Seismic wave low-frequency signal identification method and device, electronic equipment and storage medium

Abstract

The application discloses a seismic wave low-frequency signal identification method and device, electronic equipment and a storage medium, and belongs to the field of seismic waves. The seismic wave low-frequency signal identification method comprises the following steps: obtaining acceleration data of a seismic wave; determining a first seismic parameter and a second seismic parameter, wherein the first seismic parameter and the second seismic parameter are both parameters related to the displacement of the seismic wave; determining the filter cutoff frequency of the seismic wave according to the first seismic parameter and the second seismic parameter; and filtering the acceleration data of the seismic wave through the filter cutoff frequency to obtain a low-frequency noise-free signal of the seismic wave.

Description

Technical Field

[0001] The present application relates to the field of seismic waves, and specifically to a method, device, electronic device, and readable storage medium for identifying low-frequency seismic wave signals. Background Art

[0002] With the advancement of science and technology, earthquake detection and seismic data processing are becoming increasingly essential, providing a basis for better understanding and predicting earthquakes. However, low-frequency noise in seismic waves significantly impacts the assessment of structural seismic performance, making it crucial to identify and remove it. However, prior art techniques often struggle to accurately identify low-frequency noise, making it difficult to filter it out and obtain a signal free of it. Summary of the Invention

[0003] The purpose of the embodiments of the present application is to provide a method, device, electronic device and readable storage medium for identifying low-frequency signals of seismic waves, so as to at least solve the problem that it is difficult to accurately determine low-frequency noise, and thus difficult to filter out low-frequency noise and obtain a signal without low-frequency noise.

[0004] In a first aspect, an embodiment of the present application provides a method for identifying low-frequency seismic wave signals, the method comprising:

[0005] Obtain acceleration data of seismic waves;

[0006] Determining a first seismic parameter and a second seismic parameter, wherein the first seismic parameter and the second seismic parameter are both parameters related to the displacement of the seismic wave;

[0007] determining a filtering cutoff frequency of the seismic wave according to the first seismic parameter and the second seismic parameter;

[0008] The acceleration data of the seismic wave is filtered by the filtering cutoff frequency to obtain a low-frequency noise-free signal of the seismic wave.

[0009] Optionally, filtering the acceleration data of the seismic wave by the filtering cutoff frequency to obtain a low-frequency noise-free signal of the seismic wave includes:

[0010] Filtering the acceleration data of the seismic wave by the filtering cutoff frequency to obtain initial filtered acceleration data;

[0011] Integrating the acceleration data after the initial filtering to obtain displacement data of the seismic wave;

[0012] Acquiring long-period displacement spectrum data of the seismic wave;

[0013] A low-frequency noise-free signal of the seismic wave is determined based on the long-period displacement spectrum data.

[0014] Optionally, determining the low-frequency noise-free signal of the seismic wave based on the long-period displacement spectrum data includes:

[0015] Subtracting the long-period displacement spectrum data from the initial displacement data of the seismic wave to obtain a data difference;

[0016] determining a ratio between an absolute value of the data difference and the initial displacement data of the seismic wave;

[0017] If the ratio is less than a preset threshold, the acceleration data after the initial filtering is used as the low-frequency noise-free signal of the seismic wave;

[0018] If the ratio is greater than or equal to the preset threshold, the preset frequency value is added to the filter cutoff frequency to obtain the increased filter cutoff frequency, and the acceleration data of the seismic wave is filtered by the increased filter cutoff frequency to obtain intermediate filtered acceleration data, the intermediate filtered acceleration data is integrated to obtain the displacement data of the seismic wave, and the difference between the displacement data of the seismic wave and the long-period displacement spectrum data is re-determined until the absolute value of the difference between the displacement data of the seismic wave and the long-period displacement spectrum data is less than the preset threshold, and the intermediate filtered acceleration data is used as the low-frequency noise-free signal of the seismic wave.

[0019] Optionally, determining the first seismic parameter and the second seismic parameter includes:

[0020] Determine the displacement at the end of the ground motion after filtering and zero padding, the peak displacement of the ground motion after filtering, the displacement of the jth point before the arrival of the P wave after filtering, and the number of sampling points before the arrival of the P wave, where j is a positive integer greater than 0;

[0021] Determine the ratio of the displacement at the end of the ground motion after filtering and zero padding to the peak displacement of the ground motion after filtering to obtain the first earthquake parameter;

[0022] The second seismic parameter is determined according to the displacement of the jth point of the filtered displacement time history before the arrival of the P wave and the number of sampling points selected before the arrival of the P wave.

[0023] Optionally, determining the filtering cutoff frequency of the seismic wave according to the first seismic parameter and the second seismic parameter includes:

[0024] determining the azimuth of the acceleration data of the seismic wave;

[0025] determining a first cutoff frequency corresponding to the first seismic parameter according to the azimuth and the first seismic parameter;

[0026] determining a second cutoff frequency corresponding to the second seismic parameter according to the azimuth and the second seismic parameter;

[0027] An average of the first cutoff frequency and the second cutoff frequency is determined, and the average is used as the filtering cutoff frequency.

