Artificial intelligence-based oil refining area environment monitoring method and device, electronic equipment and storage medium

Abstract

The present application provides a kind of based on artificial intelligence's oil refining area environment monitoring method, device, electronic equipment and storage medium, it is related to oil refining area environment monitoring technical field, by monitoring planning, determine vertical monitoring line;Current area wind speed is detected, and hierarchical cross monitoring flight planning is carried out, and flight planning route is generated;Spectral measurement and data analysis of multiple pollutants are carried out;Pollution emission flux is calculated;Demand interaction is carried out based on artificial intelligence technology, and multiple pollution emission fluxes are visually processed.The method can effectively improve the intelligent degree of oil refining area environment monitoring, reduce the monitoring time, improve the data processing efficiency, timely respond to the environmental monitoring demand of oil refining area, realize fast, accurate environmental monitoring and pollution display.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring technology in oil refining areas, and in particular to an artificial intelligence-based method, device, electronic equipment, and storage medium for environmental monitoring in oil refining areas. Background Technology

[0002] Oil refineries generate various pollutants such as waste gas, wastewater, solid waste, and noise during the production process. These pollutants may affect the surrounding air, water quality, soil, and even ecological health.

[0003] Environmental monitoring in oil refining areas mainly involves the regular or real-time monitoring of various gaseous pollutants emitted into the atmosphere from the oil refining area. The aim is to ensure that the gases emitted by the oil refinery meet national or local environmental protection standards, while protecting the surrounding environment and public health from pollution.

[0004] In the existing technology, many steps in the environmental monitoring process of oil refining areas require manual intervention. The monitoring process is cumbersome, takes a long time, and data processing is slow. The level of intelligence is not high, and it is impossible to respond to the environmental monitoring needs of oil refining areas in a timely manner and to carry out rapid and accurate environmental monitoring and pollution display. Summary of the Invention

[0005] This invention provides an artificial intelligence-based method, device, electronic equipment, and storage medium for environmental monitoring in oil refining areas, in order to address the deficiencies in related technologies.

[0006] This invention provides an artificial intelligence-based method for environmental monitoring in oil refining areas, comprising: Determine the oil refining monitoring area, and according to the environmental monitoring density, carry out monitoring planning for the oil refining monitoring area and determine the vertical monitoring line; The current wind speed in the oil refining monitoring area is detected, and the wind speed is divided into horizontal and vertical components. Based on the horizontal wind speed, a layered and intersecting monitoring flight plan is performed on the vertical monitoring line to generate the flight plan route of the UAV. According to the flight plan route, multiple spectral measurements and data analysis of pollutants are performed on the vertical monitoring line, and the measured concentration data is recorded. Based on the measured concentration data and the vertical wind speed, the pollution emission flux at the vertical monitoring line is calculated; The system interacts with users based on artificial intelligence technology to obtain their monitoring and display requirements, and then visualizes the pollution emission flux according to these requirements.

[0007] According to the present invention, an artificial intelligence-based environmental monitoring method for oil refining areas includes, in which the monitoring area is planned according to environmental monitoring density, and vertical monitoring lines are determined, including: Obtain an electronic map of the oil refining monitoring area; In the electronic map of the area, multiple environmental monitoring points are selected according to the environmental monitoring density; The vertical monitoring line is generated based on the multiple environmental monitoring points.

[0008] According to the present invention, an artificial intelligence-based environmental monitoring method for oil refining areas, wherein the method generates a flight path for a UAV by performing layered and intersecting monitoring flight planning based on the horizontal wind speed along the vertical monitoring line, includes: The initial planning for monitoring flight is based on the horizontal wind speed, which determines the monitoring flight direction and monitoring flight speed of the UAV. Based on the monitored flight direction and the monitored flight speed, a basic flight path is planned on the vertical monitoring line to generate a basic flight path; Based on the number of cross-monitoring layers, the basic flight route is optimized in multiple layers to generate the flight planning route.

