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

Abstract

The invention discloses a gas concentration detection compensation method and system, electronic equipment and a storage medium, and relates to the technical field of gas concentration measurement. The method comprises the following steps: acquiring an initial gas concentration of target gas in a target area in a current environment; calculating an atmospheric pressure change rate, wind speed and flow direction data and an air density gradient in the target area in the current environment; according to the atmospheric pressure change rate and the air density gradient, calculating a three-dimensional motion track deviation of gas molecules in the target area; correcting the three-dimensional motion track deviation by combining the wind speed and flow direction data and the molecular weight of the target gas to obtain a gas concentration spatial distribution compensation value; and calibrating the initial gas concentration according to the gas concentration spatial distribution compensation value to obtain the target gas concentration. By implementing the technical scheme provided by the invention, the accuracy of a gas concentration detection result can be improved.

Description

Technical Field

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

[0002] With the continuous improvement of industrial production and environmental protection requirements, the accurate detection of gas concentration plays an increasingly important role in fields such as industrial safety monitoring and air pollution prevention and control. Especially in places such as chemical industrial parks and petrochemical bases, accurately grasping the concentration of target gases in a specific area is of great significance for timely discovering leakage hazards and ensuring production safety.

[0003] In the prior art, gas concentration detection is mainly carried out by fixedly installing multiple detectors in the target area for sampling and detection. These detectors are arranged at preset fixed positions, and the gas distribution in the area is monitored by long-term collection of gas concentration data. However, in the actual detection process, due to the dynamic change characteristics of the atmospheric environment, the distribution of gas in space is affected by various environmental factors. The combined effect of these environmental factors makes the gas concentration data obtained at fixed points difficult to accurately reflect the actual gas concentration distribution in the entire area, resulting in a low accuracy of 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, which includes: Obtain the initial gas concentration of the target gas in the target area under the current environment; Calculate the atmospheric pressure change rate, wind speed and flow direction data, and air density gradient in the target area under the current environment; Calculate 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; Correct the three-dimensional motion trajectory deviation in combination with the wind speed and flow direction data and the molecular weight of the target gas to obtain a gas concentration spatial distribution compensation value; Calibrate the initial gas concentration according to the gas concentration spatial distribution compensation value to obtain the target gas concentration.

[0006] By adopting the above technical solution, the initial gas concentration of the target gas in the target area is obtained as basic data. At the same time, environmental parameters such as the atmospheric pressure change rate, wind speed and flow direction data, and air density gradient in the target area under the current environment are calculated to comprehensively master the key environmental factors affecting gas distribution. Secondly, based on the obtained atmospheric pressure change rate and air density gradient, the three-dimensional motion trajectory deviation of gas molecules in the target area is calculated, so as to accurately reflect the influence degree of environmental factors on the motion trajectory of gas molecules. Thirdly, by combining the wind speed and flow direction data with the molecular weight characteristics of the target gas, the three-dimensional motion trajectory deviation is corrected to obtain a gas concentration spatial distribution compensation value that can reflect the motion characteristics of gas molecules in the actual environment. Finally, the initial gas concentration is calibrated using this compensation value to obtain the target gas concentration that accurately reflects the actual gas distribution in the target area. By considering the comprehensive influence of various environmental factors on the motion of gas molecules, a dynamic compensation mechanism for gas concentration is established, avoiding the technical problem that traditional fixed-point detection methods are difficult to cope with environmental dynamic changes, and significantly improving the accuracy of gas concentration detection results.

[0007] In the second aspect of the present application, a gas concentration detection and compensation system is provided. The system includes: An initial concentration acquisition module for acquiring the initial gas concentration of the target gas in the target area under the current environment; An environmental parameter calculation module for calculating the atmospheric pressure change rate, wind speed and flow direction data, and air density gradient in the target area under the current environment; A trajectory deviation calculation module for 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; A compensation value determination module for correcting the three-dimensional motion trajectory deviation by combining the wind speed and flow direction data with the molecular weight of the target gas to obtain a gas concentration spatial distribution compensation value; A compensation calibration module for calibrating the initial gas concentration according to the gas concentration spatial distribution compensation value to obtain the target gas concentration.

[0008] In the third aspect of the present application, a computer storage medium is provided. The computer storage medium stores multiple instructions, and the instructions are suitable for being loaded and executed by a processor to perform the above method steps.

[0009] In the fourth aspect of the present application, an electronic device is provided, including: a processor and a memory; wherein, the memory stores a computer program, and the computer program is suitable for being loaded and executed by the processor to perform the above method steps.

[0010] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: This application obtains the initial gas concentration of the target gas in the target area as basic data, and simultaneously calculates environmental parameters such as the atmospheric pressure change rate, wind speed and flow direction data, and air density gradient in the target area under the current environment to comprehensively grasp the key environmental factors affecting gas distribution. Secondly, based on the obtained atmospheric pressure change rate and air density gradient, the three-dimensional motion trajectory deviation of gas molecules in the target area is calculated, so as to accurately reflect the influence degree 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 flow direction data with the molecular weight characteristics of the target gas to obtain a gas concentration spatial distribution compensation value that can reflect the motion characteristics of gas molecules in the actual environment. Finally, the initial gas concentration is calibrated using this compensation value to obtain the target gas concentration that accurately reflects the actual gas distribution in the target area. By considering the comprehensive influence of various environmental factors on the motion of gas molecules, a dynamic compensation mechanism for gas concentration is established, avoiding the technical problem that traditional fixed-point detection methods are difficult to cope with environmental dynamic changes, and significantly improving the accuracy of gas concentration detection results. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 is a schematic flowchart of a gas concentration detection and compensation method provided by an embodiment of this application; Figure 2 is a schematic block diagram of a gas concentration detection and compensation system provided by an embodiment of this application; Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of this application.

