Earthquake information summary generation method and device, terminal and storage medium

Abstract

The invention provides an earthquake information summary generation method and device, a terminal and a storage medium. The method comprises the following steps: determining the position of a seismic source based on observation seismic waves of a plurality of seismic observation sites; based on seismic wave transmission characteristics between each seismic observation site and the seismic source position, inversion is carried out on each observation seismic wave, and original seismic waves corresponding to each observation seismic wave are obtained; fusing and splicing the original seismic waves based on time and categories to obtain seismic source seismic waves; and earthquake information is determined based on the seismic source earthquake waves, and earthquake early warning is carried out based on the earthquake information. According to the invention, data of multiple observation stations can be fused, and accurate earthquake early warning information can be determined in limited early warning time by using limited observation data.

Description

Technical Field

[0001] The present invention relates to the field of earthquake early warning technology, and in particular to a method, device, terminal and storage medium for summarizing and generating earthquake information. Background Art

[0002] China is a country with many earthquakes. The earthquake activities are not only frequent and strong, but also widely distributed, and the disasters they cause are particularly serious. Earthquake early warning is to quickly send out an alarm to the unaffected areas after the earthquake occurs. By taking advantage of the fact that electromagnetic waves propagate faster than seismic waves, early warning information is sent to each terminal before the transverse waves arrive, and the target users can gain a warning time of several seconds to tens of seconds before the destructive seismic waves arrive.

[0003] However, it takes time for the early warning technology system to capture seismic waves, automatically make judgments and decisions, and issue alarms, which makes the seismic wave recording time used for earthquake early warning too short and the contained source rupture information insufficient. Therefore, the measured information such as magnitude is often different from the actual earthquake information, and there is a risk of false alarms and missed alarms. Summary of the invention

[0004] The embodiments of the present invention provide a method, device, terminal and storage medium for generating earthquake information summary to solve the problem of deviation between earthquake warning information and actual earthquake information.

[0005] In a first aspect, an embodiment of the present invention provides a method for summarizing and generating earthquake information, comprising:

[0006] Determine the location of the earthquake source based on the observed seismic waves from multiple seismic observation stations;

[0007] Based on the seismic wave transmission characteristics between each seismic observation station and the source location, each observed seismic wave is inverted to obtain the original seismic wave corresponding to each observed seismic wave;

[0008] The original seismic waves are fused and spliced ​​based on time and category to obtain the source seismic waves;

[0009] Earthquake information is determined based on the earthquake source seismic waves, so as to provide earthquake warning based on the earthquake information.

[0010] In a possible implementation, the categories of observed seismic waves include seismic wave waveforms, seismic phase arrival times, P-wave polarities, high-frequency GNSS displacement waveforms, and strong vibration records; before each observed seismic wave is inverted based on the seismic wave transmission characteristics between each seismic observation station and the source location to obtain the original seismic wave corresponding to each observed seismic wave, the following is also included:

[0011] For each observed seismic wave, the category of the transmission characteristic model corresponding to the observed seismic wave is determined based on the category of the observed seismic wave and a preset transmission characteristic model comparison table, and the parameters of the transmission characteristic model corresponding to the observed seismic wave are determined based on the digital earth model.

[0012] In a possible implementation, before inverting each observed seismic wave based on the seismic wave transmission characteristics between each seismic observation station and the source position to obtain the original seismic wave corresponding to each observed seismic wave, the method further includes:

[0013] For multiple historically observed seismic waves of the first category, a correlation index between an original seismic wave obtained by using a transmission characteristic model of the second category for each historically observed seismic wave and a source seismic wave corresponding to the historically observed seismic wave is calculated, and a correlation index between the first category and the second category is determined based on each correlation index; wherein the first category is any observed seismic wave category, and the second category is any transmission characteristic model category;

[0014] Based on the correlation index between each observed seismic wave category and each transmission characteristic model category, the transmission characteristic model category corresponding to each observed seismic wave category is determined, and a transmission characteristic model comparison table is formed.

