Gas concentration detection compensation method, system, electronic device and storage medium

Abstract

A gas concentration detection compensation method, system, electronic device and storage medium relate to the field of gas concentration measurement technology. The method includes: obtaining the initial gas concentration of the target gas in the target area under the current environment; calculating the atmospheric pressure change rate, wind speed flow direction data and air density gradient in the target area under the current environment; calculating the three-dimensional motion trajectory deviation of the gas molecules in the target area according to the atmospheric pressure change rate and the air density gradient; correcting the three-dimensional motion trajectory deviation in combination with the wind speed flow direction data and the molecular weight of the target gas to obtain a gas concentration spatial distribution compensation value; calibrating the initial gas concentration according to the gas concentration spatial distribution compensation value to obtain the target gas concentration. Implementing the technical solution provided by this application can improve the accuracy of gas concentration detection results.

Description

Technical Field

[0001] The present application relates to the technical field of gas concentration measurement, and in particular to a gas concentration detection compensation method, system, electronic device and storage medium. Background Art

[0002] With the increasing demands for industrial production and environmental protection, accurate gas concentration detection is playing an increasingly important role in industrial safety monitoring and air pollution prevention. Particularly in chemical parks and petrochemical bases, accurately understanding the concentration of target gases in specific areas is crucial for promptly detecting potential leaks and ensuring production safety.

[0003] In existing technologies, gas concentration detection primarily involves sampling and testing by installing multiple detectors fixedly within a target area. These detectors are placed at predetermined, fixed locations and monitor the gas distribution within the area by collecting gas concentration data over a long period of time. However, in actual detection, due to the dynamic nature of the atmospheric environment, the distribution of gas in space is affected by a variety of environmental factors. The combined effect of these environmental factors makes it difficult for gas concentration data collected at fixed locations to accurately reflect the actual gas concentration distribution within the entire area, resulting in low accuracy in gas concentration detection results. Summary of the Invention

[0004] The present application provides a gas concentration detection compensation method, system, electronic device and storage medium, which can improve the accuracy of gas concentration detection results.

[0005] In a first aspect, the present application provides a gas concentration detection compensation method, the method comprising:

[0006] Obtain the initial gas concentration of the target gas in the target area under the current environment;

[0007] Calculate the atmospheric pressure change rate, wind speed and direction data, and air density gradient within the target area under the current environment;

[0008] Calculating the three-dimensional motion trajectory deviation of the gas molecules in the target area according to the atmospheric pressure change rate and the air density gradient;

[0009] Combining the wind speed and direction data and the molecular weight of the target gas to correct the three-dimensional motion trajectory deviation, and obtain a gas concentration spatial distribution compensation value;

[0010] The initial gas concentration is calibrated according to the gas concentration spatial distribution compensation value to obtain a target gas concentration.

[0011] By adopting the above technical solution, the initial gas concentration of the target gas in the target area is obtained as basic data, and environmental parameters such as the atmospheric pressure change rate, wind speed and direction data, and air density gradient in the target area under the current environment are calculated at the same time to fully grasp the key environmental factors affecting gas distribution; secondly, the three-dimensional motion trajectory deviation of the gas molecules in the target area is calculated based on the obtained atmospheric pressure change rate and air density gradient, thereby accurately reflecting the degree of influence of environmental factors on the motion trajectory of gas molecules; thirdly, the three-dimensional motion trajectory deviation is corrected by combining the wind speed and direction data with the molecular weight characteristics of the target gas, and a gas concentration spatial distribution compensation value that can reflect the motion characteristics of gas molecules in the actual environment is obtained; finally, the initial gas concentration is calibrated using this compensation value to obtain a target gas concentration that accurately reflects the actual gas distribution in the target area. By considering the comprehensive influence of multiple environmental factors on the motion of gas molecules, a dynamic compensation mechanism for gas concentration is established, which avoids the technical problem that traditional fixed-point detection methods are difficult to cope with dynamic changes in the environment, and significantly improves the accuracy of gas concentration detection results.

[0012] In a second aspect of the present application, a gas concentration detection and compensation system is provided, the system comprising:

[0013] An initial concentration acquisition module is used to obtain the initial gas concentration of the target gas in the target area under the current environment;

[0014] An environmental parameter calculation module is used to calculate the atmospheric pressure change rate, wind speed and direction data, and air density gradient within the target area under the current environment;

[0015] a trajectory deviation calculation module, configured to calculate the three-dimensional motion trajectory deviation of the gas molecules in the target area according to the atmospheric pressure change rate and the air density gradient;

[0016] a compensation value determination module, configured to correct the three-dimensional motion trajectory deviation based on the wind speed and direction data and the molecular weight of the target gas to obtain a compensation value for the spatial distribution of gas concentration;

[0017] The compensation calibration module is used to calibrate the initial gas concentration according to the gas concentration spatial distribution compensation value to obtain the target gas concentration.

[0018] In a third aspect of the present application, a computer storage medium is provided. The computer storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the above method steps.

[0019] In a fourth aspect of the present application, an electronic device is provided, comprising: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the above-mentioned method steps.

[0020] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0021] This application obtains the initial gas concentration of the target gas in the target area as basic data, and at the same time calculates environmental parameters such as the atmospheric pressure change rate, wind speed flow direction data and air density gradient in the target area under the current environment, so as to fully grasp the key environmental factors affecting gas distribution; secondly, the three-dimensional motion trajectory deviation of the gas molecules in the target area is calculated based on the obtained atmospheric pressure change rate and air density gradient, so as to accurately reflect the degree of influence of environmental factors on the motion trajectory of gas molecules; thirdly, the three-dimensional motion trajectory deviation is corrected by combining the wind speed flow direction data with the molecular weight characteristics of the target gas, and a gas concentration spatial distribution compensation value that can reflect the motion characteristics of gas molecules in the actual environment is obtained; finally, the initial gas concentration is calibrated using the compensation value to obtain a target gas concentration that accurately reflects the actual gas distribution in the target area. By considering the comprehensive influence of multiple environmental factors on the motion of gas molecules, a dynamic compensation mechanism for gas concentration is established, which avoids the technical problem that the traditional fixed-point detection method is difficult to cope with dynamic changes in the environment, and significantly improves the accuracy of gas concentration detection results. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of a gas concentration detection and compensation method provided in an embodiment of the present application;

[0023] Figure 2 This is a module diagram of a gas concentration detection and compensation system provided in an embodiment of the present application;

[0024] Figure 3 This is a structural diagram of an electronic device provided in an embodiment of the present application.