[0012] Description of the reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0013] In order to enable those skilled in the art to better understand the technical solutions in this specification, the following will clearly and completely describe the technical solutions in the embodiments of this specification with reference to the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments.

[0014] 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 solution described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, the use of words such as "for example" or "for instance" is intended to present related concepts in a specific manner.

[0015] In the description of the embodiments of the present application, the term "a plurality" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. The terms "include", "comprise", "have" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0016] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments.

[0017] Please refer to Figure 1 , and a flow schematic diagram of a gas concentration detection and compensation method is specifically proposed. This method can be implemented depending on a computer program, can be implemented depending on a single-chip microcomputer, or can run on a gas concentration detection and compensation system. This computer program can be integrated in a computer device or can run as an independent tool-class application. Specifically, this method includes steps 10 to 50, and the above steps are as follows: Step 10: Obtain the initial gas concentration of the target gas in the target area under the current environment.

[0018] Among them, in the embodiments of the present application, the target area refers to the open space range where gas concentration detection needs to be carried out. Although the detection boundary is delimited from the management and monitoring perspectives, this area is not a closed space in the physical space but an area that exchanges matter and energy with the external atmospheric environment. The air flow movement in the area is affected by both the external atmospheric environment and the disturbing effects of physical obstacles such as buildings and equipment in the area.

[0019] The target gas refers to the specific gas components that need to be key monitored in the target area, which 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 need to be monitored for concentration. These gases are usually closely related to the production activities in the area, and their concentration changes directly affect production safety.

[0020] The initial gas concentration refers to the original concentration data of the target gas collected in the target area by existing detection equipment before the concentration compensation calculation. This data reflects the gas concentration value directly measured by the detection equipment without considering the influence of environmental factors.

[0021] Specifically, due to the spatial inhomogeneity of gas distribution in the target area and the fluctuation of gas concentration with the change of environment, 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 calculation. In specific implementation, a fixed gas concentration detector network can be arranged in the target area. The detector network includes multiple gas concentration detection units, and each detection unit is 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 × 10 meters and are located at three heights of 1 meter, 3 meters, and 5 meters above the ground in the vertical direction. Each detection unit collects data every 1 minute and transmits the collected temperature, pressure, and gas concentration data to the data processing unit in real time through an industrial bus. The data processing unit performs spatial interpolation calculation on the gas concentration data collected by different detection units at the same moment to generate a three-dimensional gas concentration distribution field in the target area, so as to obtain the initial gas concentration of the target gas under the current environment.

[0022] In another feasible embodiment, a mobile detection device can also be used for gas concentration sampling. The mobile detection device can perform patrol sampling according to a preset path. Or synchronously use an aerial drone equipped with a micro gas concentration detector to perform sampling according to a spiral ascending trajectory. The mobile detection device and the aerial drone operate synchronously, respectively responsible for low-altitude and high-altitude gas concentration sampling in the target area.

[0023] Step 20: Calculate the atmospheric pressure change rate, wind speed and direction data, and air density gradient in the target area under the current environment.

[0024] Among them, in the embodiment of the present application, the atmospheric pressure change rate refers to the amount of air pressure change per unit time and unit spatial distance in the target area, which is used to characterize the spatial distribution change characteristics of the atmospheric pressure in the area.

[0025] The wind speed and direction data refer to the speed magnitude and direction information of the airflow movement in the target area.

[0026] The air density gradient refers to the change rate of the air density in the target area in space, indicating the change amount of the air density per unit distance.

[0027] Specifically, since the movement of gas molecules in 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 the gas movement trajectory. During specific implementation, detection points are evenly set in the target area along a preset spiral ascending path, and each detection point is equipped with a pressure sensor, an ultrasonic anemometer, and a temperature and humidity sensor. First, determine the tangentially adjacent detection points and radially adjacent detection points on the spiral ascending path, and collect the environmental parameters of each detection point. Then, calculate the atmospheric pressure change rate in the horizontal direction based on the pressure difference between the tangentially adjacent detection points, and calculate the atmospheric pressure change rate in the vertical direction based on the pressure difference between the radially adjacent detection points. Obtain the three-dimensional wind speed components and wind direction angles of each detection point through the ultrasonic anemometer, and construct the wind speed flow data field of the target area. At the same time, calculate the air density of each detection point using the temperature and humidity data, and calculate the air density gradient based on the air density difference between adjacent detection points. This solution can comprehensively obtain the spatial distribution characteristics of environmental parameters in the target area through a spiral-distributed detection network.

[0028] Based on the above embodiments, as another alternative embodiment, the step of calculating the atmospheric pressure change rate, wind speed flow data, and air density gradient in the target area under the current environment may further include the following steps: Step 201: Collect the environmental parameters of each detection point in the current environment, and the detection points are evenly set on a preset spiral ascending path.

[0029] Specifically, in order to obtain the three-dimensional distribution characteristics of environmental parameters in the target area, it is necessary to collect the environmental parameters of each detection point in the current environment. First, design a spiral ascending sampling path, which starts 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. A detection point is evenly set every 3 meters on this spiral path, and each detection point is equipped with an environmental parameter collection device. The environmental parameter collection 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 to the central control system in real time through an industrial-grade data acquisition module. At the same time, each detection point is equipped with a GPS positioning module for recording the precise spatial coordinates of the detection point. This layout scheme can ensure the acquisition of continuous environmental parameter data from the ground to the high altitude in the target area.

[0030] Step 202: Determine the tangentially adjacent detection points and radially adjacent detection points of the spiral ascending path.

