Infrasonic wave monitoring method and device, electronic equipment and storage medium

Abstract

The invention discloses an infrasonic wave monitoring method and device, electronic equipment and a storage medium. The method comprises the following steps: determining first waveform data; the first waveform data is used for describing data acquired in real time and related to a first sound monitoring array; determining configuration parameters based on the first waveform data; the configuration parameters are parameter information used by a preset algorithm associated with the first sound monitoring array; the preset algorithm is configured in the event processing task to process the waveform data; determining an event processing task of the first sound monitoring array based on the configuration parameters; processing second waveform data according to the event processing task of the first sound monitoring array to obtain a detection result; the second waveform data comprises the first waveform data and / or waveform data of the first sound monitoring array except the first waveform data. According to the technical scheme, the problems that the use efficiency of computing resources for infrasonic wave monitoring is low, the compatibility of a PMCC detection algorithm is poor, and the real-time computing efficiency is low are solved.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to an infrasound monitoring method, apparatus, electronic device, and storage medium. Background Technology

[0002] Infrasound monitoring is widely used in natural disaster early warning (such as volcanic eruptions and earthquakes), nuclear test monitoring, and industrial safety. Currently, infrasound monitoring generally uses the PMCC detection algorithm to extract infrasound events and their signal characteristics. However, the parameters of the PMCC algorithm are usually fixed values, which leads to problems such as low computational resource utilization efficiency, poor compatibility of the PMCC detection algorithm, and low real-time computation efficiency. Summary of the Invention

[0003] This invention provides an infrasound monitoring method, device, electronic device, and storage medium to solve problems such as low computational resource utilization efficiency, poor compatibility of PMCC detection algorithms, and low real-time computation efficiency in infrasound monitoring.

[0004] According to one aspect of the present invention, an infrasound monitoring method is provided, the method comprising:

[0005] Determine the first waveform data; the first waveform data is used to describe the data acquired in real time related to the first acoustic monitoring array;

[0006] Configuration parameters are determined based on the first waveform data; the configuration parameters are parameter information used by the preset algorithm associated with the first acoustic monitoring array; the preset algorithm is used to process the waveform data in the event processing task;

[0007] The event processing task for the first acoustic monitoring array is determined based on the configuration parameters.

[0008] The second waveform data is processed according to the event processing task of the first acoustic monitoring array to obtain the detection result; the second waveform data includes the first waveform data and / or the waveform data of the first acoustic monitoring array other than the first waveform data.

[0009] According to another aspect of the present invention, an infrasound monitoring device is provided, the device comprising:

[0010] The data determination module is used to determine the first waveform data; the first waveform data is used to describe the data acquired in real time related to the first acoustic monitoring array;

[0011] The parameter determination module is used to determine configuration parameters based on the first waveform data; the configuration parameters are parameter information used by the preset algorithm associated with the first acoustic monitoring array; the preset algorithm is used to configure the waveform data processing in the event processing task;

[0012] The task determination module is used to determine the event processing task of the first acoustic monitoring array based on the configuration parameters;

[0013] The data processing module is used to process the second waveform data according to the event processing task of the first acoustic monitoring array to obtain the detection result; the second waveform data includes the first waveform data and / or the waveform data of the first acoustic monitoring array other than the first waveform data.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] At least one processor; and

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the infrasound monitoring method according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the infrasound monitoring method according to any embodiment of the present invention.

[0019] The technical solution of this invention involves determining first waveform data; the first waveform data describes data acquired in real time related to the first acoustic monitoring array; further, configuration parameters are determined based on the first waveform data; the configuration parameters are parameter information used by a preset algorithm associated with the first acoustic monitoring array; the preset algorithm is configured to process the waveform data in an event processing task; real-time updates of the configuration parameters of the preset algorithm associated with the first acoustic monitoring array are implemented, thereby determining the event processing task of the first acoustic monitoring array based on the configuration parameters; dynamic generation of infrasound data processing tasks is implemented, and further, the second waveform data is processed according to the event processing task of the first acoustic monitoring array to obtain detection results; the second waveform data includes the first waveform data and / or waveform data of the first acoustic monitoring array other than the first waveform data; this solves the problems of low computational resource utilization efficiency, poor compatibility of PMCC detection algorithms, and low real-time computation efficiency in infrasound monitoring.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of an infrasound monitoring method provided according to an embodiment of the present invention;

[0023] Figure 2 This is a flowchart of another infrasound monitoring method provided according to an embodiment of the present invention;

[0024] Figure 3 This is a flowchart of another infrasound monitoring method provided according to an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of the structure of an infrasound monitoring device according to an embodiment of the present invention;