[0028] In a second aspect, an embodiment of the present application provides a seismic wave low-frequency signal recognition device, the seismic wave low-frequency signal recognition device comprising:

[0029] An acquisition module, used to obtain acceleration data of seismic waves;

[0030] A first determination module is configured to determine a first seismic parameter and a second seismic parameter, both of which are parameters related to the displacement of the seismic wave;

[0031] a second determining module, configured to determine a filtering cutoff frequency of the seismic wave according to the first seismic parameter and the second seismic parameter;

[0032] The filtering module is used to filter the acceleration data of the seismic wave through the filtering cutoff frequency to obtain a low-frequency noise-free signal of the seismic wave.

[0033] Optionally, the filtering module includes:

[0034] a first filtering unit, configured to filter the acceleration data of the seismic wave using the filtering cutoff frequency to obtain acceleration data after initial filtering;

[0035] an integration unit, configured to integrate the acceleration data after the initial filtering to obtain displacement data of the seismic wave;

[0036] an acquisition unit, configured to acquire long-period displacement spectrum data of the seismic wave;

[0037] The first determining unit is configured to determine a low-frequency noise-free signal of the seismic wave based on the long-period displacement spectrum data.

[0038] Optionally, the determining unit is further configured to:

[0039] Subtracting the long-period displacement spectrum data from the initial displacement data of the seismic wave to obtain a data difference;

[0040] determining a ratio between an absolute value of the data difference and the initial displacement data of the seismic wave;

[0041] If the ratio is less than a preset threshold, the acceleration data after the initial filtering is used as the low-frequency noise-free signal of the seismic wave;

[0042] If the ratio is greater than or equal to the preset threshold, the preset frequency value is added to the filter cutoff frequency to obtain the increased filter cutoff frequency, and the acceleration data of the seismic wave is filtered by the increased filter cutoff frequency to obtain intermediate filtered acceleration data, the intermediate filtered acceleration data is integrated to obtain the displacement data of the seismic wave, and the difference between the displacement data of the seismic wave and the long-period displacement spectrum data is re-determined until the absolute value of the difference between the displacement data of the seismic wave and the long-period displacement spectrum data is less than the preset threshold, and the intermediate filtered acceleration data is used as the low-frequency noise-free signal of the seismic wave.

[0043] Optionally, the first determining module includes:

[0044] The second determining unit is used to determine the displacement at the end time of the ground motion after filtering and zero padding, the peak displacement of the ground motion after filtering, the displacement of the jth point before the arrival of the P wave in the displacement time history after filtering, and the number of sampling points selected before the arrival of the P wave, where j is a positive integer greater than 0;

[0045] a third determining unit, configured to determine a ratio of the displacement at the end of the ground motion after filtering and zero padding to the peak displacement of the ground motion after filtering, to obtain the first earthquake parameter;

[0046] The fourth determination unit is used to determine the second seismic parameter according to the displacement of the jth point before the arrival of the P wave in the filtered displacement time history and the number of sampling points before the arrival of the selected P wave.

[0047] Optionally, the second determining module includes:

[0048] a fifth determining unit, configured to determine the azimuth of the acceleration data of the seismic wave;

[0049] a sixth determining unit, configured to determine a first cutoff frequency corresponding to the first seismic parameter according to the azimuth and the first seismic parameter;

[0050] a seventh determining unit, configured to determine a second cutoff frequency corresponding to the second seismic parameter according to the azimuth and the second seismic parameter;

[0051] An eighth determining unit is configured to determine an average of the first cutoff frequency and the second cutoff frequency, and use the average as the filtering cutoff frequency.

[0052] In a third aspect, an embodiment of the present application provides an electronic device comprising a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the seismic wave low-frequency signal identification method as described in any one of the above-mentioned first aspects are implemented.

[0053] In a fourth aspect, an embodiment of the present application provides a storage medium storing a program or instruction, which, when executed by a processor, implements the steps of the seismic wave low-frequency signal identification method as described in the first aspect above.

[0054] In a fifth aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the method described in the first aspect.

[0055] In a sixth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the method described in the first aspect.