[0015] In a possible implementation, the formula for calculating the correlation index between the original seismic wave obtained by using the second type of transmission characteristic model for each historically observed seismic wave and the source seismic wave corresponding to the historically observed seismic wave is:

[0016] R=k1r+k2Se+(1-k2)Sp

[0017] Among them, R is the correlation index between the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model and the source seismic wave corresponding to the historical observation seismic wave, r is the correlation coefficient between the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model and the source seismic wave corresponding to the historical observation seismic wave, Se is the sensitivity of various seismic information of the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model, Sp is the specificity of various seismic information of the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model, and k1 and k2 are preset weights.

[0018] In a possible implementation, before inverting each observed seismic wave based on the seismic wave transmission characteristics between each seismic observation station and the source position to obtain the original seismic wave corresponding to each observed seismic wave, the method further includes:

[0019] The information reliability index of each observed seismic wave is calculated based on the information reliability index calculation formula; wherein the information reliability index calculation formula is:

[0020] Q=k3R′+k4T+k5IOU T

[0021] Among them, Q is the information reliability index of the observed seismic wave, R′ is the correlation index between the category of the observed seismic wave and the category of the transmission characteristic model, T is the duration of the observed seismic wave, and IOU T is the time window intersection and comparison of the observed seismic wave and other observed seismic waves, k3, k4, k5 are preset weights;

[0022] The observed seismic waves are sorted in descending order according to the information reliability index, and the first n observed seismic waves are retained to invert the first n observed seismic waves; wherein n is a preset value.

[0023] In a possible implementation, each original seismic wave is fused and spliced ​​based on time and category, including:

[0024] Perform time calibration on each seismic observation point, and align each original seismic wave on a time scale based on the time calibration result;

[0025] The original seismic waves of each category are superimposed in the time domain and the frequency domain to obtain the superimposed signal of each category;

[0026] The superimposed signals of each category are spliced ​​together in a preset order to obtain the source seismic waves.

[0027] In a possible implementation, each original seismic wave of each category is superimposed in the time domain and the frequency domain to obtain a superimposed signal of each category, including:

[0028] Superimposing the original seismic waves of the third category in the time domain to obtain the first seismic wave of the third category; wherein the third category is any observed seismic wave category;

[0029] The original seismic waves of the third category are converted into the frequency domain and superimposed, and then the superimposed signals are converted into the time domain to obtain the second seismic waves of the third category;

[0030] A superimposed signal of a third category is determined based on the first seismic wave and the second seismic wave.

[0031] In a second aspect, an embodiment of the present invention provides a seismic information summary generating device, comprising:

[0032] A positioning module for determining the location of the earthquake source based on the observed seismic waves from multiple seismic observation sites;

[0033] An inversion module is used to invert each observed seismic wave based on the seismic wave transmission characteristics between each seismic observation station and the source position, and obtain the original seismic wave corresponding to each observed seismic wave;

[0034] A fusion module is used to fuse and splice the original seismic waves based on time and category to obtain source seismic waves;

[0035] The early warning module is used to determine earthquake information based on the earthquake source seismic waves so as to carry out earthquake early warning based on the earthquake information.

[0036] In a third aspect, an embodiment of the present invention provides a terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method described in the first aspect or any possible implementation method of the first aspect are implemented.

[0037] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in the first aspect or any possible implementation method of the first aspect are implemented.

[0038] The embodiments of the present invention provide a method, device, terminal and storage medium for summarizing and generating earthquake information. The earthquake information at the earthquake source location can be obtained by inverting each observed earthquake wave through the earthquake wave transmission characteristics between each earthquake observation station and the earthquake source location. Then, the earthquake wave at the earthquake source location is inverted using simple processing steps such as time-space fusion and waveform superposition. Compared with using the earthquake wave at the observation station location alone, the measured earthquake information is more accurate. The data from multiple observation stations are fused to achieve a transformation from data quantity to data quality, and accurate earthquake warning information can be determined within a limited warning time using limited observation data. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0040] Figure 1 It is a flow chart of the implementation of the earthquake information summary generation method provided by one embodiment of the present invention;

[0041] Figure 2 It is a structural schematic diagram of a seismic information summary generating device provided by an embodiment of the present invention;

[0042] Figure 3 is a schematic diagram of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0044] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0045] See also Figure 1 , which shows a flow chart of the implementation of the earthquake information summary generation method provided by an embodiment of the present invention, and is described in detail as follows:

[0046] Step 101, determining the earthquake source location based on the observed seismic waves from multiple seismic observation stations.