[0026] Figure 5 This is a schematic diagram of the structure of an electronic device that implements the infrasound monitoring method of the present invention, according to an embodiment of the present invention. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] Example 1

[0030] Figure 1 This is a flowchart illustrating an infrasound monitoring method provided in an embodiment of the present invention. This embodiment is applicable to situations where the configuration information of a preset algorithm needs to be adjusted in a timely manner during infrasound monitoring. The method can be executed by an infrasound monitoring device, which can be implemented in hardware and / or software. This infrasound monitoring device can be configured in any electronic device with network communication capabilities. Figure 1 As shown, the infrasound monitoring method of the present invention includes:

[0031] S110. Determine the first waveform data; the first waveform data is used to describe the data acquired in real time related to the first acoustic monitoring array.

[0032] Specifically, the infrasound monitoring array consists of multiple infrasound monitoring elements. The first waveform data can come from the waveform data of the first acoustic monitoring array and the waveform data of the first element corresponding to the first acoustic monitoring array; that is, the first waveform data includes at least the array identification information of the first acoustic monitoring array, the element identification information of the first element in the first acoustic monitoring array, and the metadata associated with the first acoustic monitoring array; the metadata includes at least the sampling rate, frequency range, longitude, latitude, and altitude.

[0033] Furthermore, after acquiring the first waveform data, it is necessary to parse the first waveform data to obtain the array identification information of the first acoustic monitoring array, the array element identification information of the first array element in the first acoustic monitoring array, and the metadata associated with the first acoustic monitoring array. This metadata is used to determine the configuration parameters of the preset algorithm for the association of the first acoustic monitoring array based on the first waveform data.

[0034] At the same time, it was determined whether the sampling rate of each first element in the first acoustic monitoring array was consistent.

[0035] If the sampling rate of each first element in the first acoustic monitoring array is consistent, the time reference of the first waveform data is normalized and preprocessed to unify the time of the first waveform data to local time or UTC standard time, ensuring that the time reference of all data is in a uniform format, and the normalized and preprocessed first waveform data is stored in the second database so that the data to be monitored can be retrieved from the second database in the event processing task.

[0036] If the sampling rates of the first array elements in the initial acoustic monitoring array are inconsistent, then the sampling rates of the first array elements are made consistent. Then, the time reference of the first waveform data after the sampling rate consistency is made normalized to the local time or UTC standard time, ensuring that the time reference of all data is in the same format. The first waveform data after normalization is stored in the second database so that the data to be monitored can be retrieved from the second database in the event processing task.

[0037] The sampling rate consistency processing for each first array element may include: designating the first array element with a sampling rate higher than the preset sampling rate as the third array element, designating the first array element with a sampling rate lower than the preset sampling rate as the fourth array element, using a resampling algorithm to reduce the sampling rate of the third array element to the preset sampling rate, and using an interpolation algorithm to increase the sampling rate of the fourth array element to the preset sampling rate, so as to ensure that the sampling rates of each first array element in the first acoustic monitoring array are consistent.

[0038] S120. Determine configuration parameters based on the first waveform data; the configuration parameters are the parameter information used by the preset algorithm associated with the first acoustic monitoring array; the preset algorithm is used to configure the processing of waveform data in the event processing task.

[0039] The preset algorithm can be the PMCC algorithm.

[0040] Specifically, the preset algorithm is used to monitor and process waveform data in the event processing task. Therefore, the configuration parameters of the preset algorithm are very important. However, the configuration parameters of the preset algorithm are currently fixed and cannot be dynamically configured. However, the array identification information of the first acoustic monitoring array, the array element identification information of the first array element in the first acoustic monitoring array, and the metadata associated with the first acoustic monitoring array included in the first waveform data may all affect the computational efficiency of the preset algorithm. That is, the dynamic adjustment of the configuration parameters of the preset algorithm is very important.

[0041] This invention establishes a preset association relationship between the array identification information of infrasound monitoring arrays, the element identification information of array elements within the infrasound monitoring arrays, and the metadata associated with the infrasound monitoring arrays and their configuration parameters. After acquiring waveform data from each infrasound monitoring array in real time, the configuration parameters of a preset algorithm are determined based on the array identification information, element identification information, and metadata associated with the infrasound monitoring arrays, along with the preset association relationship. These preset algorithm configuration parameters associated with each infrasound monitoring array are saved to a third database for subsequent retrieval from the third database and adjustment of the preset algorithm based on these parameters. The third database stores the correspondence between infrasound monitoring arrays and their associated preset algorithms.

[0042] Optionally, after determining the configuration parameters based on the first waveform data, the method further includes:

[0043] If the array identification information of the first acoustic monitoring array in the first waveform data exists in the third database, and the third database has the first configuration parameters of the preset algorithm associated with the first acoustic monitoring array, then the configuration parameters determined based on the first waveform data are updated to make the configuration parameters stored in the third database the latest.

