Natural gas storage tank leakage alarm system, method, equipment and medium

Abstract

The invention particularly relates to a natural gas storage tank leakage alarm system, method, equipment and medium, the leakage alarm system comprises a multi-mode sensor network, a central processing unit and a remote monitoring alarm platform, and the multi-mode sensor network is used for performing multi-signal fusion based on sound wave signals and infrared light signals to obtain fusion signals. And the central processing unit is used for performing gas concentration change trend analysis based on the fusion signal, performing dynamic threshold analysis on change trend information by using an alarm threshold prediction model, and determining a target alarm threshold. And the remote monitoring alarm platform is used for performing gas concentration change prediction based on the change trend information, and performing remote monitoring based on a target alarm threshold value and the concentration prediction information. The remote monitoring alarm platform performs natural gas leakage monitoring by using the target alarm threshold provided by the dynamic alarm threshold adjustment mechanism, can accurately capture the fine leakage change of the storage tank, and improves the accuracy of leakage alarm.

Description

Technical Field

[0001] The present application relates to the technical field of gas safety monitoring, and in particular to a natural gas storage tank leakage alarm system, method, equipment and medium. Background Art

[0002] With the booming development of the global energy industry, natural gas, as an efficient and environmentally friendly energy carrier, has been applied to every corner of the world. However, the highly explosive characteristics of natural gas have put forward extremely stringent standards for the safety performance of storage facilities. At present, many natural gas storage facilities are equipped with leak detection systems, which are designed to effectively protect the safety of operators and the surrounding environment through early warning mechanisms.

[0003] Most of the leakage alarm systems in related technologies rely on fixed sensor network layouts. When the gas concentration reaches the preset alarm threshold, the system will immediately start the alarm process. Although this mechanism ensures the timeliness of safety response to a certain extent, in the face of complex and changing working conditions, it only relies on a single threshold setting and static alarm strategy, which often cannot accurately capture subtle leakage changes, and is prone to false alarms or missed alarms, affecting the accuracy of natural gas storage tank leakage alarms.

[0004] Therefore, how to improve the accuracy of leakage alarm is a technical problem that needs to be solved urgently by those skilled in the art. Summary of the invention

[0005] The purpose of this application is to provide a natural gas storage tank leakage alarm system, method, device and medium to solve at least one of the above technical problems.

[0006] The above invention objectives of the present application are achieved through the following technical solutions: In the first aspect, the present application provides a natural gas storage tank leakage alarm system, which adopts the following technical solution: A natural gas storage tank leakage alarm system includes: a multimodal sensor network, a central processing unit and a remote monitoring alarm platform, wherein: A multimodal sensor network, used for acquiring sound wave signals and infrared light signals in real time, and performing multi-signal fusion based on the sound wave signals and the infrared light signals to obtain a fusion signal; A central processing unit, configured to receive the fusion signal sent by the multimodal sensor network in real time, and perform gas concentration change trend analysis based on the fusion signal to obtain change trend information; Acquire an alarm threshold prediction model, and use the alarm threshold prediction model to perform dynamic threshold analysis on the change trend information to determine a target alarm threshold, wherein the target alarm threshold is used to improve the sensitivity and accuracy of the leakage alarm; The remote monitoring and alarm platform is used to predict the change of gas concentration based on the change trend information sent by the central processing unit, determine the concentration prediction information, and perform remote monitoring based on the target alarm threshold and the concentration prediction information. When a leakage risk is detected, an audible and visual alarm signal is issued to remind relevant personnel to take countermeasures.

[0007] By adopting the above technical solution, the natural gas storage tank leakage alarm system includes: a multimodal sensor network, a central processing unit and a remote monitoring alarm platform. The multimodal sensor network is used to obtain acoustic wave signals and infrared light signals in real time, and multi-signal fusion is performed based on acoustic wave signals and infrared light signals to obtain fusion signals. Through multi-signal fusion, the advantages of these two signals can be combined to detect leakage from multiple dimensions, thereby improving the accuracy of natural gas leakage monitoring. The central processing unit is used to analyze the trend of gas concentration changes based on the fusion signal to obtain change trend information, and use the alarm threshold prediction model to perform dynamic threshold analysis on the change trend information to determine the target alarm threshold, wherein the dynamic alarm threshold adjustment mechanism is adopted to improve the sensitivity to signs of minor leakage, greatly reduce the false alarm rate, achieve more accurate risk warning, and improve the accuracy of subsequent leakage alarms. The remote monitoring alarm platform is used to predict the change of gas concentration based on the change trend information sent by the central processing unit, determine the concentration prediction information, and perform remote monitoring based on the target alarm threshold and concentration prediction information. When a leakage risk is detected, an audible and visual alarm signal is issued to remind relevant personnel to take countermeasures. The remote monitoring and alarm platform uses the target alarm threshold provided by the dynamic alarm threshold adjustment mechanism to monitor natural gas leaks. It can accurately capture subtle leakage changes in storage tanks and improve the accuracy of leak alarms.

[0008] In a preferred example, the present application can be further configured as follows: A sensor network building module, used to obtain natural gas storage tank information, perform sensor deployment location analysis based on the natural gas storage tank information, and determine multiple deployment nodes; Performing sensor analysis based on each of the deployment nodes to determine sensor information corresponding to each of the deployment nodes, wherein the sensor information includes: sensor type and sensor specification; A network is established based on the sensor information corresponding to each of the deployed nodes to obtain a multimodal sensor network.

[0009] In a preferred example, the present application may be further configured as follows: when the sensor network building module performs the sensor deployment location analysis based on the natural gas storage tank information and determines multiple deployment nodes, it is used to: Building a three-dimensional model based on the natural gas storage tank information to determine the three-dimensional model of the storage tank, and performing a windless leakage diffusion simulation based on the three-dimensional model of the storage tank to determine the first gas diffusion range; Based on the three-dimensional model of the storage tank, a leakage diffusion simulation in a variable wind environment is performed to determine the diffusion range of the second gas; A sensor deployment position analysis is performed based on the first gas diffusion range and the second gas diffusion range to determine a plurality of deployment nodes.

