A self-contained seismograph data acquisition method, a self-contained seismograph, a device and a medium

Abstract

This application provides a data acquisition method, a self-contained seismograph, equipment, and medium for a self-contained seismograph, relating to the field of earthquake monitoring technology. The method, by integrating a low-energy-consumption first sensor and a high-precision second sensor into the self-contained seismograph, employs a method where the first sensor continuously acquires initial vibration signals and compares them with a preset vibration signal threshold to determine the presence of abnormal events. Only when an abnormal event is detected is the power module activated to supply power to the second sensor to acquire target earthquake data. Power is then deactivated after acquisition. This approach ensures continuous data acquisition using the low-energy-consumption first sensor when no abnormal events are detected, reducing overall energy consumption, extending equipment runtime, and lowering monitoring costs and maintenance workload. Simultaneously, it enables timely activation of the high-precision second sensor to acquire accurate target earthquake data when an abnormal event is detected, providing a reliable basis for subsequent earthquake analysis and improving the accuracy and effectiveness of earthquake monitoring.

Description

Technical Field

[0001] This application relates to the field of earthquake monitoring technology, and in particular to a data acquisition method for a self-contained seismograph, a self-contained seismograph, equipment, and medium. Background Technology

[0002] Currently, seismometers are crucial devices for monitoring seismic activity, and the accuracy of data acquisition and their endurance are key performance indicators. In submarine seismic monitoring scenarios, seismometers are mainly divided into two categories: self-contained seismometers and submarine cable-mounted seismometers. Submarine cable-mounted seismometers can obtain external power through cables, thus having less endurance pressure; while self-contained seismometers use built-in batteries for independent power supply, requiring no external power replenishment, and are difficult to retrieve and maintain frequently after deployment. Their endurance directly determines the duration and effectiveness of long-term submarine monitoring, placing more stringent requirements on low-power design.

[0003] In existing technologies, self-contained seismographs typically employ a single-sensor architecture for data acquisition. This either uses a low-power sensor for continuous acquisition, but its detection accuracy is low, making it difficult to accurately capture key vibration parameters during an earthquake, leading to deviations in subsequent seismic analysis data; or it uses a high-precision sensor for continuous acquisition, which ensures data accuracy, but the high power consumption of the high-precision sensor quickly depletes the built-in battery, shortens the device's battery life, and requires frequent battery replacements or charging, increasing monitoring costs and maintenance workload, especially in remote field areas where maintenance is difficult. Summary of the Invention

[0004] This application provides a self-contained seismograph data acquisition method, seismograph, equipment, and medium to solve the problems in the prior art.

[0005] In a first aspect, this application provides a data acquisition method for a self-contained seismograph, wherein the seismograph has a built-in first sensor and a second sensor, and the energy consumption of the first sensor is less than that of the second sensor, and the detection accuracy of the second sensor is higher than that of the first sensor; the method includes:

[0006] Acquire the initial vibration signal continuously collected by the first sensor;

[0007] The initial vibration signal is compared with a preset vibration signal threshold to determine whether there is an abnormal event.

[0008] If an abnormal event is detected, the control power module supplies power to the second sensor to collect target seismic data and store the target seismic data in a preset storage module.

[0009] Once the target seismic data acquisition is complete, control the power module to stop supplying power to the second sensor.

[0010] In one possible design, the step of comparing the initial vibration signal with a preset vibration signal threshold to determine whether an abnormal event exists includes:

[0011] The initial vibration signal is initially compared with the preset vibration signal threshold.

[0012] If the preset triggering conditions are met after initial comparison, the historical data stored in the preset storage module is used to perform a secondary verification of the initial vibration signal.

[0013] If the initial vibration signal passes secondary verification, an abnormal event is determined to exist;

[0014] If the initial vibration signal fails the secondary verification, it is determined that there is no abnormal event.

[0015] In one possible design, the historical data includes historical earthquake data;

[0016] The step of calling the historical data stored in the preset storage module to perform secondary verification of the initial vibration signal includes:

[0017] Extract the target features of the initial vibration signal, wherein the target features include amplitude, frequency, and duration;

[0018] The extracted target features are matched with the historical features of the historical earthquake data based on similarity.

[0019] If the similarity is greater than a preset similarity threshold, the initial vibration signal is deemed to have passed the secondary verification.

[0020] If the similarity is less than or equal to the preset similarity threshold, the secondary verification of the initial vibration signal is deemed unsuccessful.

[0021] In one possible design, the preset triggering condition is that the amplitude of the initial vibration signal exceeds the preset vibration signal amplitude, and the duration is greater than the preset duration.

[0022] One possible design also includes:

[0023] Based on the historical earthquake data and historical interference data stored in the preset storage module, the preset vibration signal threshold is dynamically adjusted.

