Earthquake early warning system, method and equipment with harmful gas detection function

Abstract

The invention discloses an earthquake early warning system, method and equipment with a harmful gas detection function. Comprising a gas detection module, and an earthquake early warning module and a controller which are connected with the gas detection module, the earthquake early warning module is used for generating a gas detection instruction based on the earthquake early warning prompt and sending the gas detection instruction to the gas detection module; the gas detection module is used for determining target gas concentration of a detection area based on the gas detection instruction and sending the target gas concentration to the controller, the detection area comprises an indoor designated area and an outdoor designated area, and the target gas concentration comprises radon gas concentration, carbon dioxide concentration and methane concentration; and the controller is used for carrying out harmful gas early warning according to the received target gas concentration. Gas detection can be started in time under triggering of earthquake early warning, and the response speed and initiative of the system are improved. The indoor and outdoor designated areas are detected at the same time, the detection range is expanded, and the detection comprehensiveness and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the field of earthquake detection, and in particular to an earthquake early warning system, method and equipment with a harmful gas detection function. Background Art

[0002] Earthquakes are extremely destructive natural disasters. Although current earthquake research and monitoring methods are constantly developing, there are still many challenges and shortcomings.

[0003] In the field of gas detection, research on underground gas has shown that during the development and occurrence of earthquakes, stress changes in underground rocks may lead to the release and concentration changes of certain gases in the crust, such as radon, carbon dioxide, and methane. However, existing gas detection systems are often limited to a single detection area and cannot fully obtain gas information under different environments. Moreover, the comprehensive detection and analysis of multiple target gases is not perfect, making it difficult to fully utilize the earthquake precursor information contained in gas concentration changes. Summary of the invention

[0004] The present invention provides an earthquake early warning system, method, device and medium with harmful gas detection function, which can obtain earthquake-related information more comprehensively and timely, and improve the effect of earthquake early warning.

[0005] According to one aspect of the present invention, there is provided an earthquake early warning system with a harmful gas detection function, the system comprising: a gas detection module, an earthquake early warning module connected to the gas detection module, and a controller; An earthquake early warning module, used to generate a gas detection instruction based on the earthquake early warning prompt, and send the gas detection instruction to the gas detection module; A gas detection module, used to determine the target gas concentration of the detection area based on the gas detection instruction, and send the target gas concentration to the controller, wherein the detection area includes an indoor designated area and an outdoor designated area, and the target gas concentration includes radon concentration, carbon dioxide concentration and methane concentration; The controller is used to issue a harmful gas warning according to the received target gas concentration.

[0006] Optionally, the controller is used to directly generate a harmful gas warning prompt for early warning when the target gas concentration in a designated indoor area is greater than a corresponding concentration threshold; when the target gas concentration in a designated outdoor area is greater than a corresponding concentration threshold, obtain environmental detection data, and generate a harmful gas warning prompt in combination with the environmental detection data and the target gas concentration for early warning, wherein the environmental detection data includes industrial emissions, soil environmental parameters and groundwater level change data.

[0007] Optionally, the system also includes: an environmental detection module connected to the controller, specifically including: an industrial activity detection unit, a soil detection unit and a groundwater detection unit; the industrial activity detection unit is used to obtain historical industrial activity information within a specified range of the detection area, and determine the industrial emissions based on the historical industrial activity information, and send the industrial emissions to the controller; the soil detection unit is used to obtain soil environmental parameters of the detection area, and send the soil environmental parameters to the controller, wherein the soil environmental parameters include soil type, soil porosity and soil moisture; the groundwater detection unit is used to obtain groundwater level change data in the detection area, and send the groundwater level change data to the controller.

[0008] Optionally, the controller is specifically used to determine the correlation between the target gas concentration and the environmental detection data based on the Pearson correlation coefficient algorithm, and determine the target environmental detection data according to the correlation, and generate a harmful gas warning prompt based on the target environmental detection data; wherein, the correlation between the target gas concentration and the environmental detection data is determined based on the Pearson correlation coefficient algorithm The formula is: , in, Indicates the target gas concentration The mean vector of each component, express Radon concentration at each moment, express The carbon dioxide concentration at the moment, express The methane concentration at the time, Indicates the number of measurements, represents the mean vector of environmental detection data, express Real-time environmental monitoring data.