[0044] If the array identifier information of the first acoustic monitoring array in the first waveform data does not exist in the third database, it means that the first acoustic monitoring array has appeared for the first time. In this case, the configuration parameters of the preset algorithm associated with the first acoustic monitoring array are directly saved in the third database.

[0045] S130. Determine the event processing tasks for the first acoustic monitoring array based on the configuration parameters.

[0046] The event processing task is configured with a preset algorithm, which enables the task to perform event detection processing on waveform data during runtime. The configuration parameters of the preset algorithm during runtime are either the latest configuration parameters stored in a third database or configuration parameters determined based on real-time acquired waveform data.

[0047] Specifically, the configuration parameters of the preset algorithm associated with the first acoustic monitoring array are retrieved from the third database, and computing resources for the event processing tasks of the first acoustic monitoring array are requested according to the configuration parameters to ensure the rational use of resources.

[0048] In an embodiment of the present invention, optionally, the configuration parameters include the array identification information of the first acoustic monitoring array, and the event processing task of the first acoustic monitoring array is determined based on the configuration parameters, including steps A1-A2:

[0049] Step A1: If the feature identifiers in all current event processing tasks do not match the array identifier information of the first sound monitoring array, it indicates that the first sound monitoring array is the first secondary sound monitoring array to be accessed. Then, the control task scheduler will establish the event processing task for the first sound monitoring array based on the configuration parameters.

[0050] Step A2: If the feature identifiers in all current event processing tasks match the array identifier information of the first sound monitoring array, it means that the first sound monitoring array is not the first secondary sound monitoring array to be connected. Then, the event processing task that matches the array identifier information of the first sound monitoring array will be taken as the event processing task of the first sound monitoring array.

[0051] Step A3: Update the event processing task of the first acoustic monitoring array based on the configuration parameters.

[0052] Specifically, the event processing task of updating the first acoustic monitoring array based on configuration parameters mainly involves updating the parameter information of the preset algorithm in the event processing task of the first acoustic monitoring array based on configuration parameters, ensuring that the parameter information of the preset algorithm is the latest parameter information.

[0053] Updating the parameter information of the preset algorithm in the event processing task of the first acoustic monitoring array based on configuration parameters includes: if the configuration parameters are consistent with the parameter information of the preset algorithm in the event processing task of the first acoustic monitoring array, no operation will be triggered; if the configuration parameters are inconsistent with the parameter information of the preset algorithm in the event processing task of the first acoustic monitoring array, the configuration parameters will be written into the parameter information of the preset algorithm in the event processing task of the first acoustic monitoring array to obtain the latest parameter information of the preset algorithm, thereby ensuring the accuracy of the waveform processed by the event processing task.

[0054] S140. Process the second waveform data according to the event processing task of the first acoustic monitoring array to obtain the detection result; the second waveform data includes the first waveform data and / or the waveform data of the first acoustic monitoring array other than the first waveform data.

[0055] The second waveform data can be waveform data stored in the fourth database or waveform data received in real time, so that the corresponding waveform data can be retrieved from the database when performing event processing tasks.

[0056] Specifically, the first event processing task of the acoustic monitoring array detects events on the second waveform data according to the built-in preset algorithm, generates detection event attribute information such as start time, duration, azimuth angle, and sound speed, saves it as detection results, sends it to the detection event result database, and sends the detection results to the visualization interface for event warning.

[0057] Optionally, the event processing tasks are dynamically managed and monitored through a task scheduler. Specifically, it is determined whether each event processing task is idle. If there is no infrasound waveform data input for the event processing task of the second acoustic monitoring array within a preset time period, it indicates that the second acoustic monitoring array is damaged or the data transmission link is interrupted. In this case, the idle second acoustic monitoring array is recycled and destroyed to release computing resources and improve the utilization rate of computing resources.

[0058] The technical solution of this invention involves determining first waveform data; the first waveform data describes data acquired in real time related to the first acoustic monitoring array; further, configuration parameters are determined based on the first waveform data; the configuration parameters are parameter information used by a preset algorithm associated with the first acoustic monitoring array; the preset algorithm is configured to process the waveform data in an event processing task; real-time updates of the configuration parameters of the preset algorithm associated with the first acoustic monitoring array are achieved, avoiding the impact of fixed configuration parameters on the accuracy of the processing results obtained from processing infrasound data. Simultaneously, the event processing task of the first acoustic monitoring array is determined based on the configuration parameters; the infrasound data processing task is dynamically adjusted; further, second waveform data is processed according to the event processing task of the first acoustic monitoring array to obtain detection results; the second waveform data includes the first waveform data and / or waveform data of the first acoustic monitoring array other than the first waveform data; this solves the problems of low computational resource utilization efficiency, poor compatibility of PMCC detection algorithms, and low real-time computation efficiency in infrasound monitoring.