[0025] Description of reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0027] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "for example" or "for instance" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "for example" or "for instance" is intended to present the relevant concepts in a concrete manner.

[0028] In the description of the embodiments of the present application, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0029] The following will provide a clear and complete description of the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments.

[0030] Please refer to Figure 1 , a flow chart of a gas concentration detection and compensation method is proposed. The method can be implemented by a computer program, a single-chip microcomputer, or run on a gas concentration detection and compensation system. The computer program can be integrated into a computer device or run as an independent tool application. Specifically, the method includes steps 10 to 50, which are as follows:

[0031] Step 10: Obtain the initial gas concentration of the target gas in the target area under the current environment.

[0032] In the present embodiment, the target area refers to the open space where gas concentration detection is required. Although the detection boundary is defined from the perspective of management and monitoring, the target area is not a closed space in physical space. Instead, it is an area that exchanges matter and energy with the external atmosphere. The airflow within the area is affected by both the external atmosphere and the disturbance of physical obstacles such as buildings and equipment within the area.

[0033] Target gas refers to the specific gas components that need to be monitored in the target area. It can be flammable and explosive gases (such as methane, propane, etc.), toxic and harmful gases (such as hydrogen sulfide, ammonia, etc.) or other industrial gases that require concentration monitoring. These gases are usually closely related to production activities in the area, and their concentration changes directly affect production safety.

[0034] Initial gas concentration refers to the raw concentration data of the target gas collected by existing detection equipment within the target area before concentration compensation calculations are performed. This data reflects the gas concentration value directly measured by the detection equipment without considering the influence of environmental factors.

[0035] Specifically, due to the spatial inhomogeneity of gas distribution within the target area and the fact that gas concentration fluctuates with environmental changes, it is necessary to first obtain the initial gas concentration of the target gas in the target area under the current environment as the basis for subsequent compensation calculations. In specific implementation, a fixed gas concentration detector network can be arranged within the target area. The detector network includes multiple gas concentration detection units, each equipped with a temperature sensor, a pressure sensor, and a gas concentration sensor. The gas concentration detection units are evenly arranged at a grid spacing of 10 meters by 10 meters and are located vertically at heights of 1 meter, 3 meters, and 5 meters above the ground. Each detection unit collects data every minute and transmits the collected temperature, pressure, and gas concentration data to the data processing unit in real time via the industrial bus. The data processing unit performs spatial interpolation calculations on the gas concentration data collected by different detection units at the same time to generate a three-dimensional gas concentration distribution field within the target area, thereby obtaining the initial gas concentration of the target gas under the current environment.

[0036] In another feasible embodiment, gas concentration sampling can be performed using mobile detection equipment that can patrol and sample along a pre-set path. Alternatively, an aerial drone equipped with a miniature gas concentration detector can be used to sample along a spiral trajectory. The mobile detection equipment and the aerial drone can operate synchronously, respectively responsible for sampling low-altitude and high-altitude gas concentrations within the target area.

[0037] Step 20: Calculate the atmospheric pressure change rate, wind speed direction data and air density gradient in the target area under the current environment.

[0038] In the embodiment of the present application, the atmospheric pressure change rate refers to the change in atmospheric pressure per unit time and per unit spatial distance in the target area, and is used to characterize the spatial distribution change characteristics of the atmospheric pressure in the area.

[0039] Wind speed and direction data refers to the speed, magnitude and direction of airflow in the target area.

[0040] Air density gradient refers to the spatial rate of change of air density in the target area, which indicates the change in air density per unit distance.

[0041] Specifically, because the movement of gas molecules within the target area is affected by environmental factors such as atmospheric pressure, wind speed, and air density, it is necessary to calculate these environmental parameters to provide a basis for subsequent analysis of gas trajectory. In specific implementation, detection points are evenly distributed within the target area along a pre-set spiral path. Each detection point is equipped with a pressure sensor, an ultrasonic anemometer, and a temperature and humidity sensor. First, tangentially adjacent detection points and radially adjacent detection points along the spiral path are identified and the environmental parameters of each detection point are collected. The horizontal atmospheric pressure change rate is then calculated based on the pressure difference between tangentially adjacent detection points, and the vertical atmospheric pressure change rate is calculated based on the pressure difference between radially adjacent detection points. The ultrasonic anemometer is used to obtain the three-dimensional wind speed components and wind direction angles at each detection point to construct a wind speed and flow data field for the target area. Furthermore, the air density at each detection point is calculated using the temperature and humidity data, and the air density gradient is calculated based on the air density difference between adjacent detection points. This solution, through a spirally distributed detection network, comprehensively captures the spatial distribution characteristics of environmental parameters within the target area.

[0042] Based on the above embodiment, as another optional embodiment, the step of calculating the atmospheric pressure change rate, wind speed and direction data, and air density gradient in the target area under the current environment may further include the following steps:

[0043] Step 201: Collect environmental parameters of each detection point in the current environment, and each detection point is evenly set on a preset spiral ascending path.

[0044] Specifically, to obtain the three-dimensional distribution characteristics of environmental parameters within the target area, it is necessary to collect environmental parameters at each detection point within the current environment. First, a spiral ascending sampling path is designed, starting from the center of the target area, with a spiral radius of 15 meters, a pitch of 2.5 meters, and a maximum sampling height of 20 meters. Testing points are evenly spaced every 3 meters along this spiral path, each equipped with an environmental parameter collection device. This device includes a high-precision digital pressure sensor (accuracy of ±0.1 kPa), a three-dimensional ultrasonic anemometer (accuracy of ±0.1 m / s), a temperature sensor (accuracy of ±0.1°C), and a humidity sensor (accuracy of ±2% RH). The sampling frequency of each sensor is set to 10 Hz, and the collected data is transmitted in real time to the central control system via an industrial-grade data acquisition module. Furthermore, each detection point is equipped with a GPS positioning module to record its precise spatial coordinates. This layout ensures the acquisition of continuous environmental parameter data within the target area, from the ground to high altitude.

[0045] Step 202: Determine the tangentially adjacent detection points and the radially adjacent detection points of the spiral ascending path.