[0009] Optionally, the system also includes: a user terminal connected to the controller; the controller is also used to send harmful gas warning prompts to the user terminal.

[0010] Optionally, the system also includes: a data storage module connected to the controller and the user terminal; the controller is also used to send the target gas concentration and environmental detection data as storage data to the data storage module for storage; the user terminal is also used to receive data viewing instructions input by the user, and send the data viewing instructions to the data storage module, wherein the data viewing instructions include a target timestamp; the data storage module is used to filter out target data from the stored data based on the target timestamp, and feed the target data back to the user terminal.

[0011] Optionally, the system further includes: a gas prediction module connected to the data storage module; the gas prediction module is used to extract the stored data from the data storage module as training data, and generate a four-element time series based on the training data, and build a gas prediction model according to the four-element time series to predict harmful gases, wherein the model structure of the gas prediction model is set to two layers of long short-term memory network LSTM layers, each layer has 64 neurons, followed by a fully connected layer, the output layer uses an activation function, and the probability value between 0 and 1 output by the output layer is used to predict the probability of harmful gas generation, wherein the structure of the four-element time series is: , in, Represents the target gas concentration feature vector at time t, including the original concentration value, 12-hour moving average, first-order difference value, and second-order difference value of radon, carbon dioxide, and methane at time t. Represents the industrial emission feature vector at time t, with a value of 0 or 1, indicating whether the industrial emission exceeds the threshold at time t. represents the characteristic vector of soil environmental parameters at time t, including soil type, soil porosity, and soil moisture after normalization at time t. Represents the groundwater level at time t.

[0012] According to another aspect of the present invention, there is provided an earthquake early warning method with a harmful gas detection function, the method comprising: Generate a gas detection instruction based on the earthquake warning prompt through the earthquake warning module, and send the gas detection instruction to the gas detection module; Determine the target gas concentration of the detection area based on the gas detection instruction by the gas detection module, and send the target gas concentration to the controller, wherein the detection area includes an indoor designated area and an outdoor designated area, and the target gas concentration includes radon concentration, carbon dioxide concentration and methane concentration; The controller issues a harmful gas warning based on the received target gas concentration.

[0013] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising: 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, and the computer program is executed by the at least one processor so that the at least one processor can execute an earthquake early warning method with harmful gas detection function described in any embodiment of the present invention.

[0014] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement an earthquake early warning method with a harmful gas detection function as described in any embodiment of the present invention when executed.

[0015] The technical solution of the embodiment of the present invention can monitor the concentration change of the target gas in real time through the gas detection module, provide direct basic data for the early warning of harmful gases, cover the detection of multiple gas concentrations such as radon, carbon dioxide and methane, and increase the diversity and comprehensiveness of early warning indicators. The controller considers environmental factors such as industrial emissions, soil environmental parameters and groundwater level changes to more comprehensively evaluate the causes that may lead to the generation of harmful gases.

[0016] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 2 is a schematic diagram of the structure of an earthquake early warning system with a harmful gas detection function provided according to Embodiment 1 of the present invention; Figure 2 is a structural schematic diagram of another earthquake early warning system with a harmful gas detection function provided according to Embodiment 1 of the present invention; Figure 3 is a flow chart of an earthquake early warning method with harmful gas detection function provided according to Embodiment 2 of the present invention; Figure 4 It is a structural schematic diagram of an electronic device for implementing an earthquake early warning method with a harmful gas detection function according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0020] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. Embodiment 1

[0021] Figure 1 A structural schematic diagram of an earthquake early warning system with a harmful gas detection function is provided for the first embodiment of the present invention. The system includes: a gas detection module, an earthquake early warning module connected to the gas detection module, and a controller.

[0022] Optionally, an earthquake early warning module is used to generate a gas detection instruction based on the earthquake early warning prompt, and send the gas detection instruction to the gas detection module; the gas detection module is used to determine the target gas concentration of the detection area based on the gas detection instruction, and send the target gas concentration to the controller, wherein the detection area includes a designated indoor area and a designated outdoor area, and the target gas concentration includes radon concentration, carbon dioxide concentration and methane concentration; the controller is used to issue a harmful gas warning based on the received target gas concentration.