[0031] Specifically, in order to calculate the spatial gradient of environmental parameters, it is necessary to determine the tangential adjacent detection points and radial adjacent detection points of the spiral ascending path. First, the spatial coordinates of the detection points are converted into cylindrical coordinates (r, θ, z), where r represents the radial distance, θ represents the azimuth angle, and z represents the height. For any detection point P(r, θ, z), its tangential adjacent detection points are defined as two detection points with an azimuth angle difference of Δθ = 30° on the same spiral level, that is, P1(r, θ - 30°, z) and P2(r, θ + 30°, z); the radial adjacent detection points are defined as two detection points on adjacent spiral levels with the same azimuth angle and a height difference of one pitch, that is, P3(r - Δr, θ, z - 2.5) and P4(r + Δr, θ, z + 2.5), where Δr is the radius difference between adjacent spiral circles. A topological relation database of detection points is established through the central control system to record and update the adjacent point information of each detection point in real time.

[0032] Step 203: Calculate the atmospheric pressure change rate, wind speed and flow direction data, and air density gradient in the target area based on the environmental parameters of the tangential adjacent detection points and radial adjacent detection points.

[0033] Specifically, in order to comprehensively 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, it is necessary to calculate based on the determined tangential adjacent detection points and radial adjacent detection points in the following manner: 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 through the pressure values of the tangential adjacent detection points: ΔPh = (P2 - P1) / (2R·Δθ), where P2 and P1 are the pressure values of the tangential adjacent points, R is the current spiral radius, and Δθ is the angle difference between adjacent points; the vertical pressure change rate is calculated through the radial adjacent detection points: ΔPv = (P4 - P3) / Δz, where P4 and P3 are the pressure values of the radial adjacent points, and Δz is the pitch value of 2.5 meters.

[0034] Secondly, obtain the three components and the wind direction angle of the wind speed and flow direction data. The x-direction wind speed component Vx, y-direction wind speed component Vy, and vertical z-axis wind speed component Vz in the horizontal plane are directly measured by a three-dimensional ultrasonic anemometer. The wind direction angle α is calculated through the arctangent function: α = arctan(Vy / Vx), and when Vx is zero, α = 90° or 270°. The change rates of each wind speed component are calculated through the wind speed differences of adjacent detection points to obtain the spatial distribution characteristics of the wind speed.

[0035] Finally, calculate the two components of the air density gradient: the horizontal density gradient Δρh and the vertical density gradient Δρv. First, calculate the air density using the temperature T and pressure P at each detection point: ρ = P / (R·T), where R is the gas constant. Then, calculate the horizontal density gradient based on tangentially adjacent detection points: Δρh = (ρ2 - ρ1) / (2R·Δθ), where ρ2 and ρ1 are the air densities at tangentially adjacent points; calculate the vertical density gradient based on radially adjacent detection points: Δρv = (ρ4 - ρ3) / Δz, where ρ4 and ρ3 are the air densities at radially adjacent points.

[0036] The environmental parameter components obtained through the above calculations can fully characterize the spatial distribution characteristics of the environmental parameters within the target area. The calculation results of these discrete points are extended to the entire target area through a three-dimensional spline interpolation algorithm to obtain a continuous environmental parameter distribution field, providing accurate input data for subsequent analysis of gas movement trajectories.

[0037] Step 30: Calculate the three-dimensional motion trajectory deviation of gas molecules within the target area based on the atmospheric pressure change rate and the air density gradient.

[0038] Among them, in the embodiments of the present application, the three-dimensional motion trajectory deviation refers to the spatial displacement amount by which the target gas molecule deviates from the ideal diffusion path under the action of the current environmental factors.

[0039] Specifically, since gas molecules will deviate from the ideal diffusion path under the action of environmental factors, it is necessary to calculate the three-dimensional motion trajectory deviation of gas molecules within the target area. In specific implementation, first, calculate the first displacement component of gas molecules in the horizontal plane based on the horizontal pressure change rate ΔPh. Obtain the horizontal motion acceleration through the pressure gradient force formula: Fp = -(1 / ρ)·ΔPh, and then calculate the horizontal displacement within Δt time. Then, calculate the second displacement component of gas molecules in the vertical direction based on the vertical density gradient Δρv. Considering the buoyancy force Fb = g·(ρ - ρg), calculate the vertical motion acceleration and displacement. Convert the two displacement components into the radial component and the angular component in the spherical coordinate system, calculate the diffusion radius deviation and the deflection angle as the motion trajectory characteristic parameters. Finally, determine the actual position deviation vector of gas molecules in three-dimensional space based on these characteristic parameters to obtain the three-dimensional motion trajectory deviation. This solution realizes an accurate description of the gas molecule motion trajectory through mechanical analysis.

[0040] Based on the above embodiments, as an alternative embodiment, the step of calculating the three-dimensional motion trajectory deviation of gas molecules within the target area based on the atmospheric pressure change rate and the air density gradient may further include the following steps: Step 301: Calculate the first displacement component of gas molecules in the horizontal plane based on the atmospheric pressure change rate.

[0041] 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, obtain the horizontal pressure change rate ΔPh in the target area. According to the principle of gas dynamics, calculate the pressure gradient force Fp = -(1 / ρ)·ΔPh acting on gas molecules per unit volume, where ρ is the local air density. Under the action of the pressure gradient force, the horizontal acceleration of gas molecules ah = Fp / m, where m is the mass of gas molecules. Set the time interval Δt = 0.1 s, then the displacement of gas molecules in the horizontal direction is Δx = ah·(Δt)² / 2. Decompose this displacement onto the x-y 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, obtain the first displacement component vector_h = (Δx, Δy) of gas molecules in the horizontal plane. 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.

[0042] Step 302: Calculate the second displacement component of gas molecules in the vertical direction according to the air density gradient.

