Near-fault complex effect coupling seismic record data processing method and system
Through the Hilbert-yellow transformation and empirical modal decomposition method, the ideal velocity pulse waveform in the earthquake record is extracted, which solves the problem that the complex effects of near-fault earthquakes cannot be effectively distinguished in the prior art, and the accurate identification of forward directional effects and slip effect and the separation of dynamic and quasi-static components is achieved.
Patent Information
- Application Number
- CN202510433563.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-07
- Publication Date
- 2025-07-11
AI Technical Summary
The prior art cannot effectively distinguish and identify forward directional effect pulses and slip effect pulses in near-fault earthquakes, especially in the case of complex effect coupling, resulting in misjudgment and error analysis.
The Hilbert-yellow transformation and empirical modal decomposition method are used to extract the ideal velocity pulse waveform in the earthquake record, and the forward directional effect and slip effect are distinguished by the displacement difference between the pulse start and end time, and the non-pulse displacement components are further decomposed to achieve accurate identification of different effects.
In-depth analysis of complex effect coupled seismic records is achieved, accurately distinguishing dynamic and quasi-static components, avoiding misjudgment, and improving the accuracy of earthquake characteristics analysis.
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Figure CN120294832A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of seismic record data processing, and particularly to a method and system for processing seismic record data coupled with complex near-fault effects. Background Technique
[0002] The statements in this part only provide background technical information related to the present invention and do not necessarily constitute prior art.
[0003] Research has found that the velocity pulses carried by near-fault ground motions are the main inducements for structural damage, including forward directivity effect pulses and slip pulse effects. The latter is an important manifestation of the surface rupture displacement of the fault and has a particularly significant effect on the damage of near and cross-fault engineering structures. Near-fault ground motions not only have multi-pulse characteristics, but also the velocity pulses caused by the two effects can occur coupled in the same seismic record, which is closely related to the structural dynamic response.
[0004] Currently, the research on the pulse characteristics of near-fault ground motions mainly focuses on single pulses that only consider the forward directivity effect. In the prior art, Baker proposed a wavelet method for quantifying and identifying velocity pulses based on strong ground motion records with forward directivity effects. This method can only extract single pulse waveforms considering a single effect. Zhai et al. proposed an energy method for quantitatively determining near-fault multi-pulse ground motions, but it can only determine multi-pulse ground motions, cannot extract pulse waveforms and pulse-related parameters, and cannot conduct in-depth research on the effects of different actions. Lu and Panagioto proposed an iterative wavelet extraction method for multi-pulse records. This method can extract multi-pulse waveforms that only consider the forward directivity effect from strong ground motion records, but cannot locate the exact moments when each pulse occurs and cannot identify and distinguish different effect pulses.
[0005] The above pulse research methods only focus on the forward directivity effect, do not conduct research on velocity pulses with slip pulse effects, do not mention the coupled pulse characteristics of near-fault double effects, and do not involve further identification of non-dynamic pulse components.
[0006] The slip - pulse effect mainly describes a special phenomenon induced by the rupture of earthquake faults. In near - fault strong - motion records, the slip - pulse effect often manifests as low - frequency dynamic velocity pulse components that are very sensitive to signal - processing techniques. It should be clear that the permanent ground rupture (i.e., permanent displacement) caused by an earthquake is the inducement of the slip - pulse effect. In addition to the slip - pulse effect, site effects, basin effects, ultra - low - frequency static components, etc. can all contribute to the permanent displacement. However, existing technologies often equate the final permanent ground rupture (permanent displacement in strong - motion records) with a single slip - pulse effect, ignoring the dynamic characteristics of the slip - pulse effect and treating it as a static action. They roughly identify the slip - pulse effect in ground motion only based on the presence or absence of permanent displacement in the original earthquake data records and the fault distance. When multiple seismological effects act in a coupled manner, it is extremely easy to lead to misidentification, causing false judgment and resulting in incorrect analysis of ground - motion characteristics and engineering - used ground motion.