[0010] In a preferred example, the present application can be further configured as a remote monitoring alarm platform, and is also used for: When the concentration prediction information exceeds the target alarm threshold, a picture capture instruction is sent to the visual monitoring terminal to control the visual monitoring terminal to capture a real-time picture including the natural gas storage tank; The abnormal sound source is located based on the real-time image and the sound wave signal to determine the abnormal sound source, wherein the abnormal sound source provides relevant personnel with the leakage point of the natural gas storage tank.

[0011] In a preferred example, the present application can be further configured as follows: An environmental adaptability analysis terminal, used to monitor storage environment information, perform sensor environment adaptability analysis based on the storage environment information, and determine adaptability analysis results, wherein the adaptability analysis results include: full adaptability, partial adaptability, and non-adaptability; When the adaptability analysis result is the partial adaptability or the non-adaptability, a sensor calibration instruction is generated, wherein the sensor calibration instruction is used to prompt to perform adaptive calibration adjustment on each sensor in the multimodal sensor network.

[0012] In a preferred example, the present application may be further configured as follows: when the multimodal sensor network performs the multi-signal fusion based on the acoustic wave signal and the infrared light signal to obtain the fused signal, it is used to: Preprocessing is performed based on the acoustic wave signal and the infrared light signal to obtain a target acoustic wave signal and a target infrared light signal, wherein the preprocessing is used to improve the quality and reliability of the acoustic wave signal and the infrared light signal; Extracting acoustic wave features based on the target acoustic wave signal to obtain acoustic wave features, and extracting infrared features based on the target infrared light signal to obtain infrared features; Multi-signal fusion is performed based on the acoustic wave characteristics and the infrared characteristics to obtain a fused signal.

[0013] In a second aspect, the present application provides a natural gas storage tank leakage alarm method, which adopts the following technical solution: Acquiring an acoustic wave signal and an infrared light signal in real time, and performing multi-signal fusion based on the acoustic wave signal and the infrared light signal to obtain a fused signal; Performing gas concentration change trend analysis based on the fusion signal to obtain change trend information; Acquire an alarm threshold prediction model, and use the alarm threshold prediction model to perform dynamic threshold analysis on the change trend information to determine a target alarm threshold, wherein the target alarm threshold is used to improve the sensitivity and accuracy of the leakage alarm; Based on the change trend information, the gas concentration change is predicted, the concentration prediction information is determined, and remote monitoring is performed based on the target alarm threshold and the concentration prediction information. When a leakage risk is detected, an audible and visual alarm signal is issued to remind relevant personnel to take countermeasures.

[0014] In a third aspect, the present application provides an electronic device, which adopts the following technical solution: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the above-mentioned natural gas storage tank leakage alarm method.

[0015] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a computer program, which, when executed in a computer, causes the computer to execute the above-mentioned natural gas storage tank leakage alarm method.

[0016] In summary, the present application includes at least one of the following beneficial technical effects: The natural gas storage tank leakage alarm system includes: a multimodal sensor network, a central processing unit and a remote monitoring alarm platform. The multimodal sensor network is used to obtain acoustic signals and infrared light signals in real time, and multi-signal fusion is performed based on acoustic signals and infrared light signals to obtain fused signals. Through multi-signal fusion, the advantages of these two signals can be combined to detect leaks from multiple dimensions, thereby improving the accuracy of natural gas leakage monitoring. The central processing unit is used to analyze the trend of gas concentration changes based on the fused signal to obtain change trend information, and use the alarm threshold prediction model to perform dynamic threshold analysis on the change trend information to determine the target alarm threshold. Among them, the dynamic alarm threshold adjustment mechanism is adopted to improve the sensitivity to signs of minor leaks, greatly reduce the false alarm rate, achieve more accurate risk warnings, and improve the accuracy of subsequent leak alarms. The remote monitoring alarm platform is used to predict gas concentration changes based on the change trend information sent by the central processing unit, determine the concentration prediction information, and perform remote monitoring based on the target alarm threshold and concentration prediction information. When a leakage risk is detected, an audible and visual alarm signal is issued to remind relevant personnel to take countermeasures. The remote monitoring and alarm platform uses the target alarm threshold provided by the dynamic alarm threshold adjustment mechanism to monitor natural gas leaks. It can accurately capture subtle leakage changes in storage tanks and improve the accuracy of leak alarms.

[0017] In order to obtain the real-time status information of the storage tank more accurately, the sensor deployment location analysis is performed based on the natural gas storage tank information to determine multiple deployment nodes. The sensor deployment location analysis is used to ensure that the sensors are deployed in key locations to form a comprehensive monitoring of the storage tank and reduce monitoring blind spots. Then, sensor analysis is performed based on each deployment node to determine the sensor information corresponding to each deployment node. According to the specific environment and requirements of each deployment node, the corresponding sensor type and specifications are selected to ensure that the sensor can collect data accurately and efficiently. Furthermore, the network is established based on the sensor information corresponding to each deployment node to obtain a multimodal sensor network, wherein the multimodal sensor network can flexibly adapt to different monitoring needs and can be expanded or adjusted according to actual conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a structural schematic diagram of a natural gas storage tank leakage alarm system according to one embodiment of the present application; Figure 2 It is a flow chart of a natural gas storage tank leakage alarm method according to one embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device according to one embodiment of the present application. DETAILED DESCRIPTION

[0019] The following combination Figures 1 to 3This application is described in further detail.

[0020] This specific embodiment is merely an explanation of the present application and is not a limitation of the present application. After reading this specification, a person skilled in the art may make non-creative modifications to the present embodiment as needed, but such modifications are protected by the patent law as long as they are within the scope of the present application.

[0021] In order to make the purpose, technical scheme and advantages of the embodiment of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described in conjunction with the drawings in the embodiment of the present application. Obviously, the described embodiment is a part of the embodiment of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application. It should be noted that in the optional embodiments of the present application, the object information and other related data involved, when the embodiments in the present application are applied to specific products or technologies, need to obtain the permission or consent of the object, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions. In other words, if the data related to the object is involved in the embodiment of the present application, it needs to be obtained through the authorization and consent of the object, the authorization and consent of the relevant departments, and in accordance with the relevant laws, regulations and standards of the country and region. If personal information is involved in the embodiment, the acquisition of all personal information needs to obtain the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained, and the embodiment also needs to be implemented with the authorization and consent of the object.