[0046] Specifically, to calculate the spatial gradient of environmental parameters, it is necessary to determine the tangentially adjacent and radially adjacent detection points along the spiral path. First, the spatial coordinates of the detection points are converted to a cylindrical coordinate system (r, θ, z), where r represents radial distance, θ represents azimuth, and z represents altitude. For any detection point P(r, θ, z), its tangentially adjacent detection points are defined as two detection points on the same spiral level with an azimuth difference of Δθ = 30°: P1(r, θ - 30°, z) and P2(r, θ + 30°, z). Radially adjacent detection points are defined as two detection points on adjacent spiral levels with the same azimuth and an altitude difference of one spiral pitch: P3(r - Δr, θ, z - 2.5) and P4(r + Δr, θ, z + 2.5), where Δr is the radius difference between adjacent spiral turns. A topological database of detection points is established through a central control system, which records and updates the neighboring point information of each detection point in real time.

[0047] Step 203: Calculate the atmospheric pressure change rate, wind speed direction data and air density gradient in the target area based on the environmental parameters of the tangentially adjacent detection points and the radially adjacent detection points.

[0048] Specifically, in order to fully describe the distribution characteristics of environmental parameters in the target area, it is necessary to calculate the components of each environmental parameter in different directions. Specifically, the calculation needs to be performed based on the determined tangentially adjacent detection points and radially adjacent detection points in the following way:

[0049] First, calculate the two components of the atmospheric pressure change rate: the horizontal pressure change rate ΔPh and the vertical pressure change rate ΔPv. The horizontal pressure change rate is calculated using the pressure values ​​of the tangentially adjacent detection points: ΔPh = (P2-P1) / (2R·Δθ), where P2 and P1 are the pressure values ​​of the tangentially adjacent points, R is the current spiral radius, and Δθ is the angular difference between the adjacent points. The vertical pressure change rate is calculated using the radially adjacent detection points: ΔPv = (P4-P3) / Δz, where P4 and P3 are the pressure values ​​of the radially adjacent points, and Δz is the pitch value of 2.5 meters.

[0050] Next, the three components of wind speed and direction data, along with the wind direction angle, are obtained. A three-dimensional ultrasonic anemometer directly measures the horizontal x-axis wind speed component Vx, the y-axis wind speed component Vy, and the vertical z-axis wind speed component Vz. The wind direction angle α is calculated using the inverse tangent function: α = arctan(Vy / Vx). When Vx is zero, α = 90° or 270°. The rate of change of each wind speed component is calculated by taking the wind speed difference between adjacent measurement points to determine the spatial distribution of wind speed.

[0051] Finally, the two components of the air density gradient are calculated: the horizontal density gradient Δρh and the vertical density gradient Δρv. First, the air density is calculated using the temperature T and pressure P at each detection point: ρ = P / (R·T), where R is the gas constant. The horizontal density gradient is then calculated based on the tangentially adjacent detection points: Δρh = (ρ2-ρ1) / (2R·Δθ), where ρ2 and ρ1 are the air densities at the tangentially adjacent points. The vertical density gradient is calculated based on the radially adjacent detection points: Δρv = (ρ4-ρ3) / Δz, where ρ4 and ρ3 are the air densities at the radially adjacent points.

[0052] The environmental parameter components obtained through these calculations can fully characterize the spatial distribution characteristics of environmental parameters within the target area. The calculation results of these discrete points are extended to the entire target area using a three-dimensional spline interpolation algorithm to obtain a continuous environmental parameter distribution field, providing accurate input data for subsequent analysis of gas motion trajectories.

[0053] Step 30: Calculate the three-dimensional motion trajectory deviation of the gas molecules in the target area according to the atmospheric pressure change rate and the air density gradient.

[0054] In the embodiment of the present application, the three-dimensional motion trajectory deviation refers to the spatial displacement of the target gas molecules from the ideal diffusion path under the influence of current environmental factors.

[0055] Specifically, because gas molecules can deviate from the ideal diffusion path due to environmental factors, it is necessary to calculate the three-dimensional motion trajectory deviation of gas molecules in the target area. In specific implementation, the first displacement component of the gas molecules in the horizontal plane is calculated based on the horizontal pressure change rate ΔPh. The horizontal motion acceleration is obtained using the pressure gradient force formula: Fp=-(1 / ρ)·ΔPh, and the horizontal displacement within the time Δt is calculated. The second displacement component of the gas molecules in the vertical direction is then calculated based on the vertical density gradient Δρv. Considering the buoyancy effect Fb=g·(ρ-ρg), the vertical motion acceleration and displacement are calculated. The two displacement components are converted into radial and angular components in the spherical coordinate system, and the diffusion radius deviation and deflection angle are calculated as the motion trajectory characteristic parameters. Finally, based on these characteristic parameters, the actual position deviation vector of the gas molecules in three-dimensional space is determined to obtain the three-dimensional motion trajectory deviation. This solution achieves an accurate description of the motion trajectory of gas molecules through mechanical analysis.

[0056] Based on the above embodiment, as an optional embodiment, the step of calculating the three-dimensional motion trajectory deviation of gas molecules in the target area according to the atmospheric pressure change rate and the air density gradient may further include the following steps:

[0057] Step 301: Calculate the first displacement component of the gas molecules in the horizontal plane based on the atmospheric pressure change rate.

[0058] Specifically, in order to obtain the motion characteristics of gas molecules in the horizontal plane, it is necessary to calculate the first displacement component based on the atmospheric pressure change rate. First, the horizontal pressure change rate ΔPh in the target area is obtained. According to the principles of gas dynamics, the pressure gradient force Fp=-(1 / ρ)·ΔPh per unit volume of gas molecules is calculated, where ρ is the local air density. Under the action of the pressure gradient force, the horizontal acceleration of the gas molecules is ah=Fp / m, where m is the mass of the gas molecules. Setting the time interval Δt=0.1 seconds, the horizontal displacement of the gas molecules is Δx=ah·(Δt)² / 2. This displacement is decomposed into the xy plane, Δx=ΔS·cosθ and Δy=ΔS·sinθ, where θ is the angle between the direction of the pressure gradient force and the x-axis, and ΔS is the modulus of the horizontal displacement. Finally, the first displacement component vector_h=(Δx,Δy) of the gas molecules in the horizontal plane is obtained. This calculation method takes into account the driving effect of the pressure gradient on gas motion and can accurately describe the motion characteristics of gas molecules in the horizontal plane.

[0059] Step 302: Calculate the second displacement component of the gas molecules in the vertical direction according to the air density gradient.