[0047] In this embodiment, the epicenter location refers to the specific location where the earthquake occurs, which is located deep inside the earth and is where the seismic waves are generated. Observed seismic waves are earthquake-related signals collected by seismic observation stations. The epicenter location is a component of the three elements of an earthquake, including the geographic coordinates (longitude, latitude) and depth of the epicenter.

[0048] Determining the location of the epicenter is very important for understanding the causes of earthquakes, the characteristics of seismic wave propagation, and assessing the damage that an earthquake may cause. Currently, earthquake location methods (such as triangulation) are usually used to calculate the location and depth of the epicenter through the time differences in the arrival of seismic waves recorded by the seismic monitoring network at each monitoring station.

[0049] Step 102, based on the seismic wave transmission characteristics between each seismic observation station and the source location, each observed seismic wave is inverted to obtain the original seismic wave corresponding to each observed seismic wave.

[0050] In this embodiment, the original seismic wave refers to the seismic wave at the source location. Since each seismic observation station is usually set at a different location, the observed seismic waves collected by each seismic observation station are seismic waves transmitted through different paths. Therefore, based on the seismic wave transmission characteristics of each transmission path, that is, the seismic wave transmission characteristics between each seismic observation station and the source location, the observed seismic wave can be inverted to determine the original seismic wave.

[0051] Step 103, fusing and splicing the original seismic waves based on time and category to obtain source seismic waves.

[0052] In this embodiment, since the data types, duration of observed seismic waves, and start and end times collected by each earthquake observation station may be different, the information contained in each observed seismic wave is also different. In addition, the time from the occurrence of an earthquake to the issuance of an early warning needs to be as short as possible, which results in a short duration of data that can be used for earthquake early warning analysis. Early warning analysis based on these data is difficult and has low accuracy.

[0053] This embodiment fuses and splices the original seismic waves in terms of time and category dimensions, extracts and fuses the different information contained in multiple original seismic waves, and converts the number of signals of the original seismic waves into information volume. Compared with directly analyzing the observation data, it has higher accuracy, thereby improving the ability to obtain earthquake warning information that is as accurate as possible based on limited data time.

[0054] Step 104, determining earthquake information based on the source seismic wave, so as to provide earthquake early warning based on the earthquake information.

[0055] In this embodiment, earthquake information may include three elements of earthquake, source mechanism, earthquake rupture model, etc. The source seismic wave obtained by the above steps has more and more comprehensive useful information than a single observed seismic wave, and can reflect more earthquake information, thereby obtaining a more accurate and effective earthquake early warning effect.

[0056] The embodiment of the present invention inverts each observed seismic wave through the seismic wave transmission characteristics between each seismic observation station and the earthquake source location, so as to obtain the seismic information of the earthquake source location, and then utilizes simple processing steps such as time-space fusion and waveform superposition to invert the seismic wave at the earthquake source location. Compared with using the seismic wave at the observation station location alone, the measured seismic information is more accurate. The data from multiple observation stations are fused to realize the transformation from data quantity to data quality, and accurate earthquake warning information can be determined within a limited warning time using limited observation data.

[0057] In a possible implementation, the categories of observed seismic waves include seismic wave waveforms, seismic phase arrival times, P-wave polarities, high-frequency GNSS displacement waveforms, and strong vibration records; before each observed seismic wave is inverted based on the seismic wave transmission characteristics between each seismic observation station and the source location to obtain the original seismic wave corresponding to each observed seismic wave, the following is also included:

[0058] For each observed seismic wave, the category of the transmission characteristic model corresponding to the observed seismic wave is determined based on the category of the observed seismic wave and a preset transmission characteristic model comparison table, and the parameters of the transmission characteristic model corresponding to the observed seismic wave are determined based on the digital earth model.