[0009] According to the present invention, an artificial intelligence-based environmental monitoring method for oil refining areas includes performing multiple spectral measurements and data analysis of pollutants along the vertical monitoring line according to the flight plan route, and recording the measured concentration data, including: According to the flight planning route, the UAV is controlled and positioned for flight monitoring, and a spectral measurement command is generated when it reaches the vertical monitoring line; According to the spectral measurement instructions, perform spectral measurements of pollutants and obtain the spectral measurement data; The spectral measurement data is analyzed, and the measured concentration data is recorded.

[0010] According to the present invention, an artificial intelligence-based environmental monitoring method for oil refining areas is provided, wherein calculating the pollution emission flux at the vertical monitoring line based on the measured concentration data and the vertical wind speed includes: Obtain the flight parameters of the drone; Based on the flight parameters, match the influence coefficient; The pollution emission flux is calculated based on the measured concentration data, the vertical wind speed, and the influence coefficient.

[0011] According to the present invention, an artificial intelligence-based environmental monitoring method for oil refining areas is provided, wherein calculating the pollution emission flux based on the measured concentration data, the vertical wind speed, and the influence coefficient includes: Where i represents different vertical monitoring lines, F iLet y be the pollution emission flux of vertical monitoring line i. min The lowest floor height, y max D is the height of the highest floor. i (y) represents the pollutant concentration measured at height y of the vertical monitoring line i, k is the influence coefficient, and V p The wind speed in the vertical section is denoted as .

[0012] According to the present invention, an artificial intelligence-based environmental monitoring method for oil refining areas is provided, wherein the artificial intelligence technology interacts with users to obtain their monitoring and display requirements, and visualizes the pollution emission flux according to the monitoring and display requirements, including: Create user interfaces based on artificial intelligence technology; Through the demand interaction interface, the user can interact with the demand and obtain the monitoring and display demand. Create a basic display environment according to the monitoring and display requirements; In the basic display environment, the pollution emission flux is visualized.

[0013] The present invention also provides an artificial intelligence-based environmental monitoring device for oil refining areas, comprising: The regional monitoring planning module is used to determine the oil refining monitoring area, plan the monitoring of the oil refining monitoring area according to the environmental monitoring density, and determine the vertical monitoring line; The monitoring flight planning module is used to detect the current regional wind speed in the oil refining monitoring area, divide the wind speed into horizontal and vertical parts, and perform layered and intersecting monitoring flight planning based on the horizontal wind speed on the vertical monitoring line to generate the flight planning route of the UAV. The spectral measurement and analysis module is used to perform multiple spectral measurements and data analysis of pollutants along the vertical monitoring line according to the flight plan route, and record the measured concentration data. The emission flux calculation module is used to calculate the pollution emission flux at the vertical monitoring line based on the measured concentration data and the vertical wind speed. The pollution visualization module is used to interact with users based on artificial intelligence technology, obtain the users' monitoring and display requirements, and visualize the pollution emission flux according to the monitoring and display requirements.

[0014] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the artificial intelligence-based environmental monitoring method for oil refining areas as described above.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the artificial intelligence-based environmental monitoring method for oil refining areas as described above.

[0016] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the artificial intelligence-based environmental monitoring method for oil refining areas as described above.

[0017] This invention provides an artificial intelligence-based method, device, electronic equipment, and storage medium for environmental monitoring in oil refining areas. The method involves: planning monitoring to determine vertical monitoring lines; detecting current regional wind speeds and performing layered, cross-sectional monitoring flight planning to generate flight routes; conducting multiple spectral measurements and data analysis of pollutants; calculating pollution emission fluxes; and using artificial intelligence technology for demand interaction to visualize multiple pollution emission fluxes. This method effectively improves the intelligence level of environmental monitoring in oil refining areas, reduces monitoring time, increases data processing efficiency, and promptly responds to environmental monitoring needs in oil refining areas, achieving rapid and accurate environmental monitoring and pollution display. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this invention or related technologies, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the artificial intelligence-based environmental monitoring method for oil refining areas provided by the present invention.

[0020] Figure 2 This is a schematic diagram of the monitoring planning process for the monitoring area in the artificial intelligence-based environmental monitoring method for oil refining areas provided by the present invention.

[0021] Figure 3 This is a schematic diagram of the process of layered cross-monitoring flight planning in the artificial intelligence-based environmental monitoring method for oil refining areas provided by the present invention.