[0023] It should be noted that earthquakes may damage some structures underground or in buildings, causing the leakage of harmful gases such as radon that were originally sealed or stable. At the same time, earthquakes may also affect some storage facilities or geological environments, causing the release or concentration of gases such as carbon dioxide and methane to change. Abnormal changes in the concentration of harmful gases may pose a threat to the safety of people indoors and outdoors, so it is important to detect the concentration of harmful gases during earthquake warnings.

[0024] Among them, the earthquake early warning module plays a role first. When the earthquake monitoring network detects relevant signals of possible earthquakes, such as the initial movement of seismic waves and generates earthquake early warning prompts, the earthquake early warning module will generate gas detection instructions based on this. The gas detection module refers to a module used to detect the concentration of a specific gas. It can identify and quantitatively analyze the target gas in the detection area and transmit the detection results to the controller. The controller is used to receive data from the gas detection module, obtain other environmental data when the gas concentration is abnormal, and perform comprehensive analysis and processing on the data through a specific algorithm or model to determine whether to issue a harmful gas warning. The target gas concentration refers to the content of the specific gas to be detected in the detection area. In this system, it specifically refers to the content values ​​of radon, carbon dioxide and methane in the air. Radon is a radioactive gas. The radon concentration refers to its content in a unit volume of air, usually measured in becquerel per cubic meter (Bq / m³). The carbon dioxide concentration refers to the proportion of carbon dioxide in a unit volume of air, generally measured in units such as percentage or milligrams per cubic meter (mg / m³). Methane concentration refers to the content of methane in unit volume of air, and the unit is usually milligrams per cubic meter (mg / m³) or volume percentage.

[0025] It should be noted that radon is a radioactive rare gas that is widely present in underground rocks and soil. When an earthquake occurs, the crustal rocks are deformed by force, which will cause changes in physical properties such as the porosity of underground rocks. The radon gas originally enclosed in the rock pores will migrate and diffuse to the surface along channels such as cracks, causing the radon gas concentration near the surface to increase. The radon gas sensor in the gas detection module can detect and count alpha particles produced by radon gas decay, thereby determining the radon gas concentration in the detection area. The deformation and stress changes of underground rocks before an earthquake will cause carbon dioxide gas deep underground to be released and migrate to the surface. The carbon dioxide sensor in the gas detection module generally uses the chemical reaction or physical adsorption of carbon dioxide with the material on the surface of the sensor to cause changes in the electrical properties of the sensor, thereby detecting the carbon dioxide concentration. In addition, the underground geological structure changes during the earthquake gestation process, which may cause the decomposition of underground organic matter or the overflow of the originally sealed methane gas. When the methane sensor works in the gas detection module, for example, based on the principle of catalytic combustion, methane burns under the action of the catalyst. The heat generated by the combustion increases the temperature of the sensor, which in turn causes the electrical parameters such as the sensor resistance to change. The methane concentration is determined by detecting this change; or using the semiconductor principle, methane molecules are adsorbed on the surface of the semiconductor sensor, changing its conductivity, thereby determining the methane concentration.

[0026] Optionally, the controller is used to directly generate a harmful gas warning prompt for early warning when the target gas concentration in a designated indoor area is greater than a corresponding concentration threshold; when the target gas concentration in a designated outdoor area is greater than a corresponding concentration threshold, obtain environmental detection data, and generate a harmful gas warning prompt in combination with the environmental detection data and the target gas concentration for early warning, wherein the environmental detection data includes industrial emissions, soil environmental parameters and groundwater level change data.