[0060] Specifically, in order to obtain the motion characteristics of gas molecules in the vertical direction, it is necessary to calculate the second displacement component based on the air density gradient. First, obtain the vertical density gradient Δρv, and calculate the buoyancy Fb=g·(ρ-ρg) on ​​the gas molecules per unit volume, where g is the acceleration of gravity and ρg is the density of the gas molecules. Considering the combined effect of gravity and buoyancy, the resultant force of the gas molecules in the vertical direction is F=Fb-mg. Based on this, the vertical acceleration av=F / m is calculated. Setting the same time interval Δt=0.1 seconds, the displacement of the gas molecules in the vertical direction is Δz=av·(Δt)² / 2. This displacement is the second displacement component of the gas molecules in the vertical direction, vector_v=(0,0,Δz). This calculation method comprehensively considers the effects of buoyancy and gravity, and can accurately describe the motion characteristics of gas molecules in the vertical direction.

[0061] Step 303: Calculate the motion trajectory characteristic parameters of the gas molecules based on the first displacement component and the second displacement component.

[0062] Specifically, the first displacement component in the horizontal plane and the second displacement component in the vertical direction are converted to a spherical coordinate system, and the modulus R of the resultant displacement vector is calculated, along with the azimuth angle α = arctan(Δy / Δx) and the elevation angle β = arcsin(Δz / R). Based on these parameters, the diffusion radius deviation ΔR = R·cosβ is calculated, representing the horizontal distance the gas molecule deviates from its initial position. The trajectory deflection angle γ = arctan(Δz / ΔR) is also calculated, representing the angle between the motion trajectory and the horizontal plane. ΔR and γ are used as characteristic parameters to describe the motion trajectory of the gas molecules.

[0063] Step 304: Determine the three-dimensional motion trajectory deviation of the gas molecules based on the motion trajectory characteristic parameters.

[0064] Specifically, a local coordinate system is first constructed, with the gas molecule's initial position as the origin, establishing a right-handed rectangular coordinate system. Based on the diffusion radius deviation ΔR and the trajectory deflection angle γ, the position coordinates of the gas molecule in the new coordinate system are calculated: x' = ΔR·cosα, y' = ΔR·sinα, z' = ΔR·tanγ. The position coordinates in the local coordinate system are then transformed to the global coordinate system using a coordinate transformation matrix, resulting in the three-dimensional trajectory deviation vector D = (Dx, Dy, Dz) of the gas molecule. The direction of this vector indicates the actual direction of motion of the gas molecule, and the modulus represents the distance from the ideal diffusion path.

[0065] Based on the above embodiment, as another optional embodiment, the step of calculating the motion trajectory characteristic parameters of the gas molecules based on the first displacement component and the second displacement component may further include the following steps:

[0066] Step 3031: Convert the first displacement component and the second displacement component into radial components and angular components in the spherical coordinate system.

[0067] Specifically, in order to uniformly describe the spatial motion characteristics of gas molecules, it is necessary to convert the first displacement component and the second displacement component into radial and angular components in the spherical coordinate system. In specific implementation, first establish a spherical coordinate system (r, θ, φ), where r represents the radial distance, θ represents the azimuth angle, and φ represents the zenith angle. Substitute the first displacement component (Δx, Δy) in the horizontal plane and the second displacement component Δz in the vertical direction into the coordinate conversion equation: , azimuth angle θ = arctan (Δy / Δx), zenith angle φ = arccos (Δz / r). Then the radial component r is decomposed into the tangential component r on the spherical surface t = r·sinφ and the normal component r n = r·cosφ, and finally we get the radial component D in the spherical coordinate system. r =r n and the angular component D θ =rt .

[0068] Step 3032: Calculate the diffusion radius deviation of the gas molecules based on the radial component.

[0069] Specifically, in order to quantify the degree to which the gas molecules deviate from their initial positions, it is necessary to calculate the diffusion radius deviation of the gas molecules based on the radial component. First, obtain the radial component D in the spherical coordinate system. r , considering the radial displacement characteristics of gas molecules when they diffuse in space, the radial component D r Projected onto the horizontal plane, the diffusion radius deviation ΔR=D is obtained r cosθ, where θ is the azimuth angle. When gas molecules diffuse outward, ΔR is positive; when they contract inward, ΔR is negative. This calculation method accurately reflects the changes in the diffusion range of gas molecules in the horizontal plane.

[0070] Step 3033: Calculate the deflection angle of the gas molecule motion trajectory based on the angular component.

[0071] Specifically, in order to describe the change in the direction of gas molecule motion, it is necessary to calculate the deflection angle of the gas molecule motion trajectory based on the angular component. Obtain the angular component D in the spherical coordinate system θ , combined with the radial component D r , calculate the deflection angle β=arctan(D θ / D r This angle represents the angle between the actual trajectory of the gas molecules and the radial direction. A positive β value indicates a counterclockwise deflection, while a negative value indicates a clockwise deflection. This calculation method can quantitatively describe the degree of deviation in the direction of gas molecule motion.

[0072] Step 3034: Use the diffusion radius deviation and the deflection angle as motion trajectory characteristic parameters.

[0073] Specifically, to fully characterize the motion characteristics of gas molecules, the diffusion radius deviation and deflection angle are used as motion trajectory characteristic parameters. The calculated diffusion radius deviation ΔR and deflection angle β are combined into a binary characteristic parameter group (ΔR, β). ΔR, measured in meters, describes the radial distance the gas molecule deviates from its initial position; β, measured in radians, describes the degree of deflection in the motion trajectory. These two parameters are stored in a motion characteristic database, and an index structure is established to facilitate subsequent queries and calculations. This characteristic parameter group can uniquely determine the motion characteristics of gas molecules in space.

[0074] Step 40: Correct the three-dimensional motion trajectory deviation by combining the wind speed and direction data and the molecular weight of the target gas to obtain a compensation value for the spatial distribution of gas concentration.

[0075] In the embodiments of this application, the gas concentration spatial distribution compensation value refers to the value used to correct the ideal diffusion concentration distribution based on the deviation of the three-dimensional motion trajectory of gas molecules. The compensation value can be divided into a radial compensation component (compensating for concentration deviation in the horizontal direction) and a height compensation component (compensating for concentration deviation in the vertical direction). Its magnitude is directly related to the direction and magnitude of the three-dimensional motion trajectory deviation. By superimposing the compensation value on the ideal diffusion concentration, a gas concentration spatial distribution that is closer to the actual situation can be obtained.