[0024] In one possible design, dynamically adjusting the preset vibration signal threshold based on historical earthquake data and historical interference data stored in the preset storage module includes:

[0025] Feature extraction is performed on the historical earthquake data and the historical interference data to obtain the amplitude range, frequency characteristics and duration of earthquake events, as well as the amplitude range, frequency characteristics and duration of interference events.

[0026] The value of the preset vibration signal threshold is adjusted based on the characteristic differences between the earthquake event and the interference event.

[0027] In one possible design, after storing the target seismic data in a preset storage module, the method further includes:

[0028] The target earthquake data is categorized by acquisition time and event type and added to the historical earthquake data.

[0029] Secondly, this application provides a self-contained seismograph, comprising:

[0030] The system comprises a first sensor, a second sensor, a data processing module, and a power supply module; the first sensor has lower energy consumption than the second sensor, and the second sensor has higher detection accuracy than the first sensor; the first sensor, the second sensor, and the power supply module are all communicatively connected to the data processing module.

[0031] The power module is used to supply power to the first sensor, the second sensor and the data processing module; the data processing module is used to execute the method described in any one of the first aspects.

[0032] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0033] The memory stores computer-executed instructions;

[0034] The processor executes computer execution instructions stored in the memory to implement the method as described in any of the first aspects.

[0035] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any of the first aspects.

[0036] This application provides a data acquisition method, a self-contained seismograph, equipment, and medium for a self-contained seismograph. The method utilizes a self-contained seismograph with a low-energy-consumption first sensor and a high-precision second sensor. It employs a method where the first sensor continuously acquires initial vibration signals and compares them with a preset vibration signal threshold to determine the presence of abnormal events. Only when an abnormal event is detected does the power module supply power to the second sensor to acquire target seismic data. Power is then cut off after acquisition. This effectively solves the problems of seismic analysis data deviation, high monitoring costs, and heavy maintenance workload inherent in existing single-sensor architectures. It ensures continuous data acquisition using the low-energy-consumption first sensor when no abnormal events are detected, reducing overall energy consumption, extending equipment runtime, reducing battery replacement or charging frequency, and lowering monitoring costs and maintenance workload. Simultaneously, it enables timely activation of the high-precision second sensor to acquire accurate target seismic data when an abnormal event is detected, providing a reliable basis for subsequent seismic analysis and improving the accuracy and effectiveness of seismic monitoring. Attached Figure Description

[0037] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0038] Figure 1 A flowchart illustrating a data acquisition method for a self-contained seismograph provided in an embodiment of this application;

[0039] Figure 2 A flowchart illustrating a data acquisition method for a self-contained seismograph, provided as another embodiment of this application;

[0040] Figure 3 This is a schematic diagram of the structure of a self-contained seismograph provided in one embodiment of this application;

[0041] Figure 4 This is a structural example diagram of an electronic device provided in an embodiment of this application.

[0042] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0043] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0044] To clearly understand the technical solution of this application, the solutions of the prior art will be described in detail first.

[0045] Currently, seismometers are crucial devices for monitoring seismic activity, and the accuracy of data acquisition and their endurance are key performance indicators. In submarine seismic monitoring scenarios, seismometers are mainly divided into two categories: self-contained seismometers and submarine cable-mounted seismometers. Submarine cable-mounted seismometers can obtain external power through cables, thus having less endurance pressure; while self-contained seismometers use built-in batteries for independent power supply, requiring no external power replenishment, and are difficult to retrieve and maintain frequently after deployment. Their endurance directly determines the duration and effectiveness of long-term submarine monitoring, placing more stringent requirements on low-power design.

[0046] In existing technologies, self-contained seismographs typically employ a single-sensor architecture for data acquisition. This either uses a low-power sensor for continuous acquisition, but its detection accuracy is low, making it difficult to accurately capture key vibration parameters during an earthquake, leading to deviations in subsequent seismic analysis data; or it uses a high-precision sensor for continuous acquisition, which ensures data accuracy, but the high power consumption of the high-precision sensor quickly depletes the built-in battery, shortens the device's battery life, and requires frequent battery replacements or charging, increasing monitoring costs and maintenance workload, especially in remote field areas where maintenance is difficult.

[0047] Based on this, this application achieves seismic data acquisition through the collaborative operation of dual sensors. By using a low-energy sensor for continuous monitoring and a high-precision sensor for on-demand activation, the energy consumption of the equipment is significantly reduced and the battery life is extended while ensuring the accuracy of seismic data acquisition.

[0048] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0049] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0050] Figure 1 A flowchart illustrating a data acquisition method for a self-contained seismograph, as provided in an embodiment of this application, is shown below. Figure 1 As shown, the execution entity in this embodiment is a data processing device. This device can be implemented through a computer program, or through a medium storing the relevant computer program, such as a USB flash drive and / or optical disc; alternatively, it can be implemented through a physical device that integrates or installs the relevant computer program, such as a chip or electronic device. The electronic device may be a computer or a server, etc. The self-contained seismograph data acquisition method provided in this embodiment includes the following steps:

[0051] Specifically, the seismograph has a built-in first sensor and a second sensor, and the energy consumption of the first sensor is less than that of the second sensor, while the detection accuracy of the second sensor is higher than that of the first sensor.