[0022] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0023] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0024] The embodiment of the present application provides a natural gas storage tank leakage alarm system, including: a multimodal sensor network 101, a central processing unit 102 and a remote monitoring alarm platform 103, wherein: the multimodal sensor network 101 can obtain sound wave signals and infrared light signals in real time, and perform multi-signal fusion based on the sound wave signals and the infrared light signals to obtain a fusion signal; the central processing unit 102 can perform gas concentration change trend analysis based on the fusion signal to obtain change trend information, and use the alarm threshold prediction model to perform dynamic threshold analysis on the change trend information to determine the target alarm threshold, wherein the target alarm threshold is used to improve the sensitivity and accuracy of the leakage alarm; the remote monitoring alarm platform 103 is used to predict the gas concentration change based on the fusion signal sent by the multimodal sensor network 101, determine the concentration prediction information, and perform remote monitoring based on the target alarm threshold and the concentration prediction information, and when a leakage risk is detected, an acoustic and visual alarm signal is issued to remind relevant personnel to take countermeasures.

[0025] A natural gas storage tank leak alarm system, such as Figure 1 As shown, the system includes a multimodal sensor network 101, a central processing unit 102 and a remote monitoring alarm platform 103, wherein: The multimodal sensor network 101 is used to obtain the acoustic wave signal and the infrared light signal in real time, and perform multi-signal fusion based on the acoustic wave signal and the infrared light signal to obtain a fusion signal; For the embodiment of the present application, the multimodal sensor network 101 is composed of acoustic wave sensors and infrared sensors deployed at key positions of the storage tank. Both the acoustic wave sensors and infrared sensors should have high precision, high stability and high sensitivity to ensure that they can accurately capture the weak sound waves and infrared radiation changes generated when natural gas leaks. Of course, other types of sensors can also be included, such as temperature sensors, humidity sensors, etc. The embodiment of the present application does not limit the actual sensor types that can be included. There are many ways to build the multimodal sensor network 101, and the embodiment of the present application does not limit it. In one feasible way, the natural gas storage tank information is obtained, and the sensor deployment location analysis is performed based on the natural gas storage tank information to determine multiple deployment nodes; sensor analysis is performed based on each deployment node to determine the sensor information corresponding to each deployment node, wherein the sensor information includes: sensor type and sensor specification; network construction is performed based on the sensor information corresponding to each deployment node to obtain the multimodal sensor network 101.

[0026] If a natural gas leak occurs in a storage tank, acoustic signals and heat exchange will be generated. Therefore, it is possible to determine whether there is a natural gas leak in the storage tank through acoustic signals and infrared light signals. Specifically, the acoustic wave sensor in the multimodal sensor network 101 is used to collect acoustic wave signals in real time. The acoustic wave sensor is usually deployed at key locations around the natural gas storage tank, such as valves, pipeline connections and other leak-prone points, as well as areas where sound wave reflection or enhancement may occur. The acoustic wave signal refers to the mechanical wave signal collected by the natural gas leak or other sound sources. At the same time, the infrared sensor in the multimodal sensor network 101 is used to collect infrared light signals in real time. The infrared sensor is deployed at a suitable location that can cover the natural gas storage tank and its surrounding environment to ensure that possible leaks can be fully monitored. The above-mentioned infrared light signal refers to a light signal in the infrared band.

[0027] The acoustic wave signal and infrared light signal generated during natural gas leakage each have different characteristics, wherein the acoustic wave signal can reflect the acoustic and dynamic characteristics of the leakage, while the infrared light signal can reflect the temperature change caused by the leakage. In order to improve the accuracy of natural gas leakage detection, multi-signal fusion is performed based on the acoustic wave signal and the infrared light signal to obtain a fused signal. Through multi-signal fusion, the advantages of these two signals can be combined to detect leaks from multiple dimensions, thereby improving the accuracy of detection. There are many ways to fuse multiple signals, and the embodiments of the present application are no longer limited. In one feasible method, preprocessing is performed based on the acoustic wave signal and the infrared light signal to obtain a target acoustic wave signal and a target infrared light signal, wherein the preprocessing is used to improve the quality and reliability of the acoustic wave signal and the infrared light signal; acoustic wave feature extraction is performed based on the target acoustic wave signal to obtain an acoustic wave feature, and infrared feature extraction is performed based on the target infrared light signal to obtain an infrared feature; multi-signal fusion is performed based on the acoustic wave feature and the infrared feature to obtain a fused signal.

[0028] The central processing unit 102 is used to receive the fusion signal sent by the multimodal sensor network 101 in real time, and perform gas concentration change trend analysis based on the fusion signal to obtain change trend information; Obtain an alarm threshold prediction model, use the alarm threshold prediction model to perform dynamic threshold analysis on the change trend information, and determine the target alarm threshold, wherein the target alarm threshold is used to improve the sensitivity and accuracy of the leakage alarm; For the embodiment of the present application, the central processing unit 102 is connected to the multimodal sensor network 101 wirelessly so that the central processing unit 102 can receive the fusion signal sent by the multimodal sensor network 101 in real time, and then perform gas concentration change trend analysis based on the fusion signal to obtain change trend information. The implementation process of the gas concentration change trend analysis is as follows: pre-processing operations such as filtering and denoising are performed based on the fused signal to improve the signal-to-noise ratio and reliability of the fused signal. Of course, the pre-processing operation can also include digital filtering, signal enhancement, outlier detection and removal, etc.; then, the target feature related to the gas concentration change trend is extracted from the pre-processed fused signal, and the target feature includes but is not limited to: the frequency, amplitude, phase, change trend and other parameters corresponding to the signal at different times; the mapping relationship between the feature and the natural gas leakage concentration is obtained, and the natural gas leakage concentration data is obtained by analysis and calculation based on the mapping relationship and the target feature; then, the natural gas leakage concentration data is analyzed by using statistical methods or machine learning algorithms to determine the change trend information, wherein the change trend analysis method includes but is not limited to: time series analysis, regression analysis, cluster analysis and other methods, and the change trend information includes but is not limited to: change trend type (for example, rising, falling, stable), concentration change curve, time range, change rate and other information.