[0022] Figure 4 This is a schematic diagram of the spectral measurement and data analysis process in the artificial intelligence-based environmental monitoring method for oil refining areas provided by the present invention.

[0023] Figure 5 This is a schematic diagram of the process for calculating pollution emission flux in the artificial intelligence-based environmental monitoring method for oil refining areas provided by the present invention.

[0024] Figure 6 This is a schematic diagram of the process for visualizing pollution emission flux in the artificial intelligence-based environmental monitoring method for oil refining areas provided by the present invention.

[0025] Figure 7 This is a schematic diagram of the structure of the artificial intelligence-based environmental monitoring device for oil refining areas provided by the present invention.

[0026] Figure 8 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0028] In existing technologies, many steps in the environmental monitoring process of oil refinery areas require manual intervention. This results in cumbersome processes, long monitoring times, slow data processing, and low levels of automation, making it impossible to respond promptly to the environmental monitoring needs of oil refinery areas and to provide rapid and accurate environmental monitoring and pollution display. Therefore, this invention provides an artificial intelligence-based environmental monitoring method for oil refinery areas.

[0029] Figure 1 This is a flowchart illustrating an artificial intelligence-based environmental monitoring method for oil refining areas provided in an embodiment of the present invention. Figure 1 As shown, the method includes: S11, Determine the oil refining monitoring area, and according to the environmental monitoring density, carry out monitoring planning for the oil refining monitoring area and determine the vertical monitoring line; S12, detect the current wind speed in the oil refining monitoring area, divide the wind speed into horizontal and vertical parts, and based on the horizontal wind speed, perform layered cross-monitoring flight planning on the vertical monitoring line to generate the flight planning route of the UAV. S13, according to the flight plan route, perform multiple spectral measurements and data analysis of pollutants on the vertical monitoring line, and record the measured concentration data; S14. Calculate the pollution emission flux at the vertical monitoring line based on the measured concentration data and the vertical wind speed. S15. Interact with the user based on artificial intelligence technology to obtain the user's monitoring and display requirements, and visualize the pollution emission flux according to the monitoring and display requirements.

[0030] Specifically, the artificial intelligence-based environmental monitoring method for oil refining areas provided in this embodiment of the invention is executed by an artificial intelligence-based environmental monitoring device for oil refining areas. This device can be configured in a computer, which can be a local computer or a cloud computer. The local computer can be a computer, tablet, etc., and no specific limitation is made here.

[0031] First, execute step S11 to determine the refining monitoring area, which is the refining area that needs to be environmentally monitored.

[0032] Subsequently, by conducting monitoring planning for the oil refining monitoring area, multiple vertical monitoring lines can be identified.

[0033] Then, step S12 is executed, which involves conducting meteorological monitoring of the oil refining monitoring area to obtain the current regional wind speed. Here, the current regional wind speed is a comprehensive data that includes both the wind direction and wind speed values ​​in the current area.

[0034] The wind speed in the current area is decomposed into horizontal and vertical vectors to obtain the horizontal and vertical wind speed components. The horizontal wind speed is a comprehensive data set including both wind direction and wind speed values ​​in the horizontal region; the vertical wind speed is a comprehensive data set including both wind direction and wind speed values ​​in the vertical region.

[0035] By utilizing the horizontal wind speed, layered and intersecting monitoring flight planning is carried out on the vertical monitoring lines to generate the flight planning route of the UAV.

[0036] Following step S13, the UAV, equipped with a spectrometer, flies along a planned flight path. By measuring the absorption, reflection, or emission spectra of substances at different wavelengths, it can acquire information such as the composition and structure of substances along multiple vertical monitoring lines, identify and determine pollutants, and obtain spectral measurement data. After preprocessing the multiple spectral measurement data such as noise reduction and smoothing, and then analyzing the data, the characteristic absorption peaks of pollutants are identified. Based on the intensity and position of the characteristic absorption peaks, combined with the known absorption coefficient and atmospheric conditions, the measured concentration of pollutants can be determined, thereby obtaining the measured concentration data.

[0037] Here, pollutants may include sulfur dioxide (SO2), carbon monoxide (CO), and nitrogen oxides (NOx). X Harmful emissions include methane (CH4), volatile organic compounds (VOCs), and ozone (O3).