[0059] In this embodiment, the categories of transmission characteristic models may include layered models, ray theory models, horizontal layered models, profile models, full three-dimensional models, finite element models, finite difference models, uniform medium models, isotropic medium models, anisotropic medium models, etc. Each model describes the transmission characteristics of seismic waves differently, and there are also differences between the effects of inverting the observed seismic waves. In this regard, before the actual earthquake early warning, a transmission characteristic model comparison table can be constructed in advance, and the category of the observed seismic waves in the transmission characteristic model comparison table can be directly used during the early warning to determine the most appropriate transmission characteristic model category, without the need to select the model category in real time, thereby improving the early warning speed.

[0060] The digital earth model can provide a gridded description of the seismic wave propagation medium in the earth. For seismic observation sites and earthquake sources at arbitrary coordinates, the digital earth model can be used to accurately describe the propagation medium information of each part of the seismic wave transmission path, thereby determining the transmission characteristics of the entire transmission path and the parameters of the transmission characteristics model.

[0061] In a possible implementation, before inverting each observed seismic wave based on the seismic wave transmission characteristics between each seismic observation station and the source position to obtain the original seismic wave corresponding to each observed seismic wave, the method further includes:

[0062] For multiple historically observed seismic waves of the first category, a correlation index between an original seismic wave obtained by using a transmission characteristic model of the second category for each historically observed seismic wave and a source seismic wave corresponding to the historically observed seismic wave is calculated, and a correlation index between the first category and the second category is determined based on each correlation index; wherein the first category is any observed seismic wave category, and the second category is any transmission characteristic model category;

[0063] Based on the correlation index between each observed seismic wave category and each transmission characteristic model category, the transmission characteristic model category corresponding to each observed seismic wave category is determined, and a transmission characteristic model comparison table is formed.

[0064] In this embodiment, for each historical observed seismic wave under each observed seismic wave category, different categories of transmission characteristic models can be used for inversion, and the correlation index between the original seismic wave obtained by inversion and the source seismic wave actually collected is calculated to evaluate the correlation between the original seismic wave and the source seismic wave, and used to describe the effect of each category of transmission characteristic model applied to the inversion of each category of observed seismic wave. The higher the correlation between the original seismic wave and the source seismic wave, the more the category of the transmission characteristic model matches the category of the observed seismic wave.

[0065] The correlation index between the first category and the second category can be multiple historically observed seismic waves of the first category, and the average value of the correlation index between the original seismic wave obtained by using the transmission characteristic model of the second category for each historically observed seismic wave and the source seismic wave corresponding to the historically observed seismic wave is calculated.

[0066] In a possible implementation, the formula for calculating the correlation index between the original seismic wave obtained by using the second type of transmission characteristic model for each historically observed seismic wave and the source seismic wave corresponding to the historically observed seismic wave is:

[0067] R=k1r+k2Se+(1-k2)Sp

[0068] Among them, R is the correlation index between the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model and the source seismic wave corresponding to the historical observation seismic wave, r is the correlation coefficient between the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model and the source seismic wave corresponding to the historical observation seismic wave, Se is the sensitivity of various seismic information of the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model, Sp is the specificity of various seismic information of the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model, and k1 and k2 are preset weights.

[0069] In this embodiment, k1 and k2 can be set according to actual conditions. The correlation coefficient is used to describe the closeness of the correlation between two signal sequences. The larger the correlation coefficient, the greater the contribution that the original seismic wave can make in the process of fusion and splicing to obtain the source seismic wave.

[0070] Sensitivity, also known as the True Positive Rate, refers to the percentage of earthquake events correctly predicted by the early warning system to all actual earthquake events. Specificity, also known as the True Negative Rate, refers to the percentage of non-earthquake events correctly predicted by the early warning system to all actual earthquake events that did not occur. The original seismic wave obtained by the second category of transmission characteristic model of historical observed seismic waves can be set to be correct when the deviation between the predicted seismic information and the actual seismic information is within the corresponding threshold range. Based on sensitivity and specificity, the inversion effect of each category of transmission characteristic model on the observed seismic wave can be described from another perspective.