[0056] In an embodiment of the present application, acceleration data of a seismic wave is obtained; a first seismic parameter and a second seismic parameter are determined, both of which are parameters related to the displacement of the seismic wave; a filtering cutoff frequency of the seismic wave is determined based on the first seismic parameter and the second seismic parameter; the acceleration data of the seismic wave is filtered by the filtering cutoff frequency to obtain a low-frequency noise-free signal of the seismic wave, so that the filtering cutoff frequency can be determined more accurately, and then a low-frequency noise-free signal of the seismic wave can be obtained more accurately. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 A flowchart showing a method for identifying low-frequency seismic wave signals provided by an embodiment of the present application;

[0058] Figure 2 A schematic diagram showing a first seismic parameter and a filter cutoff frequency provided in an embodiment of the present application;

[0059] Figure 3 A schematic diagram showing a second seismic parameter and a filter cutoff frequency provided in an embodiment of the present application;

[0060] Figure 4 A schematic diagram showing seismic parameters and cutoff frequencies corresponding to a first seismic parameter and a second seismic parameter provided in an embodiment of the present application;

[0061] Figure 5 : represents the relationship between the curvature angle and cutoff frequency of Rd1 and Rd2 provided in an embodiment of the present application;

[0062] Figure 6 A schematic diagram showing a fitting result of a curvature angle function provided in an embodiment of the present application;

[0063] Figure 7 A schematic diagram showing a displacement time history after 0.011 Hz filtering provided in an embodiment of the present application;

[0064] Figure 8 A schematic diagram showing a seismic wave low-frequency signal recognition device provided by an embodiment of the present application;

[0065] Figure 9 A schematic diagram showing an electronic device provided in an embodiment of the present application;

[0066] Figure 10 A schematic diagram showing the hardware structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0067] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0068] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims refers to at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0069] The human body image analysis method provided in the embodiment of the present application is described in detail below through specific embodiments and their application scenarios in conjunction with the accompanying drawings.

[0070] Reference Figure 1 , shows a flow chart of a method for identifying low-frequency seismic wave signals provided by an embodiment of the present application. Figure 1 As shown, the seismic wave low-frequency signal recognition method includes:

[0071] Step 101: Acquire acceleration data of seismic waves.

[0072] When an earthquake occurs at a certain location, earthquake monitoring personnel at that location will record and store the seismic wave data. The seismic wave data includes seismic wave acceleration data. Therefore, step 101 can be implemented by directly downloading the seismic wave acceleration data from a medium storing seismic wave data, i.e., directly acquiring the seismic wave acceleration data. Of course, step 101 can also be implemented by acquiring seismic wave acceleration data when an earthquake occurs.

[0073] In addition, when an earthquake occurs, the earthquake occurs within a period of time, so the acceleration data of the seismic wave may essentially be an acceleration curve, that is, the acceleration data of the seismic wave may essentially be an acceleration curve of the seismic wave, and the acceleration curve has multiple discrete points.

[0074] Step 102: Determine a first seismic parameter and a second seismic parameter, where both the first seismic parameter and the second seismic parameter are parameters related to the displacement of seismic waves.

[0075] By determining the first seismic parameter and the second seismic parameter, both of which are parameters related to the displacement of seismic waves, it is convenient to subsequently determine the filter cutoff frequency according to the first seismic parameter and the second seismic parameter.

[0076] In addition, in some implementations, step 102 can be implemented as follows: determining the displacement at the end time of the seismic motion after filtering and zero padding, the peak displacement of the seismic motion after filtering, the displacement of the jth point in the displacement time series before the arrival of the P wave after filtering, and the number of sampling points selected before the arrival of the P wave, where j is a positive integer greater than 0; determining the ratio of the displacement at the end time of the seismic motion after filtering and zero padding to the peak displacement of the seismic motion after filtering to obtain the first seismic parameter; determining the second seismic parameter based on the displacement of the jth point in the displacement time series before the arrival of the P wave after filtering and the number of sampling points selected before the arrival of the P wave.

[0077] Among them, the displacement at the end of the earthquake motion after filtering and zero filling can be expressed as d end The peak displacement of the filtered earthquake motion can be expressed as PGD(i), and the first earthquake parameter can be determined as shown in the following formula:

[0078]

[0079] Among them, R d1 (i) represents the first earthquake parameter.

[0080] According to the time-history variation law of the filtered ground motion displacement, the relationship between the displacement at the end of the earthquake and the peak ground motion (PGD) can be expressed as follows: Figure 2 As shown, from Figure 2It can be seen that Rd1 decreases rapidly as the cutoff frequency increases. When the cutoff frequency increases to 0.005Hz, Rd1 drops to a low level, then fluctuates slightly and finally approaches zero.

[0081] In addition, according to the displacement of the jth point before the arrival of the P wave in the filtered displacement time history and the number of sampling points selected before the arrival of the P wave, the second seismic parameter can be determined in the following manner:

[0082]

[0083] Among them, R d2 (i) represents the second seismic parameter, d(j) represents the displacement at the jth point in the filtered displacement history before the P wave arrives, and n represents the number of sampling points selected before the P wave arrives. Furthermore, the second seismic parameter is used to characterize the transient effects of the seismic wave displacement history before the P wave arrives.

[0084] In addition, in most digital seismic records, the ground acceleration amplitude before the arrival of the P wave is extremely small, and the amplitude of the integrated displacement time history is also small. If the cutoff frequency is not appropriate, the displacement time history obtained by filtering will produce transient displacement before the arrival of the P wave, with a larger amplitude. Figure 3 It is the functional relationship between the seismic wave displacement and the filter cutoff frequency obtained by using the formula for calculating the second seismic parameter.