[0007] Therefore, limited by the defects in the strong - motion record data - processing method, the existing near - fault strong - motion record data - processing method cannot deeply analyze complex - effect - coupled data, and cannot fully study its dynamic and static characteristics; it cannot effectively distinguish between forward - directivity - effect pulses and slip - pulse effect pulses, nor can it effectively identify the components related to dynamic velocity pulses and the quasi - static components related to ultra - low - frequency non - pulse displacements. Summary of the Invention
[0008] To solve the above problems, the present invention proposes a method and system for processing near - fault complex - effect - coupled earthquake record data, which for the first time realizes the in - depth dissection of the composition components of the final displacement of the original strong - motion record. In the low - frequency components, it further effectively distinguishes the components related to dynamic velocity pulses and the quasi - static components related to ultra - low - frequency non - pulse displacements. Based on the frequency components of dynamic pulses in ground motion alone, it realizes the accurate and effective distinction between forward - directivity - effect pulses and slip - pulse effect pulses with different contributions of velocity - pulse displacements. At the same time, by using the decomposition of the residual signal frequency components after removing the pulse components, it further determines the non - pulse quasi - static components related to displacement. It solves the problems in the prior art of difficult dissection of low - frequency components of complex - effect coupling and inability to effectively distinguish complex - effect coupling.
[0009] In some embodiments, the following technical solutions are adopted: A method for processing near - fault complex - effect - coupled earthquake records, comprising: Obtain the original earthquake acceleration time - history data and perform baseline correction on the obtained data; Integrate the original earthquake acceleration time - history data after baseline correction into velocity time - history data, and extract the ideal velocity - pulse waveform in the original data based on Hilbert - Huang transform; Integrate the ideal velocity pulse into displacement time - history, and calculate the displacement at the starting moment and the displacement at the ending moment of each independent velocity pulse in the time domain; If the displacement at the starting moment and the displacement at the ending moment of the velocity pulse are the same or the deviation between the two is within the set range, then the velocity pulse is determined to be a forward directivity effect pulse; If the deviation between the displacement at the starting moment and the displacement at the ending moment of the velocity pulse is outside the set range, then the velocity pulse is determined to be a slip pulse effect.
[0010] Furthermore, it also includes: Remove the pulses determined to be forward directivity effects and slip pulse effects from the original seismic record, and decompose the remaining signal into multi-order frequency-domain narrow-band sub-signals; Integrate each order of frequency-domain narrow-band sub-signal into a displacement time history. If the frequency-domain narrow-band sub-signal contains a permanent displacement, then the corresponding narrow-band frequency domain is a displacement-related non-pulse component, corresponding to the source inversion rupture process, and define its effect mechanism.
[0011] As a further solution, perform baseline correction on the acquired data. The specific process is as follows: Use empirical mode decomposition to decompose the acquired data into multi-order frequency-domain narrow-band sub-signals; Filter the multi-order frequency-domain narrow-band sub-signals, integrate the filtered multi-order frequency-domain narrow-band sub-signals into velocity time histories and displacement time histories respectively, and screen out the frequency components in the original seismic acceleration time history data that are not contaminated by noise; In the original seismic acceleration time history data, remove the frequency components that are not contaminated by noise, and use the remaining part as the frequency components to be corrected; Perform correction on the frequency components to be corrected, and superimpose the corrected frequency components with the frequency components that are not contaminated by noise to obtain the original seismic acceleration time history data after baseline correction.
[0012] Among them, screening out the frequency components in the original seismic acceleration time history data that are not contaminated by noise is specifically: Stabilize the tail of the displacement time history at a stable level within a set oscillation amplitude range, and screen out the frequency-domain narrow-band sub-signals whose velocity time history tails oscillate around the zero axis within a set amplitude range, and perform superposition to obtain the frequency components in the original seismic acceleration time history data that are not contaminated by noise.
