 0.2s, N sta It is the integer value after rounding off 0.2 / Δt. The long time window can be 2s. N lta is the integer value after rounding off 2 / Δt. For microseismic signals, if the time interval is 0.001s, N sta =50, N lta =400.

[0087] When applying the formula for recursive calculation, it is also necessary to determine the initial value S Nsta and L Nlta , respectively calculated as follows:

[0088]

[0089] In order to better identify the P wave signal with unclear initial arrival, the amplification factor α is introduced, and its calculation formula is:

[0090]

[0091] Among them, t d is the delay time, which can be 1s for natural earthquake signals and 0.1s for microseismic data. The meaning of the amplification factor α is: when the signal does not arrive, the value of α is close to 1, and when the signal arrives, an obvious mutation will occur.

[0092] Specifically, in an implementation of this embodiment, step S103 includes the following steps:

[0093] Step S103a, calculating the ratio of the long and short time windows according to the short time window average value, the long time window average value and the amplification factor;

[0094] Step S103b, determining the detection domain of the seismic signal according to the ratio of the long to short time windows;

[0095] Step S103c, screening the long-short time window ratios exceeding the detection domain, and selecting the first extreme value point from the obtained long-short time window ratios;

[0096] Step S103d, taking the first extreme point as the extracted P wave first arrival.

[0097] In this embodiment, if the ratio of STA / LTA is r, then:

[0098]

[0099] For signals with low signal-to-noise ratio, in order to avoid misjudgment or omission of the first arrival of the P wave signal, the detection domain tol of the signal is taken as:

[0100]

[0101] Then, for the STA / LTA ratio r exceeding tol, the first extreme point is searched and taken as the extracted P wave first arrival point.

[0102] The detection threshold of STA / LTA in this embodiment is no longer a fixed value, but is flexibly set according to the absolute value of STA / LTA of the processed signal, so as to adapt to the quality of the signal or the signal-to-noise ratio, and is less likely to cause misjudgment or omission of the initial arrival of the seismic signal. Therefore, the adaptability of the improved STA / LTA algorithm is significantly enhanced.

[0103] Moreover, in this embodiment, when looking for the first arrival of the P wave based on the detection threshold, it does not directly look for the first maximum point or global maximum point of STA / LTA, but looks for the first extreme point after exceeding the detection threshold. This takes into account the possibility that the value of STA / LTA may be negative, thereby improving the robustness of the algorithm.

[0104] like Figure 1 As shown, in one implementation of the embodiment of the present invention, the epicenter position detection method further includes the following steps:

[0105] Step S200, selecting a time window, and accurately picking the extracted P wave first arrival according to the selected time window and the AIC criterion to obtain an accurate P wave first arrival.

[0106] In this embodiment, since the STA / LTA method can only roughly identify the arrival time of the P wave, it is necessary to select a specific time window based on the P wave first arrival point extracted in the previous step and apply the AIC method to accurately pick the arrival time of the P wave.

[0107] Specifically, in an implementation of this embodiment, step S200 includes the following steps:

[0108] Step S201, taking the extracted P wave first arrival as the center, selecting a preset time width before and after as the time window;

[0109] Step S202, obtaining historical earthquake records to which the AIC criterion is applied, and determining a function value of the AIC criterion according to the historical earthquake records;

[0110] Step S203, accurately picking up the first arrival of the P wave according to the function value and the time window to obtain an accurately picked first arrival of the P wave.

[0111] In this embodiment, the P wave first arrival t P The time width before and after is 0.8s for natural earthquake signals and 0.2s for microseismic signals. i (i=1,2,...,L), the function value of AIC is:

[0112] AIC(k)=klg{var(x[1,k])}+(Lk-1)lg{var(x[k+1,L])}(k=2,...,L-2)

[0113] Among them, var means to find the variance, and x[m,n] means to find the variance from the record x m To record x n Therefore, the minimum point of the AIC function is the time when the P wave arrives.

[0114] In this embodiment, the STA / LTA and AIC methods used provide relevant parameters that are respectively suitable for natural earthquake signals and artificially excited microseismic signals, which broadens the applicability of the algorithm in this embodiment to data signals in different situations. Conventional STA / LTA and AIC algorithms are either only applied to natural earthquake signals or only applied to microseismic signals, which have limitations. Therefore, the algorithm in this embodiment is more complete.