[0059] Example 2

[0060] Figure 2 This is a flowchart of another infrasound monitoring method provided by an embodiment of the present invention. The technical solution of this embodiment further optimizes the process S110 in the aforementioned embodiments based on the above embodiments. This embodiment can be combined with various optional solutions in one or more of the above embodiments. Figure 2 As shown, the infrasound monitoring method of the present invention includes:

[0061] S210. Obtain the third waveform data of the first acoustic monitoring array. The third waveform data is the waveform data emitted in real time by the infrasound monitoring array.

[0062] The third waveform data includes the first array identifier information of the first acoustic monitoring array, the first array element identifier information of the first array element contained in the first acoustic monitoring array, and the metadata associated with the first acoustic monitoring array.

[0063] Specifically, the third waveform data is parsed to obtain the array identification information of the first acoustic monitoring array, the array element identification information of the first array element in the first acoustic monitoring array, and the metadata associated with the first acoustic monitoring array.

[0064] Furthermore, after acquiring the third waveform data of the first acoustic monitoring array, the method further includes: performing normalization preprocessing on the time reference of the third waveform data, unifying the time of the third waveform data to local time or UTC standard time, ensuring that the time reference of all data is in a uniform format, and storing the normalized preprocessed third waveform data in a second database so that the data to be monitored can be retrieved from the second database in the event processing task.

[0065] S220. Update the first database based on the third waveform data to obtain the updated first database. The first database is used to store the array identification information of different infrasound monitoring arrays, the array element identification information of array elements in different infrasound monitoring arrays, and the metadata associated with each infrasound monitoring array. The metadata includes at least the sampling rate, frequency range, longitude, latitude, and altitude.

[0066] Specifically, it is determined whether the first database includes the first array identifier information and / or the first array element identifier information. If the first database includes the first array identifier information and the first array element identifier information, the first database is updated based on the comparison result between the metadata associated with the first acoustic monitoring array in the third waveform data and the metadata associated with the first acoustic monitoring array in the first database. If the first database includes the first array identifier information but does not include the first array element identifier information, the array element corresponding to the first array element identifier information is added to the first database to obtain an updated first database. If the first database does not include the first array identifier information, the first acoustic monitoring array is added to the first database to obtain an updated first database.

[0067] S230. Retrieve the basic waveform data from the first waveform data of the first acoustic monitoring array from the updated first database.

[0068] Among them, the basic waveform data in the first waveform data can be the first array identifier information of the first acoustic monitoring array, the first array element identifier information of the first array element contained in the first acoustic monitoring array, and the metadata associated with the first acoustic monitoring array.

[0069] S240. Determine configuration parameters based on the first waveform data; the configuration parameters are the parameter information used by the preset algorithm associated with the first acoustic monitoring array; the preset algorithm is used to configure the processing of waveform data in the event processing task.

[0070] Specifically, the configuration parameters are determined based on the basic waveform data in the first waveform data.

[0071] S250. Determine the event processing task of the first acoustic monitoring array based on the configuration parameters. Process the second waveform data according to the event processing task of the first acoustic monitoring array to obtain the detection result; the second waveform data includes the first waveform data and / or the waveform data of the first acoustic monitoring array other than the first waveform data.

[0072] The technical solution of this invention involves acquiring the third waveform data of a first acoustic monitoring array. This third waveform data is the real-time waveform data emitted by the infrasound monitoring array. The first database is updated based on this third waveform data to obtain an updated first database. The first database stores array identification information for different infrasound monitoring arrays, element identification information for array elements within different infrasound monitoring arrays, and metadata associated with each infrasound monitoring array. The metadata includes at least sampling rate, frequency range, longitude, latitude, and altitude. The basic waveform data from the first waveform data of the first acoustic monitoring array is then retrieved from the updated first database to ensure the accuracy of the data used to determine configuration parameters. Further, configuration parameters are determined based on the first waveform data. Based on the configuration parameters, an event processing task for the first acoustic monitoring array is determined to process the second waveform data according to the event processing task of the first acoustic monitoring array, obtaining detection results. This solution addresses the problems of low computational resource utilization efficiency, poor compatibility of PMCC detection algorithms, and low real-time computation efficiency in infrasound monitoring.

