S-wave seismic phase first arrival identification method based on actual measurement blasting-induced particle vibration signals

Abstract

The invention discloses an S-wave seismic phase first arrival identification method based on actually measured blasting-induced particle vibration signals, and relates to the field of negative effect monitoring and safety evaluation of blasting vibration induced by rock blasting excavation, and the method comprises the steps: determining a blasting scheme based on a scanning result; arranging a blasting vibration sensor; acquiring actual measurement waveforms of blasting vibration at different blasting center distances; constructing an S-wave seismic phase first arrival recognition function; and obtaining the first arrival moments of the S-wave seismic phases of the actually measured vibration waveforms at different explosion center distances. Compared with the prior art that the recognition precision of the S wave of the blasting vibration signal under the engineering scale is low and the like, by comprehensively utilizing the differences of the S wave, a noise signal, a P wave and a P wave tail wave in the aspects of energy, frequency, polarization characteristics and the like, recognition parameters such as the ratio of transverse energy to total energy, the polarization degree and the deflection angle are introduced, and the transverse energy serves as a weight coefficient; an S-wave recognition function suitable for actual measurement of blasting vibration is provided, and the technology has the advantages of small recognition error, high efficiency and the like.

Description

Technical Field

[0001] The invention relates to the field of monitoring and safety evaluation of negative effects of blasting vibration induced by rock blasting excavation, and in particular to a method for identifying the first arrival of an S-wave seismic phase based on measured blasting-induced particle vibration signals. Background Art

[0002] During the blasting and excavation process, in addition to being used to crush the rock mass, most of the energy released by the explosives will propagate outward in the form of waves, thereby affecting and damaging the facilities, equipment, buildings and other protected objects along the propagation path. In order to evaluate the negative effects of blasting vibration, it is necessary to predict the vibration. At present, most researchers at home and abroad focus on the coupled vibration peak. It is well known that blasting seismic waves are composed of different types of waves such as P waves, S waves and R waves, and the propagation attenuation characteristics of different types of waves are the same. In order to accurately evaluate the negative effects of blasting vibration, it is necessary to clarify the dominant areas of different types of waves, and the accuracy of S wave first arrival recognition has an important impact on this work.

[0003] At present, most of the research on S-wave first arrival identification is concentrated in the field of natural earthquakes. Compared with natural earthquake signals, blasting vibration has the characteristics of short duration and low signal-to-noise ratio. The existing methods have low accuracy in the field of S-wave identification of blasting vibration signals. It is difficult to distinguish the difference between S-wave and noise signals, P-wave and P-wave coda in the existing methods. Therefore, based on this situation, a method for S-wave seismic phase first arrival identification based on the measured blasting-induced particle vibration signal is proposed. Summary of the invention

[0004] The purpose of the present invention is to provide an S-wave seismic phase first arrival identification method based on the measured blasting-induced particle vibration signal according to the above-mentioned prior art conditions and to address the problem of low accuracy in identifying the first arrival of S-wave of blasting vibration signals on an engineering scale, thereby overcoming the defects of the prior art by comprehensively utilizing the differences between S-waves and P-waves and P-wave codas in terms of energy, vibration frequency and polarization characteristics.

[0005] The technical solution adopted by the present invention is:

[0006] The S-wave seismic phase first arrival identification method based on the measured blasting-induced particle vibration signal includes the following steps:

[0007] Step 1: Use a 3D laser scanner to perform a 3D scan of the rock mass on the free surface of the blasting area, and determine the blasting plan based on the scanning results;

[0008] Step 2: Based on the requirements of regulations and specifications, blasting vibration sensors are arranged according to the principle of close proximity and far distance;

[0009] Step 3, obtaining the measured waveforms of blasting vibration at different distances from the explosion center;

[0010] Step 4: Based on the differences in energy, frequency and polarization characteristics between S-waves and P-waves and P-wave codas, an S-wave phase first arrival identification function is proposed;

[0011] Step 5, based on the S-wave seismic phase first arrival identification function, obtain the S-wave seismic phase first arrival time of the measured vibration waveform at different explosion center distances.

[0012] Furthermore, in step 1, a three-dimensional laser scanner is used to perform a three-dimensional scan of the rock mass in the blasting area, mainly to obtain structural surface parameters such as cracks, so as to provide basic information for the blasting plan.