[0029] The alarm threshold prediction model is pre-stored in the electronic device. The prediction model is obtained by training the deep learning model using historical alarm data, natural gas leakage data and environmental monitoring data. The deep learning model is trained to learn the mapping relationship between feature variables and alarm thresholds. Then, the calculated change trend information is input into the alarm threshold prediction model to control the alarm threshold prediction model to calculate the dynamic target alarm threshold under the current conditions, that is, the alarm threshold prediction model will appropriately lower the alarm threshold to improve the sensitivity of the warning when the gas concentration rises rapidly; conversely, when the gas concentration remains stable or decreases, the alarm threshold is appropriately increased to reduce the possibility of false alarms. The dynamic alarm threshold adjustment mechanism is adopted to improve the sensitivity to minor signs of leakage, greatly reduce the false alarm rate, and achieve more accurate risk warnings.

[0030] The remote monitoring alarm platform 103 is used to predict the change of gas concentration based on the change trend information sent by the central processing unit 102, determine the concentration prediction information, and perform remote monitoring based on the target alarm threshold and the concentration prediction information. When a leakage risk is detected, an audible and visual alarm signal is issued to remind relevant personnel to take countermeasures.

[0031] For the embodiment of the present application, the remote monitoring alarm platform 103 can be connected to the central processing unit 102 via wireless transmission, and of course, it can also be connected to the multimodal sensor network 101 via wireless transmission. Based on the change trend information sent by the central processing unit 102, the gas concentration change is predicted to determine the concentration prediction information. The gas concentration change prediction is to predict the change of gas concentration in a future period of time based on the change trend information, that is, the gas concentration data in a future period of time. The length of the future period of time can be limited by the user according to the actual situation. Then, remote monitoring is performed based on the target alarm threshold and the concentration prediction information to determine the monitoring result, that is, when the concentration prediction information exceeds the target alarm threshold, it indicates that there is a natural gas leakage risk; otherwise, it indicates that there is no natural gas leakage risk. When it is detected that there is no natural gas leakage risk, no additional operation is performed, and the normal monitoring of the natural gas storage tank can be maintained; when it is detected that there is a leakage risk, an audible and visual alarm signal is issued to remind relevant personnel to take countermeasures. The remote monitoring alarm platform 103 uses the target alarm threshold provided by the dynamic alarm threshold adjustment mechanism to monitor natural gas leakage, which can accurately capture the subtle leakage changes of the storage tank and improve the accuracy of the leakage alarm.

[0032] It can be seen that in the embodiment of the present application, the natural gas storage tank leakage alarm system includes: a multimodal sensor network 101, a central processing unit 102 and a remote monitoring alarm platform 103. The multimodal sensor network 101 is used to obtain acoustic signals and infrared light signals in real time, and to perform multi-signal fusion based on acoustic signals and infrared light signals to obtain fused signals. Through multi-signal fusion, the advantages of these two signals can be combined to detect leaks from multiple dimensions, thereby improving the accuracy of natural gas leak monitoring. The central processing unit 102 is used to perform gas concentration change trend analysis based on the fused signal to obtain change trend information, and to perform dynamic threshold analysis on the change trend information using the alarm threshold prediction model to determine the target alarm threshold, wherein the dynamic alarm threshold adjustment mechanism is adopted to improve the sensitivity to signs of minor leaks, greatly reduce the false alarm rate, achieve more accurate risk warnings, and improve the accuracy of subsequent leak alarms. The remote monitoring alarm platform 103 is used to predict the change of gas concentration based on the change trend information sent by the central processing unit 102, determine the concentration prediction information, and perform remote monitoring based on the target alarm threshold and the concentration prediction information. When a leakage risk is detected, an audible and visual alarm signal is issued to remind relevant personnel to take countermeasures. The remote monitoring alarm platform 103 uses the target alarm threshold provided by the dynamic alarm threshold adjustment mechanism to monitor natural gas leakage, which can accurately capture subtle leakage changes in storage tanks and improve the accuracy of leakage alarms.

[0033] Furthermore, in order to enable comprehensive monitoring of the storage tank, reduce monitoring blind spots, and enable the sensor network to flexibly adapt to different monitoring requirements, in the embodiment of the present application, it also includes: A sensor network building module is used to obtain natural gas storage tank information, analyze sensor deployment locations based on the natural gas storage tank information, and determine multiple deployment nodes; Perform sensor analysis based on each deployment node to determine sensor information corresponding to each deployment node, wherein the sensor information includes: sensor type and sensor specification; The network is constructed based on the sensor information corresponding to each deployed node to obtain a multimodal sensor network 101.

[0034] For the embodiment of the present application, the natural gas storage tank information is obtained, and the natural gas storage tank information includes: storage tank type, storage tank capacity, storage tank size, storage tank material, storage tank setting method and storage tank working environment. In order to improve the comprehensiveness and accuracy of the natural gas storage tank leakage monitoring, the acoustic sensor and the infrared sensor are deployed around the storage tank. In order to obtain the real-time status information of the storage tank more accurately, the sensor deployment position analysis is performed based on the natural gas storage tank information, and multiple deployment nodes are determined. Combined with the structural characteristics of the natural gas storage tank and the location of the potential leakage source, the position analysis operation is performed to ensure that the sensor is deployed at a key position, forming a comprehensive monitoring of the storage tank and reducing the monitoring blind spot. There are many ways to analyze the sensor deployment position. In one feasible way, a three-dimensional model is built based on the natural gas storage tank information to determine the three-dimensional model of the storage tank, and a windless leakage diffusion simulation is performed based on the three-dimensional model of the storage tank to determine the first gas diffusion range; a variable wind environment leakage diffusion simulation is performed based on the three-dimensional model of the storage tank to determine the second gas diffusion range; based on the first gas diffusion range and the second gas diffusion range, the sensor deployment position analysis is performed to determine multiple deployment nodes. When analyzing the above sensor deployment locations, the effects of different altitudes and wind directions on natural gas diffusion were comprehensively considered.