[0073] Example 3

[0074] Figure 3 This is a flowchart of another infrasound monitoring method provided by an embodiment of the present invention. The technical solution of this embodiment further optimizes the process of S120 in the aforementioned embodiments based on the above embodiments. This embodiment can be combined with various optional solutions in one or more of the above embodiments. Figure 3 As shown, the infrasound monitoring method of the present invention includes:

[0075] S310. Determine the first waveform data; the first waveform data is used to describe the data acquired in real time related to the first acoustic monitoring array.

[0076] S320, the configuration parameters are the number of array elements, array element information and consistency threshold; the configuration parameters are determined based on the first waveform data.

[0077] Specifically, the first number of the first array elements in the first acoustic monitoring array is obtained from the first waveform data, along with the array element identification information, longitude, latitude, and altitude of the first array elements. The first number is determined as the number of array elements associated with the preset algorithm of the first acoustic monitoring array.

[0078] Simultaneously, based on the element identification information, longitude, latitude, and altitude of the first array element, the element information of the preset algorithm associated with the first acoustic monitoring array is determined; based on the longitude and latitude of the first array element, the element distance between each second array element and the central array element is determined; the second array elements are the other array elements in the first array element excluding the central array element. The element identification information, longitude, latitude, and altitude of the first array element can reflect the array element layout shape of the first array element in the first acoustic monitoring array.

[0079] Furthermore, a consistency threshold for a preset algorithm for determining the first acoustic monitoring station array association based on the array element distance is established; there is a first correlation between the array element distance and the consistency threshold, and the larger the array element distance, the larger the consistency threshold.

[0080] S330, the configuration parameters are time window length and window overlap rate; the configuration parameters are determined based on the first waveform data.

[0081] Specifically, the first sampling rate of the first acoustic monitoring array in the first waveform data is obtained; the time window length of the preset algorithm associated with the first acoustic monitoring array is determined based on the first sampling rate; there is a second correlation between the sampling rate and the time window length, and the lower the sampling rate, the larger the time window length.

[0082] Simultaneously, the window overlap rate of the preset algorithm for the first acoustic monitoring array association is determined based on the first sampling rate. A third correlation exists between the window overlap rate and the sampling rate; the higher the sampling rate, the lower the window overlap rate. Alternatively, the window overlap rate of the preset algorithm for the first acoustic monitoring array association is determined based on the time window length and preset step size. The determination of the preset step size includes: since there is a correspondence between the preset step size and the sampling rate, after determining the sampling rate, the preset step size can be determined based on the correspondence between the preset step size and the sampling rate, and the sampling rate itself.

[0083] S340, the configuration parameters are frequency band and frequency threshold; the configuration parameters are determined based on the first waveform data.

[0084] Specifically, the first frequency range of the first acoustic monitoring array in the first waveform data is obtained; based on the first frequency range and the preset frequency range, the frequency band of the preset algorithm associated with the first acoustic monitoring array is determined; the preset frequency range is used to describe the frequency value for dividing a frequency band.

[0085] Simultaneously, a preset algorithm for associating the first acoustic monitoring array is determined based on the first frequency range; a fourth association relationship exists between the frequency range and the frequency threshold.

[0086] S350, the configuration parameters are time threshold and azimuth angle threshold; the configuration parameters are determined based on the first waveform data.

[0087] Specifically, the first sampling rate of the first acoustic monitoring array in the first waveform data is obtained; based on the longitude and latitude of the first array element in the first acoustic monitoring array, the array element distance between each second array element and the central array element is determined; the second array element refers to the other array elements in the first array element excluding the central array element. A time threshold for a preset algorithm associated with the first acoustic monitoring array is determined based on the first sampling rate and the array element distance; there is a fifth correlation between the sampling rate, the array element distance, and the time threshold, and the lower the sampling rate and the larger the array element distance, the higher the time threshold.

[0088] Simultaneously, the azimuth threshold of the preset algorithm for the first acoustic monitoring array association is determined based on the first quantity; there is a sixth correlation between the number of array elements in the infrasound monitoring array and the azimuth threshold, and the more array elements there are, the smaller the azimuth threshold is. The first quantity is the number of the first array elements in the first acoustic monitoring array.

[0089] S360. Determine the event processing task of the first acoustic monitoring array based on the configuration parameters; process the second waveform data according to the event processing task of the first acoustic monitoring array to obtain the detection result; the second waveform data includes the first waveform data and / or the waveform data of the first acoustic monitoring array other than the first waveform data.