[0052] S201. Obtain the initial vibration signal continuously collected by the first sensor.

[0053] Optionally, the first sensor is a low-energy vibration sensor, which is configured to be continuously operational and to collect environmental vibration signals, i.e., initial vibration signals, in the area where the seismograph is located in real time.

[0054] The first sensor can operate continuously without additional triggering conditions. Its core function is to monitor regional vibrations around the clock, avoiding the omission of potential seismic anomalies.

[0055] Optionally, the first sensor may be a low-power MEMS accelerometer, whose operating current is typically in the microampere range, enabling continuous acquisition of vibration signals with low energy consumption, and transmitting the acquired initial vibration signals to the data processing module of the self-contained seismograph in real time.

[0056] Alternatively, an accelerometer, speedometer, or pressure sensor can be used to acquire the initial vibration signal.

[0057] S202. Compare the initial vibration signal with the preset vibration signal threshold to determine whether there is an abnormal event.

[0058] Optionally, after receiving the initial vibration signal transmitted by the first sensor, the data processing module preprocesses the initial vibration signal. The preprocessing may include signal filtering, amplitude extraction, frequency analysis, etc., and compares the preprocessed initial vibration signal with a preset vibration signal threshold to determine whether there is an abnormal vibration event, i.e., potential seismic activity, in the current area.

[0059] The preset vibration signal threshold is a judgment standard based on historical earthquake data, regional geological characteristics, and environmental vibration baseline data. It may include one or more of the following: vibration amplitude threshold, vibration frequency threshold, and vibration duration threshold. For example, if the amplitude of the initial vibration signal exceeds the preset amplitude threshold and the duration of the amplitude exceeds the preset time threshold, an abnormal event is determined to exist; if the initial vibration signal is only a short-term, low-amplitude environmental disturbance, it is determined that there is no abnormal event.

[0060] Optionally, the preset vibration signal threshold can be configured and updated through the host computer of the self-contained seismograph to adapt to the differences in geological environment in different monitoring areas and improve the accuracy of abnormal event judgment.

[0061] S203. If an abnormal event is detected, the control power module supplies power to the second sensor to collect target seismic data and store the target seismic data in a preset storage module.

[0062] Optionally, when the data processing module determines that an abnormal event has occurred, indicating that seismic activity may be occurring in the current area, it is necessary to activate the high-precision sensor for accurate data acquisition. Specifically, the data processing module sends a power supply control signal to the power supply module, controlling the power supply module to supply power to the second sensor, causing the second sensor to switch from sleep mode to working mode.

[0063] The second sensor is a high-precision vibration sensor, which has a higher detection accuracy than the first sensor. It can be a high-precision piezoelectric accelerometer or a fiber optic vibration sensor, and can accurately collect key parameters such as vibration amplitude, frequency, and phase during an earthquake, i.e., target earthquake data.

[0064] It should be noted that after the data processing module determines that an abnormal event exists and controls the power module to supply power to the high-precision second sensor, the high-precision vibration sensor has a rapid start-up response capability. It can complete the power supply start-up process within milliseconds and quickly enter a stable working state. It can immediately carry out accurate acquisition of target seismic data, effectively avoiding the omission of key seismic vibration parameters due to start-up delay. This further ensures the integrity and timeliness of seismic monitoring data and provides comprehensive and reliable basic data support for subsequent seismic analysis.

[0065] It should be noted that the target earthquake data is the main data for subsequent earthquake intensity analysis and source location, and the accuracy of the target earthquake data acquisition directly determines the effectiveness of earthquake monitoring.

[0066] Optionally, during the process of the second sensor acquiring target seismic data, the data processing module receives the target seismic data transmitted by the second sensor in real time and controls the storage of the target seismic data to a preset storage module.

[0067] Optionally, the preset storage module can use a flash memory chip, which has a power-off data protection function to ensure that the target seismic data will not be lost due to power failure.

[0068] Optionally, the data processing module can also upload the target earthquake data to the remote monitoring center in real time via a wireless communication module (such as 4G, Beidou, LoRa, etc.) to achieve remote synchronization of earthquake data.

[0069] S204. Once the target seismic data acquisition is complete, control the power module to stop supplying power to the second sensor.

[0070] Optionally, after the second sensor completes the acquisition of target seismic data, such as acquiring complete data of the main shock wave and aftershock waves, or reaching the preset acquisition duration, the data processing module determines that data acquisition is complete, sends a power-off control signal to the power module, controls the power module to stop supplying power to the second sensor, and causes the second sensor to re-enter sleep mode.