[0013] Furthermore, in step 2, the distance between the measuring points and the explosion center should be selected according to the logarithmic rule of close to close and far to sparse, and the distance between the measuring points and the explosion center should be greater than 30m.

[0014] Furthermore, in step 3, the measured waveforms of blasting vibration at different distances from the explosion center are obtained and exported in a txt text format.

[0015] Further, in step 4, the S-wave phase first arrival identification function is proposed to include the following steps:

[0016] Step 4.1, after the P wave arrives, calculate the eigenvector of the maximum eigenvalue λ1 of the covariance matrix M formed by the sampling point data of the time window length l is the polarization direction of P wave;

[0017] Covariance matrix:

[0018]

[0019] Where M is the covariance matrix, which is used to describe the covariance relationship between vibration signals in the three directions of x, y, and z; cov(a,b) represents the covariance between variables a and b, and covariance is used to measure the linear correlation between two variables; x, y, and z represent the vibration components in the three orthogonal directions of north-south, east-west, and vertical. In blasting vibration monitoring, x, y, and z correspond to vibration signals in three directions respectively;

[0020] Step 4.2, after the P wave arrives, calculate the time window length l sampling points point by point, and calculate the maximum eigenvalue λ of the covariance matrix of each time window data i The corresponding eigenvector And calculate and The angle α is normalized:

[0021]

[0022] In the formula, cs1 is the value after normalization of the angle α;

[0023] Step 4.3, introduce the polarization degree cs2 to reduce the influence of P-wave coda and noise signal on S-wave phase picking:

[0024]

[0025] Where cs2 is the degree of polarization, which is used to describe the polarization characteristics of the vibration signal; λ1, λ2, and λ3 are the three eigenvalues ​​of the covariance matrix M, and satisfy λ1≥λ2≥λ3;

[0026] Step 4.4, introduce cs3 to describe the ratio of the measured waveform lateral energy to the total energy:

[0027]

[0028] Among them, L, Q, and T are the components of the polarization coordinate system obtained through coordinate transformation. The transformation formula is:

[0029]

[0030] Where cs3 is the ratio of transverse energy to total energy, which is used to describe the proportion of transverse energy in the measured waveform in the Q and T directions to the total energy; Q i 、T i , L i Respectively represent the vibration signal value of the i-th sampling point in the L, Q, and T directions; u ij is the element of the coordinate transformation matrix, representing the transformation coefficient from the original coordinate system x, y, z to the polarization coordinate system L, Q, T;

[0031] Step 4.5, construct the S-wave first arrival identification function CF, and introduce the transverse energy as the weight coefficient:

[0032]

[0033] Where CF is the wave first arrival identification function, which is used to comprehensively evaluate whether the current time t is the first arrival time of the S wave; Q(t) and T(t) represent the vibration signal values ​​in the Q and T directions at the current time t; represents the transverse energy amplitude at the current time t.

[0034] Furthermore, in step 5, the constructed S-wave first arrival identification function is used to identify the first arrival time of the S-wave seismic phase of the measured blasting vibration signal, and the specific arrival time of the S-wave seismic phase is given.

[0035] The beneficial effects of the present invention are:

[0036] 1. Improve the accuracy of S-wave phase first arrival identification:

[0037] Comprehensive use of multiple parameters: By introducing multiple parameters such as polarization characteristics, energy ratio and transverse energy amplitude, the S-wave first arrival recognition function is constructed, which can more accurately distinguish S-waves from P-waves, P-wave codas and noise signals. Reduce interference effects: By introducing polarization degree and transverse energy ratio, the interference of P-wave codas and noise signals on S-wave seismic phase picking is effectively reduced, improving the accuracy of recognition.

[0038] 2. Improve recognition efficiency:

[0039] Automatic identification: By constructing the S-wave first arrival identification function, the automatic identification of the first arrival time of the S-wave seismic phase is realized, which reduces manual intervention and improves the identification efficiency. Sliding time window calculation: The sliding time window calculation method is used to analyze the vibration signal point by point, which can quickly locate the first arrival time of the S-wave.