[0090] The technical solution of this invention involves determining first waveform data. This first waveform data describes the data acquired in real-time related to the first acoustic monitoring array. Configuration parameters include the number of array elements, element information, consistency threshold, time window length, window overlap rate, frequency band, frequency threshold, time threshold, and azimuth threshold. These configuration parameters are determined based on the first waveform data; that is, the configuration parameters of the preset algorithm configured in real-time in this invention solve the problems of poor data compatibility and low real-time computation efficiency in traditional infrasound event detection algorithms. Further, the event processing task for the first acoustic monitoring array is determined based on the configuration parameters. The second waveform data is processed according to the event processing task of the first acoustic monitoring array to obtain the detection result. The second waveform data includes the first waveform data and / or waveform data from the first acoustic monitoring array other than the first waveform data, solving the problem of low computational resource utilization efficiency in infrasound monitoring.

[0091] Example 4

[0092] Figure 4 This is a schematic diagram of an infrasound monitoring device provided in an embodiment of the present invention. This embodiment is applicable to situations where the configuration information of a preset algorithm needs to be adjusted in a timely manner during infrasound monitoring. The infrasound monitoring device can be implemented in hardware and / or software, and can be configured in any electronic device with network communication capabilities. Figure 4 As shown, the infrasound monitoring device includes:

[0093] The data determination module 410 is used to determine the first waveform data; the first waveform data is used to describe the data acquired in real time related to the first acoustic monitoring array;

[0094] The parameter determination module 420 is used to determine configuration parameters based on the first waveform data; the configuration parameters are parameter information used by the preset algorithm associated with the first acoustic monitoring array; the preset algorithm is configured to process the waveform data in the event processing task;

[0095] The task determination module 430 is used to determine the event processing task of the first acoustic monitoring array based on the configuration parameters.

[0096] The data processing module 440 is used to process the second waveform data according to the event processing task of the first acoustic monitoring array to obtain the detection result; the second waveform data includes the first waveform data and / or the waveform data of the first acoustic monitoring array other than the first waveform data.

[0097] Based on the above embodiments, optionally, the data determination module is used to: acquire the third waveform data of the first acoustic monitoring array, wherein the third waveform data is waveform data emitted in real time by the infrasound monitoring array; update the first database based on the third waveform data to obtain the updated first database; the first database is used to store array identification information of different infrasound monitoring arrays, array element identification information of array elements in different infrasound monitoring arrays, and metadata associated with each infrasound monitoring array; the metadata includes at least sampling rate, frequency range, longitude, latitude, and altitude; and retrieve the basic waveform data of the first waveform data of the first acoustic monitoring array from the updated first database.

[0098] Based on the above embodiments, optionally, the third waveform data includes the first array identifier information of the first acoustic monitoring array, the first array element identifier information of the array elements included in the first acoustic monitoring array, and the metadata associated with the first acoustic monitoring array; the data determination module includes an update unit, which is used to: determine whether the first database includes the first array identifier information and / or the first array element identifier information; if the first database includes the first array identifier information and the first array element identifier information, then update the first database based on the comparison result between the metadata associated with the first acoustic monitoring array in the third waveform data and the metadata associated with the first acoustic monitoring array in the first database; if the first database includes the first array identifier information but does not include the first array element identifier information, then add the array element corresponding to the first array element identifier information to the first database to obtain the updated first database; if the first database does not include the first array identifier information, then add the first acoustic monitoring array to the first database to obtain the updated first database.

[0099] Based on the above embodiments, optionally, the configuration parameters are the number of array elements, array element information, and a consistency threshold; the parameter determination module includes a first parameter determination unit, which is used to: obtain the first number of the first array elements in the first acoustic monitoring array in the first waveform data, as well as the array element identification information, longitude, latitude, and altitude of the first array elements; determine the first number as the number of array elements in the preset algorithm associated with the first acoustic monitoring array; determine the array element information of the preset algorithm associated with the first acoustic monitoring array based on the array element identification information, longitude, latitude, and altitude of the first array elements; determine the array element distance between each second array element and the center array element based on the longitude and latitude of the first array elements; the second array elements are the other array elements in the first array elements besides the center array element; determine the consistency threshold of the preset algorithm associated with the first acoustic monitoring array based on the array element distance; there is a first correlation between the array element distance and the consistency threshold, and the larger the array element distance, the larger the consistency threshold.

[0100] Based on the above embodiments, optionally, the configuration parameters are time window length and window overlap rate; the parameter determination module includes a second parameter determination unit, which is used to: obtain the first sampling rate of the first acoustic monitoring array in the first waveform data; determine the time window length of the preset algorithm associated with the first acoustic monitoring array based on the first sampling rate; there is a second correlation between the sampling rate and the time window length, and the lower the sampling rate, the larger the time window length; determine the window overlap rate of the preset algorithm associated with the first acoustic monitoring array based on the first sampling rate, and there is a third correlation between the window overlap rate and the sampling rate, and the higher the sampling rate, the lower the window overlap rate; or, determine the window overlap rate of the preset algorithm associated with the first acoustic monitoring array based on the time window length and the preset step size.