[0071] Optionally, the criteria for determining the completion of target seismic data acquisition can be that the second sensor continuously acquires data for a preset duration (e.g., 30 minutes), or that the vibration signal amplitude is detected to fall below a preset baseline threshold for a preset duration (e.g., 5 minutes). By promptly stopping the power supply to the second sensor, unnecessary energy consumption caused by prolonged operation of the high-precision sensor can be avoided.

[0072] Furthermore, after the power module stops supplying power to the second sensor, the first sensor continues to operate and monitor regional vibrations to ensure a timely response to any subsequent aftershocks or new seismic activity.

[0073] This application provides a data acquisition method for a self-contained seismograph. By integrating a low-energy-consumption first sensor and a high-precision second sensor into the self-contained seismograph, the method employs a method where the first sensor continuously acquires initial vibration signals and compares them with a preset vibration signal threshold to determine if any abnormal events exist. Only when an abnormal event is detected does the power module supply power to the second sensor to acquire target seismic data. After acquisition is complete, the power supply is stopped. This method effectively solves the problems of seismic analysis data deviation, high monitoring costs, and heavy maintenance workload inherent in the single-sensor architecture of existing technologies. It ensures that data is continuously acquired using the low-energy-consumption first sensor when no abnormal events are detected, reducing overall energy consumption, extending equipment battery life, reducing battery replacement or charging frequency, and lowering monitoring costs and maintenance workload. At the same time, it can promptly activate the high-precision second sensor to acquire accurate target seismic data when an abnormal event is detected, providing a reliable basis for subsequent seismic analysis and improving the accuracy and effectiveness of seismic monitoring.

[0074] It should be noted that the self-contained seismograph data acquisition method provided in this application can be applied to seabed observation systems, as well as to scenarios such as self-contained seismograph equipment upgrades and operation and maintenance support, specifically covering the deployment of self-contained seismographs for long-term deep-sea seismic observation and seabed resource exploration.

[0075] Figure 2 A flowchart illustrating a data acquisition method for a self-contained seismograph, as provided in another embodiment of this application, is shown below. Figure 2 As shown, as an optional implementation, based on any of the above embodiments, a comparison is made between the initial vibration signal and a preset vibration signal threshold to determine whether an abnormal event exists, including the following steps:

[0076] S201. Perform a preliminary comparison between the initial vibration signal and the preset vibration signal threshold.

[0077] It should be noted that the initial comparison is a rapid screening process. The data processing module directly matches and compares the pre-processed initial vibration signal (such as the extracted vibration amplitude, frequency and other parameters) with the preset vibration signal threshold.

[0078] The preset triggering condition is that the key parameters of the initial vibration signal reach or exceed the preset vibration signal threshold, such as the vibration amplitude exceeding the preset amplitude threshold or the vibration frequency falling into the preset abnormal frequency range.

[0079] It should be noted that preliminary comparison can quickly screen out candidate signals that may belong to abnormal events, eliminate obvious low-amplitude and short-term environmental interference signals, and achieve preliminary signal stratification screening.

[0080] S202. If the preset triggering conditions are met after preliminary comparison, the historical data stored in the preset storage module is called to perform a secondary verification of the initial vibration signal.

[0081] The historical data stored in the preset storage module may include baseline data of normal environmental vibration in the monitoring area and vibration characteristic data (such as amplitude variation, frequency distribution range, duration characteristics, etc.) corresponding to historical earthquake events in and around the monitoring area.

[0082] Optionally, after the data processing module calls the aforementioned historical data, it can use a signal feature matching algorithm (such as a correlation analysis algorithm, a feature vector comparison algorithm, etc.) to compare the current initial vibration signal with historical normal environmental vibration data and historical earthquake vibration data respectively.

[0083] S203. If the initial vibration signal passes the secondary verification, an abnormal event is determined to exist.

[0084] S204. If the initial vibration signal fails the secondary verification, it is determined that there is no abnormal event.

[0085] Optionally, the criteria for passing the secondary verification can be: the feature matching degree between the current initial vibration signal and historical seismic vibration data reaches a preset matching threshold (e.g., above 80%), and the feature matching degree with historical normal environmental vibration data is below a preset exclusion threshold (e.g., below 30%). Further, if the feature matching degree between the current initial vibration signal and historical normal environmental vibration data reaches or exceeds the preset exclusion threshold, or if the feature matching degree with historical seismic vibration data does not reach the preset matching threshold, then the secondary verification is deemed to have failed, and the current signal is still considered an environmental interference signal.

[0086] The preset vibration signal threshold is a judgment standard based on historical earthquake data, regional geological characteristics, and environmental vibration baseline data. It may include one or more of the following: vibration amplitude threshold, vibration frequency threshold, and vibration duration threshold. For example, if the amplitude of the initial vibration signal exceeds the preset amplitude threshold and the duration of the amplitude exceeds the preset time threshold, the preliminary comparison is determined to meet the preset triggering conditions. If the initial vibration signal is only a short-term, low-amplitude environmental disturbance, the preliminary comparison does not meet the preset triggering conditions, and it is directly determined that there is no abnormal event.