[0035] Then, sensor analysis is performed based on each deployment node to determine the sensor information corresponding to each deployment node, wherein the sensor information includes: sensor type and sensor specification. According to the specific environment and requirements of each deployment node, the corresponding sensor type and specification are selected to ensure that the sensor can collect data accurately and efficiently. In the process of performing sensor analysis, it is preferred to determine which dimensions of data need to be collected at each deployment node, and select the type of sensor corresponding to the dimension. Preferably, for the acoustic wave sensor, it can be deployed at key locations around the storage tank, such as near the inlet and outlet pipelines, valve connections, etc., so as to capture the acoustic wave signal generated during the leak in time; for the infrared sensor, it can be deployed inside the storage tank or near the external position of the storage tank to ensure that the sensor can directly contact the natural gas that may leak. At the same time, the sensor specifications can also be determined based on the detection accuracy, so that the acoustic wave signal and infrared light signal collected by the sensor meet the data accuracy requirements. Finally, the network is established based on the sensor information corresponding to each deployment node to obtain a multimodal sensor network 101, wherein the multimodal sensor network 101 can flexibly adapt to different monitoring needs and can be expanded or adjusted according to actual conditions. That is, the sensor information is classified and encoded first to facilitate subsequent data processing and network management. Then, according to the monitoring needs and sensor distribution, a suitable network topology is selected, such as star, tree, mesh, etc., where the network topology can cover all deployed nodes and realize effective transmission and processing of data; then, according to the sensor information and network topology corresponding to each deployed node, the network nodes are configured to ensure that each node can correctly identify and connect to its adjacent nodes and realize normal data transmission.

[0036] It can be seen that in the embodiment of the present application, in order to more accurately obtain the real-time status information of the storage tank, the sensor deployment location analysis is performed based on the natural gas storage tank information to determine multiple deployment nodes. The sensor deployment location analysis is used to ensure that the sensor is deployed in a key position to form a comprehensive monitoring of the storage tank and reduce the monitoring blind spot. Then, based on each deployment node, the sensor analysis is performed to determine the sensor information corresponding to each deployment node. According to the specific environment and requirements of each deployment node, the corresponding sensor type and specification are selected to ensure that the sensor can collect data accurately and efficiently. Furthermore, based on the sensor information corresponding to each deployment node, the network is established to obtain a multimodal sensor network 101, wherein the multimodal sensor network 101 can flexibly adapt to different monitoring needs and can be expanded or adjusted according to actual conditions.

[0037] Furthermore, in order to determine the optimal sensor deployment node, thereby improving the accuracy and efficiency of monitoring, in the embodiment of the present application, the sensor network building module performs sensor deployment location analysis based on natural gas storage tank information and determines multiple deployment nodes, which is used to: Building a three-dimensional model based on the natural gas storage tank information, determining the three-dimensional model of the storage tank, and performing a windless leakage diffusion simulation based on the three-dimensional model of the storage tank to determine the diffusion range of the first gas; Based on the three-dimensional model of the storage tank, a simulation of leakage and diffusion in a variable wind environment is performed to determine the diffusion range of the second gas; A sensor deployment position analysis is performed based on the first gas diffusion range and the second gas diffusion range to determine a plurality of deployment nodes.

[0038] For the embodiment of the present application, the electronic device pre-stores the natural gas storage tank information, and the natural gas storage tank information includes but is not limited to: storage tank type, storage tank capacity, storage tank size, storage tank shape, storage tank material, storage tank setting method, storage tank working environment, and storage tank component information. Then, based on the storage tank size and storage tank shape in the natural gas storage tank information, a basic geometric shape is created in the three-dimensional model software, such as a cylinder, a sphere, etc., and necessary details and features are added to the basic geometric shape according to the storage tank component information, such as a valve, a pipe, a support structure, an insulation layer, etc. Then, the model is finely adjusted to determine that the geometric shape, size, and proportion of the model are consistent with the actual storage tank, and at the same time, the structure and details of the model are optimized to improve the performance and rendering speed of the model. After that, according to the material and working environment of the storage tank, appropriate materials and textures are applied to the model to enhance the realism and visual effect of the model, and finally, a three-dimensional model of the storage tank is obtained. By constructing a three-dimensional model of the natural gas storage tank information, the shape, size, and material of the storage tank can be accurately simulated, laying the foundation for subsequent leakage and diffusion simulation.

[0039] Then, obtain the storage tank leakage simulation parameters, which are summarized by technicians based on a large number of actual situations and can characterize most storage tank leakage situations. The storage tank leakage simulation parameters include but are not limited to: the size, position, pressure, temperature, etc. of the leakage port. Then, based on the storage tank three-dimensional model and the storage tank leakage simulation parameters, a windless leakage diffusion simulation is performed to determine the first gas diffusion range. The windless leakage diffusion simulation mainly focuses on the natural diffusion process of the leaked gas. For the windless leakage diffusion simulation, a windless simulation scene is established according to the set storage tank leakage simulation parameters, including setting boundary conditions, initial conditions and physical properties of the gas; then, the storage tank three-dimensional model is placed in the windless simulation scene for simulation operation, and the diffusion process of the gas after the storage tank leaks is calculated. After the windless leakage diffusion simulation is completed, the simulation data is extracted, wherein the simulation data includes but is not limited to: concentration distribution map, diffusion speed; finally, based on the range exceeding the preset concentration threshold in the concentration distribution map, it is determined as the boundary of the diffusion range and recorded as the first gas diffusion range, wherein the preset concentration threshold is determined in accordance with relevant safety standards and regulations, and the specific numerical value is no longer limited in the embodiment of this application.