[0076] Specifically, since wind speed and target gas molecular weight will affect the actual motion trajectory of gas molecules, it is necessary to correct the three-dimensional motion trajectory deviation to obtain an accurate gas concentration spatial distribution compensation value. Obtain the three-dimensional wind speed components (Vx, Vy, Vz) and target gas molecular weight M in the target area. For the three-dimensional motion trajectory deviation vector D = (Dx, Dy, Dz), calculate the wind speed influence coefficient , where V0 is the reference wind speed 1m / s; calculate the relative mass coefficient , where M0 is the average molecular weight of air, 29 g / mol. Multiplying the two influence coefficients by the deviation vector yields the corrected displacement vector D' = D·kv·km. Finally, based on this corrected displacement vector, the spatial distribution compensation value for gas concentration, ΔC = C0·(1-|D'| / R0), is calculated, where C0 is the ideal diffusion concentration and R0 is the reference distance. This scheme improves the accuracy of concentration distribution prediction by accounting for the effects of wind speed and molecular weight.

[0077] Based on the above embodiment, as another optional embodiment, the step of correcting the three-dimensional motion trajectory deviation by combining wind speed and direction data and the molecular weight of the target gas to obtain the gas concentration spatial distribution compensation value may further include the following steps:

[0078] Step 401: Obtain wind speed and wind direction angle from wind speed and direction data.

[0079] Specifically, in order to determine the impact of airflow on the movement of gas molecules, it is necessary to obtain the wind speed and wind direction angle in the wind speed and direction data. First, obtain the x-direction wind speed component Vx and the y-direction wind speed component Vy in the horizontal plane, as well as the vertical z-axis wind speed component Vz from the three-dimensional ultrasonic anemometer. Calculate the synthetic wind speed , with units of meters per second. The wind direction angle α = arctan(Vy / Vx) is then calculated. When Vx is zero, if Vy > 0, α = 90°; if Vy < 0, α = 270°. The wind speed elevation angle β = arcsin(Vz / V) is also calculated to characterize the vertical motion characteristics of the airflow.

[0080] Step 402: Calculate the relative mass coefficient of the gas molecules according to the ratio of the molecular weight of the target gas to the molecular weight of standard atmosphere.

[0081] Specifically, in order to characterize the motion characteristics of the target gas molecules in the air, it is necessary to calculate the relative mass coefficient of the gas molecules based on the ratio of the molecular weight of the target gas to the molecular weight of the standard atmosphere. Obtain the molecular weight M of the target gas and the average molecular weight M0 of the standard atmosphere (taken as 29g / mol). Calculate the relative mass coefficient This coefficient reflects the mass difference between the target gas molecules and the air molecules. When km > 1, it means that the target gas molecules are more massive than air molecules; when km < 1, it means that the target gas molecules are less massive than air molecules. The calculation of this coefficient takes into account the effect of molecular weight on the motion characteristics of the gas.

[0082] Step 403: Calculate the airflow force on the gas molecules based on the relative mass coefficient and the wind speed.

[0083] Specifically, to accurately describe the effect of airflow on the motion of gas molecules, it is necessary to calculate the airflow force acting on the gas molecules based on the relative mass coefficient and wind speed. According to the principles of aerodynamics, the airflow force acting on the gas molecules is calculated as F=1 / 2·ρ·Cd·A·V²·km, where ρ is the air density, Cd is the drag coefficient (taken as 0.47), A is the effective cross-sectional area of ​​the gas molecules, V is the resultant wind speed, and km is the relative mass coefficient. The airflow force is decomposed into a horizontal component, Fh=F·cosβ, and a vertical component, Fv=F·sinβ, where β is the wind speed elevation angle. This calculation method considers the combined effects of gas molecule properties and wind field characteristics.

[0084] Step 404: Calculate the displacement correction coefficients of the gas molecules in the horizontal and vertical directions according to the airflow force.

[0085] Specifically, to quantify the impact of airflow on gas trajectory, it's necessary to calculate correction coefficients for the horizontal and vertical displacements of gas molecules based on the airflow force. Based on the horizontal airflow force Fh, the horizontal displacement correction coefficient kh = Fh·Δt² / (2m·d0) is calculated, where Δt is the characteristic time (1 second), m is the gas molecular mass, and d0 is the reference displacement (1 meter). Similarly, based on the vertical airflow force Fv, the vertical displacement correction coefficient kv = Fv·Δt² / (2m·d0) is calculated. These correction coefficients reflect the proportional change in displacement caused by the airflow.

[0086] Step 405: Correct the three-dimensional motion trajectory deviation based on the horizontal and vertical displacement correction coefficients to obtain a gas concentration spatial distribution compensation value.

[0087] Specifically, a frequency domain analysis method is used to correct three-dimensional motion trajectory deviations. First, the three-dimensional motion trajectory deviation D(x, y, z) is converted into a frequency domain representation D(fx, fy, fz) using a three-dimensional fast Fourier transform (3D-FFT). This transform decomposes complex spatial motion characteristics into simple harmonic components of different frequencies. In the frequency domain, the trajectory deviation is decomposed into a horizontal component Dh(fx, fy) and a vertical component Dv(fz). These components are convolved with the horizontal displacement correction coefficients Kh(f) and vertical displacement correction coefficients Kv(f) obtained previously through a Fourier transform, respectively. The convolution operation effectively captures the characteristics of airflow effects on motion at different scales. Next, a three-dimensional inverse fast Fourier transform (3D-IFFT) is performed on the convolution result to obtain the corrected time-domain motion trajectory D'(x, y, z). Finally, by comparing the trajectory differences before and after correction, the gas concentration spatial distribution compensation value ΔC(x, y, z) is calculated for each spatial point. This frequency domain analysis method can more comprehensively consider the dynamic impact of airflow on gas motion, improving the accuracy of concentration distribution prediction. Through frequency domain processing, it can effectively filter out the influence of noise while retaining important motion characteristics, making the correction results more stable and reliable.

[0088] Based on the above embodiment, as another optional embodiment, the step of correcting the three-dimensional motion trajectory deviation based on the horizontal and vertical displacement correction coefficients to obtain the gas concentration spatial distribution compensation value may further include the following steps:

[0089] Step 4051: Use Fourier transform to convert the three-dimensional motion trajectory deviation into frequency domain space.