[0115] like Figure 1 As shown, in one implementation of the embodiment of the present invention, the epicenter position detection method further includes the following steps:

[0116] Step S300, analyzing the accurately picked up P wave first arrival according to the principal component analysis algorithm to determine the epicenter azimuth of the seismic signal.

[0117] In this embodiment, based on the accurately picked P-wave first arrival, the PCA method is applied to determine the azimuth of the epicenter.

[0118] Specifically, in an implementation of this embodiment, step S300 includes the following steps:

[0119] Step S301, converting the spatial rectangular coordinate system and the spatial polar coordinate system for the accurately picked P wave first arrival according to the principal component analysis algorithm;

[0120] Step S302, determining the epicenter azimuth of the seismic signal according to the P-wave characteristics.

[0121] In this embodiment, since the seismic record usually includes data in one vertical direction and two horizontal directions, the seismic record in three directions can simulate the motion trajectory of the particle at the station location. The essence of the principal component analysis method (or polarization analysis method) is to convert the motion trajectory of the particle into a spatial rectangular coordinate system and a spatial polar coordinate system, so that the main direction falls on the main axis, and the azimuth is calculated using the vibration characteristics of the wave.

[0122] Specifically, in an implementation of this embodiment, step S301 includes the following steps:

[0123] Step S301a, constructing a matrix A according to the accurately picked P wave first arrival, the recorded seismic data in the order of vertical direction, north-south direction and east-west direction, and determining the covariance matrix of the matrix A.

[0124] In this embodiment, it is assumed that a period of time is recorded [t a ,t b ] does not contain other interference, t a is the arrival time of the P wave, [t a ,t b ] The number of recording points in the time is n, then the three-directional seismic records of length n (all column vectors) form a matrix A in the order of vertical, north-south, and east-west, that is:

[0125]

[0126] Furthermore, the covariance matrix of the matrix A is determined. The covariance matrix M=cov(A) of the matrix A is a 3×3 real symmetric matrix, that is:

[0127]

[0128] In this embodiment, since the covariance matrix M is a semi-positive definite matrix, its eigenvalue is a non-negative real number.

[0129] Specifically, in an implementation of this embodiment, step S302 includes the following steps:

[0130] Step S302a, calculating the eigenvalues ​​of the covariance matrix;

[0131] Step S302b, sorting the obtained eigenvalues ​​in descending order, and determining the corresponding eigenvector according to the sorting;

[0132] Step S302c, determining the epicenter azimuth of the seismic signal according to the determined eigenvector and the set angle parameter.

[0133] In this embodiment, for the above covariance matrix M, its eigenvalues ​​are calculated and arranged in descending order as [λ1λ2λ3], and the corresponding eigenvectors are [e1 e2 e3], and the angle parameter is α=tan -1 (|e 13 / e 12 |)·(180 / π), then the epicenter azimuth is:

[0134]

[0135] The starting point of the time window used by the PCA method in this embodiment is based on the P wave first arrival determined by the improved STA / LTA and AIC two-step method. For the seismic records used, the time window length with a small azimuth calculation error is 0.2 to 0.3 seconds. The starting point of the time window used to determine the azimuth using PCA in this embodiment is different from the visual estimation method used in the prior art, but is the P wave first arrival accurately determined by the improved STA / LTA and AIC two-step method.

[0136] like Figure 1 As shown, in one implementation of the embodiment of the present invention, the epicenter position detection method further includes the following steps:

[0137] Step S400, determining the epicenter position of the time series of the seismic signal according to the epicenter azimuth and the seismic records of multiple stations, and outputting the determined epicenter position.

[0138] In this embodiment, the above-mentioned steps S100 to S300 are used to process the data of the earthquake records of each station to obtain the epicenter azimuths recorded by multiple stations; then, among the epicenter azimuths corresponding to these stations, the epicenter azimuths and station positions determined by two stations are selected to determine the epicenter position.