[0027] Among them, for the designated indoor area, since the space is relatively closed and relatively less disturbed by complex external factors, when the gas detection module detects that the indoor target gas concentration is greater than the preset corresponding concentration threshold, the controller directly generates a harmful gas warning prompt. This is because once the harmful gas in the indoor environment exceeds the standard, the risk of direct exposure to personnel is high and the source of the gas is relatively single, which is mostly related to building materials, poor indoor ventilation or local small leakage sources. Therefore, no more additional data is needed to assist in judgment. Direct warning can quickly notify indoor personnel to take countermeasures, such as turning on ventilation equipment and evacuating dangerous areas. For the designated outdoor area, the situation is more complicated and is affected by the interaction of various natural and human factors. When the outdoor target gas concentration is greater than the threshold, the controller needs to obtain environmental detection data, including industrial emissions, soil environmental parameters and groundwater level change data. Industrial emissions data can reflect the contribution of industrial activities such as surrounding factories to the concentration of harmful gases in the atmosphere. Some industrial production processes will emit a large amount of carbon dioxide, methane and other gases. Soil environmental parameters have an important impact on harmful gases such as radon gas originating from the soil. For example, changes in soil porosity and mineral composition will cause changes in the radon gas release rate. Changes in groundwater levels are also related to the release of harmful gases. Rising water levels may squeeze gases in soil pores and release them, such as methane. The controller will comprehensively analyze these environmental detection data and target gas concentrations to determine whether the excessive concentration of harmful gases is caused by geological changes caused by earthquakes, industrial emissions, or other environmental factors, thereby generating more accurate and targeted harmful gas warnings so that relevant departments or personnel can take corresponding measures such as checking surrounding industrial enterprises and monitoring specific geological areas to effectively respond to the risks brought by abnormal outdoor harmful gas concentrations.

[0028] Figure 2 A schematic diagram of the structure of an earthquake early warning system with a harmful gas detection function is provided for the first embodiment of the present invention. Figure 2 The system also includes: an environmental detection module connected to the controller, specifically including: an industrial activity detection unit, a soil detection unit and a groundwater detection unit, a user terminal, a data storage module and an earthquake prediction module.

[0029] Optionally, the system also includes: an environmental detection module connected to the controller, specifically including: an industrial activity detection unit, a soil detection unit and a groundwater detection unit; the industrial activity detection unit is used to obtain historical industrial activity information within a specified range of the detection area, and determine the industrial emissions based on the historical industrial activity information, and send the industrial emissions to the controller; the soil detection unit is used to obtain soil environmental parameters of the detection area, and send the soil environmental parameters to the controller, wherein the soil environmental parameters include soil type, soil porosity and soil moisture; the groundwater detection unit is used to obtain groundwater level change data in the detection area, and send the groundwater level change data to the controller.

[0030] Among them, environmental monitoring data is relevant data reflecting the environmental conditions around the detection area, providing auxiliary information for judging whether there is an earthquake. Industrial emissions refer to the amount of various pollutants emitted into the atmosphere during industrial production activities, and mainly focus on emissions that affect the concentration of target gases. Soil environmental parameters include soil texture, porosity, water content, temperature and other soil physical properties and pH, nutrient content and other chemical properties related parameters, which will affect the migration and release of gases in the soil. Groundwater level change data refers to the numerical record of the rise or fall of groundwater levels over a certain period of time. Its changes may be related to crustal movement and will also affect the activity of underground gas.

[0031] Specifically, the environmental detection module is used to comprehensively collect various environmental-related data and assist the controller in making early warning judgments on harmful gases. Among them, the industrial activity detection unit will collect historical industrial activity information within the specified range of the detection area through various channels. For example, you can connect to the database of the local environmental protection department to obtain the production records of factories in the area, such as the factory's start-up time, production product types and other basic data. Energy consumption data can also be retrieved, because energy usage is often closely related to industrial production scale and emissions. At the same time, waste gas emission monitoring data reported by enterprises will also be collected. The industrial activity detection unit will determine industrial emissions based on the historical industrial activity information obtained. For example, for some chemical companies, if the process for producing a certain chemical product is known, the theoretical emissions of target gases such as carbon dioxide can be calculated based on the raw material input, chemical reaction equation and production time. Combined with the actual operation data of the company's waste gas treatment equipment, the actual industrial emissions discharged into the atmosphere can be further accurately calculated.