[0013] As a further solution, extract the ideal velocity pulse waveform in the original data based on Hilbert-Huang transform. The specific method is as follows: Integrate the original seismic acceleration time history data after baseline correction into velocity time history data, and use empirical mode decomposition to decompose the acquired velocity time history data into multi-order frequency-domain narrow-band sub-signals; Select the low-frequency narrow-band sub-signals that make a significant contribution to the total ground motion energy, and superimpose them to generate a rough pulse signal; The rough pulse signal is discretized into several closed and non-closed rainflow parts by the rainflow counting method, and the non-closed rainflow parts are retained to obtain an ideal velocity pulse waveform.
[0014] As a further solution, the ideal velocity pulse waveform contains multiple independent velocity pulses. For each independent velocity pulse: Determine the starting time and the ending time; according to the displacement time history obtained by integrating the ideal velocity pulse, determine the displacement S0 corresponding to the starting time and the displacement S corresponding to the ending time E ; if the absolute value of the difference between the two displacements is zero, or the absolute value of the difference between the two displacements is within the range of 0.2 times the permanent displacement, then this independent velocity pulse is determined to be a forward directivity effect pulse; otherwise, this independent velocity pulse is determined to be a slip pulse.
[0015] In some other embodiments, the following technical solution is adopted: A near-fault complex effect coupled seismic record data processing system, comprising: A raw data processing module, configured to obtain raw seismic acceleration time history data and perform baseline correction on the obtained data; An ideal velocity pulse waveform extraction module, configured to integrate the raw seismic acceleration time history data after baseline correction into velocity time history data, and extract the ideal velocity pulse waveform in the raw data based on the Hilbert-Huang transform; A pulse effect identification module, which integrates the ideal velocity pulse into a displacement time history and calculates the displacement at the starting time and the displacement at the ending time of each independent velocity pulse in the time domain; If the displacement at the starting time and the displacement at the ending time of the velocity pulse are the same or the deviation between the two is within a set range, then this velocity pulse is determined to be a forward directivity effect pulse; If the deviation between the displacement at the starting time and the displacement at the ending time of the velocity pulse is outside the set range, then this velocity pulse is determined to be a slip pulse.
[0016] Furthermore, it further includes: A non-dynamic pulse displacement effect identification module, configured to remove the pulses determined to be forward directivity effects and slip pulses from the raw seismic record, and decompose the remaining signals into multi-order frequency-domain narrow-band sub-signals; integrate each order of frequency-domain narrow-band sub-signals into a displacement time history. If the frequency-domain narrow-band sub-signal contains a permanent displacement, then the corresponding narrow-band frequency domain is a displacement-related non-pulse component, corresponding to the source inversion rupture process, and defining its effect mechanism.
[0017] In some other embodiments, the following technical solution is adopted: A terminal device includes a processor and a memory. The processor is used to implement instructions, and the memory is used to store multiple instructions, which are adapted to be loaded and executed by the processor for the above-mentioned processing method of near-fault complex effect-coupled seismic recording data.
[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention extracts the ideal velocity pulses in the original data through Hilbert-Huang transform, analyzes each independent pulse, and effectively distinguishes and identifies the forward directivity effect pulses and slip pulse effect pulses based on the displacement amounts corresponding to the starting and ending moments of each independent pulse, realizing effective decoupling and accurate identification of the complex effect-coupled seismic recording data. At the same time, the pulse components are removed from the original record, and the residual signals are further judged for effects to identify the displacement-related non-dynamic pulse components, realizing the decoupling and identification of complex effects in ground motion.
[0019] Compared with the prior art solution that directly uses the overall performance of the original seismic record for single slip pulse effect identification, the present invention first proposes to decouple and judge complex effects through different frequency components. The essence of the method is consistent with the physical mechanism of complex effects, and the identification result is more accurate and reliable. Different effects are further dissected in different frequency components and verified with source inversion and dynamic GPS data, avoiding misjudgment.
