Forest fire prevention unmanned aerial vehicle automatic inspection system based on meteorological factors

Abstract

The application discloses a forest fire prevention unmanned plane automatic inspection system based on meteorological factors, which comprises a meteorological data acquisition device, an unmanned plane field and an edge computing device, a remote data analysis and flight management system and an unmanned plane; the meteorological data acquisition device is used for collecting meteorological factor data under different meteorological conditions, special holidays or different seasons in real time; the unmanned plane field and the edge computing device are used for receiving the meteorological factor data, performing cleaning processing to obtain processed data, and controlling the unmanned plane to cruise in an inspection area; the remote data analysis and flight management system is used for analyzing the processed data, judging forest fire danger meteorological grades under different conditions, formulating different unmanned plane cruise tasks, and sending the unmanned plane cruise tasks; the unmanned plane automatically executes the cruise tasks according to control commands; the system can automatically increase the unmanned plane forest fire prevention inspection frequency according to special nodes, meets actual inspection requirements, and makes forest fire prevention more efficient and intelligent.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of forest fire prevention unmanned aerial vehicle inspection, and particularly relates to a forest fire prevention unmanned aerial vehicle automatic inspection system based on meteorological factors. BACKGROUND

[0002] The traditional unmanned aerial vehicle inspection system generally performs cruising according to a pre-set inspection task and cruising frequency fixed time point, without considering the fire occurrence probability under different seasons and different meteorological conditions, so that the unmanned aerial vehicle forest fire prevention inspection frequency cannot meet the actual inspection demand; or a special date, a special season and a real-time meteorological condition are set by an inspector, and the cruising plan and the cruising frequency are manually adjusted, which needs to consume a large amount of manpower and material resources, has low timeliness, causes waste of human resources and reduction of inspection efficiency. SUMMARY

[0003] The present application provides a forest fire prevention unmanned aerial vehicle automatic inspection system based on meteorological factors, to overcome the technical problem that the existing unmanned aerial vehicle forest fire prevention inspection system needs to set and adjust the cruising plan and the cruising frequency by an inspector in advance when performing an inspection task, consumes a large amount of manpower and material resources, has low efficiency, and does not consider the different fire occurrence probabilities under different meteorological conditions, special holidays or seasons, so that the unmanned aerial vehicle forest fire prevention inspection frequency cannot meet the actual inspection demand.

[0004] In order to achieve the above-mentioned purpose, the technical scheme of the present application is as follows:

[0005] A forest fire prevention unmanned aerial vehicle automatic inspection system based on meteorological factors, comprising: a meteorological data acquisition device, an unmanned aerial vehicle airport and an edge computing device, a remote data analysis and flight management system and an unmanned aerial vehicle;

[0006] The meteorological data acquisition device is used for real-time acquisition of meteorological factor data under different meteorological conditions, special holidays or different seasons, and the meteorological factor data includes but is not limited to temperature, air humidity, wind speed, rainfall and snow thickness;

[0007] The unmanned aerial vehicle airport and the edge computing device include an edge computing unit and an unmanned aerial vehicle airport unit, the edge computing unit is used for receiving meteorological factor data and processing the meteorological factor data to obtain processed data, and the unmanned aerial vehicle airport unit is used for controlling the unmanned aerial vehicle to cruise in the inspection area;

[0008] The remote data analysis and flight management system is used for receiving the processed data, analyzing the processed data, judging the forest fire danger meteorological grade under different meteorological conditions, special holidays or different seasons, formulating different cruising tasks of the unmanned aerial vehicle according to the forest fire danger meteorological grade, and sending the cruising tasks of the unmanned aerial vehicle to the unmanned aerial vehicle airport unit.

[0009] The unmanned aerial vehicle automatically performs a cruise task according to the control command of the unmanned airfield unit, and completes automatic cruising in the inspection area.

[0010] Further, the remote data analysis and flight management system comprises a data communication module, a data storage module, a flight task calculation module, a flight task manual correction module and a route planning module.

[0011] The data communication module is used for receiving the processed data sent by the edge computing unit and sending control command data to the flight task calculation module, the flight task manual correction module and the route planning module;

[0012] The data storage module is used for storing the cruise task obtained by the flight task calculation module;

[0013] The flight task calculation module is used for judging the forest fire danger weather grade under different weather conditions, special holidays or different seasons according to the processed data received by the data communication module every day, and formulating the cruise task of the unmanned aerial vehicle according to the forest fire danger weather grade;

[0014] The flight task manual correction module is used for manually correcting the flight task;

[0015] The route planning module is used for setting the inspection route of the unmanned aerial vehicle.