[0139] Specifically, in an implementation of this embodiment, step S400 includes the following steps:

[0140] Step S401, selecting any two stations from a plurality of stations, and determining the epicenter azimuths and horizontal positions recorded correspondingly by the two stations;

[0141] Step S402, calculating the coordinates of the epicenter positions detected by the two stations according to the epicenter azimuths and horizontal positions recorded by the two stations;

[0142] Step S403, averaging all calculated epicenter coordinates to obtain a final epicenter, and outputting the final epicenter.

[0143] In this embodiment, the azimuth of the epicenter measured by one of the stations A is θ1 (in radians), and the horizontal position coordinates of the station A are (x1, y1). The azimuth of the epicenter measured by the other station B is θ2 (in radians), and the horizontal position coordinates of the station B are (x2, y2). Then, the equations of the straight lines passing through the two stations are:

[0144]

[0145] In the above formula, k1=cotθ1, k2=cotθ2, are the slopes of the two straight lines. The coordinates of the epicenter are obtained as follows:

[0146]

[0147] When there are n epicenter azimuths and station location coordinates measured by n stations, the obtained n(n-1) / 2 epicenter location coordinates can be averaged to serve as the final estimated epicenter location.

[0148] This embodiment provides a specific calculation formula for estimating the epicenter position in a horizontal rectangular coordinate system from the positions and azimuths of two stations. The calculation formula for the epicenter position can accurately calculate the epicenter position for natural earthquakes where the epicenter position is expressed in longitude and latitude, or for earthquake sources that excite weak signals.

[0149] The effects achieved in this embodiment are described below with specific examples.

[0150] First, for an earthquake with a focal depth of 10 km, a dip of 90°, a slip angle of 30°, a strike of 33°, a triangular focal time function, and a seismic moment of 107 dyne·cm, the epicenter is taken as the coordinate origin, the x-axis points to the east, the y-axis points to the north, and the z-axis is vertically downward. The earthquake records received under a certain crustal model are calculated at two stations A (40.2317, 30.19855, 0) and B (47.31287, -104.252274, 10) (the coordinate value unit is kilometers) (station A is as follows: Figure 2 As shown, station B is Figure 3 The calculated theoretical arrival times of P waves are 8.903s and 18.768s respectively.

[0151] First, the improved STA / LTA is used to extract the first arrival of the P wave from the three-component (x, y, z components) records (such as Figure 4As shown in the figure, the rough arrival time is 8.95s. Figure 4 The STA / LTA value is negative, but because the improved STA / LTA method detects data points whose absolute value exceeds the threshold, the algorithm can still adapt well to this situation. Next, AIC is applied to the waveform records of 0.8s before and after the 8.95s data point to accurately pick the P wave arrival time. When the AIC function value is the smallest (such as Figure 5 The time point corresponding to the minimum value is taken as the first arrival point of the P wave. The arrival times of the z, x, and y components of station A are corrected to 8.8s, 8.85s, and 8.8s respectively using AIC, as shown in Figure 2 As shown in Figure 1, this is very close to the calculated theoretical arrival time of 8.903s. Similarly, for the z, x, and y component records of station B, the P wave first arrivals extracted using the improved STA / LTA method are 18.9s, 18.85s, and 18.85s, respectively. Figure 3 As shown, after that, AIC was applied and the results were calibrated to 18.75s, 18.65s, and 18.65s, respectively, which are very close to the theoretical arrival time of 18.768s.

[0152] Next, the P wave first arrival is extracted from the hammer test records done on land. Figure 6 As shown in the figure, the positions of the hammering points and receiving points (the solid circles in the figure are the positions of the hammering points, and the hollow circles are the positions of the receiving points). The horizontal coordinates of all hammering points are 10m, and the vertical coordinates are 20m, 40m, 80m, 120m, and 150m respectively; the vertical coordinates of all receiving points are 0m, and the horizontal coordinates range from 0 to 28m. The distance between adjacent receiving points is 4m.