[0032] In a specific embodiment, the soil detection unit can use a variety of soil detection methods to determine the soil type, such as soil texture analysis methods, by collecting soil samples, using mechanical screening and other methods to distinguish the soil particle size composition, such as the proportion of sand particles, silt particles, and clay particles, so as to determine whether it is sand, loam or clay and other different types of soil. Different soil types have different adsorption, storage and migration capabilities for gas. For example, sand has large pores, and gas is relatively easy to migrate in it, while clay has small pores and is more adsorbent to gas. Understanding the soil type helps to analyze the activity state of the target gas in the soil. In addition, the soil detection unit can also use soil porosity measuring instruments, such as the ring knife method, to drive a certain volume of ring knife into the soil to take out the original soil sample, and by measuring the total volume of the soil sample, the volume of solid particles, etc., the porosity calculation formula (porosity = (total volume - solid particle volume) / total volume × 100%) is used to obtain the soil porosity value. Soil porosity directly affects the storage space and migration channels of gas in the soil. A large porosity means that the gas can diffuse more smoothly in the soil, which will also affect the efficiency of underground gas release to the surface. The soil detection unit can use sensors to detect soil moisture. For example, the sensor is inserted into the soil, and the soil moisture is measured by emitting and receiving electromagnetic waves of a specific frequency and based on the changes in the propagation characteristics of the electromagnetic waves.

[0033] In a specific embodiment, the groundwater detection unit can obtain the groundwater level change data in the detection area by installing water level monitoring sensors at different depths underground. The higher the water level, the greater the pressure on the sensor. The water level height can be accurately measured by converting the pressure signal into an electrical signal. By continuously recording the water level values ​​at different time points, the groundwater level change data can be obtained and sent to the controller. Because the rise and fall of the groundwater level is often related to changes in crustal stress, it will also affect the activity of underground gas.

[0034] Optionally, the controller is specifically used to determine the correlation between the target gas concentration and the environmental detection data based on the Pearson correlation coefficient algorithm, and determine the target environmental detection data according to the correlation, and generate a harmful gas warning prompt based on the target environmental detection data; wherein, the correlation between the target gas concentration and the environmental detection data is determined based on the Pearson correlation coefficient algorithm The formula is: , in, Indicates the target gas concentration The mean vector of each component, express Radon concentration at each moment, express The carbon dioxide concentration at the moment, express The methane concentration at the time, Indicates the number of measurements, represents the mean vector of environmental detection data, express Real-time environmental monitoring data.

[0035] It should be noted that the controller needs to compare the change in harmful gas concentration with the time of industrial activity. If the increase in harmful gas concentration coincides with the factory production time and the peak period of exhaust gas emissions, it may be caused by industrial emissions. The controller also needs to study the relationship between harmful gas concentration and soil environmental parameters. If the change in gas concentration is synchronized with the activity of soil microorganisms (reflected by factors such as temperature and humidity), it may be the gas produced by microbial activity. In addition, the controller also needs to analyze the correlation between harmful gas concentration and groundwater level changes. When the water level drops and the harmful gas concentration rises at the same time, and it conforms to the law of dissolved gas release, the drop in groundwater level is considered to be one of the sources of gas.

[0036] Among them, the Pearson correlation coefficient algorithm is a statistical indicator used to measure the degree of linear correlation between two variables, and its value range is between -1 and 1. When the correlation coefficient is 1, it means that the two variables are completely positively correlated; when it is -1, it means that it is completely negatively correlated; and when the coefficient is 0, it indicates that there is no linear correlation between the two variables. In the controller of the earthquake early warning system, the use of the Pearson correlation coefficient algorithm is to explore the linear correlation between the target gas concentration and the environmental detection data. When the controller judges that the target gas concentration is not correlated with the environmental detection data based on the Pearson correlation coefficient value calculated above, it indicates that the abnormal change of the target gas concentration at this time is difficult to explain by conventional environmental factors such as industrial emissions, soil environmental parameters, and groundwater level changes. After excluding the interference of non-earthquake-related environmental factors, it is highly suspected that this abnormal gas concentration is caused by geological activities such as earthquake incubation, so the controller will generate an earthquake early warning prompt and send information to the relevant receiving terminal or early warning platform to remind people in the affected area to prepare for the earthquake.

[0037] Optionally, the system also includes: a user terminal connected to the controller; the controller is also used to send harmful gas warning prompts to the user terminal.