[0040] 3. Strong adaptability:

[0041] Applicable to complex environments: This method can effectively deal with the S-wave identification problem under low signal-to-noise ratio conditions and is suitable for complex geological conditions and blasting environments. Applicability to engineering scale: By introducing the lateral energy weight coefficient and polarization characteristic parameters, it can meet the S-wave identification requirements of blasting vibration signals at the engineering scale.

[0042] 4. Provide scientific basis:

[0043] Blasting plan optimization: Obtain the structural parameters of the rock mass in the blasting area through 3D laser scanning to provide a scientific basis for the formulation of the blasting plan and optimize the blasting effect. Safety monitoring support: Arrange sensors based on the requirements of the "Safety Monitoring Regulations for Blasting of Hydropower and Water Conservancy Projects" (DL / T5333-2021) to ensure the reliability of monitoring data and provide support for blasting safety monitoring.

[0044] 5. Reduce errors:

[0045] Normalization: Normalize the polarization angle to standardize the parameter range and reduce the calculation error. Comprehensive identification function: By constructing a comprehensive identification function, the error that may be caused by single parameter identification is avoided and the robustness of identification is improved.

[0046] 6. Easy to operate and promote:

[0047] Standardized data format: The measured waveform data is exported in txt format, which is convenient for subsequent analysis and processing, and improves the operability and scalability of the method. Clear process: The method has clear steps, from data acquisition, parameter calculation to S wave first arrival identification, and the process is clear, which is easy for engineering and technical personnel to understand and apply.

[0048] 7.Technological innovation:

[0049] Novel identification function: A S-wave first arrival identification function based on the transverse energy weight coefficient is proposed, which is innovative in the existing technology. Multi-parameter fusion: By integrating multiple parameters such as polarization characteristics, energy ratio and transverse energy amplitude, high-precision identification of the first arrival time of the S-wave seismic phase is achieved.

[0050] 8. Engineering application value

[0051] Improve blasting efficiency: By accurately identifying the first arrival time of the S wave, it is possible to better analyze the blasting vibration effect, optimize blasting parameters, and improve blasting efficiency. Ensure project safety: Provide reliable technical support for blasting vibration safety monitoring, reduce the impact of blasting on the surrounding environment and structure, and ensure project safety.

[0052] This S-wave seismic phase first arrival identification method based on the measured blasting-induced particle vibration signal constructs a high-precision S-wave first arrival identification function by comprehensively utilizing the differences between S-waves and noise signals, P-waves and P-wave codas in terms of energy, frequency and polarization characteristics. This method has the advantages of small identification error, high efficiency, strong adaptability and easy operation. It can effectively improve the accuracy and reliability of S-wave identification of blasting vibration signals at an engineering scale and has important engineering application value. 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, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0054] Figure 1 This is a flow chart of the S-wave seismic phase first arrival identification method of the present invention;

[0055] Figure 2 This is a schematic diagram of the arrangement of blasting vibration measuring points of the vibration sensor in step 2 of the present invention;

[0056] Figure 3 The blasting vibration waveform diagram in step 3 of the present invention;

[0057] Figure 4 This is the first arrival identification diagram of the S-wave seismic phase of the blasting vibration signal measured in step 5 of the invention. DETAILED DESCRIPTION

[0058] The following will be combined with the accompanying drawings of the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] At present, it is difficult to distinguish the difference characteristics between S waves and noise signals, P waves and P wave coda waves in the process of S wave first arrival identification. This embodiment provides an S wave seismic phase first arrival identification method based on the measured blasting induced particle vibration signal, such as Figure 1 As shown, the S-wave seismic phase first arrival identification method includes the following steps:

[0060] Step 1 is to obtain the structural surface parameters such as cracks in the rock mass, so as to provide basic information for formulating the blasting plan. Therefore, a 3D laser scanner is used to perform a 3D scan of the rock mass on the free surface of the blasting area, and the blasting plan is determined based on the scanning results. Among them, the 3D laser scanner is used to perform a 3D scan of the rock mass in the blasting area, mainly to obtain structural surface parameters such as cracks, and provide basic information for the blasting plan.