[0153] like Figure 7 As shown, Figure 7 The three-component data obtained by exciting at point (10,20) are shown. Due to the close distance, the P wave and S wave cannot be distinguished. Now the improved STA / LTA is applied to the three-component data received by each station; Figure 8 and Fig. 9 As shown, Figure 8 and Fig. 9 They are applied to the three-component data received by station 1 and station 8 respectively. It can be seen that the first arrival of the signal can be identified very clearly. Figure 8 and Fig. 9 The peak positions are marked, and some sub-graphs indicate the first extreme point identified by STA / LTA. For the z, x, and y component data of station 1, the P wave first arrivals extracted by STA / LTA were 1.036s, 1.041s, and 0.979s, respectively, and then corrected to 0.970s, 0.999s, and 0.962s by AIC, respectively. Figure 7The P wave first arrivals picked manually in the 2017 data are very close; for station 8, the P wave first arrivals extracted by STA / LTA are 1.068s, 1.065s, and 0.974s, and then corrected by AIC to 1.003s, 1.013s, and 0.965s, respectively, which are also consistent with Figure 7 The first arrival of the P wave picked manually is consistent with that in the figure.

[0154] It can be seen that no matter it is natural earthquake data or microseismic data, regardless of the signal-to-noise ratio, since the detection threshold is adaptively set according to the global maximum value of the STA / LTA absolute value, the improved STA / LTA can extract the first arrival of the P wave very well, and then AIC can be applied on this basis to accurately pick up the arrival time of the P wave.

[0155] With the accurate extraction of the first arrival of the P wave, the appropriate time window can be determined and the azimuth of the epicenter can be determined using the PCA method. Figure 2 and Figure 3 Taking the natural earthquake data in as an example, taking the P wave arrival time determined by the improved STA / LTA and AIC two-step method as the starting point, a 0.3s time window was selected, and the epicenter azimuths estimated by stations A and B were 51.148° and 155.642° respectively.

[0156] Finally, according to the formula, the coordinates of the epicenter are calculated to be (0.816, -1.551) km, which is 1.75 km away from the actual epicenter. It should be pointed out that the selection of the two stations is arbitrary, one of which is located at the same depth as the epicenter and the other is located on the surface; if both stations are located on the surface, the positioning accuracy is expected to be further improved; and if there are multiple station records, the epicenter position can be obtained in a statistical sense, thereby obtaining a higher positioning accuracy.

[0157] It is worth mentioning that there is also a standard method for calculating STA / LTA. At the same time, the STA / LTA value of the current point can be expressed by the characteristic function value of the subsequent data points. These are all implementation methods of the STA / LTA ratio method in the algorithm of this embodiment and fall within the protection scope of this embodiment.

[0158] This embodiment achieves the following technical effects through the above technical solution:

[0159] This embodiment uses an improved STA / LTA algorithm, which can be flexibly set according to the absolute value of STA / LTA of the processed signal, so as to adapt to the signal quality or the signal-to-noise ratio, and is not prone to misjudgment or omission of the first arrival of the seismic signal; and when looking for the first arrival of the P wave according to the detection threshold, the robustness of the algorithm is improved by looking for the first extreme point after exceeding the detection threshold; and the first arrival of the P wave determined based on the improved STA / LTA and AIC two-step method, for the seismic record used, makes the time window length with a smaller azimuth calculation error; this embodiment accurately extracts the P wave arrival time based on the improved STA / LTA and AIC criterion method, and applies the PCA method to determine the epicenter azimuth, which can accurately detect the epicenter position within a small range.

[0160] Exemplary Devices

[0161] Based on the above embodiments, the present invention further provides an epicenter position detection device, comprising:

[0162] A P wave first arrival extraction module is used to obtain the time series of seismic signals and extract the P wave first arrival in the time series of seismic signals according to a long and short time window algorithm;

[0163] The accurate picking module is used to select a time window and accurately pick the extracted P wave first arrival according to the selected time window and the AIC criterion to obtain an accurate P wave first arrival;

[0164] A principal component analysis module, used to analyze the accurately picked P wave first arrival according to the principal component analysis algorithm to determine the epicenter azimuth of the seismic signal;

[0165] The epicenter position output module is used to determine the epicenter position of the time series of the seismic signal according to the epicenter azimuth and the seismic records of multiple stations, and output the determined epicenter position.

[0166] Based on the above embodiment, the present invention further provides a terminal, whose principle block diagram can be as follows: Fig.11 shown.