[0038] Then, step S14 is performed to calculate the pollution emission flux at each vertical monitoring line using the measured concentration data and the vertical wind speed.

[0039] Finally, step S15 is executed, which uses artificial intelligence technology to interact with the user, obtain the user's monitoring and display requirements, and visualize the pollution emission flux according to the monitoring and display requirements. For example, if the monitoring and display requirement is "I want to view the pollutant situation in the real environment," then the visualized display interface can show the pollution emission flux in the real environment.

[0040] The artificial intelligence-based environmental monitoring method for oil refining areas provided in this invention involves: determining vertical monitoring lines through monitoring planning; detecting current regional wind speeds and performing layered, cross-sectional monitoring flight planning to generate flight routes; conducting multiple spectral measurements and data analysis of pollutants; calculating pollution emission fluxes; and using artificial intelligence technology for demand interaction to visualize multiple pollution emission fluxes. This method effectively improves the intelligence level of environmental monitoring in oil refining areas, reduces monitoring time, increases data processing efficiency, and promptly responds to environmental monitoring needs in oil refining areas, achieving rapid and accurate environmental monitoring and pollution display.

[0041] like Figure 2 As shown, based on the above embodiments, the step of planning the monitoring of the oil refining monitoring area according to the environmental monitoring density and determining the vertical monitoring line includes: S21, Obtain an electronic map of the oil refining monitoring area; S22, Select multiple environmental monitoring points in the regional electronic map according to the environmental monitoring density; S23, Generate the vertical monitoring line based on the multiple environmental monitoring points.

[0042] Specifically, an electronic map of the oil refining monitoring area can be obtained first. Then, according to a preset environmental monitoring density, the distribution of monitoring locations can be planned on the electronic map. Multiple environmental monitoring points can be selected, and straight lines perpendicular to the horizontal plane can be constructed at these points to generate multiple vertical monitoring lines. Each environmental monitoring point can correspond to one vertical monitoring line.

[0043] like Figure 3 As shown, based on the above embodiments, the step of generating a UAV flight path by performing layered intersecting monitoring flight planning based on the horizontal wind speed along the vertical monitoring line includes: S31, based on the horizontal wind speed, perform initial planning for monitoring flight, and determine the monitoring flight direction and monitoring flight speed of the UAV; S32, according to the monitored flight direction and the monitored flight speed, perform basic route planning for the monitored flight on the vertical monitoring line to generate a basic flight route; S33, according to the number of cross-monitoring layers, perform multi-level optimization on the basic flight route to generate the flight planning route.

[0044] Specifically, the initial planning for the monitoring flight is based on the wind direction and wind speed values ​​corresponding to the horizontal wind speed, determining the monitoring flight direction and speed of the UAV. Here, the monitoring flight direction is consistent with the wind direction in the horizontal wind speed calculation; the monitoring flight speed is consistent with the wind speed values ​​in the horizontal wind speed calculation.

[0045] Based on the monitoring flight direction and speed, basic flight path planning can be carried out at multiple vertical monitoring lines to generate basic flight paths. This allows the basic flight paths to pass through multiple vertical monitoring lines with relatively static wind speeds in the horizontal portion, effectively reducing the impact of natural winds on pollutant measurements in the oil refining monitoring area.

[0046] Based on the preset number of cross-monitoring layers, the basic flight route is optimized in multiple layers to generate a flight planning route. This allows the flight planning route to pass through multiple vertical monitoring lines at multiple different horizontal altitudes with relatively static wind speeds in the horizontal portion. As a result, at different vertical monitoring lines and at different heights of each vertical monitoring line, the impact of natural wind on pollutant measurement in the oil refining monitoring area can be effectively reduced.

[0047] like Figure 4 As shown, based on the above embodiments, the step of performing multiple spectral measurements and data analysis of pollutants along the vertical monitoring line according to the flight plan route, and recording the measured concentration data, includes: S41, Control and position the UAV for flight monitoring according to the flight planning route, and generate a spectral measurement command when it arrives at the vertical monitoring line; S42, according to the spectral measurement instruction, perform spectral measurement of pollutants and obtain the spectral measurement data; S43, perform data analysis on the spectral measurement data and record the measured concentration data.