[0038] Among them, the user terminal is used to enable personnel in the detection area and related affected areas to receive harmful gas warning prompt information in a timely manner so as to take corresponding risk avoidance measures. After the communication module built into the user terminal receives the warning prompt data packet sent by the controller, the relevant application in the operating system or the warning function module that comes with the system will parse the data. The text information is extracted and converted into visual prompt content, such as a window with eye-catching text popping up on the screen, which may be accompanied by vibration, sound and other reminder methods, so that users can quickly perceive and pay attention to the warning information. By setting up the user terminal, the harmful gas warning prompt can be effectively conveyed to the relevant personnel, enhancing people's ability to cope with earthquake disasters and protecting life and property safety.

[0039] Optionally, the system also includes: a data storage module connected to the controller and the user terminal; the controller is also used to send the target gas concentration and environmental detection data as storage data to the data storage module for storage; the user terminal is also used to receive data viewing instructions input by the user, and send the data viewing instructions to the data storage module, wherein the data viewing instructions include a target timestamp; the data storage module is used to filter out target data from the stored data based on the target timestamp, and feed the target data back to the user terminal.

[0040] Among them, the data storage module is used to store key data and extract and feedback corresponding data according to requirements, so as to facilitate subsequent viewing and analysis operations. During operation, the controller will continuously monitor the target gas concentration and environmental detection data, and integrate them into storage data in a predetermined format and send them to the data storage module. The data storage module can be a relational database such as MySQL, SQL Server, etc., or a non-relational database MongoDB. The data storage module will classify and store the received storage data according to its key attributes such as data type and time. For example, using the timestamp as an important index, the target gas concentration and environmental detection data collected at the same time are grouped together and stored in the corresponding table or collection of the database in an orderly manner, so as to facilitate subsequent rapid query and screening according to the time dimension. The target timestamp is used to indicate the specific time point or time period corresponding to the data that the user wants to view. The user terminal can send a viewing instruction with a target timestamp to the data storage module. After receiving the data viewing instruction, the data storage module will perform a data screening operation. For example, if a relational database is used, an SQL statement will be written with the target timestamp as the filtering condition to search the corresponding table where the data is stored, find the target data that meets the target timestamp requirement from the stored data, and then package the filtered target data and feed it back to the user terminal, so that the user can view the specific data content of concern on the terminal device, assisting in analyzing earthquake-related situations or understanding the monitoring situation during system operation, etc.

[0041] Optionally, the system further includes: a gas prediction module connected to the data storage module; the gas prediction module is used to extract the stored data from the data storage module as training data, and generate a four-element time series based on the training data, and build a gas prediction model according to the four-element time series to predict harmful gases, wherein the model structure of the gas prediction model is set to two layers of long short-term memory network LSTM layers, each layer has 64 neurons, followed by a fully connected layer, the output layer uses an activation function, and the probability value between 0 and 1 output by the output layer is used to predict the probability of harmful gas generation, wherein the structure of the four-element time series is: , in, Represents the target gas concentration feature vector at time t, including the original concentration value, 12-hour moving average, first-order difference value, and second-order difference value of radon, carbon dioxide, and methane at time t. Represents the industrial emission feature vector at time t, with a value of 0 or 1, indicating whether the industrial emission exceeds the threshold at time t. represents the characteristic vector of soil environmental parameters at time t, including soil type, soil porosity, and soil moisture after normalization at time t. Represents the groundwater level at time t.

[0042] Among them, the controller generates a quaternary time series based on the extracted training data. For the target gas concentration feature vector, the original concentration values ​​of radon, carbon dioxide, and methane at each time t are recorded, which reflects the actual gas content at that time; at the same time, their 12-hour moving average is calculated, which can smooth out short-term fluctuation interference and more clearly present the trend change of gas concentration; the first-order difference value reflects the rate of change of gas concentration at adjacent moments, and the second-order difference value further describes the change of concentration change rate. The industrial emission feature vector can take the value of 0 or 1, which is determined by judging whether the industrial emissions at time t exceed the preset threshold, intuitively reflecting the abnormality of industrial emissions. The soil environmental parameter feature vector includes soil type, soil porosity, and soil moisture after normalization. The normalization operation enables parameters of different magnitudes to participate in subsequent calculations and analysis at the same scale, better reflecting the soil environmental status. The groundwater level height value directly records the water level at the corresponding moment.