[0085] Step 103: Determine the filter cutoff frequency of the seismic wave according to the first seismic parameter and the second seismic parameter.

[0086] Among them, such as Figure 2 and Figure 3 As shown, R d1 and R d2 There is a significant change before it tends to a stable value. Using only one parameter to determine the cutoff frequency may cause another parameter to have a significant change near this cutoff frequency. Therefore, in the embodiment of the present application, R is also considered. d1 and R d2 Two parameters. That is, determining the filter cutoff frequency of the seismic wave according to the first seismic parameter and the second seismic parameter can make the determined filter cutoff frequency more accurate.

[0087] In addition, in some implementations, step 103 can be implemented as follows: determining the azimuth of the acceleration data of the seismic wave; determining a first cutoff frequency corresponding to the first seismic parameter based on the azimuth and the first seismic parameter; determining a second cutoff frequency corresponding to the second seismic parameter based on the azimuth and the second seismic parameter; determining the mean of the first cutoff frequency and the second cutoff frequency, and using the mean as the filtering cutoff frequency.

[0088] The azimuth of the acceleration data of the seismic wave can be determined as follows: Figure 4As shown, the azimuth angle between two adjacent points represents the curvature of the i-th frequency, which can be determined according to the following formula:

[0089]

[0090] Among them, θ f (i-1) is the azimuth from R(i-1) to R(i), θ p (i) is the azimuth from R(i) to R(i+1).

[0091] In addition, in the embodiment of the present application, the curvature angle at the i-th frequency may also be defined:

[0092] θ(i)=|θ p (i)-θ f (i-1)|

[0093] Where θ(i) represents the curvature angle at the i-th frequency.

[0094] The larger the curvature angle, the more significant the change in the R parameter, that is, the more significant the change in the first earthquake parameter and the second earthquake parameter. Figure 2 and Figure 3 R d1 and R d2 The curvature angle can be expressed as Figure 5 shown. Figure 5 The curvature angles of Rd1 and Rd2 in the figure are preprocessed using the moving average method. When the curvature angle is close to zero, Rd1 and Rd2 do not change significantly. When the cutoff frequency is greater than a certain critical value, the curvature angle θ approaches a straight line. Therefore, there is a certain frequency below which the θ function is significantly greater than zero; when the cutoff frequency is greater than this frequency, the θ function is sufficiently linear, which is called the unstable critical frequency. Figure 5 As shown, the θ function in the unstable stage adopts nonlinear fitting. In the embodiment of the present application, a 5th-order polynomial fitting is adopted, and linear fitting is adopted in the stable stage. Figure 6 is the fitted θ curve. Figure 6 It can be seen that the instability critical frequencies of Rd1 and Rd2 are 0.01 Hz and 0.016 Hz, respectively. This is equivalent to determining the first cutoff frequency corresponding to the first seismic parameter based on the azimuth and the first seismic parameter, and determining the second cutoff frequency corresponding to the second seismic parameter based on the azimuth and the second seismic parameter, in a fitting manner.

[0095] In addition, in the embodiment of the present application, the average of the first cutoff frequency and the second cutoff frequency can be determined, and the average is used as the filtering cutoff frequency.

[0096] Step 104: filtering the acceleration data of the seismic wave by using the filtering cutoff frequency to obtain a seismic wave signal free of low-frequency noise.

[0097] Among them, after determining the filtering cutoff frequency, the acceleration data of the seismic wave can be directly filtered using the filtering cutoff frequency, and the filtered data becomes a seismic wave signal without low-frequency noise.

[0098] In addition, in some implementations, step 104 can be implemented as follows: filtering the acceleration data of the seismic wave by the filtering cutoff frequency to obtain the initial filtered acceleration data; integrating the initial filtered acceleration data to obtain the displacement data of the seismic wave; obtaining the long-period displacement spectrum data of the seismic wave; and determining the low-frequency noise-free signal of the seismic wave based on the long-period displacement spectrum data.

[0099] In addition, in some implementations, the implementation method for determining the low-frequency noise-free signal of the seismic wave based on the long-period displacement spectrum data can be: subtracting the long-period displacement spectrum data from the initial displacement data of the seismic wave to obtain a data difference; determining the ratio between the absolute value of the data difference and the initial displacement data of the seismic wave; if the ratio is less than a preset threshold, the initial filtered acceleration data is used as the low-frequency noise-free signal of the seismic wave; if the ratio is greater than or equal to the preset threshold, the preset frequency value is added to the filter cutoff frequency to obtain the increased filter cutoff frequency, and the acceleration data of the seismic wave is filtered by the increased filter cutoff frequency to obtain intermediate filtered acceleration data, the intermediate filtered acceleration data is integrated to obtain the displacement data of the seismic wave, and the difference between the displacement data of the seismic wave and the long-period displacement spectrum data is re-determined until the absolute value of the difference between the displacement data of the seismic wave and the long-period displacement spectrum data is less than the preset threshold, and the intermediate filtered acceleration data is used as the low-frequency noise-free signal of the seismic wave.