[0040] At the same time, obtain variable wind environment parameters, which include but are not limited to: wind speed, wind direction, turbulence intensity, etc. These parameters should be set based on actual meteorological data or forecast requirements, and the embodiments of this application are no longer limited. Then, based on the three-dimensional model of the storage tank, a variable wind environment leakage diffusion simulation is performed to determine the second gas diffusion range. The variable wind environment leakage diffusion simulation mainly focuses on the gas diffusion process of the leaked gas in a complex wind environment. For the simulation of variable wind environment leakage diffusion, a variable wind environment simulation scene is established according to the set storage tank leakage simulation parameters and variable wind environment parameters, including but not limited to: boundary conditions, initial conditions and wind force changes; then, the three-dimensional model of the storage tank is placed in the variable wind environment simulation scene for simulation operation, and the diffusion process of the gas after the storage tank leaks is calculated. After the simulation of the leakage diffusion of the variable wind environment is completed, the simulation data is extracted, wherein the simulation data includes but is not limited to: concentration distribution diagram, diffusion speed; finally, based on the range exceeding the preset concentration threshold in the concentration distribution diagram, it is determined as the boundary of the diffusion range and recorded as the second gas diffusion range, wherein the preset concentration threshold is determined in accordance with relevant safety standards and regulations, and the specific value is no longer limited in the embodiments of this application. Windless leakage diffusion simulation and variable wind environment leakage diffusion simulation based on the three-dimensional model of the storage tank can more accurately predict the diffusion range and path of natural gas when it leaks. This precise simulation and prediction provides a scientific basis for the analysis of sensor deployment locations, helps to determine the optimal sensor deployment nodes, and thus improves the accuracy and efficiency of monitoring.

[0041] Finally, the sensor deployment position analysis is performed based on the first gas diffusion range and the second gas diffusion range to determine multiple deployment nodes, wherein the sensors deployed at the deployment nodes need to be able to fully cover the first gas diffusion range and the second gas diffusion range, so as to fully monitor the storage tank and reduce the monitoring blind spots. Of course, key areas can also be selected based on the first gas diffusion range and the second gas diffusion range, wherein the key areas are areas with high gas concentrations, boundary areas of the diffusion range, etc., and the key areas are the focus of sensor deployment; then, the deployment positions of the sensors are preliminarily selected within the key areas to ensure that the deployment positions can fully cover the diffusion range and minimize the blind spots, and based on the preliminarily selected deployment positions, the deployment positions are optimized and added in combination with environmental factors and monitoring requirements to ensure that the sensors installed at the optimized multiple deployment nodes can fully cover the first gas diffusion range and the second gas diffusion range.

[0042] It can be seen that in the embodiment of the present application, a three-dimensional model is constructed based on the natural gas storage tank information to determine the three-dimensional model of the storage tank. Then, a windless leakage diffusion simulation is performed based on the three-dimensional model of the storage tank to determine the first gas diffusion range. At the same time, a variable wind environment leakage diffusion simulation is performed based on the three-dimensional model of the storage tank to determine the second gas diffusion range. Finally, the sensor deployment position analysis is performed based on the first gas diffusion range and the second gas diffusion range to determine multiple deployment nodes. Windless leakage diffusion simulation and variable wind environment leakage diffusion simulation based on the three-dimensional model of the storage tank can more accurately predict the diffusion range and path of natural gas during leakage. This precise simulation and prediction provides a scientific basis for the analysis of sensor deployment positions, helps to determine the optimal sensor deployment nodes, and thus improves the accuracy and efficiency of monitoring.

[0043] Furthermore, in order to improve the accuracy of leak point location and provide valuable time and resources for relevant personnel to handle emergencies, in the embodiment of the present application, the remote monitoring alarm platform 103 is also used to: When the concentration prediction information exceeds the target alarm threshold, a picture capture instruction is sent to the visual monitoring terminal to control the visual monitoring terminal to capture real-time pictures including the natural gas storage tank; The abnormal sound source is located based on real-time images and sound wave signals to determine the abnormal sound source, wherein the abnormal sound source provides relevant personnel with the leakage point of the natural gas storage tank.

[0044] For the embodiment of the present application, when the concentration prediction information exceeds the target alarm threshold, it indicates that there is a natural gas leak in the storage tank. In order to facilitate subsequent relevant personnel to deal with the storage tank leakage failure in a timely and rapid manner, the real-time image and sound signal of the storage tank will be combined to locate the abnormal sound source, thereby achieving a more accurate positioning effect, improving the accuracy of positioning, and helping to quickly lock the leakage point, providing valuable time and resources for relevant personnel to deal with the emergency.

[0045] Specifically, when the concentration prediction information exceeds the target alarm threshold, the alarm mechanism is triggered and a picture capture instruction is generated. The picture capture instruction is sent to the visual monitoring terminal through wireless transmission to control the visual monitoring terminal to capture a real-time picture including the natural gas storage tank. The real-time picture should be clear and accurate, and be able to reflect the actual situation of the natural gas storage tank and its surrounding environment. Then, the acoustic signal is analyzed using signal processing technology to extract characteristic information related to natural gas leakage, such as the frequency, amplitude, phase and other parameters of the acoustic signal. Then, the sound source position is calculated based on the arrival time difference and intensity difference of the acoustic signal between different receivers, and the acoustic signal positioning result is integrated with the real-time picture to intuitively display the abnormal sound source position, that is, the abnormal sound source is the leakage point position marked in the real-time picture.

[0046] It can be seen that in the embodiment of the present application, when the concentration prediction information exceeds the target alarm threshold, a picture capture instruction is sent to the visual monitoring terminal to control the visual monitoring terminal to capture a real-time picture including the natural gas storage tank. Then, the abnormal sound source is located based on the real-time picture and the sound wave signal to determine the abnormal sound source. The abnormal sound source is located in combination with the real-time picture and sound signal of the storage tank to achieve a more accurate positioning effect, improve the accuracy of positioning, help to quickly lock the leakage point, and provide valuable time and resources for relevant personnel to deal with emergencies.