[0090] Specifically, to analyze gas motion characteristics in the frequency domain, a Fourier transform is required to convert the three-dimensional trajectory deviations into the frequency domain. The three-dimensional trajectory deviation vector D(x, y, z) is discretely sampled in the spatial domain with a sampling interval of Δx = Δy = Δz = 0.1 meters, constructing a 256×256×256 three-dimensional data matrix. A three-dimensional fast Fourier transform (3D-FFT) is performed on this data matrix to obtain the frequency domain representation D(fx, fy, fz). The transformation utilizes the Cooley-Tukey algorithm, which accelerates the computational process through butterfly operations. The converted frequency domain data contains the frequency characteristics of the trajectory at different spatial scales, facilitating subsequent decomposition and correction.

[0091] Step 4052: Decompose the trajectory deviation in the frequency domain space into horizontal and vertical components, and perform convolution operations with the corresponding horizontal and vertical displacement correction coefficients respectively.

[0092] Specifically, in order to process the motion features in the horizontal and vertical directions separately, it is necessary to decompose the trajectory deviation in the frequency domain space and perform convolution operations. The frequency domain data D(fx,fy,fz) is decomposed into the horizontal component Dh(fx,fy) and the vertical component Dv(fz). For the horizontal direction, a two-dimensional frequency response function is constructed: , where α is the attenuation coefficient. For the vertical direction, a one-dimensional frequency response function Hv(fz)=exp(-β·|fz|) is constructed, where β is the height correction factor. Convolution operations are performed separately: D'h=Dh⊗Hh and D'v=Dv⊗Hv, where ⊗ represents the convolution operation. This decomposition method can specifically correct motion characteristics in different directions.

[0093] Step 4053: Convert the convolution operation result into time domain space through inverse Fourier transform to obtain the corrected motion trajectory.

[0094] Specifically, to obtain the corrected actual motion trajectory, the convolution result must be converted to the time domain via an inverse Fourier transform. First, the corrected horizontal component D'h and vertical component D'v are recombined in the frequency domain to form a complete three-dimensional spectrum D'(fx, fy, fz). A three-dimensional inverse fast Fourier transform (3D-IFFT) is then performed on the combined result to obtain the corrected trajectory D'(x, y, z) in the time domain. To eliminate oscillations during the transformation, a Hanning window function is used for smoothing. The resulting corrected trajectory reflects the actual motion characteristics after accounting for airflow.

[0095] Step 4054: Calculate the gas concentration spatial distribution compensation value in the target area based on the corrected motion trajectory.

[0096] Specifically, in order to calculate the compensation value of the spatial distribution of gas concentration, it is necessary to process based on the corrected motion trajectory. First, calculate the position difference ΔD=D'-D between the trajectory before and after correction. Establish a three-dimensional grid with a spacing of 0.1 meters in the target area, and for each grid point (x, y, z), calculate its distance r to the center of the corrected trajectory. Then, according to the distance r, the compensation value of the spatial distribution of gas concentration at the grid point is calculated: ΔC(x, y, z)=C0·(|ΔD| / D0)·exp(-r / L), where C0 is the initial concentration, D0 is the reference distance of 1 meter, and L is the characteristic length of 5 meters. When the distance r is greater than 15 meters, set ΔC=0. This method describes the spatial distribution change of gas concentration through an exponential decay function, where the size of the compensation value is directly related to the position difference and spatial distance, which can effectively reflect the actual impact of airflow on the gas diffusion process.

[0097] Step 50: Calibrate the initial gas concentration according to the gas concentration spatial distribution compensation value to obtain the target gas concentration.

[0098] Specifically, in order to achieve accurate calibration of the target gas concentration, the weighted iteration method is used to process the compensation value of the spatial distribution of gas concentration. Construct a weight function w(r)=exp(-r² / 2σ²), where r is the spatial distance and σ is the characteristic length. For each grid point in the target area, calculate the weighted compensation value of the surrounding spatial points, that is, ΔC'=∑(wi·ΔCi) / ∑wi, wi is the weight value of the i-th neighboring point, calculated by the weight function. Δci is the original compensation value of the i-th neighboring point, and then the target gas concentration is calculated iteratively: C(n+1)=C0+λ·ΔC', where λ is the relaxation factor, the value range is (0,1), and n is the number of iterations. The calculation is stopped when the difference between the results of two adjacent iterations is less than the preset threshold. This method takes into account spatial correlation, and the calibration results are smoother and more continuous.

[0099] Based on the above embodiment, as another optional embodiment, the step of calibrating the initial gas concentration according to the gas concentration spatial distribution compensation value to obtain the target gas concentration may further include the following steps:

[0100] Step 501: Calculate the spatial gradient of the gas concentration spatial distribution compensation value.

[0101] Specifically, in order to accurately describe the spatial variation characteristics of gas concentration, it is necessary to calculate the spatial gradient of the gas concentration spatial distribution compensation value. A three-dimensional grid system is established in the target area with a grid spacing of 0.1 meters. For each grid point (x, y, z), the first-order differences in the three directions are calculated:

[0102] Gx=(ΔC(x+h,y,z)-ΔC(xh,y,z)) / (2h);

[0103] Gy=(ΔC(x,y+h,z)-ΔC(x,yh,z)) / (2h);

[0104] Gz=(ΔC(x,y,z+h)-ΔC(x,y,zh)) / (2h);

[0105] Where h is the grid spacing, which is 0.1 meters. ΔC(x,y,z) represents the concentration compensation value at point (x,y,z). Gx, Gy, and Gz represent the concentration gradients in the x, y, and z directions, respectively. Then calculate the modulus of the spatial gradient: ,This method obtains the rate of change of the compensation value in all directions of space.

[0106] Step 502: Construct a gas concentration calibration coefficient matrix based on the spatial gradient.

[0107] Specifically, to achieve accurate concentration calibration, a gas concentration calibration coefficient matrix needs to be constructed based on spatial gradients. First, the calibration coefficient calculation function k(G) = k0 exp(-|G| / G0) is defined, where k0 is the baseline calibration coefficient (value 1.0) and G0 is the reference gradient value (value 0.1). For each grid point (i, j, k) within the target area, the corresponding calibration coefficient k(i, j, k) is calculated based on the spatial gradient |G| at that point, forming a three-dimensional calibration coefficient matrix K. This matrix reflects the differences in concentration calibration weights at different locations, with regions with large gradients receiving smaller calibration coefficients to avoid overcalibration.