[0043] It should be noted that the two-layer long short-term memory network (LSTM) layer is selected to build the model because LSTM has unique advantages in processing time series data, can effectively capture the long-term dependencies in sequence data, and overcome the gradient vanishing or gradient explosion problems that traditional neural networks are prone to when processing longer time series. Each layer is set with 64 neurons. The number of neurons determines the complexity of the network and the ability to learn data features. 64 neurons can fully mine various feature information in the quaternary time series without overfitting. A fully connected layer is connected after the two LSTM layers. The fully connected layer plays the role of integrating the features extracted by the previous LSTM layer, synthesizing the features of different dimensions, and further refining high-level semantic information that is valuable for the prediction of harmful gases. The output layer uses an activation function to convert the output result of the fully connected layer into a probability value between 0 and 1, which represents the probability of harmful gas generation. For example, a probability value close to 1 indicates that according to the current input quaternary time series data features, the probability of generating harmful gases is high; while a probability value close to 0 indicates that the probability of generating harmful gases is low. The output results can intuitively provide quantitative references for harmful gas prediction and assist relevant personnel in making decisions.

[0044] In a specific implementation, the controller gradually inputs the generated quaternion time series data into the constructed gas prediction model. The model calculates the probability of harmful gas generation at the moment corresponding to each input time series based on the learned characteristics and rules. As new time series data is continuously input, the prediction of the probability of harmful gas generation can be continuously updated, thereby achieving dynamic prediction of harmful gas generation in the detection area.

[0045] The technical solution of the embodiment of the present invention can monitor the concentration change of the target gas in real time through the gas detection module, provide direct basic data for the early warning of harmful gases, cover the detection of multiple gas concentrations such as radon, carbon dioxide and methane, and increase the diversity and comprehensiveness of early warning indicators. The controller considers environmental factors such as industrial emissions, soil environmental parameters and groundwater level changes to more comprehensively evaluate the causes that may lead to the generation of harmful gases.

[0046] Embodiment 2

[0047] Figure 3 A flowchart of an earthquake early warning method with harmful gas detection function is provided for the second embodiment of the present invention. This embodiment can be applied to earthquake prediction scenarios. Figure 3 As shown, the method includes: S310. Generate a gas detection instruction based on the earthquake warning prompt through the earthquake warning module, and send the gas detection instruction to the gas detection module.

[0048] S320. Determine the target gas concentration of the detection area based on the gas detection instruction through the gas detection module, and send the target gas concentration to the controller, wherein the detection area includes a designated indoor area and a designated outdoor area, and the target gas concentration includes radon concentration, carbon dioxide concentration and methane concentration.

[0049] S330, issuing a harmful gas warning according to the received target gas concentration through the controller.

[0050] The technical solution of the embodiment of the present invention can monitor the concentration change of the target gas in real time through the gas detection module, provide direct basic data for the early warning of harmful gases, cover the detection of multiple gas concentrations such as radon, carbon dioxide and methane, and increase the diversity and comprehensiveness of early warning indicators. The controller considers environmental factors such as industrial emissions, soil environmental parameters and groundwater level changes to more comprehensively evaluate the causes that may lead to the generation of harmful gases.

[0051] Embodiment 3 Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, 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 assistants, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0052] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0053] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0054] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as an earthquake early warning method with a harmful gas detection function.

[0055] In some embodiments, an earthquake early warning method with a harmful gas detection function may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the earthquake early warning method with a harmful gas detection function described above may be executed. Alternatively, in other embodiments, the processor 11 may be configured to execute an earthquake early warning method with a harmful gas detection function in any other appropriate manner (e.g., by means of firmware).

[0056] Various implementations 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), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0057] Computer programs for implementing 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, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0058] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0059] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0060] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0061] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0062] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0063] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An earthquake early warning system with harmful gas detection function, characterized in that: include: A gas detection module, an earthquake early warning module and a controller connected to the gas detection module; The earthquake early warning module is used to generate a gas detection instruction based on the earthquake early warning prompt, and send the gas detection instruction to the gas detection module; The gas detection module is used to determine the target gas concentration of the detection area based on the gas detection instruction, and send the target gas concentration to the controller, wherein the detection area includes an indoor designated area and an outdoor designated area, and the target gas concentration includes radon concentration, carbon dioxide concentration and methane concentration; The controller is used to issue a harmful gas warning according to the received target gas concentration.