[0071] In a possible implementation, before inverting each observed seismic wave based on the seismic wave transmission characteristics between each seismic observation station and the source position to obtain the original seismic wave corresponding to each observed seismic wave, the method further includes:

[0072] The information reliability index of each observed seismic wave is calculated based on the information reliability index calculation formula; wherein the information reliability index calculation formula is:

[0073] Q=k3R′+k4T+k5IOU T

[0074] Among them, Q is the information reliability index of the observed seismic wave, R′ is the correlation index between the category of the observed seismic wave and the category of the transmission characteristic model, T is the duration of the observed seismic wave, and IOU T is the time window intersection and comparison of the observed seismic wave and other observed seismic waves, k3, k4, k5 are preset weights;

[0075] The observed seismic waves are sorted in descending order according to the information reliability index, and the first n observed seismic waves are retained to invert the first n observed seismic waves; wherein n is a preset value.

[0076] In this embodiment, k3, k4, k5 and n can be set according to actual conditions. The larger the correlation index between the category of the observed seismic wave and the category of the transmission characteristic model, the better the effect of the source seismic wave obtained by fusion splicing based on the observed seismic wave. The longer the duration of the observed seismic wave, the more useful information may be contained in the observed seismic wave. The time window intersection-combination ratio of the observed seismic wave and other observed seismic waves = the overlapping length of the time window of the observed seismic wave and other observed seismic waves / the time window length of all observed seismic waves. The smaller the time window intersection-combination ratio, the observed seismic wave involves the time period not collected by other observed seismic waves, and contains more information not in other observed seismic waves.

[0077] By setting reasonable weights to weight and combine the above indicators, we can make a comprehensive description of the information content of each observed seismic wave and the effect of the source seismic waves obtained by inversion, fusion and splicing, so as to select observed seismic waves with higher processing value and save time in data processing.

[0078] In addition, when the category of observed seismic waves includes earthquake precursor data, the earthquake precursor data (groundwater level changes, geothermal changes, electromagnetic changes, and infrasound waves before the arrival of the earthquake phase) can also be used as calculation items in the information reliability index calculation formula. The greater the groundwater level changes, geothermal changes, electromagnetic changes, and infrasound waves before the arrival of the earthquake phase, the greater the information content of the observed seismic waves.

[0079] In a possible implementation, each original seismic wave is fused and spliced ​​based on time and category, including:

[0080] Perform time calibration on each seismic observation point, and align each original seismic wave on a time scale based on the time calibration result;

[0081] The original seismic waves of each category are superimposed in the time domain and the frequency domain to obtain the superimposed signal of each category;

[0082] The superimposed signals of each category are spliced ​​together in a preset order to obtain the source seismic waves.

[0083] In this embodiment, time calibration can solve the problem of inconsistent time at each seismic observation station, thereby aligning each original seismic wave. Superimposing each original seismic wave according to category and splicing them in a preset order can solve the problem of data heterogeneity, thereby obtaining source seismic waves with a unified format, which is convenient for analyzing in a preset manner to obtain seismic information.

[0084] Time-frequency fusion refers to combining information in the time domain and frequency domain to extract useful features from the data and perform more effective signal processing and analysis. In the time domain, the signal is represented as a function of time, and its change over time can be observed. In the frequency domain, the signal is decomposed into a combination of sine waves and cosine waves of different frequencies, and the frequency components of the signal can be analyzed. Time-frequency fusion technology combines the advantages of the time domain and the frequency domain, and can provide information on the signal in both time and frequency, thereby increasing the useful information in the earthquake source seismic waves.

[0085] In a possible implementation, each original seismic wave of each category is superimposed in the time domain and the frequency domain to obtain a superimposed signal of each category, including:

[0086] Superimposing the original seismic waves of the third category in the time domain to obtain the first seismic wave of the third category; wherein the third category is any observed seismic wave category;

[0087] The original seismic waves of the third category are converted into the frequency domain and superimposed, and then the superimposed signals are converted into the time domain to obtain the second seismic waves of the third category;

[0088] A superimposed signal of a third category is determined based on the first seismic wave and the second seismic wave.

[0089] In this embodiment, the original seismic waves are directly superimposed in the time domain to realize information fusion in the time dimension, and are superimposed after conversion to the frequency domain to realize information fusion in the frequency domain dimension. Finally, the two types of fused waveforms are superimposed again in the time domain to complete the time-frequency fusion of the original seismic waves of the third category.