[0087] This application provides a data acquisition method for a self-contained seismograph. First, an initial vibration signal is compared with a preset vibration signal threshold. When the initial comparison meets a preset trigger condition, historical data stored in a preset storage module is used to perform a secondary verification of the initial vibration signal. Based on the secondary verification result, it is determined whether an abnormal event exists. Compared to relying solely on a single threshold comparison to determine abnormal events, this method effectively avoids misjudgments caused by accidental factors or interference signals, improving the accuracy and reliability of abnormal event judgment. It reduces the occurrence of incorrect activation of high-precision sensors for data acquisition due to misjudgment, further reducing equipment energy consumption and extending the battery life of the self-contained seismograph. Furthermore, it reduces unnecessary data storage and processing, improving data acquisition and processing efficiency.

[0088] As an optional implementation, based on any of the above embodiments, historical data includes historical earthquake data.

[0089] Optionally, the historical data in this embodiment includes historical earthquake data of the monitoring area and its surroundings. Additionally, baseline data of past normal environmental vibrations in the monitoring area may be included to further improve verification accuracy.

[0090] Historical earthquake data can include vibration characteristic datasets corresponding to multiple historical earthquake events, and can include information such as amplitude variation curves, frequency distribution ranges, vibration duration, and signal attenuation patterns at different stages during the propagation of seismic waves.

[0091] Specifically, the initial vibration signal is verified a second time by calling historical data stored in the preset storage module, including the following steps:

[0092] First, target features of the initial vibration signal are extracted, including amplitude, frequency, and duration.

[0093] The target features are parameters that characterize the essential properties of vibration signals and can distinguish between earthquake and non-earthquake interference. Specifically, they include amplitude features, frequency features, and duration features. Amplitude features can be selected from the peak amplitude, peak-to-valley difference, and amplitude rise rate of the initial vibration signal; frequency features can be selected from the dominant frequency, bandwidth, and frequency spectrum distribution of the signal; and duration features can be selected from the duration after the initial vibration signal reaches a preset amplitude threshold and the rise time from the start of the signal to the peak amplitude.

[0094] Optionally, the data processing module uses a preset feature extraction algorithm (such as a time-domain feature extraction algorithm or a frequency-domain analysis algorithm) to accurately extract the above-mentioned target features and form the feature vector of the initial vibration signal.

[0095] Secondly, the extracted target features are matched with the historical features of historical earthquake data based on similarity.

[0096] Optionally, historical features corresponding to the feature dimensions can be retrieved from the historical earthquake data in the preset storage module, namely, historical amplitude features, historical frequency features, and historical duration features that correspond one-to-one with the target features, to construct a historical earthquake feature library.

[0097] Optionally, a preset similarity matching algorithm (such as cosine similarity algorithm, Euclidean distance similarity algorithm, dynamic time warping algorithm, etc.) is used to calculate the similarity value between the feature vector of the initial vibration signal and the feature vector of each historical earthquake event in the historical earthquake feature database. Furthermore, to improve matching accuracy, different weights can be assigned to features of different dimensions (e.g., amplitude feature weight 0.4, frequency feature weight 0.4, duration feature weight 0.2), ultimately obtaining a comprehensive similarity value.

[0098] Finally, if the similarity is greater than the preset similarity threshold, the initial vibration signal is deemed to have passed the secondary verification; if the similarity is less than or equal to the preset similarity threshold, the initial vibration signal is deemed to have failed the secondary verification.

[0099] The preset similarity threshold is a judgment threshold obtained by training with a large amount of historical data. It can be flexibly configured by the host computer according to the geological characteristics of the monitoring area. For example, the preset similarity threshold can be configured to 85%.

[0100] It should be noted that if the calculated overall similarity is greater than the preset similarity threshold, it indicates that the characteristics of the current initial vibration signal are highly consistent with the characteristics of historical earthquake signals, and the secondary verification of the initial vibration signal is deemed successful. If the overall similarity is less than or equal to the preset similarity threshold, it indicates that the characteristics of the current initial vibration signal differ significantly from those of historical earthquake signals, and it is highly likely to be an environmental interference signal, and the secondary verification of the initial vibration signal is deemed unsuccessful.

[0101] Optionally, as an alternative implementation, based on any of the above embodiments, the preset triggering condition is that the amplitude of the initial vibration signal exceeds the preset vibration signal amplitude and the duration is greater than the preset duration.