2. The system according to claim 1, characterized in that The controller is used to directly generate a harmful gas warning prompt for warning when the target gas concentration in the designated indoor area is greater than the corresponding concentration threshold; when the target gas concentration in the designated outdoor area is greater than the corresponding concentration threshold, obtain environmental detection data, and generate a harmful gas warning prompt in combination with the environmental detection data and the target gas concentration for warning, wherein the environmental detection data includes industrial emissions, soil environmental parameters and groundwater level change data.

3. The system according to claim 2, characterized in that The system further comprises: an environment detection module connected to the controller, specifically comprising: an industrial activity detection unit, a soil detection unit and a groundwater detection unit; The industrial activity detection unit is used to obtain historical industrial activity information within a specified range of the detection area, determine industrial emissions based on the historical industrial activity information, and send the industrial emissions to the controller; The soil detection unit is used to obtain soil environmental parameters of the detection area and send the soil environmental parameters to the controller, wherein the soil environmental parameters include soil type, soil porosity and soil moisture; The groundwater detection unit is used to obtain groundwater level change data in the detection area and send the groundwater level change data to the controller.

4. The system according to claim 3, characterized in that The controller is specifically used to determine the correlation between the target gas concentration and the environmental detection data based on the Pearson correlation coefficient algorithm, determine the target environmental detection data according to the correlation, and generate a harmful gas warning prompt according to the target environmental detection data; Among them, the correlation between the target gas concentration and the environmental detection data is determined based on the Pearson correlation coefficient algorithm The formula is: ， in, Indicates the target gas concentration The mean vector of each component, express Radon concentration at each moment, express The carbon dioxide concentration at the moment, express The methane concentration at the time, Indicates the number of measurements, represents the mean vector of environmental detection data, express Real-time environmental monitoring data.

5. The system according to claim 2, characterized in that The system further comprises: a user terminal connected to the controller; The controller is also used to send the harmful gas warning prompt to the user terminal.

6. The system according to claim 5, characterized in that The system further comprises: a data storage module connected to the controller and the user terminal; The controller is further used to send the target gas concentration and environmental detection data as storage data to the data storage module for storage; The user terminal is further used to receive a data viewing instruction input by a user, and send the data viewing instruction to the data storage module, wherein the data viewing instruction includes a target timestamp; The data storage module is used to filter out target data from the stored data based on the target timestamp and feed the target data back to the user terminal.

7. The system according to claim 6, characterized in that The system further comprises: a gas prediction module connected to the data storage module; The gas prediction module is used to extract the stored data from the data storage module as training data, and generate a four-element time series based on the training data, and build a gas prediction model according to the four-element time series to predict harmful gases, wherein the model structure of the gas prediction model is set to two layers of long short-term memory network LSTM layers, each layer has 64 neurons, followed by a fully connected layer, the output layer adopts an activation function, and the probability value between 0 and 1 output by the output layer is used to predict the probability of harmful gas generation, wherein the structure of the four-element time series is: ， in, Represents the target gas concentration feature vector at time t, including the original concentration value, 12-hour moving average, first-order difference value, and second-order difference value of radon, carbon dioxide, and methane at time t. Represents the industrial emission feature vector at time t, with a value of 0 or 1, indicating whether the industrial emission exceeds the threshold at time t. represents the characteristic vector of soil environmental parameters at time t, including soil type, soil porosity, and soil moisture after normalization at time t. Represents the groundwater level at time t.

8. An earthquake early warning method with harmful gas detection function, characterized in that: An earthquake early warning system with a harmful gas detection function as described in any one of claims 1 to 7, comprising: Generate a gas detection instruction based on the earthquake warning prompt through the earthquake warning module, and send the gas detection instruction to the gas detection module; Determine the target gas concentration of the detection area based on the gas detection instruction by the gas detection module, and send the target gas concentration to the controller, wherein the detection area includes an indoor designated area and an outdoor designated area, and the target gas concentration includes radon concentration, carbon dioxide concentration and methane concentration; The controller issues a harmful gas warning based on the received target gas concentration.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, wherein the computer program is executed by the at least one processor so as to enable the at least one processor to perform the method of claim 8 .

10. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method described in claim 8 when the instructions are executed.

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