[0047] Furthermore, in order to improve the measurement accuracy and stability of the sensor, in the embodiment of the present application, it also includes: An environmental adaptability analysis terminal is used to monitor the storage environment information, perform sensor environment adaptability analysis based on the storage environment information, and determine adaptability analysis results, wherein the adaptability analysis results include: full adaptability, partial adaptability, and non-adaptability; When the adaptability analysis result is partially adapted or unadapted, a sensor calibration instruction is generated, wherein the sensor calibration instruction is used to remind each sensor in the multimodal sensor network 101 to perform adaptive calibration adjustment.

[0048] For the embodiments of the present application, the environment in which the sensor is located will affect the accuracy of the sensor to a certain extent. In order to improve the accuracy of the sensor acquisition signal, the sensor environment adaptability analysis is performed based on the stored environmental information, and the adaptability analysis result is determined so that when the sensor is in a partially adapted or unadapted state, the sensor can be automatically calibrated in time to significantly improve the measurement accuracy and stability of the sensor and extend its service life.

[0049] Specifically, the storage environment information is monitored, and the storage environment information includes but is not limited to: temperature, humidity, air pressure, vibration, electromagnetic interference and chemical properties of the storage environment, and the sensor environment adaptability analysis is performed based on the storage environment information to determine the adaptability analysis result, wherein the adaptability analysis result includes: full adaptability, partial adaptability and inadaptability. For the sensor environment adaptability analysis, the electronic device pre-stores the judgment standard of the sensor environment adaptability, and the judgment standard specifies the temperature range, humidity range, air pressure range, vibration threshold, electromagnetic interference intensity, etc. of different adaptabilities. Therefore, the storage environment information is matched with the judgment standard to determine the adaptability analysis result. When the adaptability analysis result is full adaptability, it indicates that the current environment of the storage tank will not affect the data acquisition accuracy of the sensor, and no additional operation is performed. When the adaptability analysis result is partial adaptability or inadaptability, a sensor calibration instruction is generated, and the sensor calibration instruction is used to adjust the sensor parameters to achieve adaptive calibration adjustment of each sensor in the multimodal sensor network 101.

[0050] It can be seen that in the embodiment of the present application, the sensor environment adaptability analysis is performed based on the stored environment information to determine the adaptability analysis result. Then, when the adaptability analysis result is partially adapted or unadapted, a sensor calibration instruction is generated to automatically calibrate the sensor in time to significantly improve the measurement accuracy and stability of the sensor and extend its service life.

[0051] Furthermore, in order to more comprehensively reflect the state and characteristics of the leakage of the storage tank, thereby improving the accuracy of leakage monitoring, in the embodiment of the present application, the multimodal sensor network 101 performs multi-signal fusion based on the acoustic wave signal and the infrared light signal to obtain the fused signal, and is used to: Preprocessing is performed based on the acoustic wave signal and the infrared light signal to obtain a target acoustic wave signal and a target infrared light signal, wherein the preprocessing is used to improve the quality and reliability of the acoustic wave signal and the infrared light signal; Extracting acoustic wave features based on the target acoustic wave signal to obtain acoustic wave features, and extracting infrared features based on the target infrared light signal to obtain infrared features; Multi-signal fusion is performed based on acoustic wave features and infrared features to obtain a fused signal.

[0052] For the embodiment of the present application, in order to improve the quality and reliability of the acoustic wave signal and the infrared light signal, the acoustic wave signal and the infrared light signal are preprocessed to obtain the target acoustic wave signal and the target infrared light signal, wherein the preprocessing includes but is not limited to: denoising, echo cancellation, endpoint detection, pre-emphasis, denoising, baseline correction, light scattering correction, signal enhancement, signal synchronization and alignment, etc. Then, the target acoustic wave signal is subjected to acoustic wave feature extraction by using signal processing technology and algorithms, such as Fourier transform, wavelet transform, etc., to obtain acoustic wave features, and the acoustic wave features include but are not limited to: the frequency, amplitude, phase, duration and other features of the leaking acoustic wave, and these features can reflect the characteristics and degree of the natural gas leak. At the same time, the target infrared light signal is subjected to feature extraction by using image processing technology and algorithms, such as edge detection, image segmentation, feature extraction, etc., to obtain infrared features, and the infrared features include but are not limited to: the temperature distribution, thermal radiation intensity, temperature gradient and other features of the leaking area, and these features can reflect the characteristics and location of the natural gas leak. Then, the fusion algorithm is used to fuse the acoustic wave features and infrared features to obtain a fused signal. That is, in the operation of multi-signal fusion, the fusion algorithm will comprehensively consider the weight and complementarity of the two feature data to generate a more accurate and reliable fusion signal. Acoustic wave signals and infrared light signals have different physical properties and application scenarios. Fusion of them can make full use of their respective advantages to achieve information complementarity and enhancement. The fused signal obtained has richer information and higher accuracy, and can more comprehensively reflect the state and characteristics of the storage tank leakage, thereby improving the accuracy of leak monitoring.

[0053] It can be seen that in the embodiment of the present application, preprocessing is performed based on the sound wave signal and the infrared light signal to obtain the target sound wave signal and the target infrared light signal, and then the sound wave feature extraction is performed based on the target sound wave signal to obtain the sound wave feature, and the infrared feature extraction is performed based on the target infrared light signal to obtain the infrared feature. Finally, multi-signal fusion is performed based on the sound wave feature and the infrared feature to obtain a fused signal, wherein the fused signal has richer information and higher accuracy, and can more comprehensively reflect the state and characteristics of the storage tank leakage, thereby improving the accuracy of leakage monitoring.

[0054] The above embodiment introduces a natural gas storage tank leakage alarm system from a system perspective, and the following embodiment introduces a natural gas storage tank leakage alarm method from a method flow perspective. Please refer to the following embodiment for details.