[0100] It should be noted that the preset threshold value can be set according to actual needs, and the preset frequency value can be set according to actual needs.

[0101] For example, the preset threshold is 0.15, the long-period displacement spectrum value is represented by DSP, the initial displacement data of the seismic wave is represented by PG, the filter cutoff frequency is 0.011Hz, the preset frequency value is 0.001Hz, and when the absolute value of the difference between PG and DSP is less than 0.15, the acceleration data after initial filtering is used as the low-frequency noise-free signal of the seismic wave; when the absolute value of the difference between PG and DSP is greater than or equal to 0.15, the preset frequency value is added to the filter cutoff frequency. At this time, the added filter cutoff frequency is 0.01 2Hz, the acceleration data of the seismic wave is filtered again at 0.012Hz to obtain the intermediate filtered acceleration data, the intermediate filtered acceleration data is integrated to obtain the displacement data of the seismic wave, and the absolute value of the difference between the displacement data of the seismic wave and the DSP is determined again. If the absolute value is less than 0.15, it can be determined that there is no low-frequency noise signal of the seismic wave. If the absolute value is still greater than 0.15, the filter cutoff frequency is continuously increased according to the preset frequency value until the absolute value of the difference between the displacement data of the seismic wave and the DSP is less than 0.15.

[0102] In an embodiment of the present application, acceleration data of a seismic wave is obtained; a first seismic parameter and a second seismic parameter are determined, both of which are parameters related to the displacement of the seismic wave; a filtering cutoff frequency of the seismic wave is determined based on the first seismic parameter and the second seismic parameter; the acceleration data of the seismic wave is filtered by the filtering cutoff frequency to obtain a low-frequency noise-free signal of the seismic wave, so that the filtering cutoff frequency can be determined more accurately, and then a low-frequency noise-free signal of the seismic wave can be obtained more accurately.

[0103] The embodiment of the present application provides a seismic wave low-frequency signal recognition device, and the seismic wave low-frequency signal recognition device 200 includes:

[0104] An acquisition module 201 is used to acquire acceleration data of seismic waves;

[0105] A first determination module 202 is configured to determine a first seismic parameter and a second seismic parameter, both of which are parameters related to the displacement of seismic waves;

[0106] A second determining module 203 is configured to determine a filter cutoff frequency of the seismic wave according to the first seismic parameter and the second seismic parameter;

[0107] The filtering module 204 is used to filter the acceleration data of the seismic wave through a filtering cutoff frequency to obtain a seismic wave signal free of low-frequency noise.

[0108] Optionally, the filtering module 204 includes:

[0109] a first filtering unit, configured to filter the acceleration data of the seismic wave by a filtering cutoff frequency to obtain acceleration data after initial filtering;

[0110] An integration unit, used to integrate the acceleration data after initial filtering to obtain displacement data of seismic waves;

[0111] An acquisition unit, used for acquiring long-period displacement spectrum data of seismic waves;

[0112] The first determining unit 202 is configured to determine a low-frequency noise-free signal of a seismic wave based on the long-period displacement spectrum data.

[0113] Optionally, the determining unit is further configured to:

[0114] Subtract the long-period displacement spectrum data from the initial displacement data of the seismic wave to obtain the data difference;

[0115] determining the ratio between the absolute value of the data difference and the initial displacement data of the seismic wave;

[0116] If the ratio is less than a preset threshold, the acceleration data after initial filtering is regarded as the low-frequency noise-free signal of the seismic wave;

[0117] If the ratio is greater than or equal to a preset threshold, the preset frequency value is added to the filter cutoff frequency to obtain the increased filter cutoff frequency, and the acceleration data of the seismic wave is filtered by the increased filter cutoff frequency to obtain intermediate filtered acceleration data, the intermediate filtered acceleration data is integrated to obtain the displacement data of the seismic wave, and the difference between the displacement data of the seismic wave and the long-period displacement spectrum data is re-determined until the absolute value of the difference between the displacement data of the seismic wave and the long-period displacement spectrum data is less than the preset threshold, and the intermediate filtered acceleration data is used as the low-frequency noise-free signal of the seismic wave.

[0118] Optionally, the first determining module 202 includes:

[0119] The second determining unit is used to determine the displacement at the end time of the earthquake motion after filtering and zero padding, the peak displacement of the earthquake motion after filtering, the displacement of the jth point before the arrival of the P wave in the displacement time history after filtering, and the number of sampling points selected before the arrival of the P wave;

[0120] The third determining unit is configured to determine the ratio of the displacement at the end of the ground motion after filtering and zero padding to the peak displacement of the ground motion after filtering, so as to obtain a first earthquake parameter;

[0121] The fourth determination unit is used to determine the second seismic parameter according to the displacement of the jth point before the arrival of the P wave in the filtered displacement time history and the number of sampling points selected before the arrival of the P wave, where j is a positive integer greater than 0.