[0020] Other features and advantages of the additional aspects of the present invention will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of this aspect. Description of the Drawings
[0021] Figure 1 It is a flow chart of the processing method of near-fault complex effect-coupled seismic recording data in the embodiment of the present invention; Figures 2(a) and 2(b) are respectively schematic diagrams of the displacement and velocity time histories of the uncontaminated frequency-domain narrowband sub-signals in the embodiment of the present invention; Figure 3 It is a schematic diagram of the pulse effect identification process in the embodiment of the present invention; Figure 4 It is an example of the processing result of complex effect-coupled strong ground motion recording data in the embodiment of the present invention; Figure 5 It is a schematic diagram of the data processing result in Example 1; Figure 6 It is a schematic diagram of the data processing result and inversion result in Example 2. Detailed Embodiments
[0022] It should be noted that the following detailed description is illustrative and aims to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present application belongs.
[0023] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular forms are also intended to include the plural forms. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.
[0024] Embodiment 1 In one or more embodiments, a method for processing near-fault complex effect coupled seismic recording data is disclosed, combined with Figure 1 , and specifically includes the following processes: S101: Obtain the original seismic acceleration time history data and perform baseline correction on the obtained data.
[0025] Specifically, the original seismic acceleration time history data can be obtained from seismic monitoring agencies, seismic databases (such as USGS, IRIS, etc.) or relevant research institutions; the seismic acceleration time history data is usually time series data, including timestamps and corresponding acceleration values.
[0026] The process of performing baseline correction on the obtained data in this embodiment is specifically as follows: S1011: Decompose the obtained data into multi-order frequency-domain narrow-band sub-signals by using empirical mode decomposition; S1012: Filter the multi-order frequency-domain narrow-band sub-signals, integrate the filtered narrow-band sub-signals of each order into velocity time history and displacement time history respectively, and screen out the frequency components in the original seismic acceleration time history data that are not contaminated by noise. In this embodiment, a Butterworth filter is used to filter each order of narrow-band sub-signals, filter out the components with extremely small energy and not related to strong vibrations, and extract the main energy frequency band of each order of frequency-domain narrow-band sub-signals.
[0027] The frequency-domain narrow-band sub-signals that meet the following two conditions are determined to be not contaminated by noise: ① The tail of the displacement time history is stable at a set oscillation amplitude (a very small oscillation amplitude) range, as shown in Figure 2(a).
[0028] ② The tail of the velocity time history oscillates around the zero axis within a set amplitude range, as shown in Figure 2(b). Superimpose the filtered narrowband sub-signals in the frequency domain that meet the above two conditions to obtain the frequency components not contaminated by noise.
[0029] S1013: In the original seismic acceleration time history data, remove the frequency components not contaminated by noise, and use the remaining part as the frequency components to be corrected. S1014: Correct the frequency components to be corrected, perform piecewise slope detection on the displacement time history, and use the moment when the slope sign changes as the correction moment; correct the displacement time history through linear fitting; superimpose the corrected frequency components and the frequency components not contaminated by noise to obtain the original seismic acceleration time history data after baseline correction.
[0030] S102: Integrate the original seismic acceleration time history data after baseline correction into velocity time history data, and extract the ideal velocity pulse waveform in the original data based on the Hilbert-Huang transform.
[0031] In this embodiment, the frequency index is defined as the ratio of the peak ground velocity (PGV) to the peak ground acceleration (PGA); the energy change is defined as the contribution degree of the narrowband sub-signal in the frequency domain to the total energy.
[0032] In this embodiment, the narrowband sub-signals in the frequency domain of the low-frequency components that contribute greatly to the original record are screened out through the Hilbert-Huang transform; as a specific example, narrowband sub-signals with a frequency index greater than 0.12 and an energy change greater than 0.1 can be selected.