[0167] The terminal includes: a processor, a memory, an interface, a display screen and a communication module connected via a system bus; wherein the processor of the terminal is used to provide computing and control capabilities; the memory of the terminal includes a storage medium and an internal memory; the storage medium stores an operating system and a computer program; the internal memory provides an environment for the operation of the operating system and the computer program in the storage medium; the interface is used to connect to external devices, such as mobile terminals and computers; the display screen is used to display corresponding information; and the communication module is used to communicate with a cloud server or a mobile terminal.

[0168] When the computer program is executed by a processor, it is used to implement the operation of an epicenter position detection method.

[0169] It can be understood by those skilled in the art that Fig.11 The principle block diagram shown in the figure is only a block diagram of a partial structure related to the scheme of the present invention, and does not constitute a limitation on the terminal to which the scheme of the present invention is applied. The specific terminal may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0170] In one embodiment, a terminal is provided, which includes: a processor and a memory, wherein the memory stores an epicenter position detection program, and the epicenter position detection program is used to implement the operation of the above epicenter position detection method when executed by the processor.

[0171] In one embodiment, a storage medium is provided, wherein the storage medium stores an epicenter position detection program, and the epicenter position detection program is used to implement the operation of the above epicenter position detection method when executed by a processor.

[0172] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and / or volatile memory.

[0173] In summary, the present invention provides a method, device, terminal and storage medium for detecting the epicenter position, the method comprising: obtaining the time series of the seismic signal, and extracting the P wave first arrival in the time series of the seismic signal according to the long and short time window algorithm; selecting the time window, and accurately picking up the extracted P wave first arrival according to the selected time window and according to the AIC criterion to obtain the accurate P wave first arrival; analyzing the accurately picked up P wave first arrival according to the principal component analysis algorithm to determine the epicenter azimuth of the seismic signal; determining the epicenter position of the time series of the seismic signal according to the epicenter azimuth and the seismic records of multiple stations, and outputting the determined epicenter position. The present invention accurately extracts the P wave arrival time based on the improved STA / LTA and AIC criterion method, and applies the PCA method to determine the epicenter azimuth, which can accurately detect the epicenter position within a small range.

[0174] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A method for detecting epicenter position, characterized in that: include: Acquire a time series of seismic signals, and extract the first arrival of a P wave in the time series of the seismic signals according to a long-short time window algorithm; Select a time window, and accurately pick the extracted P wave first arrival according to the selected time window and the AIC criterion to obtain the accurate P wave first arrival; Analyze the accurately picked P wave first arrival according to the principal component analysis algorithm to determine the epicenter azimuth of the seismic signal; Determine the epicenter position of the time series of the seismic signal according to the epicenter azimuth and the seismic records of multiple stations, and output the determined epicenter position; The method of determining the epicenter position of the time series of the seismic signal according to the epicenter azimuth and the seismic records of multiple stations, and outputting the determined epicenter position, comprises: Select any two stations from a plurality of stations and determine the epicenter azimuth and horizontal position of the corresponding records of the two stations; Calculating the coordinates of the epicenter positions detected by the two stations based on the epicenter azimuths and horizontal positions recorded by the two stations; Averaging all calculated epicenter coordinates to obtain a final epicenter position, and outputting the final epicenter position; The azimuth of the epicenter measured by one of the stations A is , The unit is radians, and the horizontal position coordinates of station A are The epicenter azimuth measured by another station B is , The unit is radians, and the horizontal position coordinates of station B are , then the equations of the straight lines passing through the two stations are: ； In the above formula, , , are the slopes of the two straight lines respectively; the coordinates of the epicenter are obtained as follows: ； When there is The epicenter azimuth and station location coordinates measured by the stations can be obtained The coordinates of the epicenter locations are averaged to obtain the final estimated epicenter location.

2. The epicenter position detection method according to claim 1, characterized in that: The step of acquiring the time series of the seismic signal and extracting the first arrival of the P wave in the time series of the seismic signal according to the long-short time window algorithm comprises: Acquiring a time series of the seismic signal; Improving the long and short time window algorithm according to a recursive algorithm to obtain an improved long and short time window algorithm; According to the improved long-short time window algorithm, the first arrival of the P wave in the time series of the seismic signal is extracted.