[0090] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0091] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0092] Figure 2 The schematic diagram of the structure of the earthquake information summary generating device provided by the embodiment of the present invention is shown. For the convenience of explanation, only the part related to the embodiment of the present invention is shown, which is described in detail as follows:

[0093] like Figure 2 As shown, the earthquake information summary generating device 2 comprises:

[0094] A positioning module 21, used to determine the earthquake source location based on the observed seismic waves of multiple seismic observation sites;

[0095] An inversion module 22 is used to invert each observed seismic wave based on the seismic wave transmission characteristics between each seismic observation station and the source position, and obtain the original seismic wave corresponding to each observed seismic wave;

[0096] A fusion module 23 is used to fuse and splice the original seismic waves based on time and category to obtain source seismic waves;

[0097] The early warning module 24 is used to determine earthquake information based on the earthquake source seismic waves, so as to perform earthquake early warning based on the earthquake information.

[0098] In a possible implementation, the categories of observed seismic waves include seismic wave waveforms, seismic phase arrival times, P-wave polarity, high-frequency GNSS displacement waveforms, and strong vibration records; the inversion module 22 is also used for:

[0099] Based on the seismic wave transmission characteristics between each seismic observation station and the source location, each observed seismic wave is inverted to obtain the original seismic wave corresponding to each observed seismic wave. For each observed seismic wave, based on the category of the observed seismic wave and a preset transmission characteristic model comparison table, the category of the transmission characteristic model corresponding to the observed seismic wave is determined, and the parameters of the transmission characteristic model corresponding to the observed seismic wave are determined based on the digital earth model.

[0100] In a possible implementation, the inversion module 22 is further used for:

[0101] Based on the seismic wave transmission characteristics between each seismic observation station and the source location, each observed seismic wave is inverted respectively to obtain the original seismic wave corresponding to each observed seismic wave, and for multiple historical observed seismic waves of the first category, the correlation index between the original seismic wave obtained by using the transmission characteristic model of the second category for each historical observed seismic wave and the source seismic wave corresponding to the historical observed seismic wave is calculated, and the correlation index between the first category and the second category is determined based on each correlation index; wherein the first category is any observed seismic wave category, and the second category is any transmission characteristic model category;

[0102] Based on the correlation index between each observed seismic wave category and each transmission characteristic model category, the transmission characteristic model category corresponding to each observed seismic wave category is determined, and a transmission characteristic model comparison table is formed.

[0103] In a possible implementation, the formula for calculating the correlation index between the original seismic wave obtained by using the second type of transmission characteristic model for each historically observed seismic wave and the source seismic wave corresponding to the historically observed seismic wave is:

[0104] R=k1r+k2Se+(1-k2)Sp

[0105] Among them, R is the correlation index between the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model and the source seismic wave corresponding to the historical observation seismic wave, r is the correlation coefficient between the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model and the source seismic wave corresponding to the historical observation seismic wave, Se is the sensitivity of various seismic information of the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model, Sp is the specificity of various seismic information of the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model, and k1 and k2 are preset weights.

[0106] In a possible implementation, the inversion module 22 is further used for:

[0107] Based on the seismic wave transmission characteristics between each seismic observation station and the source location, each observed seismic wave is inverted respectively to obtain the original seismic wave corresponding to each observed seismic wave. The information reliability index of each observed seismic wave is calculated based on the information reliability index calculation formula; wherein, the information reliability index calculation formula is:

[0108] Q=k3R′+k4T+k5IOU T

[0109] Among them, Q is the information reliability index of the observed seismic wave, R′ is the correlation index between the category of the observed seismic wave and the category of the transmission characteristic model, T is the duration of the observed seismic wave, and IOUT is the time window intersection and comparison of the observed seismic wave and other observed seismic waves, k3, k4, k5 are preset weights;

[0110] The observed seismic waves are sorted in descending order according to the information reliability index, and the first n observed seismic waves are retained to invert the first n observed seismic waves; wherein n is a preset value.