[0016] Further, the edge computing unit comprises a data receiving module, a data caching module and a data cleaning and processing module;

[0017] The data receiving module is connected with the weather collecting device and is used for receiving the weather factor data collected by the weather collecting device;

[0018] The data caching module is connected with the data receiving module and is used for saving the weather factor data received by the data receiving module;

[0019] The data cleaning and processing module is connected with the data caching module and is used for cleaning and processing the saved weather factor data to obtain processed data.

[0020] Further, the unmanned airfield unit comprises a flight command communication module, a flight control module and an unmanned airfield device;

[0021] The flight command communication module is used for receiving data from the data caching module and control commands and data synchronization commands from the remote data analysis and flight management system;

[0022] The flight control module is used for controlling the operation of the unmanned airfield and the unmanned aerial vehicle;

[0023] The unmanned airport device is used for providing an intelligent airport for the unmanned aerial vehicle.

[0024] Further, the flight task calculation module is used for judging different weather conditions, special holidays or forest fire danger weather grades of different seasons according to the processed data received by the data communication module every day, and formulating a cruising task of the unmanned aerial vehicle according to the forest fire danger weather grade, including:

[0025] S21: extracting the processed data, the data being temperature T, relative humidity r RH and wind speed value V at 14 o'clock of the day before the inspection day;

[0026] S22: determining the number of days M with continuous precipitation less than a precipitation threshold value from the processed data;

[0027] S23: calculating the precipitation R t within 24 hours of the inspection day and the day before;

[0028] S24: calculating the minimum thickness H t of snow within 24 hours of the inspection day and the day before;

[0029] S25: calculating the forest fire danger weather index FFDI according to the data obtained from S41-S44, as shown in formula (1),

[0030] I FFDI =(f(V)+f(T)+f(r RH )+f(M))×C t ×C h (1)

[0031] wherein, I FFDI represents the forest fire danger weather index, f(V) represents the wind speed factor weather index function, f(T) represents the temperature factor weather index function, f(M) represents the drought weather factor index function, C t represents a precipitation correction coefficient, R t is greater than or equal to a preset value, C t is 0; R t is less than the preset value, C t is 1; C h represents a snow correction coefficient, H t is greater than or equal to a preset value, C h is 0; H t is less than the preset value, C h is 1;

[0032] The forest fire danger weather is divided into five grades, and the value of the calculated forest fire danger weather index I FFDI belongs to which grade is judged;

[0033] S26: According to the forest fire weather index I FFDI and the date D of the inspection day, the number of inspections X per day is calculated t As shown in equation (2),

[0034] X t = f I + f h + f s (2)

[0035] f I is the number of inspections set according to the level of forest fire weather;

[0036] f h is the number of inspections calculated according to whether it is a special holiday, as shown in equation (3),

[0037]

[0038] f s is the number of inspections calculated according to whether it is a special season, as shown in equation (4),

[0039]

[0040] S27: Calculate the inspection time point according to the number of inspections;

[0041] S28: Formulate the cruise mission according to the flight mission parameters preset by the route planning module;

[0042] S29: Store the cruise mission to the data storage module, and at the same time, send the flight mission to the flight control module of the unmanned airport unit through the data communication module.

[0043] Further, calculating the inspection time point according to the number of inspections includes:

[0044] S271: Set the starting inspection time T s point and the ending inspection time T e point;

[0045] S272: Calculate the inspection time, as shown in equation (5),

[0046]

[0047] where K represents the Kth inspection, T s represents the starting inspection time point, T e represents the ending inspection time point, X t represents the number of inspections, and Round is the rounding function, and f(K) represents the Kth inspection time point.

[0048] Further, the flight control module sets a timer according to the set cruise mission, and when the timed time is reached, the unmanned aerial vehicle flight control module controls the unmanned aerial vehicle to cruise according to the following steps:

[0049] S41, extracting real-time meteorological factor data from the data cache module of the meteorological data acquisition device;

[0050] S42, judging whether the current unmanned aerial vehicle take-off condition is met according to the meteorological factor data, the take-off condition requiring that the wind speed and 24-hour rainfall are both less than a threshold value, and the take-off determination being shown as formula (6),

[0051]

[0052] wherein V represents the current wind speed value, the unit being meter per second, v represents the set wind speed threshold value, t represents the current time, accurate to minutes, R represents the set rainfall threshold value, R t represents 24-hour rainfall; fly represents the take-off condition, when fly = 1, it represents that the take-off is possible; when fly = 0, it represents that the take-off is not possible;

[0053] S43, when the meteorological factor data meets the take-off condition, controlling the unmanned aerial vehicle to take off and execute the cruise mission according to the set cruise mission and cruise route.