[0048] Specifically, in this embodiment of the invention, the drone can be controlled and positioned for flight monitoring according to the planned flight route, the drone's positioning signal can be acquired in real time, and the drone's positioning signal can be identified. When it is determined that the drone has arrived at any vertical monitoring line, a spectral measurement command is generated and sent to the drone, so that the drone performs spectral measurement of pollutants according to the spectral measurement command, and acquires spectral measurement data. This allows the acquisition of multiple spectral measurement data at different heights for each vertical monitoring line, and then the multiple spectral measurement data are analyzed to record the measured concentration data of the oil refining monitoring area.

[0049] like Figure 5As shown, based on the above embodiment, the step of calculating the pollution emission flux at the vertical monitoring line according to the measured concentration data and the vertical wind speed includes: S51, Obtain the flight parameters of the UAV; S52, based on the flight parameters, match the influence coefficient; S53, calculate the pollution emission flux based on the measured concentration data, the vertical wind speed, and the influence coefficient.

[0050] Specifically, the impact coefficient is related to the performance of the UAV. During the flight of the UAV, the interaction with the surrounding air will cause air disturbance, which will affect the detection of pollutants. Setting the impact coefficient can balance the detection impact caused by air disturbance, thereby improving the accuracy of pollutant detection and making the calculation of pollution emission flux more in line with reality.

[0051] Based on the above embodiments, the step of calculating the pollution emission flux according to the measured concentration data, the vertical wind speed, and the influence coefficient includes: Where i represents different vertical monitoring lines, F i Let y be the pollution emission flux of vertical monitoring line i. min The lowest floor height, y max D is the height of the highest floor. i (y) represents the pollutant concentration measured at height y of the vertical monitoring line i, k is the influence coefficient, and V p The wind speed in the vertical section is denoted as .

[0052] like Figure 6 As shown, based on the above embodiments, the step of interacting with users using artificial intelligence technology to obtain their monitoring and display requirements, and then visualizing the pollution emission flux according to those requirements, includes: S61, based on artificial intelligence technology, creates a user interface for meeting user needs; S62, through the demand interaction interface, interact with the user to obtain the monitoring and display demand; S63, Create a basic display environment according to the monitoring and display requirements; S64, In the basic display environment, the pollution emission flux is visualized.

[0053] Specifically, in this embodiment of the invention, a demand interaction interface is created based on artificial intelligence technology. When a user needs to view the pollutant situation in the oil refining monitoring area, they can input their demand through the demand interaction interface in the form of voice, text, or other means. This allows the user's monitoring and display needs to be obtained, and then the monitoring and display needs are identified. Based on the monitoring and display needs, a basic display environment is created, and then multiple pollutant emission fluxes are visualized in the basic display environment, making it convenient for users to intuitively view the pollutant situation in the oil refining monitoring area.

[0054] It is understandable that different basic display environments may be created based on different monitoring and display needs. These different basic display environments may include: two-dimensional map display environment, three-dimensional map display environment, real-scene map display environment, and area outline display environment. For example, in this embodiment of the invention, if the user's monitoring and display need is entered by voice as "I want to view the pollutant situation in the real-scene environment," then the corresponding basic display environment is "real-scene map display environment."

[0055] like Figure 7 As shown, based on the above embodiments, this embodiment of the invention provides an artificial intelligence-based environmental monitoring device for oil refining areas, comprising: The regional monitoring planning module 71 is used to determine the oil refining monitoring area, carry out monitoring planning for the oil refining monitoring area according to the environmental monitoring density, and determine the vertical monitoring line; The monitoring flight planning module 72 is used to detect the current regional wind speed in the oil refining monitoring area, divide the wind speed into horizontal and vertical parts, and perform layered and intersecting monitoring flight planning based on the horizontal wind speed on the vertical monitoring line to generate the flight planning route of the UAV. The spectral measurement and analysis module 73 is used to perform multiple spectral measurements and data analysis of pollutants along the vertical monitoring line according to the flight planning route, and record the measured concentration data. The emission flux calculation module 74 is used to calculate the pollution emission flux at the vertical monitoring line based on the measured concentration data and the vertical wind speed. The pollution visualization module 75 is used to interact with users based on artificial intelligence technology, obtain the user's monitoring and display requirements, and visualize the pollution emission flux according to the monitoring and display requirements.