[0055] The embodiment of the present application provides a natural gas storage tank leakage alarm method, which is executed by an electronic device, such as Figure 2 As shown, the natural gas storage tank leakage alarm method includes steps S201, S202, S203 and S204, wherein: Step S201: Acquire the acoustic wave signal and the infrared light signal in real time, and perform multi-signal fusion based on the acoustic wave signal and the infrared light signal to obtain a fusion signal; Step S202: Analyze the change trend of gas concentration based on the fusion signal to obtain change trend information; Step S203: obtaining an alarm threshold prediction model, using the alarm threshold prediction model to perform dynamic threshold analysis on the change trend information, and determining a target alarm threshold, wherein the target alarm threshold is used to improve the sensitivity and accuracy of the leakage alarm; Step S204: Predict gas concentration changes based on the change trend information, determine the concentration prediction information, and perform remote monitoring based on the target alarm threshold and the concentration prediction information. When a leakage risk is detected, an audible and visual alarm signal is issued to remind relevant personnel to take countermeasures.

[0056] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the natural gas storage tank leakage alarm method described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0057] An electronic device is provided in an embodiment of the present application, such as Figure 3 As shown, Figure 3 The electronic device 300 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation on the embodiments of the present application.

[0058] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0059] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but it does not mean that there is only one bus or only one type of bus.

[0060] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0061] The memory 303 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the contents shown in the above method embodiment.

[0062] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0063] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0064] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method in any of the above embodiments is implemented.

[0065] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0066] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A natural gas storage tank leakage alarm system, characterized in that: include: Multimodal sensor network, central processing unit and remote monitoring alarm platform, including: A multimodal sensor network, used for acquiring sound wave signals and infrared light signals in real time, and performing multi-signal fusion based on the sound wave signals and the infrared light signals to obtain a fusion signal; A central processing unit, configured to receive the fusion signal sent by the multimodal sensor network in real time, and perform gas concentration change trend analysis based on the fusion signal to obtain change trend information; Acquire an alarm threshold prediction model, and use the alarm threshold prediction model to perform dynamic threshold analysis on the change trend information to determine a target alarm threshold, wherein the target alarm threshold is used to improve the sensitivity and accuracy of the leakage alarm; The remote monitoring and alarm platform is used to predict the change of gas concentration based on the change trend information sent by the central processing unit, determine the concentration prediction information, and perform remote monitoring based on the target alarm threshold and the concentration prediction information. When a leakage risk is detected, an audible and visual alarm signal is issued to remind relevant personnel to take countermeasures.

2. The natural gas storage tank leakage alarm system according to claim 1, characterized in that: Also includes: A sensor network building module, used to obtain natural gas storage tank information, perform sensor deployment location analysis based on the natural gas storage tank information, and determine multiple deployment nodes; Performing sensor analysis based on each of the deployment nodes to determine sensor information corresponding to each of the deployment nodes, wherein the sensor information includes: sensor type and sensor specification; A network is established based on the sensor information corresponding to each of the deployed nodes to obtain a multimodal sensor network.

3. The natural gas storage tank leakage alarm system according to claim 2, characterized in that: When performing the sensor deployment location analysis based on the natural gas storage tank information and determining multiple deployment nodes, the sensor network building module is used to: Building a three-dimensional model based on the natural gas storage tank information to determine the three-dimensional model of the storage tank, and performing a windless leakage diffusion simulation based on the three-dimensional model of the storage tank to determine the first gas diffusion range; Based on the three-dimensional model of the storage tank, a leakage diffusion simulation in a variable wind environment is performed to determine the diffusion range of the second gas; A sensor deployment position analysis is performed based on the first gas diffusion range and the second gas diffusion range to determine a plurality of deployment nodes.

4. The natural gas storage tank leakage alarm system according to claim 1, characterized in that: Remote monitoring and alarm platform is also used for: When the concentration prediction information exceeds the target alarm threshold, a picture capture instruction is sent to the visual monitoring terminal to control the visual monitoring terminal to capture a real-time picture including the natural gas storage tank; The abnormal sound source is located based on the real-time image and the sound wave signal to determine the abnormal sound source, wherein the abnormal sound source provides relevant personnel with the leakage point of the natural gas storage tank.

5. The natural gas storage tank leakage alarm system according to claim 1, characterized in that: Also includes: An environmental adaptability analysis terminal, used to monitor storage environment information, perform sensor environment adaptability analysis based on the storage environment information, and determine adaptability analysis results, wherein the adaptability analysis results include: full adaptability, partial adaptability, and non-adaptability; When the adaptability analysis result is the partial adaptability or the non-adaptability, a sensor calibration instruction is generated, wherein the sensor calibration instruction is used to prompt to perform adaptive calibration adjustment on each sensor in the multimodal sensor network.

6. The natural gas storage tank leakage alarm system according to claim 1, characterized in that: When the multi-signal fusion based on the acoustic wave signal and the infrared light signal is performed to obtain the fused signal, the multi-modal sensor network is used to: Preprocessing is performed based on the acoustic wave signal and the infrared light signal to obtain a target acoustic wave signal and a target infrared light signal, wherein the preprocessing is used to improve the quality and reliability of the acoustic wave signal and the infrared light signal; Extracting acoustic wave features based on the target acoustic wave signal to obtain acoustic wave features, and extracting infrared features based on the target infrared light signal to obtain infrared features; Multi-signal fusion is performed based on the acoustic wave characteristics and the infrared characteristics to obtain a fused signal.

7. A natural gas storage tank leakage alarm method, characterized in that: include: Acquiring an acoustic wave signal and an infrared light signal in real time, and performing multi-signal fusion based on the acoustic wave signal and the infrared light signal to obtain a fused signal; Performing gas concentration change trend analysis based on the fusion signal to obtain change trend information; Acquire an alarm threshold prediction model, and use the alarm threshold prediction model to perform dynamic threshold analysis on the change trend information to determine a target alarm threshold, wherein the target alarm threshold is used to improve the sensitivity and accuracy of the leakage alarm; Based on the change trend information, the gas concentration change is predicted, the concentration prediction information is determined, and remote monitoring is performed based on the target alarm threshold and the concentration prediction information. When a leakage risk is detected, an audible and visual alarm signal is issued to remind relevant personnel to take countermeasures.

8. An electronic device, characterized in that: include: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the natural gas storage tank leakage alarm method according to claim 7.

9. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed in a computer, the computer is caused to execute the natural gas storage tank leakage alarm method as described in claim 7.

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