[0108] Step 503: Perform weighted calibration on the initial gas concentration according to the gas concentration calibration coefficient matrix.

[0109] Specifically, to properly calibrate the initial gas concentration, a weighted calibration is required based on the calibration coefficient matrix. For each grid point within the target area, the initial gas concentration, C0, is multiplied by the calibration coefficient k and the compensation value, ΔC, at that point to obtain the calibrated concentration value, C' = C0 + k·ΔC. Taking into account the physical meaning of concentration, the valid range of the calibration result is set: when C' < 0, C' = 0; when C' > Cmax, C' = Cmax, where Cmax is the saturation concentration of the gas. This weighted calibration method ensures the physical rationality of the concentration calibration.

[0110] Step 504: iteratively optimize the gas concentration after weighted calibration until the difference between two adjacent iterative results is less than a preset threshold, and use the optimized result as the target gas concentration.

[0111] Specifically, to obtain a stable and reliable target gas concentration, iterative optimization of the weighted calibrated gas concentration is required. This optimization is performed using a relaxation iteration method: C(n+1)=C(n)+α·(C'-C(n)), where C(n) is the result of the nth iteration, α is the relaxation factor (set to 0.5), and C' is the weighted calibration value. After each iteration, the maximum difference between two consecutive results, δ=max|C(n+1)-C(n)|, is calculated. Iterations are terminated when δ is less than a preset threshold ε (set to 0.001) or the number of iterations reaches the upper limit (100), and the final result is used as the target gas concentration.

[0112] See Figure 2 , is a module schematic diagram of a gas concentration detection and compensation system provided in an embodiment of the present application, wherein the system includes:

[0113] An initial concentration acquisition module is used to obtain the initial gas concentration of the target gas in the target area under the current environment;

[0114] An environmental parameter calculation module is used to calculate the atmospheric pressure change rate, wind speed and direction data, and air density gradient within the target area under the current environment;

[0115] a trajectory deviation calculation module, configured to calculate the three-dimensional motion trajectory deviation of the gas molecules in the target area according to the atmospheric pressure change rate and the air density gradient;

[0116] a compensation value determination module, configured to correct the three-dimensional motion trajectory deviation based on the wind speed and direction data and the molecular weight of the target gas to obtain a compensation value for the spatial distribution of gas concentration;

[0117] The compensation calibration module is used to calibrate the initial gas concentration according to the gas concentration spatial distribution compensation value to obtain the target gas concentration.

[0118] Optionally, the environmental parameter calculation module is further used to collect environmental parameters of each detection point in the current environment, and each of the detection points is evenly arranged on a preset spiral ascending path;

[0119] Determining tangentially adjacent detection points and radially adjacent detection points on the spiral ascending path;

[0120] The atmospheric pressure change rate, wind speed direction data and air density gradient in the target area are calculated based on the environmental parameters of the tangentially adjacent detection points and the radially adjacent detection points.

[0121] Optionally, the trajectory deviation calculation module is further configured to calculate a first displacement component of the gas molecules in the horizontal plane based on the atmospheric pressure change rate;

[0122] Calculating a second displacement component of the gas molecules in the vertical direction according to the air density gradient;

[0123] Calculating motion trajectory characteristic parameters of the gas molecules based on the first displacement component and the second displacement component;

[0124] The three-dimensional motion trajectory deviation of the gas molecules is determined based on the motion trajectory characteristic parameters.

[0125] Optionally, the trajectory deviation calculation module is further configured to convert the first displacement component and the second displacement component into radial components and angular components in a spherical coordinate system;

[0126] calculating the diffusion radius deviation of the gas molecules according to the radial component;

[0127] Calculating the deflection angle of the gas molecule motion trajectory based on the angular component;

[0128] The diffusion radius deviation and the deflection angle are used as motion trajectory characteristic parameters.

[0129] Optionally, the compensation value determination module is further configured to obtain the wind speed and wind direction angle from the wind speed and direction data;

[0130] Calculating the relative mass coefficient of the gas molecules according to the ratio of the molecular weight of the target gas to the molecular weight of standard atmosphere;

[0131] Calculating the airflow force on the gas molecules based on the relative mass coefficient and the wind speed;

[0132] Calculating displacement correction coefficients of gas molecules in the horizontal and vertical directions according to the airflow force;

[0133] The three-dimensional motion trajectory deviation is corrected based on the displacement correction coefficients in the horizontal and vertical directions to obtain a gas concentration spatial distribution compensation value.

[0134] Optionally, the compensation value determination module is further configured to convert the three-dimensional motion trajectory deviation into a frequency domain space using Fourier transform;

[0135] Decomposing the trajectory deviation in the frequency domain space into a horizontal component and a vertical component, and performing convolution operations with corresponding horizontal and vertical displacement correction coefficients respectively;

[0136] The convolution operation result is converted into time domain space through inverse Fourier transform to obtain the corrected motion trajectory;

[0137] A gas concentration spatial distribution compensation value in the target area is calculated based on the corrected motion trajectory.

[0138] Optionally, the compensation calibration module is further used to calculate the spatial gradient of the gas concentration spatial distribution compensation value;

[0139] constructing a gas concentration calibration coefficient matrix based on the spatial gradient;

[0140] and performing weighted calibration on the initial gas concentration according to the calibration coefficient matrix;

[0141] The gas concentration after weighted calibration is iteratively optimized until the difference between two adjacent iterative results is less than a preset threshold, and the optimized result is used as the target gas concentration.

[0142] It should be noted that the above embodiments provide systems that implement their functions using only the division of the above functional modules as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0143] An embodiment of the present application also provides a computer storage medium, which can store multiple instructions. The instructions are suitable for being loaded by a processor and executing a gas concentration detection compensation method of the above embodiment. The specific execution process can be found in the specific description of the above embodiment and will not be repeated here.

[0144] Please refer to Figure 3 The present application also discloses an electronic device. Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0145] The communication bus 302 is used to implement the connection and communication between these components.

[0146] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0147] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0148] The processor 301 may include one or more processing cores. Using various interfaces and circuits, the processor 301 connects to various components within the server. It executes instructions, programs, code sets, or instruction sets stored in the memory 305, as well as accesses data stored in the memory 305, to perform various server functions and process data. Optionally, the processor 301 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 301 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing content displayed on the display screen; and the modem handles wireless communications. It is understood that the modem may not be integrated into the processor 301 but implemented as a separate chip.