[0102] It should be noted that by setting preset vibration signal amplitude and preset duration, instantaneous spike interference can be effectively eliminated, avoiding false triggering caused by a single amplitude threshold. Specifically, the preset vibration signal amplitude is the threshold value for distinguishing between normal environmental vibration and potentially abnormal vibration, and the preset duration is the time threshold value for filtering instantaneous interference. Only when the vibration amplitude simultaneously meets both conditions is the initial comparison deemed to meet the preset triggering conditions, proceeding to the subsequent secondary verification process. If only the amplitude exceeds the preset vibration signal amplitude but the duration does not reach the preset duration, or only the duration exceeds the preset duration but the amplitude does not reach the preset vibration signal amplitude, the initial comparison is deemed not to meet the preset triggering conditions, ruling out the possibility that the initial vibration signal is an abnormal event.

[0103] This application provides a data acquisition method for a self-contained seismograph. During secondary verification, it first extracts target features such as amplitude, frequency, and duration of the initial vibration signal. Then, it performs similarity matching between these target features and historical features from historical earthquake data. The success of the secondary verification is determined based on the comparison result between the similarity score and a preset similarity threshold. This fully utilizes the patterns and characteristic information contained in historical earthquake data. Compared to simple comparison methods, it can more scientifically and accurately evaluate the initial vibration signal, effectively filtering out interference signals generated by non-seismic factors and improving the accuracy of anomaly event detection.

[0104] As an optional implementation, based on any of the above embodiments, it further includes: dynamically adjusting the preset vibration signal threshold based on historical earthquake data and historical interference data stored in the preset storage module.

[0105] Optionally, based on the historical earthquake data and historical interference data stored in the preset storage module, the preset vibration signal threshold is dynamically adjusted. Specifically, this includes: extracting features from the historical earthquake data and historical interference data to obtain the amplitude range, frequency characteristics, and duration of the earthquake event, as well as the amplitude range, frequency characteristics, and duration of the interference event; and adjusting the value of the preset vibration signal threshold according to the characteristic differences between the earthquake event and the interference event.

[0106] Optionally, historical data stored within a specified time period (such as the last 3 months or the last 6 months) can be retrieved from the preset storage module and can be classified and labeled according to earthquake data and interference data.

[0107] Among them, historical earthquake data are target earthquake data collected by the second sensor after passing secondary verification and the corresponding initial vibration signal of the first sensor; historical interference data are signal data that are determined to be non-abnormal events after preliminary comparison or secondary verification, including different types of interference signal data such as instantaneous spike interference and continuous interference.

[0108] Optionally, feature statistical analysis can be performed on the classified historical earthquake data and historical interference data to extract the distribution patterns of the initial vibration signal amplitude and duration characteristics corresponding to the two types of data. For example, the minimum amplitude, average amplitude, minimum duration, and average duration of the initial vibration signal in the historical earthquake data can be statistically analyzed; the maximum amplitude, longest duration, and amplitude-duration distribution interval of various interference signals in the historical interference data can be statistically analyzed.

[0109] Optionally, based on statistical results, the rationality of the current preset vibration signal threshold (which may include preset vibration signal amplitude and preset duration) is evaluated. Specifically, if the initial vibration signal amplitude of some historical earthquake data is close to the current preset amplitude threshold, posing a risk of missed judgment, or if the amplitude-duration characteristics of a large amount of historical interference data are close to the current threshold, posing a risk of misjudgment, then it is determined that the current preset vibration signal threshold needs to be adjusted.

[0110] Optionally, based on the above-mentioned statistical results and evaluation conclusions, a preset threshold adjustment algorithm (such as a statistical learning algorithm) is used to calculate the range of the optimal preset vibration signal threshold, thereby dynamically adjusting the preset vibration signal amplitude and / or preset duration. For example, if statistics show that the minimum amplitude of the initial vibration signal in historical earthquake data is 0.09g, and the current preset amplitude threshold is 0.1g, indicating a potential for missed detection, the preset amplitude threshold is lowered to 0.08g. If a signal with an amplitude of 0.12g and a duration of 2.8 seconds is found in historical interference data, which is close to the current preset duration of 3 seconds and could easily lead to false triggering, the preset duration is adjusted to 3.2 seconds to ensure that all historical interference data can be effectively filtered. The adjusted preset vibration signal threshold is automatically updated in the configuration parameters of the data processing module.

[0111] Optionally, to ensure the safety and accuracy of threshold adjustment, a preset threshold adjustment range limit can be set, such as the amplitude threshold adjustment range not exceeding ±0.05g and the duration threshold adjustment range not exceeding ±1 second, to avoid large fluctuations in the threshold due to data statistical deviations.