[0043] Specifically, in order to obtain the motion characteristics of gas molecules in the vertical direction, it is necessary to calculate the second displacement component according to the air density gradient. First, obtain the vertical density gradient Δρv, and calculate the buoyancy force Fb = g·(ρ - ρg) acting on gas molecules per unit volume, where g is the acceleration due to gravity and ρg is the gas molecule density. Considering the combined action of gravity and buoyancy, the resultant force of gas molecules in the vertical direction is F = Fb - mg. Accordingly, calculate the vertical acceleration av = F / m. Set the same time interval Δt = 0.1 s, then the displacement of gas molecules in the vertical direction is Δz = av·(Δt)² / 2. This displacement is the second displacement component vector_v = (0, 0, Δz) of gas molecules in the vertical direction. This calculation method comprehensively considers the influence of buoyancy and gravity and can accurately describe the motion characteristics of gas molecules in the vertical direction.

[0044] Step 303: Calculate the motion trajectory characteristic parameters of gas molecules based on the first displacement component and the second displacement component.

[0045] Specifically, convert the first displacement component in the horizontal plane and the second displacement component in the vertical direction to the spherical coordinate system, and calculate the modulus R of the resultant displacement vector, and calculate the azimuth angle α = arctan(Δy / Δx), and the elevation angle β = arcsin(Δz / R). Calculate the diffusion radius deviation ΔR = R·cosβ based on these parameters, which represents the horizontal distance of gas molecules deviating from the initial position; calculate the trajectory deflection angle γ = arctan(Δz / ΔR), which represents the angle between the motion trajectory and the horizontal plane. Take ΔR and γ as the characteristic parameters to describe the motion trajectory of gas molecules.

[0046] Step 304: Determine the three-dimensional motion trajectory deviation of gas molecules based on the motion trajectory characteristic parameters.

[0047] Specifically, first construct a local coordinate system. Taking the initial position of the gas molecule as the origin, establish a right-handed rectangular coordinate system. According to the diffusion radius deviation ΔR and the trajectory deflection angle γ, calculate the position coordinates of the gas molecule in the new coordinate system: x' = ΔR·cosα, y' = ΔR·sinα, z' = ΔR·tanγ. Then convert the position coordinates in the local coordinate system to the global coordinate system through a coordinate transformation matrix to obtain the three-dimensional motion trajectory deviation vector D = (Dx, Dy, Dz) of the gas molecule. The direction of this vector indicates the actual motion direction of the gas molecule, and the modulus represents the distance deviating from the ideal diffusion path.

[0048] Based on the above embodiments, as another alternative embodiment, the step of calculating the motion trajectory characteristic parameters of gas molecules based on the first displacement component and the second displacement component may further include the following steps: Step 3031: Convert the first displacement component and the second displacement component into a radial component and an angular component in the spherical coordinate system.

[0049] 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 a radial component and an angular component 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 transformation equations: radial component , azimuth angle θ = arctan(Δy / Δx), zenith angle φ = arccos(Δz / r). Then decompose the radial component r into a tangential component r t = r·sinφ and a normal component r n = r·cosφ. Finally, obtain the radial component D r = r n and the angular component D θ = r t .

[0050] Step 3032: Calculate the diffusion radius deviation of gas molecules according to the radial component.

[0051] Specifically, in order to quantify the degree to which gas molecules deviate from the initial position, it is necessary to calculate the diffusion radius deviation of gas molecules according to the radial component. First, obtain the radial component D r in the spherical coordinate system. Considering the displacement characteristics of gas molecules along the radial direction during spatial diffusion, the radial component D rProjected onto the horizontal plane, the diffusion radius deviation ΔR = D r ·cosθ, where θ is the azimuth angle. When gas molecules diffuse outward, ΔR is positive; when contracting inward, ΔR is negative. This calculation method can accurately reflect the change in the diffusion range of gas molecules in the horizontal plane.

[0052] Step 3033: Calculate the deflection angle of the gas molecule movement trajectory based on the angular component.

[0053] Specifically, to describe the change in the movement direction of gas molecules, it is necessary to calculate the deflection angle of the gas molecule movement trajectory based on the angular component. Obtain the angular component D θ , combined with the radial component D r , and calculate the deflection angle β = arctan(D θ / D r ) through the arctangent function. This angle represents the angle between the actual movement trajectory of gas molecules and the radial direction. When β is positive, it means the gas molecule movement trajectory deflects counterclockwise; when it is negative, it means clockwise deflection. This calculation method can quantitatively describe the deviation degree of the gas molecule movement direction.

[0054] Step 3034: Use the diffusion radius deviation and the deflection angle as the movement trajectory characteristic parameters.

[0055] Specifically, to completely characterize the movement characteristics of gas molecules, it is necessary to use the diffusion radius deviation and the deflection angle as the movement trajectory characteristic parameters. Combine the calculated diffusion radius deviation ΔR and the deflection angle β to form a binary characteristic parameter group (ΔR, β). The unit of ΔR is meters, which describes the radial distance of gas molecules deviating from the initial position; the unit of β is radians, which describes the deflection degree of the movement trajectory. Store these two parameters in the movement characteristic database and establish an index structure for subsequent query and calculation. This characteristic parameter group can uniquely determine the movement characteristics of gas molecules in space.

[0056] Step 40: Combine the wind speed and flow direction data and the molecular weight of the target gas to correct the three-dimensional movement trajectory deviation to obtain the gas concentration spatial distribution compensation value.