[0061] Step 2: Arrange blasting vibration sensors according to the principle of close proximity and far distance based on the requirements of regulations and specifications. Specifically, based on the relevant requirements of the "Regulations on Safety Monitoring of Blasting in Hydropower and Water Conservancy Projects" (DL / T5333-2021), the distance between the measuring points and the explosion center should be selected in a logarithmic manner in the manner of close proximity and far distance; at the same time, the distance between the measuring points and the explosion center should be greater than 30m to ensure that the S wave and the P wave can be separated in the waveform.

[0062] Step 3, obtaining the measured waveforms of blasting vibration at different distances from the explosion center; after obtaining the measured waveforms of blasting vibration at different distances from the explosion center, export them in txt text format.

[0063] Step 4: Based on the differences between S-waves and P-waves and the energy, frequency and polarization characteristics of P-wave codas, an S-wave phase first arrival identification function is proposed.

[0064] Specifically, the S-wave phase first arrival identification function is proposed to include the following steps:

[0065] Step 4.1, after the P wave arrives, calculate the eigenvector of the maximum eigenvalue λ1 of the covariance matrix M formed by the sampling point data of the time window length l is the polarization direction of the P wave; the eigenvalue reflects the variance of the data in the direction of the eigenvector, and the direction corresponding to the maximum eigenvalue is the direction in which the data changes most significantly; the eigenvector It represents the polarization direction of the P wave, that is, the main direction of the P wave vibration.

[0066] The covariance matrix is ​​a 3×3 matrix used to describe the covariance relationship between the three components x, y, and z. Its structure is as follows:

[0067]

[0068] Where M is the covariance matrix, which is used to describe the covariance relationship between vibration signals in the three directions of x, y, and z; x, y, and z represent vibration components in the three orthogonal directions of north-south, east-west, and vertical. In blasting vibration monitoring, x, y, and z correspond to vibration signals in three directions respectively; cov(a, b) represents the covariance between variables a and b. Covariance is used to measure the linear correlation between two variables. The calculation formula is:

[0069]

[0070] In the formula, a i and b i are the i-th sampling point values ​​of variables a and b respectively; and are the means of variables a and b respectively; n is the total number of sampling points.

[0071] The calculation process is as follows: first, after the P wave arrives, select the sampling point data within the time window length l, that is, the vibration signals in the three directions of x, y, and z; then, calculate the covariance between the three directions of x, y, and z respectively, and construct the covariance matrix M; then, perform eigenvalue decomposition on the covariance matrix M to obtain the maximum eigenvalue λ1 and its corresponding eigenvector Finally, the polarization direction is determined, and the eigenvector This is the polarization direction of the P wave.

[0072] Through the above calculations, the polarization direction of the P wave can be determined, providing a basis for the subsequent identification of the first arrival of the S wave phase.

[0073] Step 4.2, after the P wave arrives, calculate the time window length l sampling points point by point, and calculate the maximum eigenvalue λ of the covariance matrix of each time window data i The corresponding eigenvector And calculate and The angle α is normalized:

[0074]

[0075] Where cs1 is the value after normalization of the angle α, and its value range is [0,1], which is convenient for subsequent calculation and comparison; is the maximum eigenvalue λ of the covariance matrix corresponding to the i-th time window data i The characteristic vector of represents the polarization direction of the vibration signal in the i-th time window; Representation vector and The dot product of and Represents vectors and Model.

[0076] The calculation process is as follows: starting from the arrival of the P wave, the time window is slid point by point, one sampling point is slid each time, and l sampling point data are taken each time; then the covariance matrix is ​​calculated for each time window data, and its maximum eigenvalue λ is calculated. i The corresponding eigenvector Then calculate and The included angle α is normalized to obtain cs1.

[0077] Through the above calculations, the difference between the polarization direction of the vibration signal and the polarization direction of the P wave in different time windows can be quantified, providing a basis for the subsequent identification of the first arrival of the S wave seismic phase.