[0122] Optionally, the second determining module 203 includes:

[0123] a fifth determining unit, configured to determine an azimuth of the acceleration data of the seismic wave;

[0124] a sixth determining unit, configured to determine a first cutoff frequency corresponding to the first seismic parameter according to the azimuth and the first seismic parameter;

[0125] a seventh determining unit, configured to determine a second cutoff frequency corresponding to the second seismic parameter according to the azimuth and the second seismic parameter;

[0126] The eighth determining unit is configured to determine an average of the first cutoff frequency and the second cutoff frequency, and use the average as the filtering cutoff frequency.

[0127] In an embodiment of the present application, acceleration data of a seismic wave is obtained; a first seismic parameter and a second seismic parameter are determined, both of which are parameters related to the displacement of the seismic wave; a filtering cutoff frequency of the seismic wave is determined based on the first seismic parameter and the second seismic parameter; the acceleration data of the seismic wave is filtered by the filtering cutoff frequency to obtain a low-frequency noise-free signal of the seismic wave, so that the filtering cutoff frequency can be determined more accurately, and then a low-frequency noise-free signal of the seismic wave can be obtained more accurately.

[0128] The seismic wave low-frequency signal recognition device in the embodiment of the present application can be an electronic device, or a component in the electronic device, such as an integrated circuit or chip. The electronic device can be a terminal, or other devices other than a terminal. For example, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a mobile internet device (MID), an augmented reality (AR) / virtual reality (VR) device, a robot, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc. It can also be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), a teller machine, or a self-service machine, etc., and the embodiment of the present application does not specifically limit it.

[0129] The seismic wave low-frequency signal recognition device in the embodiment of the present application can be a device having an operating system. The operating system can be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0130] The seismic wave low-frequency signal recognition device provided in the embodiment of the present application can achieve Figure 1 To avoid repetition, the various processes implemented in the method embodiment are not described here.

[0131] Alternatively, as Figure 3 As shown, an embodiment of the present application also provides an electronic device 300, including a processor 301 and a memory 302, wherein the memory 302 stores a program or instruction that can be run on the processor 301. When the program or instruction is executed by the processor 301, the various steps of the above-mentioned embodiment of the seismic wave low-frequency signal recognition method are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0132] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0133] Figure 4 A schematic diagram of the hardware structure of an electronic device implementing an embodiment of the present application.

[0134] The electronic device 1000 includes but is not limited to components such as a radio frequency unit 1001 , a network module 1002 , an audio output unit 1003 , an input unit 1004 , a sensor 1005 , a display unit 1006 , a user input unit 1007 , an interface unit 1008 , a memory 1009 , and a processor 1010 .

[0135] Those skilled in the art will understand that the electronic device 1000 may also include a power source (such as a battery) to power each component, and the power source may be logically connected to the processor 1010 through a power management system, thereby implementing functions such as charging, discharging, and power consumption management through the power management system. Figure 4 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be repeated here.

[0136] Among them, processor 1010 is used to obtain acceleration data of seismic waves; determine a first seismic parameter and a second seismic parameter, both of which are parameters related to the displacement of seismic waves; determine a filtering cutoff frequency of the seismic wave based on the first seismic parameter and the second seismic parameter; filter the acceleration data of the seismic wave by the filtering cutoff frequency to obtain a seismic wave signal without low-frequency noise.

[0137] In an embodiment of the present application, acceleration data of a seismic wave is obtained; a first seismic parameter and a second seismic parameter are determined, both of which are parameters related to the displacement of the seismic wave; a filtering cutoff frequency of the seismic wave is determined based on the first seismic parameter and the second seismic parameter; the acceleration data of the seismic wave is filtered by the filtering cutoff frequency to obtain a low-frequency noise-free signal of the seismic wave, so that the filtering cutoff frequency can be determined more accurately, and then a low-frequency noise-free signal of the seismic wave can be obtained more accurately.

[0138] Optionally, the processor 1010 is used to: filter the acceleration data of the seismic wave by the filtering cutoff frequency to obtain the initial filtered acceleration data; integrate the initial filtered acceleration data to obtain the displacement data of the seismic wave; obtain the long-period displacement spectrum data of the seismic wave; and determine the low-frequency noise-free signal of the seismic wave based on the long-period displacement spectrum data.

[0139] Optionally, the processor 1010 is used to: subtract the long-period displacement spectrum data from the initial displacement data of the seismic wave to obtain a data difference; determine the ratio between the absolute value of the data difference and the initial displacement data of the seismic wave; if the ratio is less than a preset threshold, use the initial filtered acceleration data as the seismic wave's low-frequency noise-free signal; if the ratio is greater than or equal to the preset threshold, add the preset frequency value to the filter cutoff frequency to obtain the increased filter cutoff frequency, and filter the seismic wave's acceleration data by the increased filter cutoff frequency to obtain intermediate filtered acceleration data, integrate the intermediate filtered acceleration data to obtain the seismic wave's displacement data, and re-determine the difference between the seismic wave's displacement data and the long-period displacement spectrum data, until the absolute value of the difference between the seismic wave's displacement data and the long-period displacement spectrum data is less than the preset threshold, and use the intermediate filtered acceleration data as the seismic wave's low-frequency noise-free signal.