[0033] Superimpose the extracted narrowband sub-signals in the frequency domain to obtain the initial velocity pulse waveform; then discretize the initial velocity pulse waveform into closed and non-closed parts through the rainflow counting method, and retain the non-closed parts to obtain the ideal velocity pulse waveform, in which the start time and end time of each pulse can be accurately located.
[0034] The ideal velocity pulse only contains components related to the inherent velocity pulse. In the time domain of the ideal velocity pulse, the position of each velocity pulse in the record can be accurately located, so it can accurately reflect the pulse characteristics in the ground motion.
[0035] S103: Integrate the ideal velocity pulse into displacement time history, and calculate the displacement at the start time and the displacement at the end time of each independent velocity pulse in the time domain; judge whether the pulse is a forward directivity effect pulse or a slip pulse based on the displacement at the start time and the displacement at the end time.
[0036] Figure 3 The specific implementation process of pulse effect identification is given; specifically, the ideal velocity pulse waveform contains multiple independent velocity pulses. For each independent velocity pulse: Determine the starting time and the ending time; according to the displacement time history obtained by integrating the ideal velocity pulse, determine the displacement S0 corresponding to the starting time and the displacement S corresponding to the ending time E ; If = 0, or is within the range of 0.2 times the permanent displacement, that is, the displacement difference between the two is zero or close to 0, then this independent velocity pulse makes no contribution to the permanent displacement and is determined to be a forward directivity effect pulse; if is outside the range of 0.2 times the permanent displacement, that is, the displacement difference between the two is large, then this independent velocity pulse makes a contribution to the permanent displacement and is determined to be a slip pulse effect pulse.
[0037] Figure 4 Examples of the processing results of complex effect coupled strong ground motion record data obtained by using the method of this embodiment are given Figure 4 In the velocity time history curve in, the dotted part is the extracted ideal velocity pulse waveform, which contains 3 independent velocity pulses. The starting time and the ending time of each independent velocity pulse can be clearly obtained from the figure; Figure 4 In the displacement time history curve in, the dotted part is obtained by integrating the ideal velocity pulse. By corresponding to the ideal velocity pulse waveform, the displacements corresponding to the starting time and the ending time of each independent velocity pulse can be obtained. By comparing the displacement differences between the two, it can be seen that the displacement difference of Pulse 1 is close to 0 and makes no contribution to the permanent displacement, and it can be determined to be a forward directivity effect pulse; the displacement differences of Pulse 2 and Pulse 3 are much greater than 0 and make contributions to the permanent displacement, and they can be determined to be slip pulse effect pulses.
[0038] After judging each independent velocity pulse in the ideal velocity pulse one by one, based on the obtained ideal velocity pulse waveform, the number of pulses, the pulse amplitude, and the pulse period parameters are further obtained; among them, the number of pulses is obtained by detecting the number of peak points, the pulse amplitude is the amplitude of the ideal pulse, and the pulse period is determined according to the instantaneous frequency at the moment when the pulse occurs.
[0039] S104: Remove the pulses determined to be forward directivity effects and slip pulse effects from the original seismic record, and decompose the remaining signal into multi-order frequency-domain narrow-band sub-signals; Integrate each order of frequency-domain narrow-band sub-signal into a displacement time history. If the frequency-domain narrow-band sub-signal contains permanent displacement, the corresponding narrow-band frequency domain is a displacement-related non-pulse component, corresponding to the earthquake source inversion rupture process, and its effect mechanism is defined, so that the pseudo-static components (pseudo-static displacement effects) of other displacement-related non-dynamic pulses that can also form permanent displacement can be further judged.
[0040] Compared with the solution in the prior art that directly uses the overall performance of the original seismic record to identify the single slip pulse effect, the method of this embodiment first extracts the ideal velocity pulse, analyzes each independent pulse, and based on the displacement amounts corresponding to the start time and end time of each independent pulse, effectively distinguishes and identifies the forward directivity effect pulse and the slip pulse effect; then removes the forward directivity effect pulse and the slip pulse effect from the original seismic record, further determines the effect of the remaining signal, and identifies the pseudo-static component related to displacement, truly realizing the decoupled identification of complex effects in ground motion.