[0101] Based on the above embodiments, optionally, the configuration parameters are frequency bands and frequency thresholds; the parameter determination module includes a third parameter determination unit, which is used to: obtain a first frequency range of the first acoustic monitoring array in the first waveform data; determine the frequency bands of a preset algorithm associated with the first acoustic monitoring array based on the first frequency range and a preset frequency range; the preset frequency range is used to describe the frequency value for dividing a frequency band; determine the frequency threshold of the preset algorithm associated with the first acoustic monitoring array based on the first frequency range; there is a fourth correlation between the frequency range and the frequency threshold.

[0102] Based on the above embodiments, optionally, the configuration parameters are a time threshold and an azimuth threshold; the parameter determination module includes a fourth parameter determination unit, and the tenth parameter determination unit is used to: obtain the first sampling rate of the first acoustic monitoring array in the first waveform data; determine the time threshold of the preset algorithm associated with the first acoustic monitoring array based on the first sampling rate and the array element distance; there is a fifth correlation between the sampling rate and the array element distance and the time threshold, and the time threshold is higher when the sampling rate is low and the array element distance is large; determine the azimuth threshold of the preset algorithm associated with the first acoustic monitoring array based on the first quantity; there is a sixth correlation between the number of array elements in the infrasound monitoring array and the azimuth threshold, and the more array elements there are, the smaller the azimuth threshold is.

[0103] Based on the above embodiments, optionally, the configuration parameters include the array identification information of the first acoustic monitoring array. The task determination module is used to: if the feature identifiers in all current event processing tasks do not match the array identification information of the first acoustic monitoring array, then control the task scheduler to establish event processing tasks for the first acoustic monitoring array based on the configuration parameters; if the feature identifiers in all current event processing tasks match the array identification information of the first acoustic monitoring array, then use the event processing task that matches the array identification information of the first acoustic monitoring array as the event processing task for the first acoustic monitoring array; and update the event processing tasks for the first acoustic monitoring array based on the configuration parameters.

[0104] The infrasound monitoring device provided in the embodiments of the present invention can execute the infrasound monitoring method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0105] Example 5

[0106] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0107] Figure 5 A schematic diagram of an electronic device that can be used to implement the infrasound monitoring method of embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0108] like Figure 5As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0109] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0110] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as infrasound monitoring methods.

[0111] In some embodiments, the infrasound monitoring method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the infrasound monitoring method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the infrasound monitoring method by any other suitable means (e.g., by means of firmware).

[0112] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transferring data and instructions to the storage system, the at least one input device, and the at least one output device.

[0113] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0114] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0115] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0116] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0117] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0118] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0119] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for monitoring infrasound, characterized in that, The method includes: Determine the first waveform data; the first waveform data is used to describe the data acquired in real time related to the first acoustic monitoring array; Configuration parameters are determined based on the first waveform data; the configuration parameters are parameter information used by the preset algorithm associated with the first acoustic monitoring array; the preset algorithm is used to process the waveform data in the event processing task; The event processing task for the first acoustic monitoring array is determined based on the configuration parameters. The second waveform data is processed according to the event processing task of the first acoustic monitoring array to obtain the detection result; the second waveform data includes the first waveform data and / or the waveform data of the first acoustic monitoring array other than the first waveform data.

2. The method according to claim 1, characterized in that, Determine the first waveform data, including: Acquire the third waveform data of the first acoustic monitoring array, wherein the third waveform data is the waveform data emitted in real time by the infrasound monitoring array; The first database is updated based on the third waveform data to obtain the updated first database; the first database is used to store array identification information of different infrasound monitoring arrays, array element identification information of array elements in different infrasound monitoring arrays, and metadata associated with each infrasound monitoring array; the metadata includes at least sampling rate, frequency range, longitude, latitude, and altitude. The base waveform data of the first waveform data of the first acoustic monitoring array is retrieved from the updated first database.

3. The method according to claim 2, characterized in that, The third waveform data includes the first array identifier information of the first acoustic monitoring array, the first element identifier information of the first array element contained in the first acoustic monitoring array, and the metadata associated with the first acoustic monitoring array. Accordingly, the first database is updated based on the third waveform data to obtain the updated first database, including: Determine whether the first database includes the first array identifier information and / or the first array element identifier information; If the first database includes the first array identifier information and the first array element identifier information, then the first database is updated based on the comparison result between the metadata associated with the first acoustic monitoring array in the third waveform data and the metadata associated with the first acoustic monitoring array in the first database. If the first database includes the first array identifier information but does not include the first array element identifier information, then the array element corresponding to the first array element identifier information is added to the first database to obtain the updated first database. If the first database does not include the identification information of the first array, then the first acoustic monitoring array is added to the first database to obtain an updated first database.