[0056] Based on the above embodiments, the regional monitoring and planning module is specifically used for: Obtain an electronic map of the oil refining monitoring area; In the electronic map of the area, multiple environmental monitoring points are selected according to the environmental monitoring density; The vertical monitoring line is generated based on the multiple environmental monitoring points.

[0057] Based on the above embodiments, the monitoring flight planning module is specifically used for: The initial planning for monitoring flight is based on the horizontal wind speed, which determines the monitoring flight direction and monitoring flight speed of the UAV. Based on the monitored flight direction and the monitored flight speed, a basic flight path is planned on the vertical monitoring line to generate a basic flight path; Based on the number of cross-monitoring layers, the basic flight route is optimized in multiple layers to generate the flight planning route.

[0058] Based on the above embodiments, the spectral measurement and analysis module is specifically used for: According to the flight planning route, the UAV is controlled and positioned for flight monitoring, and a spectral measurement command is generated when it reaches the vertical monitoring line; According to the spectral measurement instructions, perform spectral measurements of pollutants and obtain the spectral measurement data; The spectral measurement data is analyzed, and the measured concentration data is recorded.

[0059] Based on the above embodiments, the emission flux calculation module is specifically used for: Obtain the flight parameters of the drone; Based on the flight parameters, match the influence coefficient; The pollution emission flux is calculated based on the measured concentration data, the vertical wind speed, and the influence coefficient.

[0060] Based on the above embodiments, the emission flux calculation module is further specifically used for: Where i represents different vertical monitoring lines, F i Let y be the pollution emission flux of vertical monitoring line i. min The lowest floor height, y max D is the height of the highest floor. i (y) represents the pollutant concentration measured at height y of the vertical monitoring line i, k is the influence coefficient, and V p The wind speed in the vertical section is denoted as .

[0061] Based on the above embodiments, the pollution visualization module is specifically used for: Create user interfaces based on artificial intelligence technology; Through the demand interaction interface, the user can interact with the demand and obtain the monitoring and display demand. Create a basic display environment according to the monitoring and display requirements; In the basic display environment, the pollution emission flux is visualized.

[0062] Specifically, the functions of each module in the AI-based oil refining area environmental monitoring device provided in this embodiment of the invention correspond one-to-one with the operation flow of each step in the above-mentioned method-like embodiments, and the achieved effects are also the same. For details, please refer to the above embodiments, and this will not be repeated in this embodiment of the invention.

[0063] Figure 8 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 8 As shown, the electronic device may include a processor 810, a communications interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communications interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 can call logical instructions in the memory 830 to execute the artificial intelligence-based environmental monitoring method for oil refining areas provided in the above embodiments.

[0064] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to related technologies, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0065] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the artificial intelligence-based environmental monitoring method for oil refining areas provided in the above embodiments.

[0066] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the artificial intelligence-based environmental monitoring method for oil refining areas provided in the above embodiments.

[0067] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The 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 the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0068] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of software products. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0069] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An artificial intelligence-based method for environmental monitoring in oil refining areas, characterized in that, include: Determine the oil refining monitoring area, and according to the environmental monitoring density, carry out monitoring planning for the oil refining monitoring area and determine the vertical monitoring line; The current wind speed in the oil refining monitoring area is detected, the wind speed is divided into horizontal and vertical parts, and based on the horizontal wind speed, a layered and intersecting monitoring flight plan is performed on the vertical monitoring line to generate the flight planning route of the UAV. According to the flight plan route, multiple spectral measurements and data analysis of pollutants were conducted along the vertical monitoring line, and the measured concentration data were recorded. Based on the measured concentration data and the vertical wind speed, the pollution emission flux at the vertical monitoring line is calculated; The system interacts with users based on artificial intelligence technology to obtain their monitoring and display requirements, and then visualizes the pollution emission flux according to these requirements.