[0057] Among them, in the embodiments of the present application, the gas concentration spatial distribution compensation value refers to the value obtained by correcting the ideal diffusion concentration distribution according to the three-dimensional movement trajectory deviation of gas molecules. The compensation value can be divided into a radial compensation component (compensating the concentration deviation in the horizontal direction) and a height compensation component (compensating the concentration deviation in the vertical direction), and its magnitude is directly related to the direction and amplitude of the three-dimensional movement trajectory deviation. By superimposing the compensation value on the ideal diffusion concentration, a gas concentration spatial distribution closer to the actual situation can be obtained.

[0058] Specifically, since the wind speed and the molecular weight of the target gas will affect the actual movement trajectory of gas molecules, it is necessary to correct the three-dimensional movement trajectory deviation to obtain an accurate compensation value for the spatial distribution of gas concentration. Obtain the three-dimensional wind speed components (Vx, Vy, Vz) and the molecular weight M of the target gas in the target area. For the three-dimensional movement trajectory deviation vector D = (Dx, Dy, Dz), calculate the wind speed influence coefficient , where V0 is the reference wind speed of 1 m / s; calculate the relative mass coefficient , where M0 is the average molecular weight of air, 29 g / mol. Multiply the two influence coefficients by the deviation vector to obtain the corrected displacement vector D' = D·kv·km. Finally, calculate the compensation value for the spatial distribution of gas concentration ΔC = C0·(1 - |D'| / R0) according to the corrected displacement vector, where C0 is the ideal diffusion concentration and R0 is the reference distance. This solution improves the accuracy of concentration distribution prediction by considering the influence of wind speed and molecular weight.

[0059] Based on the above embodiments, as another alternative embodiment, the step of correcting the three-dimensional movement trajectory deviation by combining the wind speed and direction data and the molecular weight of the target gas to obtain the compensation value for the spatial distribution of gas concentration may further include the following steps: Step 401: Obtain the wind speed and wind direction angle in the wind speed and direction data.

[0060] Specifically, to determine the influence of the air flow 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 wind speed component Vx in the x direction and the wind speed component Vy in the y direction in the horizontal plane, and the wind speed component Vz in the vertical direction of the z axis from a three-dimensional ultrasonic anemometer. Calculate the resultant wind speed , whose unit is m / s. Then calculate the wind direction angle α = arctan(Vy / Vx). When Vx is zero, if Vy > 0, then α = 90°, and if Vy < 0, then α = 270°. At the same time, calculate the wind speed elevation angle β = arcsin(Vz / V) to characterize the vertical movement characteristics of the air flow.

[0061] Step 402: Calculate the relative mass coefficient of gas molecules according to the ratio of the molecular weight of the target gas to the molecular weight of the standard atmosphere.

[0062] Specifically, to characterize the movement characteristics of target gas molecules in the air, it is necessary to calculate the relative mass coefficient of gas molecules according to 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 (take 29 g / mol). Calculate the relative mass coefficient , this coefficient reflects the mass difference of target gas molecules relative to air molecules. When km > 1, it indicates that the mass of target gas molecules is greater than that of air molecules; when km < 1, it indicates that the mass of target gas molecules is less than that of air molecules. The calculation of this coefficient takes into account the influence of molecular weight on the motion characteristics of gases.

[0063] Step 403: Calculate the airflow force acting on gas molecules based on the relative mass coefficient and wind speed.

[0064] Specifically, in order to accurately describe the influence of airflow on the motion of gas molecules, it is necessary to calculate the airflow force acting on gas molecules based on the relative mass coefficient and wind speed. According to the principles of aerodynamics, the airflow force F acting on gas molecules is calculated as F = 1 / 2·ρ·Cd·A·V²·km, where ρ is the air density, Cd is the drag coefficient (taking 0.47), A is the effective cross-sectional area of gas molecules, V is the resultant wind speed, and km is the relative mass coefficient. Decompose the airflow force into a horizontal component Fh = F·cosβ and a vertical component Fv = F·sinβ, where β is the elevation angle of the wind speed. This calculation method takes into account the comprehensive influence of gas molecule characteristics and wind field characteristics.

[0065] Step 404: Calculate the displacement correction coefficients of gas molecules in the horizontal and vertical directions based on the airflow force.

[0066] Specifically, in order to quantify the influence degree of airflow on the gas motion trajectory, it is necessary to calculate the displacement correction coefficients of gas molecules in the horizontal and vertical directions based on the airflow force. Based on the horizontal airflow force Fh, calculate the horizontal displacement correction coefficient kh = Fh·Δt² / (2m·d0), where Δt is the characteristic time (taking 1 second), m is the mass of gas molecules, and d0 is the reference displacement (taking 1 meter). Similarly, based on the vertical airflow force Fv, calculate the vertical displacement correction coefficient kv = Fv·Δt² / (2m·d0). These correction coefficients reflect the proportion of displacement change caused by the airflow action.

[0067] Step 405: Correct the three-dimensional motion trajectory deviation based on the displacement correction coefficients in the horizontal and vertical directions to obtain the gas concentration spatial distribution compensation value.

[0068] Specifically, the frequency-domain analysis method is used to correct the three-dimensional motion trajectory deviation. First, the three-dimensional motion trajectory deviation D(x, y, z) is converted into a frequency-domain representation D(fx, fy, fz) through three-dimensional fast Fourier transform (3D-FFT). This conversion can decompose complex spatial motion characteristics into simple harmonic components of different frequencies. In the frequency-domain space, the trajectory deviation is decomposed into a horizontal component Dh(fx, fy) and a vertical component Dv(fz), and they are respectively convolved with the horizontal displacement correction coefficient Kh(f) and the vertical displacement correction coefficient Kv(f) obtained by Fourier transform in advance. The convolution operation can effectively capture the influence characteristics of air flow on motions of different scales. Then, the three-dimensional inverse fast Fourier transform (3D-IFFT) is performed on the convolution operation 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) at each spatial point is calculated. This frequency-domain analysis method can more comprehensively consider the dynamic influence of air flow on gas motion and improve the accuracy of concentration distribution prediction. Through frequency-domain processing, the influence of noise can be effectively filtered out while important motion feature information is retained, making the correction result more stable and reliable.