4. The method according to claim 1, characterized in that, The configuration parameters are the number of array elements, array element information, and consistency threshold; the configuration parameters are determined based on the first waveform data, including: Obtain the first number of the first array elements in the first acoustic monitoring array in the first waveform data, as well as the array element identification information, longitude, latitude and altitude of the first array elements; The first quantity is determined as the number of array elements in the preset algorithm associated with the first acoustic monitoring array; The array element information of the preset algorithm for the association of the first acoustic monitoring array is determined based on the array element identification information, longitude, latitude and altitude of the first array element. Based on the longitude and latitude of the first array element, the array element distance between each second array element and the central array element is determined; the second array element is the other array elements in the first array element excluding the central array element. The consistency threshold of the preset algorithm for the first acoustic monitoring array association is determined based on the array element distance; there is a first correlation between the array element distance and the consistency threshold, and the larger the array element distance, the larger the consistency threshold.

5. The method according to claim 1, characterized in that, The configuration parameters are time window length and window overlap rate; the configuration parameters are determined based on the first waveform data, including: Obtain the first sampling rate of the first acoustic monitoring array in the first waveform data; The time window length of the preset algorithm for the first acoustic monitoring array association is determined based on the first sampling rate; there is a second correlation between the sampling rate and the time window length, and the lower the sampling rate, the longer the time window length; The window overlap rate of the preset algorithm for the first acoustic monitoring array association is determined based on the first sampling rate. There is a third correlation between the window overlap rate and the sampling rate, and the higher the sampling rate, the lower the window overlap rate. Alternatively, the window overlap rate of the preset algorithm for the first acoustic monitoring array association is determined based on the time window length and preset step size of the preset algorithm.

6. The method according to claim 1, characterized in that, The configuration parameters are frequency band division and frequency threshold; the configuration parameters are determined based on the first waveform data, including: Obtain the first frequency range of the first acoustic monitoring array in the first waveform data; Based on the first frequency range and the preset frequency range, the frequency bands of the preset algorithm associated with the first acoustic monitoring array are determined; the preset frequency range is used to describe the frequency values ​​that divide a frequency band. The frequency threshold of the preset algorithm associated with the first acoustic monitoring array is determined based on the first frequency range; there is a fourth correlation between the frequency range and the frequency threshold.

7. The method according to claim 4, characterized in that, The configuration parameters are a time threshold and an azimuth angle threshold; the configuration parameters are determined based on the first waveform data, including: Obtain the first sampling rate of the first acoustic monitoring array in the first waveform data; The time threshold of the preset algorithm for the first acoustic monitoring array association is determined based on the first sampling rate and the array element distance; there is a fifth correlation between the sampling rate, the array element distance and the time threshold, and the time threshold is higher when the sampling rate is low and the array element distance is large. Based on the first quantity, the azimuth threshold of the preset algorithm associated with the first acoustic monitoring array is determined; there is a sixth correlation between the number of array elements in the infrasound monitoring array and the azimuth threshold, and the more array elements there are, the smaller the azimuth threshold is.

8. The method according to claim 1, characterized in that, The configuration parameters include the array identification information of the first acoustic monitoring array. Based on the configuration parameters, the event processing tasks of the first acoustic monitoring array are determined, including: If the feature identifiers in all current event processing tasks do not match the array identifier information of the first acoustic monitoring array, the control task scheduler will establish an event processing task for the first acoustic monitoring array based on the configuration parameters. If any feature identifier in all current event processing tasks matches the array identifier information of the first acoustic monitoring array, then the event processing task that matches the array identifier information of the first acoustic monitoring array will be used as the event processing task of the first acoustic monitoring array. The event processing task of the first acoustic monitoring array is updated based on the configuration parameters.

9. An infrasound monitoring device, characterized in that, The device includes: The data determination module is used to determine the first waveform data; the first waveform data is used to describe the data acquired in real time related to the first acoustic monitoring array; The parameter determination module is used to determine configuration parameters based on the first waveform data; the configuration parameters are parameter information used by the preset algorithm associated with the first acoustic monitoring array; the preset algorithm is used to configure the waveform data processing in the event processing task; The task determination module is used to determine the event processing task of the first acoustic monitoring array based on the configuration parameters; The data processing module is used to process the second waveform data according to the event processing task of the first acoustic monitoring array to obtain the detection result; the second waveform data includes the first waveform data and / or the waveform data of the first acoustic monitoring array other than the first waveform data.

10. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the infrasound monitoring method according to any one of claims 1-8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the infrasound monitoring method according to any one of claims 1-8.

Images