[0112] This application provides a data acquisition method for a self-contained seismograph. By extracting features from historical earthquake data and historical interference data stored in a preset storage module, it comprehensively acquires characteristic information of earthquake events and interference events, including amplitude range, frequency characteristics, and duration. Then, based on the characteristic differences between earthquake events and interference events, it dynamically adjusts the value of a preset vibration signal threshold. This enables the self-contained seismograph to adaptively optimize the threshold setting according to the earthquake and interference characteristics of different regions and time periods, improving the sensitivity and accuracy of earthquake event detection. It effectively reduces misjudgments caused by interference signals and missed judgments caused by unreasonable threshold settings, ensuring timely and accurate capture of real earthquake events. This provides more reliable and effective data support for earthquake monitoring and early warning work, enhancing the applicability and practicality of the self-contained seismograph in various practical scenarios.

[0113] As an optional implementation, based on any of the above embodiments, after storing the target seismic data in a preset storage module, the method further includes: adding the target seismic data to historical seismic data according to acquisition time and event type.

[0114] Optionally, after storing the target seismic data, the data processing module automatically extracts the attribute information of the batch of data. The attribute information includes acquisition time information and event type information. The acquisition time information can be accurate to the millisecond level, including year, month, day, hour, minute, second, and millisecond. The event type information can be based on the secondary verification results and the feature annotation of the target seismic data.

[0115] Optionally, according to preset data classification rules, the target earthquake data is associated and bound with the extracted attribute information, and then added to the historical earthquake data set in the preset storage module. For example, a hierarchical storage directory is established in the historical earthquake data set by "year-month", and the target earthquake data collected at the corresponding time is stored in the corresponding directory. An "event type" label is added to each data entry to form a structured historical earthquake database, which facilitates rapid retrieval and feature extraction during subsequent secondary verification and dynamic threshold adjustment.

[0116] This application provides a data acquisition method for a self-contained seismograph. After storing the target seismic data in a preset storage module, it further categorizes and adds the data to historical seismic data according to acquisition time and event type. This rich and organized historical seismic data provides more sufficient and accurate data support for dynamically adjusting preset vibration signal thresholds, improving the accuracy and reliability of seismic monitoring and enabling the seismograph to better adapt to the seismic monitoring needs of different regions and geological conditions.

[0117] Figure 3 This is a schematic diagram of the structure of a self-contained seismograph provided in an embodiment of this application, as shown below. Figure 3 As shown, an embodiment of this application provides a self-contained seismograph 30, comprising:

[0118] The system comprises a first sensor 31, a second sensor 32, a data processing module 33, and a power supply module 34. The first sensor 31 has lower power consumption than the second sensor 32, and the second sensor 32 has higher detection accuracy than the first sensor 31. The first sensor 31, the second sensor 32, and the power supply module 34 are all communicatively connected to the data processing module 33. The power supply module 34 is used to supply power to the first sensor 31, the second sensor 32, and the data processing module 33. The data processing module 33 is used to execute the above-described method embodiment.

[0119] Specifically, the data processing module 33 is used to: acquire the initial vibration signal continuously collected by the first sensor 31; compare the initial vibration signal with a preset vibration signal threshold to determine whether there is an abnormal event; if an abnormal event is determined to exist, control the power supply module 34 to supply power to the second sensor 32 so as to use the second sensor 32 to collect target earthquake data and store the target earthquake data in a preset storage module; and when the target earthquake data acquisition is completed, control the power supply module 34 to stop supplying power to the second sensor 32.

[0120] It should be noted that the technical effects of the self-contained seismograph solution provided in this embodiment have been described in the above-mentioned self-contained seismograph data acquisition method, and will not be repeated here.

[0121] Optionally, when the data processing module 33 compares the initial vibration signal with a preset vibration signal threshold to determine whether an abnormal event exists, it is specifically used to: perform a preliminary comparison between the initial vibration signal and the preset vibration signal threshold; if the preliminary comparison determines that the preset triggering conditions are met, call the historical data stored in the preset storage module to perform a secondary verification of the initial vibration signal; if the secondary verification of the initial vibration signal passes, determine that an abnormal event exists; if the secondary verification of the initial vibration signal fails, determine that no abnormal event exists.

[0122] Optionally, historical data includes historical earthquake data.

[0123] Optionally, when the data processing module 33 calls the historical data stored in the preset storage module to perform secondary verification of the initial vibration signal, it is specifically used to: extract the target features of the initial vibration signal, wherein the target features include amplitude, frequency and duration; perform similarity matching between the extracted target features and the historical features of the historical earthquake data; if the similarity is greater than the preset similarity threshold, determine that the secondary verification of the initial vibration signal is passed; if the similarity is less than or equal to the preset similarity threshold, determine that the secondary verification of the initial vibration signal is failed.

[0124] Optionally, the preset triggering condition is that the amplitude of the initial vibration signal exceeds the preset vibration signal amplitude, and the duration is greater than the preset duration.

[0125] Optionally, the data processing module 33 is also used to: dynamically adjust the preset vibration signal threshold based on the historical earthquake data and historical interference data stored in the preset storage module.