[0041] The method of this embodiment is verified through two examples as follows: Example 1: Taking a piece of original seismic data recorded by the seismic station CHY101NS as an example for analysis. In this record, the permanent displacement of the original record is caused by the ultra-low frequency downward oscillation before the strong earthquake (the first 30 s of the record), and has little relation with the strong earthquake process (30 s to 50 s).
[0042] If the method in the prior art that determines the slip pulse effect according to the existence of permanent displacement in the original seismic data is adopted, it will be determined as a slip pulse effect record, but this is a wrong judgment.
[0043] The independent velocity pulses in the ideal velocity pulse and their corresponding displacement time histories obtained by using the identification method of this embodiment are as Figure 5 shown. According to the identification results, it can be seen that there is no velocity pulse contributing to the permanent displacement (the displacement difference between the start time and end time of the two independent velocity pulses is within the range of 0.2 times the permanent displacement), that is, there is no slip pulse effect. The dynamic pulse is caused by the forward directivity effect, and the permanent displacement is composed of the ultra-low frequency non-pulse pseudo-static component; the method of this example can obtain very accurate decoupled identification results.
[0044] Example 2: Taking a piece of original seismic data recorded by the seismic station TCU075EW as an example for analysis. The independent velocity pulses in the ideal velocity pulse and their corresponding displacement time histories are obtained by using the identification method of this embodiment. At the same time, the proposed identification method is verified based on the existing seismic inversion work. The specific results are as Figure 6 shown. It can be seen that the Hisada inversion work proves that the static term constitutes the final permanent displacement of the original record, and the permanent displacement is not contributed by the dynamic pulse (slip pulse effect); in the traditional method, this record will be determined as a slip pulse effect record, resulting in misjudgment. In the method proposed in this embodiment, various effects can be accurately identified, and the complex effect identification results can be mutually verified with the Hisada seismic inversion results.
[0045] In summary, the method of this embodiment firstly proposes to further dissect through the frequency components of strong ground motion records, further distinguish the low-frequency components into the low-frequency components of dynamic pulses and the non-pulse components related to ultra-low-frequency displacements, and based on the low-frequency components of dynamic pulses, distinguish the forward directivity effect pulses and the slip pulse effect pulses according to the displacement contribution of each independent pulse; and through the further decomposition and displacement identification of the residual signal, the quasi-static components related to ultra-low-frequency displacements are identified. Compared with the rough determination of the slip pulse effect from the overall displacement performance of the original seismic record, the method of this embodiment can effectively decouple and identify different effect frequency components from the seismic record data with complex effect coupling, and the identification results are accurate and reliable, solving the problem that the existing technology cannot effectively analyze the strong ground motion records with complex effect coupling; it helps to realize the refined analysis of ground motion characteristics and engineering ground motion, and promotes the development of related theoretical research.
[0046] Embodiment 2 In one or more embodiments, a processing system for near-fault complex effect coupling seismic record data is disclosed, specifically including: The original data processing module is used to obtain the original seismic acceleration time history data and perform baseline correction on the obtained data; The ideal velocity pulse waveform extraction module is used to integrate the original seismic acceleration time history data after baseline correction into velocity time history data, and extract the ideal velocity pulse waveform in the original data based on the Hilbert-Huang transform; The pulse effect identification module integrates the ideal velocity pulse into displacement time history, and calculates the displacement at the start time and the displacement at the end time of each independent velocity pulse in the time domain; If the displacement at the start time of the velocity pulse is the same as the displacement at the end time or the deviation between the two is within the set range, then the velocity pulse is determined to be a forward directivity effect pulse; If the deviation between the displacement at the start time of the velocity pulse and the displacement at the end time is outside the set range, then the velocity pulse is determined to be a slip pulse effect pulse.