[0111] In a possible implementation, the fusion module 23 is specifically configured to:

[0112] Perform time calibration on each seismic observation point, and align each original seismic wave on a time scale based on the time calibration result;

[0113] The original seismic waves of each category are superimposed in the time domain and the frequency domain to obtain the superimposed signal of each category;

[0114] The superimposed signals of each category are spliced ​​together in a preset order to obtain the source seismic waves.

[0115] In a possible implementation, the fusion module 23 is specifically configured to:

[0116] Superimposing the original seismic waves of the third category in the time domain to obtain the first seismic wave of the third category; wherein the third category is any observed seismic wave category;

[0117] The original seismic waves of the third category are converted into the frequency domain and superimposed, and then the superimposed signals are converted into the time domain to obtain the second seismic waves of the third category;

[0118] Determining a third type of superimposed signal based on the first seismic wave and the second seismic wave

[0119] The embodiment of the present invention inverts each observed seismic wave through the seismic wave transmission characteristics between each seismic observation station and the earthquake source location, so as to obtain the seismic information of the earthquake source location, and then utilizes simple processing steps such as time-space fusion and waveform superposition to invert the seismic wave at the earthquake source location. Compared with using the seismic wave at the observation station location alone, the measured seismic information is more accurate. The data from multiple observation stations are fused to realize the transformation from data quantity to data quality, and accurate earthquake warning information can be determined within a limited warning time using limited observation data.

[0120] Figure 3 is a schematic diagram of a terminal provided by an embodiment of the present invention. Figure 3 As shown, the terminal 3 of this embodiment includes: a processor 30, a memory 31, and a computer program 32 stored in the memory 31 and executable on the processor 30. When the processor 30 executes the computer program 32, the steps in the above-mentioned various earthquake information summary generation method embodiments are implemented, for example Figure 1 Alternatively, when the processor 30 executes the computer program 32, the functions of each module / unit in the above-mentioned device embodiments are realized, for example, Figure 2 Functions of the modules / units 21 to 24 are shown.

[0121] Exemplarily, the computer program 32 may be divided into one or more modules / units, which are stored in the memory 31 and executed by the processor 30 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program 32 in the terminal 3. For example, the computer program 32 may be divided into Figure 2 Modules / units 21 to 24 are shown.

[0122] The terminal 3 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal 3 may include, but is not limited to, a processor 30 and a memory 31. Those skilled in the art will appreciate that Figure 3 It is only an example of terminal 3 and does not constitute a limitation on terminal 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal may also include input and output devices, network access devices, buses, etc.

[0123] The processor 30 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0124] The memory 31 may be an internal storage unit of the terminal 3, such as a hard disk or memory of the terminal 3. The memory 31 may also be an external storage device of the terminal 3, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal 3. Further, the memory 31 may also include both an internal storage unit of the terminal 3 and an external storage device. The memory 31 is used to store the computer program and other programs and data required by the terminal. The memory 31 may also be used to temporarily store data that has been output or is to be output.

[0125] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0126] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0127] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0128] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0129] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0130] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0131] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various earthquake information summary generation method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0132] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for generating earthquake information summary, characterized in that: include: Determine the location of the earthquake source based on the observed seismic waves from multiple seismic observation stations; Based on the seismic wave transmission characteristics between each seismic observation station and the earthquake source position, each observed seismic wave is inverted to obtain the original seismic wave corresponding to each observed seismic wave; The original seismic waves are fused and spliced ​​based on time and category to obtain the source seismic waves; Earthquake information is determined based on the source seismic wave, so as to perform earthquake early warning based on the earthquake information.

2. The earthquake information summary generation method according to claim 1, characterized in that: The categories of observed seismic waves include seismic wave waveforms, seismic phase arrival times, P-wave polarity, high-frequency GNSS displacement waveforms, and strong vibration records; before inverting each observed seismic wave based on the seismic wave transmission characteristics between each seismic observation station and the source location to obtain the original seismic wave corresponding to each observed seismic wave, it also includes: For each observed seismic wave, the category of the transmission characteristic model corresponding to the observed seismic wave is determined based on the category of the observed seismic wave and a preset transmission characteristic model comparison table, and the parameters of the transmission characteristic model corresponding to the observed seismic wave are determined based on the digital earth model.