[0140] Optionally, the processor 1010 is used to: determine the displacement at the end time of the seismic motion after filtering and zero padding, the peak displacement of the seismic motion after filtering, the displacement of the jth point in the displacement time series before the arrival of the P wave after filtering, and the number of sampling points selected before the arrival of the P wave, where j is a positive integer greater than 0; determine the ratio of the displacement at the end time of the seismic motion after filtering and zero padding to the peak displacement of the seismic motion after filtering to obtain a first seismic parameter; determine the second seismic parameter based on the displacement of the jth point in the displacement time series before the arrival of the P wave after filtering and the number of sampling points selected before the arrival of the P wave.

[0141] Optionally, processor 1010 is used to: determine the azimuth of the acceleration data of the seismic wave; determine a first cutoff frequency corresponding to the first seismic parameter based on the azimuth and the first seismic parameter; determine a second cutoff frequency corresponding to the second seismic parameter based on the azimuth and the second seismic parameter; determine the mean of the first cutoff frequency and the second cutoff frequency, and use the mean as the filtering cutoff frequency.

[0142] In an embodiment of the present application, acceleration data of a seismic wave is obtained; a first seismic parameter and a second seismic parameter are determined, both of which are parameters related to the displacement of the seismic wave; a filtering cutoff frequency of the seismic wave is determined based on the first seismic parameter and the second seismic parameter; the acceleration data of the seismic wave is filtered by the filtering cutoff frequency to obtain a low-frequency noise-free signal of the seismic wave, so that the filtering cutoff frequency can be determined more accurately, and then a low-frequency noise-free signal of the seismic wave can be obtained more accurately.

[0143] It should be understood that in an embodiment of the present application, the input unit 1004 may include a graphics processing unit (GPU) 10041 and a microphone 10042, and the graphics processor 10041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 1006 may include a display panel 10061, and the display panel 10061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 1007 includes a touch panel 10071 and at least one of other input devices 10072. The touch panel 10071 is also called a touch screen. The touch panel 10071 may include two parts: a touch analysis device and a touch controller. Other input devices 10072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which will not be repeated here.

[0144] The memory 1009 can be used to store software programs and various data. The memory 1009 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, applications or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). In addition, the memory 1009 may include a volatile memory or a non-volatile memory, or the memory x09 may include both volatile and non-volatile memory. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM), and a direct memory bus random access memory (DRRAM). The memory 1009 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0145] Processor 1010 may include one or more processing units. Optionally, processor 1010 integrates an application processor and a modem processor. The application processor primarily handles operations related to the operating system, user interface, and application programs, while the modem processor primarily processes wireless communication signals, such as a baseband processor. It is understood that the modem processor may not be integrated into processor 1010.

[0146] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned embodiment of the seismic wave low-frequency signal identification method are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0147] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes a computer readable storage medium, such as a computer readable only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0148] The chip provided by the embodiment of the present application includes a processor and a communication interface, the communication interface is coupled with the processor, the processor is used to run programs or instructions to realize the processes of the above-mentioned seismic wave low-frequency signal identification method embodiments and achieve the same technical effects. To avoid repetition, details are not described here.

[0149] It should be understood that the chip mentioned in the embodiment of the present application can also be referred to as a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0150] The embodiment of the present application provides a computer program product stored in a storage medium, which is executed by at least one processor to realize the processes of the above-mentioned seismic wave low-frequency signal identification method embodiments and achieve the same technical effects. To avoid repetition, details are not described here.

[0151] It should be noted that in this paper, the term "include", "contain" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes elements inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the method and device in the embodiment of the present application is not limited to the order of functions shown or discussed, but can also include functions performed in a substantially simultaneous manner or in the opposite order according to the functions involved, for example, the described method can be performed in an order different from the described order, and various steps can also be added, omitted or combined. In addition, the features described with reference to some examples can be combined in other examples.