[0078] Step 4.3, introduce the polarization degree cs2 to reduce the influence of P-wave coda and noise signal on S-wave phase picking:

[0079]

[0080] Where cs2 is the degree of polarization, which is used to describe the polarization characteristics of the vibration signal. The value range of cs2 is [0,1]. When cs2 is close to 1, it means that the signal has a strong polarization characteristic, such as P wave. When cs2 is close to 0, it means that the signal polarization characteristic is weak, such as noise or S wave. λ1, λ2, and λ3 are the three eigenvalues ​​of the covariance matrix M, and they satisfy λ1≥λ2≥λ3. The eigenvalue reflects the variance of the data in the direction of the eigenvector: λ1 is the largest eigenvalue, corresponding to the direction in which the data changes most significantly, which is the polarization direction of the P wave; λ2 is the middle eigenvalue, corresponding to the direction in which the data changes less significantly; λ3 is the smallest eigenvalue, corresponding to the direction in which the data changes least.

[0081] (λ1-λ2) 2 +(λ2-λ3) 2 +(λ1-λ3) 2 The numerator measures the difference between the three eigenvalues. If λ1 is much larger than λ2 and λ3, it means that the signal has significant polarization characteristics in a certain direction, such as P waves. If the difference between λ1, λ2, and λ3 is small, it means that the signal polarization characteristics are weak, such as noise or S waves. (λ1+λ2+λ3) 2 It is the square of the sum of the eigenvalues ​​and is used to normalize the numerator so that the value range of cs2 is [0,1].

[0082] The purpose of calculating the degree of polarization cs2 is: first, to reduce the influence of P-wave coda and noise: P-waves usually have strong polarization characteristics, that is, cs2 is close to 1; while S-waves and noise have weak polarization characteristics, that is, cs2 is close to 0; by introducing the degree of polarization cs2, P-waves and S-waves can be distinguished, and the interference of P-wave coda and noise on S-wave phase picking can be reduced. Second, the accuracy of S-wave identification can be improved: in the identification of the first arrival of S-wave seismic phase, the degree of polarization cs2 can be used as a weighting factor to suppress P-wave coda and noise signals and highlight the characteristics of S-waves.

[0083] By introducing the polarization degree cs2, the interference of P-wave coda and noise signals can be effectively reduced, and the accuracy of S-wave phase first arrival identification can be improved.

[0084] Step 4.4, introduce the ratio of transverse energy to total energy cs3, which describes the ratio of the transverse energy to the total energy of the measured waveform;

[0085] The calculation formula of the ratio of transverse energy to total energy cs3 is:

[0086]

[0087] Among them, L, Q, and T are polarization coordinate system components obtained through coordinate transformation. L is the component along the P-wave polarization direction, that is, the p1 direction; Q is one of the components perpendicular to the L direction; T is another component perpendicular to the L direction and is orthogonal to Q; L, Q, and T are converted from x, y, and z through coordinate transformation;

[0088] The transformation formula is:

[0089]

[0090] Where cs3 is the ratio of transverse energy to total energy, which is used to describe the proportion of transverse energy Q and T in the measured waveform to the total energy. The value range of cs3 is [0,1]. When cs3 is close to 1, it means that the transverse energy is dominant, such as S wave; when cs3 is close to 0, it means that the longitudinal energy L direction is dominant, such as P wave. i 、T i , L i Respectively represent the vibration signal value of the i-th sampling point in the L, Q, and T directions. i j is an element of the coordinate transformation matrix, which represents the transformation coefficient from the original coordinate system x, y, z to the polarization coordinate system L, Q, T; each row of the transformation matrix is ​​a unit vector, which represents the basis vector of the polarization coordinate system.

[0091] In the above calculation, It represents the sum of the energy in the Q and T directions within the time window, i.e., the transverse energy; Represents the total energy in the L, Q, and T directions within the time window. By calculating the ratio of transverse energy to total energy, P waves and S waves can be distinguished: the energy of P waves is mainly concentrated in the L direction, that is, the longitudinal direction, and the ratio of transverse energy to total energy cs3 is small; the energy of S waves is mainly concentrated in the Q and T directions, that is, the transverse direction, and the ratio of transverse energy to total energy cs3 is large. Through coordinate transformation, the vibration signal can be decomposed into components along the polarization direction L of the P wave and perpendicular to the polarization direction Q and T of the P wave; each row of the transformation matrix is ​​the basis vector of the polarization coordinate system, where the first row is the polarization direction of the P wave, that is direction; the second and third rows are Two directions that are orthogonal.