[0126] Optionally, when dynamically adjusting the preset vibration signal threshold based on historical earthquake data and historical interference data stored in the preset storage module, the data processing module 33 is specifically used to: extract features from the historical earthquake data and historical interference data to obtain the amplitude range, frequency characteristics and duration of the earthquake event, as well as the amplitude range, frequency characteristics and duration of the interference event; and adjust the value of the preset vibration signal threshold according to the characteristic differences between the earthquake event and the interference event.

[0127] Optionally, after storing the target earthquake data in a preset storage module, the data processing module 33 is also used to: add the target earthquake data to the historical earthquake data according to the acquisition time and event type.

[0128] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, as shown below. Figure 4 As shown, the electronic device 40 provided in this embodiment includes a processor 41 and a memory 42 communicatively connected to the processor 41.

[0129] The memory 42 stores computer execution instructions; the processor 41 executes the computer execution instructions stored in the memory 42 to implement a self-contained seismograph data acquisition method provided in any of the above embodiments.

[0130] The program may include program code, which includes computer-executable instructions. Memory 42 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk storage device.

[0131] In this embodiment, the memory 42 and the processor 41 are connected via a bus. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 4 The bus is represented by a single straight line, but this does not mean that there is only one bus or one type of bus.

[0132] This application also provides a computer-readable storage medium, which stores computer-executable instructions. When executed by a processor, the computer-executable instructions are used to implement a self-contained seismograph data acquisition method provided in any of the above embodiments.

[0133] This application also provides a computer program product, including a computer program that, when executed by a processor, implements a self-contained seismograph data acquisition method provided in any of the above embodiments.

[0134] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0135] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0136] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0137] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0138] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0139] The aforementioned storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0140] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. The processor and storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components in an electronic control unit or main control device.

[0141] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0142] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A data acquisition method for a self-contained seismograph, characterized in that, The seismograph has a built-in first sensor and a second sensor, wherein the energy consumption of the first sensor is less than that of the second sensor, and the detection accuracy of the second sensor is higher than that of the first sensor; the method includes: Acquire the initial vibration signal continuously collected by the first sensor; The initial vibration signal is compared with a preset vibration signal threshold to determine whether there is an abnormal event. If an abnormal event is detected, the control power module supplies power to the second sensor to collect target seismic data and store the target seismic data in a preset storage module. Once the target seismic data acquisition is complete, control the power module to stop supplying power to the second sensor.

2. The method according to claim 1, characterized in that, The step of comparing the initial vibration signal with a preset vibration signal threshold to determine whether an abnormal event exists includes: The initial vibration signal is initially compared with the preset vibration signal threshold. If the preset triggering conditions are met after initial comparison, the historical data stored in the preset storage module is used to perform a secondary verification of the initial vibration signal. If the initial vibration signal passes secondary verification, an abnormal event is determined to exist; If the initial vibration signal fails the secondary verification, it is determined that there is no abnormal event.

3. The method according to claim 2, characterized in that, The historical data includes historical earthquake data; The step of calling the historical data stored in the preset storage module to perform secondary verification of the initial vibration signal includes: Extract the target features of the initial vibration signal, wherein the target features include amplitude, frequency, and duration; The extracted target features are matched with the historical features of the historical earthquake data based on similarity. If the similarity is greater than a preset similarity threshold, the initial vibration signal is deemed to have passed the secondary verification. If the similarity is less than or equal to the preset similarity threshold, the secondary verification of the initial vibration signal is deemed unsuccessful.

4. The method according to claim 2, characterized in that, The preset triggering condition is that the amplitude of the initial vibration signal exceeds the preset vibration signal amplitude, and the duration is greater than the preset duration.

5. The method according to claim 1, characterized in that, Also includes: Based on the historical earthquake data and historical interference data stored in the preset storage module, the preset vibration signal threshold is dynamically adjusted.

6. The method according to claim 5, characterized in that, The step of dynamically adjusting the preset vibration signal threshold based on the historical earthquake data and historical interference data stored in the preset storage module includes: Feature extraction is performed on the historical earthquake data and the historical interference data to obtain the amplitude range, frequency characteristics and duration of earthquake events, as well as the amplitude range, frequency characteristics and duration of interference events. The value of the preset vibration signal threshold is adjusted based on the characteristic differences between the earthquake event and the interference event.

7. The method according to any one of claims 1-6, characterized in that, After storing the target seismic data in a preset storage module, the method further includes: The target earthquake data is categorized by acquisition time and event type and added to the historical earthquake data.

8. A self-contained seismograph, characterized in that, include: The system comprises a first sensor, a second sensor, a data processing module, and a power supply module. The first sensor consumes less energy than the second sensor, and the second sensor has higher detection accuracy than the first sensor; the first sensor, the second sensor, and the power module are all communicatively connected to the data processing module. The power module is used to supply power to the first sensor, the second sensor and the data processing module; the data processing module is used to execute the method according to any one of claims 1-7.

9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

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