[0069] Based on the above embodiments, as another alternative embodiment, the step of correcting the three-dimensional motion trajectory deviation based on the displacement correction coefficients in the horizontal and vertical directions to obtain the gas concentration spatial distribution compensation value may further include the following steps: Step 4051: Convert the three-dimensional motion trajectory deviation to the frequency-domain space by using Fourier transform.

[0070] Specifically, in order to analyze the gas motion characteristics in the frequency domain, it is necessary to convert the three-dimensional motion trajectory deviation to the frequency-domain space by using Fourier transform. The three-dimensional motion trajectory deviation vector D(x, y, z) is discretely sampled in the spatial domain with a sampling interval of Δx = Δy = Δz = 0.1 m to construct a 256×256×256 three-dimensional data matrix. The three-dimensional fast Fourier transform (3D-FFT) is performed on this data matrix to obtain the frequency-domain representation D(fx, fy, fz). The Cooley-Tukey algorithm is used in the transformation process to accelerate the calculation process through butterfly operations. The converted frequency-domain data contains the frequency characteristics of the motion trajectory at different spatial scales, which is convenient for subsequent decomposition and correction.

[0071] Step 4052: Decompose the trajectory deviation in the frequency-domain space into a horizontal component and a vertical component, and respectively perform convolution operations with the corresponding horizontal and vertical displacement correction coefficients.

[0072] Specifically, in order to process the motion characteristics in the horizontal and vertical directions separately, it is necessary to perform component decomposition and convolution operations on the trajectory deviation in the frequency domain space. The frequency domain data D(fx, fy, fz) is decomposed into a horizontal component Dh(fx, fy) and a 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 coefficient. Convolution operations are performed separately: D'h = Dh ⊗ Hh and D'v = Dv ⊗ Hv, where ⊗ represents the convolution operation. This decomposition and processing method can specifically correct the motion characteristics in different directions.

[0073] Step 4053: Convert the result of the convolution operation into the time domain space through inverse Fourier transform to obtain the corrected motion trajectory.

[0074] Specifically, in order to obtain the corrected actual motion trajectory, it is necessary to convert the result of the convolution operation into the time domain space through inverse Fourier transform. First, the corrected horizontal component D'h and vertical component D'v are recombined in the frequency domain into a complete three-dimensional spectrum D'(fx, fy, fz). Then, perform a three-dimensional inverse fast Fourier transform (3D-IFFT) on the combined result to obtain the corrected trajectory D'(x, y, z) in the time domain space. To eliminate the pseudo-oscillations during the transformation process, a Hanning window function is used for smoothing. The finally obtained corrected trajectory reflects the actual motion characteristics considering the influence of air flow.

[0075] Step 4054: Calculate the compensation value of the gas concentration spatial distribution within the target area based on the corrected motion trajectory.

[0076] Specifically, in order to calculate the compensation value of the gas concentration spatial distribution, it is necessary to process based on the corrected motion trajectory. First, calculate the position difference ΔD = D' - D between the corrected and uncorrected trajectories. A three-dimensional grid with a spacing of 0.1 meter is established within the target area. For each grid point (x, y, z), calculate the distance r from it to the center of the corrected trajectory. Then, calculate the compensation value of the gas concentration spatial distribution at this grid point according to the distance r: 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, let ΔC = 0. This method describes the change in the spatial distribution of gas concentration through an exponential decay function, where the magnitude of the compensation value is directly related to the position difference and spatial distance, and can effectively reflect the actual influence of air flow on the gas diffusion process.

[0077] Step 50: Calibrate the initial gas concentration according to the compensation value of the gas concentration spatial distribution to obtain the target gas concentration.

[0078] Specifically, to achieve precise calibration of the target gas concentration, the weighted iteration method is used to process the gas concentration spatial distribution compensation value. A weight function w(r)=exp(-r² / 2σ²) is constructed, where r is the spatial distance and σ is the characteristic length. For each grid point within the target area, the weighted compensation value of the surrounding spatial points is calculated, i.e., ΔC'=∑(wi·ΔCi) / ∑wi, where 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 through iteration: C(n + 1)=C0 + λ·ΔC', where λ is the relaxation factor, with a value range of (0,1), and n is the number of iterations. The calculation stops when the difference between the results of two adjacent iterations is less than the preset threshold. This method takes into account the spatial correlation, and the calibration result is smoother and more continuous.

[0079] Based on the above embodiments, as another alternative 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: Step 501: Calculate the spatial gradient of the gas concentration spatial distribution compensation value.

[0080] Specifically, to accurately describe the spatial variation characteristics of the 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 within the target area, with a grid spacing of 0.1 m. For each grid point (x, y, z), the first-order differences in three directions are calculated respectively: Gx=(ΔC(x + h, y, z)-ΔC(x - h, y, z)) / (2h); Gy=(ΔC(x, y + h, z)-ΔC(x, y - h, z)) / (2h); Gz=(ΔC(x, y, z + h)-ΔC(x, y, z - h)) / (2h); where h is the grid spacing, with a value of 0.1 m, ΔC(x, y, z) represents the concentration compensation value at the point (x, y, z), and Gx, Gy, and Gz represent the concentration gradients in the x, y, and z directions respectively. Then calculate the modulus value of the spatial gradient: , and this method obtains the change rate of the compensation value in all directions in space.

[0081] Step 502: Construct a gas concentration calibration coefficient matrix based on the spatial gradient.