3. The epicenter position detection method according to claim 2, characterized in that: The step of improving the long and short time window algorithm according to the recursive algorithm to obtain an improved long and short time window algorithm includes: Obtaining a characteristic function for reflecting the change of the amplitude and frequency of the original signal; The short-time window average value and the long-time window average value are calculated by the recursive algorithm according to the characteristic function to obtain the improved short- and long-time window algorithm.

4. The epicenter position detection method according to claim 3, characterized in that: The method of calculating the short-time window average value and the long-time window average value by using the recursive algorithm according to the characteristic function comprises: The amplification factor is determined according to the short-time window average value.

5. The epicenter position detection method according to claim 4, characterized in that: The step of extracting the first arrival of a P wave in the time series of the seismic signal according to the improved long-short time window algorithm comprises: Calculate the ratio of the long time window to the short time window according to the short time window average value, the long time window average value and the amplification factor; Determining the detection domain of the seismic signal according to the ratio of the long to short time windows; Screening the long-short time window ratios exceeding the detection domain, and selecting the first extreme value point from the obtained long-short time window ratios; The first extreme point is taken as the extracted P wave first arrival.

6. The epicenter position detection method according to claim 1, characterized in that: The selecting of the time window and accurately picking the extracted P wave first arrival according to the selected time window and the AIC criterion to obtain an accurate P wave first arrival include: Taking the extracted P wave first arrival as the center, a preset time width is selected before and after as the time window; Acquire historical earthquake records to which the AIC criterion is applied, and determine a function value of the AIC criterion according to the historical earthquake records; Accurate picking is performed according to the function value and the time window to obtain an accurately picked P wave first arrival.

7. The epicenter position detection method according to claim 1, characterized in that: The method of analyzing the accurately picked up P wave first arrival according to the principal component analysis algorithm to determine the epicenter azimuth of the seismic signal includes: Converting the accurately picked P wave first arrival into a spatial rectangular coordinate system and a spatial polar coordinate system according to the principal component analysis algorithm; The epicenter azimuth of the seismic signal is determined based on the P-wave characteristics.

8. The epicenter position detection method according to claim 7, characterized in that: The converting of the spatial rectangular coordinate system and the spatial polar coordinate system for the accurately picked P wave first arrival according to the principal component analysis algorithm includes: According to the accurately picked P wave first arrival, the recorded seismic data is formed into a matrix in the order of vertical direction, north-south direction and east-west direction. , and determine the matrix The covariance matrix of .

9. The epicenter position detection method according to claim 8, characterized in that: Determining the epicenter azimuth of the seismic signal according to the P-wave characteristics comprises: Calculating eigenvalues ​​of the covariance matrix; Sort the obtained eigenvalues ​​in descending order, and determine the corresponding eigenvectors according to the sorting; The epicenter azimuth of the seismic signal is determined according to the determined eigenvector and the set angle parameter.

10. An epicenter position detection device, used to implement the epicenter position detection method according to any one of claims 1 to 9, characterized in that: include: A P wave first arrival extraction module is used to obtain the time series of seismic signals and extract the P wave first arrival in the time series of seismic signals according to a long and short time window algorithm; The accurate picking module is used to select a time window and accurately pick the extracted P wave first arrival according to the selected time window and the AIC criterion to obtain an accurate P wave first arrival; A principal component analysis module, used to analyze the accurately picked P wave first arrival according to the principal component analysis algorithm to determine the epicenter azimuth of the seismic signal; The epicenter position output module is used to determine the epicenter position of the time series of the seismic signal according to the epicenter azimuth and the seismic records of multiple stations, and output the determined epicenter position.

11. A terminal, characterized in that: include: A processor and a memory, wherein the memory stores an epicenter position detection program, and when the epicenter position detection program is executed by the processor, it is used to implement the operation of the epicenter position detection method as described in any one of claims 1-9.

12. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and the storage medium stores an epicenter position detection program. When the epicenter position detection program is executed by a processor, it is used to implement the operation of the epicenter position detection method as described in any one of claims 1 to 9.

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