[0149] Among them, the memory 305 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may also optionally be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 , the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a gas concentration detection compensation method.

[0150] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call an application program for a gas concentration detection compensation method stored in the memory 305. When executed by one or more processors 301, the electronic device 300 executes one or more methods such as those in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should know that this application is not limited to the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0151] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0152] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic, such as the division of units, which is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interface, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0153] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0154] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0155] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of this application. The aforementioned memory includes various media that can store program code, such as USB flash drives, mobile hard drives, magnetic disks, or optical disks.

[0156] The above are merely exemplary embodiments of the present disclosure and are not intended to limit the scope of the present disclosure. In other words, any equivalent variations and modifications made in accordance with the teachings of the present disclosure are still within the scope of the present disclosure. Those skilled in the art will readily conceive of other embodiments of the present disclosure after considering the disclosure and the practical implications thereof.

[0157] This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not described herein. The description and examples are to be considered as exemplary only, and the scope and spirit of the present disclosure are to be defined by the claims.

Claims

1. A gas concentration detection and compensation method, characterized in that: The method comprises: Obtaining an initial gas concentration of the target gas in the target area under the current environment, wherein the initial gas concentration refers to the gas concentration of the three-dimensional gas concentration distribution field; Calculate the atmospheric pressure change rate, wind speed and direction data, and air density gradient within the target area under the current environment; Calculating the three-dimensional motion trajectory deviation of the gas molecules in the target area according to the atmospheric pressure change rate and the air density gradient; Calculating the three-dimensional motion trajectory deviation of the gas molecules in the target area according to the atmospheric pressure change rate and the air density gradient includes: Calculating a first displacement component of the gas molecules in the horizontal plane based on the atmospheric pressure change rate; Calculating a second displacement component of the gas molecules in the vertical direction according to the air density gradient; Calculating motion trajectory characteristic parameters of the gas molecules based on the first displacement component and the second displacement component; determining a three-dimensional motion trajectory deviation of the gas molecules based on the motion trajectory characteristic parameters; Combining the wind speed and direction data and the molecular weight of the target gas to correct the three-dimensional motion trajectory deviation, and obtain a gas concentration spatial distribution compensation value; The three-dimensional motion trajectory deviation is corrected in combination with the wind speed and direction data and the molecular weight of the target gas to obtain a gas concentration spatial distribution compensation value, including: Obtaining wind speed and wind direction angle from the wind speed and direction data; Calculating the relative mass coefficient of the gas molecules according to the ratio of the molecular weight of the target gas to the molecular weight of standard atmosphere; Calculating the airflow force on the gas molecules based on the relative mass coefficient and the wind speed; Calculating displacement correction coefficients of gas molecules in the horizontal and vertical directions according to the airflow force; Correcting the three-dimensional motion trajectory deviation based on the horizontal and vertical displacement correction coefficients to obtain a gas concentration spatial distribution compensation value; The initial gas concentration is calibrated according to the gas concentration spatial distribution compensation value to obtain a target gas concentration.

2. The gas concentration detection compensation method according to claim 1, characterized in that: The calculation of the atmospheric pressure change rate, wind speed and direction data, and air density gradient within the target area under the current environment includes: Collecting environmental parameters of each detection point in the current environment, wherein each detection point is evenly arranged on a preset spiral ascending path; Determining tangentially adjacent detection points and radially adjacent detection points on the spiral ascending path; The atmospheric pressure change rate, wind speed direction data and air density gradient in the target area are calculated based on the environmental parameters of the tangentially adjacent detection points and the radially adjacent detection points.

3. The gas concentration detection compensation method according to claim 1, characterized in that: The calculating of the motion trajectory characteristic parameters of the gas molecules based on the first displacement component and the second displacement component includes: Converting the first displacement component and the second displacement component into radial components and angular components in a spherical coordinate system; calculating the diffusion radius deviation of the gas molecules according to the radial component; Calculating the deflection angle of the gas molecule motion trajectory based on the angular component; The diffusion radius deviation and the deflection angle are used as motion trajectory characteristic parameters.

4. The gas concentration detection and compensation method according to claim 1, characterized in that: The three-dimensional motion trajectory deviation is corrected based on the displacement correction coefficients in the horizontal and vertical directions to obtain a gas concentration spatial distribution compensation value, including: Converting the three-dimensional motion trajectory deviation into frequency domain space using Fourier transform; Decomposing the trajectory deviation in the frequency domain space into a horizontal component and a vertical component, and performing convolution operations with corresponding horizontal and vertical displacement correction coefficients respectively; The convolution operation result is converted into time domain space through inverse Fourier transform to obtain the corrected motion trajectory; A gas concentration spatial distribution compensation value in the target area is calculated based on the corrected motion trajectory.

5. The gas concentration detection and compensation method according to claim 1, characterized in that: The calibrating the initial gas concentration according to the gas concentration spatial distribution compensation value to obtain a target gas concentration includes: Calculating the spatial gradient of the gas concentration spatial distribution compensation value; constructing a gas concentration calibration coefficient matrix based on the spatial gradient; performing weighted calibration on the initial gas concentration according to the gas concentration calibration coefficient matrix; The gas concentration after weighted calibration is iteratively optimized until the difference between two adjacent iterative results is less than a preset threshold, and the optimized result is used as the target gas concentration.

6. A gas concentration detection and compensation system, characterized in that: For implementing a gas concentration detection and compensation method according to claim 1, the gas concentration detection and compensation system comprises: An initial concentration acquisition module is used to obtain the initial gas concentration of the target gas in the target area under the current environment; An environmental parameter calculation module is used to calculate the atmospheric pressure change rate, wind speed and direction data, and air density gradient within the target area under the current environment; a trajectory deviation calculation module, configured to calculate the three-dimensional motion trajectory deviation of the gas molecules in the target area according to the atmospheric pressure change rate and the air density gradient; a compensation value determination module, configured to correct the three-dimensional motion trajectory deviation based on the wind speed and direction data and the molecular weight of the target gas to obtain a compensation value for the spatial distribution of gas concentration; The compensation calibration module is used to calibrate the initial gas concentration according to the gas concentration spatial distribution compensation value to obtain the target gas concentration.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the method according to any one of claims 1 to 5.

8. An electronic device, characterized in that: The electronic device comprises a processor, a memory, a user interface and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method according to any one of claims 1 to 5.

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