[0082] Specifically, to achieve precise concentration calibration, it is necessary to construct a gas concentration calibration coefficient matrix based on the spatial gradient. First, define the calibration coefficient calculation function k(G) = k0·exp(-|G| / G0), where k0 is the reference calibration coefficient (with a value of 1.0) and G0 is the reference gradient value (with a value of 0.1). For each grid point (i, j, k) in the target area, calculate the corresponding calibration coefficient k(i, j, k) according to the spatial gradient |G| at this point to form a three-dimensional calibration coefficient matrix K. This matrix reflects the weight differences in concentration calibration at different positions. Areas with large gradients obtain smaller calibration coefficients to avoid over-calibration.

[0083] Step 503: Perform weighted calibration on the initial gas concentration according to the gas concentration calibration coefficient matrix.

[0084] Specifically, to reasonably calibrate the initial gas concentration, weighted calibration needs to be performed according to the calibration coefficient matrix. For each grid point in the target area, multiply the initial gas concentration C0 by the calibration coefficient k and the compensation value ΔC at this point to obtain the calibrated concentration value C' = C0 + k·ΔC. Considering the physical meaning of the concentration, set the effective range of the calibration result: when C' < 0, let C' = 0; when C' > Cmax, let C' = Cmax, where Cmax is the saturation concentration of the gas. This weighted calibration method ensures the physical rationality of the concentration calibration.

[0085] Step 504: Iteratively optimize the gas concentration after weighted calibration until the difference between adjacent two iteration results is less than a preset threshold, and take the optimized result as the target gas concentration.

[0086] Specifically, to obtain a stable and reliable target gas concentration, it is necessary to iteratively optimize the gas concentration after weighted calibration. The relaxation iteration method is used for optimization: C(n + 1) = C(n) + α·(C' - C(n)), where C(n) is the result of the nth iteration, α is the relaxation factor (with a value of 0.5), and C' is the weighted calibration value. Calculate the maximum difference δ = max|C(n + 1) - C(n)| between adjacent two results after each iteration. Stop the iteration when δ is less than the preset threshold ε (with a value of 0.001) or the number of iterations reaches the upper limit (100 times), and take the final result as the target gas concentration.

[0087] Please refer to Figure 2 , which is a schematic diagram of the modules of a gas concentration detection and compensation system provided by an embodiment of the present application. Among them, the system includes: An initial concentration acquisition module, configured to acquire the initial gas concentration of the target gas in the target area under the current environment; An environmental parameter calculation module, configured to calculate the atmospheric pressure change rate, wind speed and flow direction data, and air density gradient in the target area under the current environment; A trajectory deviation calculation module, configured to calculate 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; A compensation value determination module, configured to correct the three-dimensional motion trajectory deviation by combining the wind speed and flow direction data and the molecular weight of the target gas to obtain a gas concentration spatial distribution compensation value; A compensation calibration module, configured to calibrate the initial gas concentration according to the gas concentration spatial distribution compensation value to obtain the target gas concentration.

[0088] Optionally, the environmental parameter calculation module is further configured to collect environmental parameters of each detection point in the current environment, and each of the detection points is uniformly arranged on a preset spiral ascending path; Determine the tangential adjacent detection points and the radial adjacent detection points of the spiral ascending path; Calculate the atmospheric pressure change rate, the wind speed and flow direction data, and the air density gradient in the target area based on the environmental parameters of the tangential adjacent detection points and the radial adjacent detection points.

[0089] Optionally, the trajectory deviation calculation module is further configured to calculate a first displacement component of gas molecules in the horizontal plane based on the atmospheric pressure change rate; Calculate a second displacement component of gas molecules in the vertical direction according to the air density gradient; Calculate the motion trajectory characteristic parameters of gas molecules based on the first displacement component and the second displacement component; Determine the three-dimensional motion trajectory deviation of gas molecules based on the motion trajectory characteristic parameters.

[0090] Optionally, the trajectory deviation calculation module is further configured to convert the first displacement component and the second displacement component into a radial component and an angular component in the spherical coordinate system; Calculate the diffusion radius deviation of gas molecules according to the radial component; Calculate the deflection angle of the gas molecule motion trajectory based on the angular component; Use the diffusion radius deviation and the deflection angle as the motion trajectory characteristic parameters.

[0091] Optionally, the compensation value determination module is further configured to obtain the wind speed and the wind direction angle in the wind speed and flow direction data; Calculate the relative mass coefficient of gas molecules according to the ratio of the molecular weight of the target gas to the standard atmospheric molecular weight; Calculate the airflow force exerted on gas molecules based on the relative mass coefficient and the wind speed; Calculate the displacement correction coefficients of gas molecules in the horizontal direction and the vertical direction according to the airflow force; Based on the displacement correction coefficients in the horizontal and vertical directions, correct the three-dimensional motion trajectory deviation to obtain the gas concentration spatial distribution compensation value.

[0092] Optionally, the compensation value determination module is further configured to convert the three-dimensional motion trajectory deviation to the frequency domain space by using Fourier transform; Decompose the trajectory deviation in the frequency domain space into horizontal and vertical direction components, and perform convolution operations with the corresponding displacement correction coefficients in the horizontal and vertical directions respectively; Convert the convolution operation result back to the time domain space through inverse Fourier transform to obtain the corrected motion trajectory; Calculate the gas concentration spatial distribution compensation value in the target area based on the corrected motion trajectory.

[0093] Optionally, the compensation calibration module is further configured to calculate the spatial gradient of the gas concentration spatial distribution compensation value; Construct a gas concentration calibration coefficient matrix based on the spatial gradient; And perform weighted calibration on the initial gas concentration according to the calibration coefficient matrix; Iteratively optimize the weighted calibrated gas concentration until the difference between adjacent two iteration results is less than a preset threshold, and take the optimized result as the target gas concentration.