[0152] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), including a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0153] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. A method for identifying low-frequency seismic wave signals, characterized in that: The seismic wave low-frequency signal recognition method comprises: Obtain acceleration data of seismic waves; Determining a first seismic parameter and a second seismic parameter, wherein the first seismic parameter and the second seismic parameter are both parameters related to the displacement of the seismic wave; determining a filtering cutoff frequency of the seismic wave according to the first seismic parameter and the second seismic parameter; Filtering the acceleration data of the seismic wave by the filtering cutoff frequency to obtain a low-frequency noise-free signal of the seismic wave; The filtering of the acceleration data of the seismic wave by the filter cutoff frequency to obtain a low-frequency noise-free signal of the seismic wave includes: Filtering the acceleration data of the seismic wave by the filtering cutoff frequency to obtain initial filtered acceleration data; Integrating the acceleration data after the initial filtering to obtain displacement data of the seismic wave; Acquiring long-period displacement spectrum data of the seismic wave; Determining a low-frequency noise-free signal of the seismic wave based on the long-period displacement spectrum data; Wherein, determining the low-frequency noise-free signal of the seismic wave based on the long-period displacement spectrum data includes: Subtracting the long-period displacement spectrum data from the initial displacement data of the seismic wave to obtain a data difference; determining a ratio between an absolute value of the data difference and the initial displacement data of the seismic wave; If the ratio is less than a preset threshold, the acceleration data after the initial filtering is used as the low-frequency noise-free signal of the seismic wave; If the ratio is greater than or equal to the preset threshold, the preset frequency value is added to the filter cutoff frequency to obtain the increased filter cutoff frequency, and the acceleration data of the seismic wave is filtered by the increased filter cutoff frequency to obtain intermediate filtered acceleration data, the intermediate filtered acceleration data is integrated to obtain the displacement data of the seismic wave, and the difference between the displacement data of the seismic wave and the long-period displacement spectrum data is re-determined until the absolute value of the difference between the displacement data of the seismic wave and the long-period displacement spectrum data is less than the preset threshold, and the intermediate filtered acceleration data is used as the low-frequency noise-free signal of the seismic wave.

2. The method for identifying low-frequency seismic wave signals according to claim 1, wherein: The determining of the first seismic parameter and the second seismic parameter includes: Determine the displacement at the end of the ground motion after filtering and zero padding, the peak displacement of the ground motion after filtering, the displacement of the jth point before the arrival of the P wave after filtering, and the number of sampling points before the arrival of the P wave, where j is a positive integer greater than 0; Determine the ratio of the displacement at the end of the ground motion after filtering and zero padding to the peak displacement of the ground motion after filtering to obtain the first earthquake parameter; The second seismic parameter is determined according to the displacement of the jth point of the filtered displacement time history before the arrival of the P wave and the number of sampling points selected before the arrival of the P wave.

3. The method for identifying low-frequency seismic wave signals according to claim 1, wherein: The determining of the filtering cutoff frequency of the seismic wave according to the first seismic parameter and the second seismic parameter includes: determining the azimuth of the acceleration data of the seismic wave; determining a first cutoff frequency corresponding to the first seismic parameter according to the azimuth and the first seismic parameter; determining a second cutoff frequency corresponding to the second seismic parameter according to the azimuth and the second seismic parameter; An average of the first cutoff frequency and the second cutoff frequency is determined, and the average is used as the filtering cutoff frequency.

4. A seismic wave low-frequency signal recognition device, characterized in that: The seismic wave low-frequency signal recognition device comprises: An acquisition module, used to obtain acceleration data of seismic waves; A first determination module is configured to determine a first seismic parameter and a second seismic parameter, both of which are parameters related to the displacement of the seismic wave; a second determining module, configured to determine a filtering cutoff frequency of the seismic wave according to the first seismic parameter and the second seismic parameter; a filtering module, configured to filter the acceleration data of the seismic wave by the filtering cutoff frequency to obtain a low-frequency noise-free signal of the seismic wave; Wherein, the filtering module includes: a first filtering unit, configured to filter the acceleration data of the seismic wave using the filtering cutoff frequency to obtain acceleration data after initial filtering; an integration unit, configured to integrate the acceleration data after the initial filtering to obtain displacement data of the seismic wave; an acquisition unit, configured to acquire long-period displacement spectrum data of the seismic wave; a first determining unit, configured to determine a low-frequency noise-free signal of the seismic wave based on the long-period displacement spectrum data; The determining unit is further configured to: Subtracting the long-period displacement spectrum data from the initial displacement data of the seismic wave to obtain a data difference; determining a ratio between an absolute value of the data difference and the initial displacement data of the seismic wave; If the ratio is less than a preset threshold, the acceleration data after the initial filtering is used as the low-frequency noise-free signal of the seismic wave; If the ratio is greater than or equal to the preset threshold, the preset frequency value is added to the filter cutoff frequency to obtain the increased filter cutoff frequency, and the acceleration data of the seismic wave is filtered by the increased filter cutoff frequency to obtain intermediate filtered acceleration data, the intermediate filtered acceleration data is integrated to obtain the displacement data of the seismic wave, and the difference between the displacement data of the seismic wave and the long-period displacement spectrum data is re-determined until the absolute value of the difference between the displacement data of the seismic wave and the long-period displacement spectrum data is less than the preset threshold, and the intermediate filtered acceleration data is used as the low-frequency noise-free signal of the seismic wave.

5. An electronic device, characterized in that: It includes a processor and a memory, the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the steps of the seismic wave low-frequency signal identification method according to any one of claims 1 to 3 are implemented.

6. A storage medium, characterized in that The storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of the seismic wave low-frequency signal identification method according to any one of claims 1 to 3 are implemented.

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