[0047] Further, it further includes: The non-dynamic pulse displacement effect identification module is used to remove the pulses determined to be forward directivity effects and slip pulse effects from the original seismic record, and decompose the remaining signal into multi-order frequency-domain narrow-band sub-signals; integrate each order of frequency-domain narrow-band sub-signals into displacement time history. If the frequency-domain narrow-band sub-signal contains permanent displacement, the corresponding narrow-band frequency domain is the non-pulse component related to displacement, corresponding to the source inversion rupture process, and defining its effect mechanism.
[0048] The specific implementation methods of the above modules are the same as those in Embodiment 1 and will not be elaborated here.
[0049] Embodiment 3 In one or more embodiments, a terminal device is disclosed, which includes a processor and a memory. The processor is configured to implement instructions, and the memory is configured to store multiple instructions, and the instructions are adapted to be loaded and executed by the processor to perform the method for processing near-fault complex effect coupled seismic recording data described in Embodiment 1.
[0050] It should be understood that in this embodiment, the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.
[0051] The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A part of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.
[0052] In the implementation process, each step of the above method may be completed by the integrated logic circuit in hardware in the processor or instructions in software form.
[0053] Although the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, it is not a limitation on the protection scope of the present invention. Those skilled in the art should understand that based on the technical solutions of the present invention, various modifications or deformations that can be made by those skilled in the art without creative efforts are still within the protection scope of the present invention.
Claims
1. A method for processing near-fault complex effect coupled seismic recording data, characterized in that, Including: Obtain the original seismic acceleration time history data and perform baseline correction on the obtained data; Integrate the original seismic acceleration time history data after baseline correction into velocity time history data, and extract the ideal velocity pulse waveform in the original data based on Hilbert-Huang transform; Integrate the ideal velocity pulse into displacement time history, and calculate the displacement at the starting moment and the displacement at the ending moment of each independent velocity pulse in the time domain; If the displacement at the starting moment and the displacement at the ending moment of the velocity pulse are the same or the deviation between the two is within the set range, then this velocity pulse is determined to be a forward directivity effect pulse; If the deviation between the displacement at the starting moment and the displacement at the ending moment of the velocity pulse is outside the set range, then this velocity pulse is determined to be a slip pulse; 2. The method for processing near-fault complex effect coupled seismic recording data according to claim 1, wherein Also including: Remove the pulses determined to be forward directivity effect and slip effect from the original seismic record, and decompose the remaining signal into multi-order frequency domain narrow band sub-signals; Integrate each order of frequency domain narrow band sub-signal into displacement time history. If the frequency domain narrow band sub-signal contains permanent displacement, then the corresponding narrow band frequency domain is the displacement-related non-pulse component, corresponding to the source inversion rupture process, and define its effect mechanism; 3. A method for processing near-fault complex effect-coupled seismic recording data as described in claim 1, characterized in that, Perform baseline correction on the obtained data. The specific process is as follows: Use empirical mode decomposition to decompose the obtained data into multi-order frequency domain narrow band sub-signals; Filter the multi-order frequency domain narrow band sub-signals, integrate the filtered narrow band sub-signals of each order into velocity time history and displacement time history respectively, and screen out the frequency components in the original seismic acceleration time history data that are not contaminated by noise; In the original seismic acceleration time history data, remove the frequency components that are not contaminated by noise, and the remaining part is used as the frequency components to be corrected; Correct the frequency components to be corrected, and superimpose the corrected frequency components with the frequency components that are not contaminated by noise to obtain the original seismic acceleration time history data after baseline correction; 4. A method for processing near-fault complex effect coupled seismic recording data according to claim 3, characterized in that Screen out the frequency components in the original seismic acceleration time history data that are not contaminated by