[0094] It should be noted that: when the system provided in the above embodiment realizes its functions, only the division of the above functional modules is used for illustration. In actual application, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the device is 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 belong to the same concept, and the specific implementation process can be seen in the method embodiment, which will not be elaborated here.

[0095] The embodiment of the present application also provides a computer storage medium, which can store multiple instructions. The instructions are suitable for being loaded and executed by a processor to perform a gas concentration detection and compensation method in the above embodiment. The specific execution process can refer to the specific description in the above embodiment, and will not be elaborated here.

[0096] Please refer to Figure 3 The present application also discloses an electronic device. Figure 3 It is a schematic structural diagram of an electronic device disclosed in the embodiment of the present application. 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.

[0097] Among them, the communication bus 302 is used to realize the connection and communication between these components.

[0098] Among them, the user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may further include a standard wired interface and a wireless interface.

[0099] Among them, the network interface 304 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0100] Among them, the processor 301 may include one or more processing cores. The processor 301 connects various parts within the entire server through various interfaces and circuits. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by invoking data stored in the memory 305, it performs various functions of the server and processes data. Optionally, the processor 301 may be implemented in at least one of the following hardware forms: digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 301 may integrate one or a combination of several of the central processing unit (CPU), graphics processing unit (GPU), and modem, etc. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 301 and may be implemented separately through a single chip.

[0101] Among them, the memory 305 may include a Random Access Memory (RAM), or may also include a 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. Among them, the program storage area can store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area can store the data involved in the above-mentioned method embodiments. Optionally, the memory 305 may also be at least one storage device located far from the aforementioned processor 301. Refer to Figure 3 , in the memory 305 as a computer storage medium, an operating system, a network communication module, a user interface module, and an application program of a gas concentration detection and compensation method may be included.

[0102] In Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user to obtain the data input by the user; while the processor 301 can be used to call the application program of a gas concentration detection and compensation method stored in the memory 305. When executed by one or more processors 301, the electronic device 300 is caused to execute the method of one or more of the above embodiments. It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences 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 by this application.

[0103] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0104] In several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, 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 displayed or discussed coupling or direct coupling or communication connection to each other can be through some service interfaces. The indirect coupling or communication connection of devices or units can be in electrical or other forms.

[0105] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0106] In addition, the functional units in each embodiment of the present application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0107] If the integrated unit is implemented in the form of 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 the present application, in essence, or the part that contributes to the prior art, or all or part of this 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 to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present application. And the aforementioned memory includes: various media such as USB flash drives, mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0108] The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, all equivalent changes and modifications made in accordance with the teachings of the present disclosure still fall within the scope covered by the present disclosure. Those skilled in the art will easily think of other implementation schemes of the present disclosure after considering the specification and the practice of the present disclosure.

[0109] The present application aims to cover any variations, uses, or adaptive changes of the present disclosure. These variations, uses, or adaptive changes follow the general principles of the present disclosure and include common general knowledge or conventional technical means in the technical field not recorded in the present disclosure. The specification and the embodiments are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A gas concentration detection and compensation method, characterized in that: The method comprises: Obtain the initial gas concentration of the target gas in the target area under the current environment; 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; 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 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 and 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 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; The three-dimensional motion trajectory deviation of the gas molecules is determined based on the motion trajectory characteristic parameters.

4. The gas concentration detection and compensation method according to claim 3, wherein 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.

5. The gas concentration detection and compensation method according to claim 1, wherein The correction of the three-dimensional motion trajectory deviation by combining the wind speed and flow direction data and the molecular weight of the target gas to obtain a gas concentration spatial distribution compensation value includes: 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; 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.

6. The gas concentration detection compensation method according to claim 5, 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; Decompose the trajectory deviation in the frequency domain space into horizontal and vertical components, and perform convolution operations with the corresponding displacement correction coefficients in the horizontal and vertical directions respectively; Convert the convolution operation result into the time domain space through inverse Fourier transform to obtain the corrected motion trajectory; Calculate the gas concentration spatial distribution compensation value within the target area based on the corrected motion trajectory; 7. The gas concentration detection and compensation method according to claim 1, wherein The calibration of the initial gas concentration according to the gas concentration spatial distribution compensation value to obtain the target gas concentration includes: Calculate the spatial gradient of the gas concentration spatial distribution compensation value; Construct a gas concentration calibration coefficient matrix based on the spatial gradient; Perform weighted calibration on the initial gas concentration according to the gas concentration calibration coefficient matrix; Iteratively optimize the weighted calibrated gas concentration until the difference between adjacent two iteration results is less than a preset threshold, and take the optimized result as the target gas concentration.

8. A gas concentration detection and compensation system, characterized in that, The system includes: An initial concentration acquisition module for acquiring the initial gas concentration of the target gas in the target area under the current environment; An environmental parameter calculation module for calculating the atmospheric pressure change rate, wind speed and flow direction data, and air density gradient in the target area under the current environment; A trajectory deviation calculation module for 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; A compensation value determination module for correcting the three-dimensional motion trajectory deviation in combination with the wind speed and flow direction data and the molecular weight of the target gas to obtain the gas concentration spatial distribution compensation value; A compensation calibration module for calibrating the initial gas concentration according to the gas concentration spatial distribution compensation value to obtain the target gas concentration.

9. A computer-readable storage medium, characterized in that, A computer-readable storage medium stores multiple instructions, and the instructions are suitable for being loaded and executed by a processor to perform the gas concentration detection and compensation method according to any one of claims 1-7.

10. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface. 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 to enable the electronic device to perform the gas concentration detection and compensation method according to any one of claims 1-7.

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