2. The method for monitoring the environment of oil refining areas based on artificial intelligence according to claim 1, characterized in that, The process of planning the monitoring of the oil refining monitoring area according to environmental monitoring density and determining vertical monitoring lines includes: Obtain an electronic map of the oil refining monitoring area; In the electronic map of the area, multiple environmental monitoring points are selected according to the environmental monitoring density; The vertical monitoring line is generated based on the multiple environmental monitoring points.

3. The method for monitoring the environment of oil refining areas based on artificial intelligence according to claim 1, characterized in that, The process of generating a UAV flight path by performing layered intersecting monitoring flight planning based on the horizontal wind speed along the vertical monitoring line includes: The initial planning for monitoring flight is based on the horizontal wind speed, which determines the monitoring flight direction and monitoring flight speed of the UAV. Based on the monitored flight direction and the monitored flight speed, a basic flight path is planned on the vertical monitoring line to generate a basic flight path; Based on the number of cross-monitoring layers, the basic flight route is optimized in multiple layers to generate the flight planning route.

4. The method for monitoring the environment of oil refining areas based on artificial intelligence according to claim 1, characterized in that, Following the flight plan route, multiple spectral measurements and data analysis of pollutants are performed along the vertical monitoring line, and the measured concentration data is recorded, including: According to the flight planning route, the UAV is controlled and positioned for flight monitoring, and a spectral measurement command is generated when it reaches the vertical monitoring line; According to the spectral measurement instructions, perform spectral measurements of pollutants to obtain spectral measurement data; parse the spectral measurement data and record the measured concentration data.

5. The method for monitoring the environment of an oil refining area based on artificial intelligence according to any one of claims 1-4, characterized in that, The step of calculating the pollution emission flux at the vertical monitoring line based on the measured concentration data and the vertical wind speed includes: Obtain the flight parameters of the drone; Based on the flight parameters, match the influence coefficient; The pollution emission flux is calculated based on the measured concentration data, the vertical wind speed, and the influence coefficient.

6. The method for monitoring the environment of oil refining areas based on artificial intelligence according to claim 5, characterized in that, The calculation of the pollution emission flux based on the measured concentration data, the vertical wind speed, and the influence coefficient includes: Where i represents different vertical monitoring lines, F i Let y be the pollution emission flux of vertical monitoring line i. min The lowest floor height, y max D is the height of the highest floor. i (y) represents the pollutant concentration measured at height y of the vertical monitoring line i, k is the influence coefficient, and V p The wind speed in the vertical section is denoted as .

7. The method for monitoring the environment of an oil refining area based on artificial intelligence according to any one of claims 1-4, characterized in that, The process of interacting with users based on artificial intelligence technology to obtain their monitoring and display requirements, and then visualizing the pollution emission flux according to those requirements, includes: Create user interfaces based on artificial intelligence technology; Through the demand interaction interface, the user can interact with the demand and obtain the monitoring and display demand. Create a basic display environment according to the monitoring and display requirements; In the basic display environment, the pollution emission flux is visualized.

8. An artificial intelligence-based environmental monitoring device for oil refining areas, characterized in that, include: The regional monitoring planning module is used to determine the oil refining monitoring area, plan the monitoring of the oil refining monitoring area according to the environmental monitoring density, and determine the vertical monitoring line; The monitoring flight planning module is used to detect the current regional wind speed in the oil refining monitoring area, divide the wind speed into horizontal and vertical parts, and perform layered and intersecting monitoring flight planning based on the horizontal wind speed on the vertical monitoring line to generate the flight planning route of the UAV. The spectral measurement and analysis module is used to perform multiple spectral measurements and data analysis of pollutants along the vertical monitoring line according to the flight plan route, and record the measured concentration data. The emission flux calculation module is used to calculate the pollution emission flux at the vertical monitoring line based on the measured concentration data and the vertical wind speed. The pollution visualization module is used to interact with users based on artificial intelligence technology, obtain the users' monitoring and display requirements, and visualize the pollution emission flux according to the monitoring and display requirements.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the artificial intelligence-based environmental monitoring method for oil refining areas as described in any one of claims 1-7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the artificial intelligence-based environmental monitoring method for oil refining areas as described in any one of claims 1-7.

Images