[0092] By introducing the ratio of lateral energy to total energy cs3, the proportion of lateral energy in the measured waveform can be quantified, thereby effectively distinguishing P waves from S waves and providing a basis for identifying the first arrival of the S-wave phase.

[0093] Step 4.5, construct the S-wave first arrival identification function CF, and introduce the transverse energy as the weight coefficient:

[0094]

[0095] Where CF is the wave first arrival identification function, which is used to comprehensively evaluate whether the current time t is the first arrival time of the S wave; Q(t) and T(t) represent the vibration signal values ​​in the Q and T directions at the current time t; represents the transverse energy amplitude at the current time t.

[0096] cs1 2 、cs2 2 、cs3 2 These three factors weight the first arrival time of the S wave from the perspectives of polarization direction difference, polarization characteristics, and energy ratio, and the influence of these factors is further highlighted through square operations. As a weight coefficient, it directly reflects the transverse energy at the current time t; the larger the transverse energy, the larger the CF value, and the more likely it is the first arrival time of the S wave. The CF function combines the polarization direction difference cs1, polarization characteristics cs2, energy ratio cs3 and transverse energy amplitude It can more accurately identify the first arrival time of the S wave.

[0097] By constructing the CF function, the first arrival time of the S wave can be identified more accurately, providing a reliable basis for the analysis of blasting vibration signals.

[0098] Step 5, based on the S-wave seismic phase first arrival identification function, obtain the S-wave seismic phase first arrival time of the measured vibration waveform at different explosion center distances; use the constructed S-wave first arrival identification function to identify the S-wave seismic phase first arrival time of the measured blasting vibration signal, and give the specific arrival time of the S-wave seismic phase first arrival.

[0099] In summary, the S-wave phase first arrival identification method based on the measured blasting-induced particle vibration signal proposes an S-wave identification function by comprehensively utilizing the differences between S-waves, P-waves and P-wave codas in energy, vibration frequency and polarization characteristics, so as to realize the accurate identification of the S-wave phase first arrival of blasting-induced seismic waves on an engineering scale, and further achieve the purpose of accurate prediction of blasting-induced vibration.

[0100] Furthermore, in order to verify the actual effect of the S-wave seismic phase first arrival identification method based on the measured blasting-induced particle vibration signal, taking the rock excavation of a green petrochemical base as an example, the S-wave seismic phase first arrival identification of blasting vibration at an engineering scale was carried out based on the measured vibration waveform of a single-hole blasting test.

[0101] First, a 3D laser scanner is used to perform a 3D scan of the rock mass on the free surface of the blasting area, and the blasting plan is determined based on the scanning results. Then, based on the requirements of the regulations and specifications, the blasting vibration sensors are arranged according to the principle of close density and far sparseness. The blasting vibration measurement points are arranged as follows: Figure 2 Then, the measured blasting vibration waveforms at different blasting center distances are obtained. The measured blasting vibration waveforms are shown in Figure 3 As shown in the figure; then, based on the differences in energy, frequency and polarization characteristics between S-wave and P-wave, P-wave coda, etc., an S-wave seismic phase first arrival recognition function is constructed; finally, based on the S-wave first arrival recognition function, the S-wave seismic phase first arrival recognition of the measured blasting vibration signal is picked up, and the following is obtained: Figure 4 The figure shows the first arrival identification diagram of the S-wave phase of the measured blasting vibration signal.

[0102] It can be seen that the S-wave seismic phase first arrival identification method based on the measured blasting-induced particle vibration signal is different from the existing technology in terms of low S-wave identification accuracy of blasting vibration signals at engineering scale. By comprehensively utilizing the differences between S-waves and noise signals, P-waves and P-wave codas in energy, frequency and polarization characteristics, introducing identification parameters such as the ratio of lateral energy to total energy, polarization degree and deflection angle, and taking lateral energy as the weight coefficient, a S-wave identification function suitable for measured blasting vibration is proposed. This technology has the advantages of small identification error and high efficiency.