3. The earthquake information summary generation method according to claim 2, characterized in that: Before inverting each observed seismic wave based on the seismic wave transmission characteristics between each seismic observation station and the earthquake source position to obtain the original seismic wave corresponding to each observed seismic wave, the method further includes: For multiple historically observed seismic waves of the first category, a correlation index between an original seismic wave obtained by using a transmission characteristic model of the second category for each historically observed seismic wave and a source seismic wave corresponding to the historically observed seismic wave is calculated, and a correlation index between the first category and the second category is determined based on each correlation index; wherein the first category is any observed seismic wave category, and the second category is any transmission characteristic model category; Based on the correlation index between each observed seismic wave category and each transmission characteristic model category, the transmission characteristic model category corresponding to each observed seismic wave category is determined, and the transmission characteristic model comparison table is formed.

4. The earthquake information summary generation method according to claim 3, characterized in that: The formula for calculating the correlation index between the original seismic wave obtained by using the second type of transmission characteristic model for each historically observed seismic wave and the source seismic wave corresponding to the historically observed seismic wave is: R=k1r+k2Se+(1-k2)Sp Among them, R is the correlation index between the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model and the source seismic wave corresponding to the historical observation seismic wave, r is the correlation coefficient between the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model and the source seismic wave corresponding to the historical observation seismic wave, Se is the sensitivity of various seismic information of the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model, Sp is the specificity of various seismic information of the original seismic wave obtained by the historical observation seismic wave using the second category transmission characteristic model, and k1 and k2 are preset weights.

5. The earthquake information summary generation method according to claim 3, characterized in that: Before inverting each observed seismic wave based on the seismic wave transmission characteristics between each seismic observation station and the earthquake source position to obtain the original seismic wave corresponding to each observed seismic wave, the method further includes: The information reliability index of each observed seismic wave is calculated based on the information reliability index calculation formula; wherein the information reliability index calculation formula is: Q=k3R′+k4T+k5IOU T Among them, Q is the information reliability index of the observed seismic wave, R′ is the correlation index between the category of the observed seismic wave and the category of the transmission characteristic model, T is the duration of the observed seismic wave, and IOU T is the time window intersection and comparison of the observed seismic wave and other observed seismic waves, k3, k4, k5 are preset weights; The observed seismic waves are sorted in descending order according to the information reliability index, and the first n observed seismic waves are retained to invert the first n observed seismic waves; wherein n is a preset value.

6. The earthquake information summary generation method according to claim 1, characterized in that: The fusing and splicing of the original seismic waves based on time and category includes: Perform time calibration on each seismic observation point, and align each original seismic wave on a time scale based on the time calibration result; The original seismic waves of each category are superimposed in the time domain and the frequency domain to obtain the superimposed signal of each category; The superimposed signals of each category are spliced ​​together in a preset order to obtain the source seismic waves.

7. The earthquake information summary generation method according to claim 6, characterized in that: The method of respectively superimposing the original seismic waves of each category in the time domain and the frequency domain to obtain the superimposed signals of each category includes: Superimposing the original seismic waves of the third category in the time domain to obtain the first seismic wave of the third category; wherein the third category is any observed seismic wave category; Converting the original seismic waves of the third category into the frequency domain and superimposing them respectively, and then converting the superimposed signals into the time domain to obtain the second seismic waves of the third category; The superimposed signal of the third category is determined based on the first seismic wave and the second seismic wave.

8. A device for generating earthquake information summary, characterized in that: include: A positioning module for determining the location of the earthquake source based on the observed seismic waves from multiple seismic observation sites; An inversion module, for inverting each observed seismic wave based on the seismic wave transmission characteristics between each seismic observation station and the earthquake source position, to obtain an original seismic wave corresponding to each observed seismic wave; A fusion module is used to fuse and splice the original seismic waves based on time and category to obtain source seismic waves; The early warning module is used to determine earthquake information based on the earthquake source seismic wave, so as to carry out earthquake early warning based on the earthquake information.

9. A terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method as claimed in any one of claims 1 to 7 are implemented.

Images