noise. Specifically: Stabilize the tail of the displacement time history at a stable level within a set oscillation amplitude range, and screen out the frequency domain narrow band sub-signals whose velocity time history tail oscillates around the zero axis within the set amplitude range, and perform superposition to obtain the frequency components in the original seismic acceleration time history data that are not contaminated by noise; 5. A method for processing near-fault complex effect coupled seismic recording data according to claim 1, characterized in that, Extract the ideal velocity pulse waveform in the original data based on Hilbert-Huang transform. Specifically: Integrate the original seismic acceleration time history data after baseline correction into velocity time history data, and use empirical mode decomposition to decompose the obtained velocity time history data into multi-order frequency domain narrow band sub-signals; Select the low-frequency narrow band sub-signals that make a significant contribution to the total energy of the ground motion, and superimpose them to generate a rough pulse signal; Discretize the rough pulse signal into several closed and non-closed rain flow parts by the rain flow counting method, and retain the non-closed rain flow parts to obtain the ideal velocity pulse waveform; 6. A method for processing near-fault complex effect coupled seismic recording data according to claim 1, wherein, The ideal velocity pulse waveform contains multiple independent velocity pulses. For each independent velocity pulse: Determine the starting time and the ending time; according to the displacement time history obtained by integrating the ideal velocity pulse, determine the displacement S0 corresponding to the starting time and the displacement S corresponding to the ending time E ; If the absolute value of the displacement difference between the two is zero or the absolute value of the displacement difference between the two is within 0.2 times the permanent displacement range, then the independent velocity pulse is determined to be a forward directivity effect pulse; otherwise, the independent velocity pulse is determined to be a slip pulse effect pulse.
7. A method for processing near-fault complex effect coupled seismic recording data according to claim 6, characterized in that, After each independent velocity pulse in the ideal velocity pulse is determined one by one, it further includes: Based on the obtained ideal velocity pulse waveform, the number of pulses, pulse amplitude, and pulse period parameters are further obtained; among them, the number of pulses is obtained by detecting the number of peak points, the pulse amplitude is the amplitude of the ideal pulse, and the pulse period is determined according to the instantaneous frequency at the moment when the pulse occurs.
8. A processing system for near-fault complex effect-coupled seismic recording data, characterized in that, It includes: The raw data processing module is used to obtain the raw seismic acceleration time history data and perform baseline correction on the obtained data; The ideal velocity pulse waveform extraction module is used to integrate the baseline-corrected raw seismic acceleration time history data into velocity time history data and extract the ideal velocity pulse waveform in the raw data based on the Hilbert-Huang transform; The pulse effect identification module integrates the ideal velocity pulse into displacement time history and calculates the displacement at the starting moment and the displacement at the ending moment of each independent velocity pulse in the time domain; If the displacement at the starting moment and the displacement at the ending moment of the velocity pulse are the same or the deviation between the two is within the set range, then the velocity pulse is determined to be a forward directivity effect pulse; If the deviation between the displacement at the starting moment and the displacement at the ending moment of the velocity pulse is outside the set range, then the velocity pulse is determined to be a slip pulse effect pulse.
9. A processing system for near-fault complex effect coupled seismic recording data according to claim 8, characterized in that It further includes: The non-dynamic pulse displacement effect identification module is used to remove the pulses determined to be forward directivity effects and slip pulse effects from the original seismic record, and decompose the remaining signal into multi-order frequency-domain narrow-band sub-signals; integrate each order of frequency-domain narrow-band sub-signal into displacement time history. If the frequency-domain narrow-band sub-signal contains permanent displacement, the corresponding narrow-band frequency domain is the displacement-related non-pulse component, corresponding to the source inversion rupture process, and its effect mechanism is defined.
10. A terminal device, comprising a processor and a memory, the processor being configured to implement instructions; the memory being configured to store a plurality of instructions, characterized in that, The instructions are suitable for being loaded and executed by a processor for the near-fault complex effect coupling seismic record data processing method according to any one of claims 1-7.