[0103] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for identifying the first arrival of an S-wave seismic phase based on measured blasting-induced particle vibration signals, characterized in that: The S-wave seismic phase first arrival identification method comprises the following steps: Step 1: Use a 3D laser scanner to perform a 3D scan of the rock mass on the free surface of the blasting area, and determine the blasting plan based on the scanning results; Step 2: Based on the requirements of regulations and specifications, blasting vibration sensors are arranged according to the principle of close proximity and far distance; Step 3, obtaining the measured waveforms of blasting vibration at different distances from the explosion center; Step 4: Based on the differences in energy, frequency and polarization characteristics between S-waves and P-waves and P-wave codas, an S-wave phase first arrival identification function is proposed; Step 5, based on the S-wave seismic phase first arrival identification function, obtain the S-wave seismic phase first arrival time of the measured vibration waveform at different explosion center distances.

2. The S-wave seismic phase first arrival identification method based on the measured blasting-induced particle vibration signal according to claim 1 is characterized in that: In step 1, a 3D laser scanner is used to perform a 3D scan of the rock mass in the blasting area, mainly to obtain structural surface parameters such as cracks, providing basic information for the blasting plan.

3. The S-wave seismic phase first arrival identification method based on the measured blasting-induced particle vibration signal according to claim 1 is characterized in that: In step 2, the distance between the measuring points and the explosion center should be selected according to the logarithmic rule of close to close and far to sparse, and the distance between the measuring points and the explosion center should be greater than 30m.

4. The S-wave seismic phase first arrival identification method based on the measured blasting-induced particle vibration signal according to claim 1 is characterized in that: In step 3, the measured waveforms of blasting vibration at different distances from the explosion center are obtained and exported in txt text format.

5. The S-wave seismic phase first arrival identification method based on measured blasting-induced particle vibration signals according to claim 1 is characterized in that: In step 4, the S-wave phase first arrival identification function is proposed to include the following steps: Step 4.1, after the P wave arrives, calculate the eigenvector of the maximum eigenvalue λ1 of the covariance matrix M formed by the sampling point data of the time window length l is the polarization direction of P wave; Covariance matrix: Where M is the covariance matrix, which is used to describe the covariance relationship between vibration signals in the three directions of x, y, and z; cov(a,b) represents the covariance between variables a and b, and covariance is used to measure the linear correlation between two variables; x, y, and z represent the vibration components in the three orthogonal directions of north-south, east-west, and vertical. In blasting vibration monitoring, x, y, and z correspond to vibration signals in three directions respectively; Step 4.2, after the P wave arrives, calculate the time window length l sampling points point by point, and calculate the maximum eigenvalue λ of the covariance matrix of each time window data i The corresponding eigenvector And calculate and The angle α is normalized: In the formula, cs1 is the value after normalization of the angle α; Step 4.3, introduce the polarization degree cs2 to reduce the influence of P-wave coda and noise signal on S-wave phase picking: Where cs2 is the degree of polarization, which is used to describe the polarization characteristics of the vibration signal; λ1, λ2, and λ3 are the three eigenvalues ​​of the covariance matrix M, and satisfy λ1≥λ2≥λ3; Step 4.4, introduce cs3 to describe the ratio of the measured waveform lateral energy to the total energy: Among them, L, Q, and T are the components of the polarization coordinate system obtained through coordinate transformation. The transformation formula is: Where cs3 is the ratio of transverse energy to total energy, which is used to describe the proportion of transverse energy in the measured waveform in the Q and T directions to the total energy; Q i 、T i , L i Respectively represent the vibration signal value of the i-th sampling point in the L, Q, and T directions; u ij is the element of the coordinate transformation matrix, representing the transformation coefficient from the original coordinate system x, y, z to the polarization coordinate system L, Q, T; Step 4.5, construct the S-wave first arrival identification function CF, and introduce the transverse energy as the weight coefficient: Where CF is the wave first arrival identification function, which is used to comprehensively evaluate whether the current time t is the first arrival time of the S wave; Q(t) and T(t) represent the vibration signal values ​​in the Q and T directions at the current time t; represents the transverse energy amplitude at the current time t.

6. The S-wave seismic phase first arrival identification method based on the measured blasting-induced particle vibration signal according to claim 1 is characterized in that: In step 5, the constructed S-wave first arrival identification function is used to identify the first arrival time of the S-wave seismic phase of the measured blasting vibration signal, and the specific arrival time of the S-wave seismic phase is given.

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