[0054] Further, the data cleaning processing module includes the following steps of cleaning and processing the meteorological factor data:

[0055] S31, extracting meteorological factor data, and using a limit symbol filtering algorithm to denoise the meteorological factor data, as shown in formula (7),

[0056]

[0057] wherein Y represents a sampling value, k represents the kth extracted data, Y(k) represents the kth sampling value, Y(k-1) represents the last sampling value, and ΔY represents a sampling deviation threshold value;

[0058] S32, calculating the sampling average value of each minute after denoising, as shown in formula (8),

[0059]

[0060] wherein T represents the sampling average value of each minute, and n represents the number of extracted data within 1 minute;

[0061] S33, sending the calculated data to a remote data analysis and flight management system, and the data format being ID, meteorological factor type name, meteorological factor type symbol, meteorological factor collection time, and meteorological factor value.

[0062] The application provides a forest fire prevention unmanned aerial vehicle automatic inspection system based on meteorological factors, which is characterized in that a meteorological data acquisition device, an unmanned aerial vehicle airport, an edge computing device and a remote data analysis and flight management system are arranged at a forest fire detection point, different meteorological condition, special holiday or different season meteorological factor data collected by the edge computing unit is processed, the meteorological data is processed and analyzed again by the remote data analysis and flight management system, and different meteorological condition, special holiday or different season unmanned aerial vehicle cruise tasks are automatically generated by using the data, so that the unmanned aerial vehicle automatic cruise is controlled, the trouble of manual intervention is saved, the unmanned aerial vehicle forest fire prevention inspection frequency is automatically increased in special holidays or seasons, the actual inspection demand is met, the forest fire prevention is more efficient and intelligent. BRIEF DESCRIPTION OF DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, below the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0064] Figure 1 The system block diagram of the forest fire prevention unmanned aerial vehicle automatic inspection system based on meteorological factors provided by the present application. DETAILED DESCRIPTION

[0065] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme in the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0066] The present embodiment provides a forest fire prevention unmanned aerial vehicle automatic inspection system based on meteorological factors, as shown in the figure, comprising: a meteorological data acquisition device, an unmanned aerial vehicle airport and an edge computing device, a remote data analysis and flight management system and an unmanned aerial vehicle. Figure 1

[0067] The meteorological data acquisition device is used for real-time acquisition of different meteorological condition, special holiday or different season meteorological factor data, and the meteorological factor data includes but is not limited to temperature, air humidity, wind speed, rainfall and snow thickness.

[0068] ​The unmanned airport and edge computing device includes an edge computing unit and an unmanned airport unit, the edge computing unit is used for receiving meteorological factor data and processing the meteorological factor data to obtain processed data; the unmanned airport unit is used for controlling the unmanned aerial vehicle to cruise the inspection area;

[0069] The remote data analysis and flight management system is used for receiving the processed data, analyzing the processed data, judging the forest fire danger weather grade under different weather conditions, special holidays or different seasons, formulating different unmanned aerial vehicle cruise tasks according to the forest fire danger weather grade, and sending the unmanned aerial vehicle cruise tasks to the unmanned airport unit;

[0070] The unmanned aerial vehicle automatically executes the cruise task according to the control command of the unmanned airport unit to complete the automatic cruising of the inspection area.

[0071] Specifically, the meteorological data, i.e. a small meteorological station, integrates temperature, air humidity, wind speed, rainfall and snow thickness ultrasonic detector and other sensors, and is electrically connected with the edge computing unit to collect various meteorological factor data, which can collect meteorological factor data under different weather conditions, special holidays or different seasons to provide more inspection conditions for unmanned aerial vehicle cruising; the unmanned airport and edge computing device includes an edge computing unit and an unmanned airport unit, the edge computing unit is used for receiving meteorological factor data and processing the meteorological factor data to obtain processed data; the unmanned airport unit is used for controlling the unmanned airport hatch opening and closing, the push rod loosening and clamping, the unmanned aerial vehicle charging and providing network and live streaming service; the unmanned airport and edge computing device can clean the collected data to remove noise in the data, making the data more accurate; the remote data analysis and flight management system is used for receiving the processed data, analyzing the processed data, formulating the unmanned aerial vehicle cruise task according to the analysis result, and sending the unmanned aerial vehicle cruise task to the unmanned airport unit; the remote data analysis and flight management system can formulate the unmanned aerial vehicle cruise task according to the data, which saves the trouble of manual intervention, meets the actual inspection demand, and makes the forest fire prevention more efficient and intelligent; the unmanned aerial vehicle automatically executes the cruise task according to the control command of the unmanned airport unit to complete the automatic cruising of the inspection area, the unmanned aerial vehicle is a small multi-rotor unmanned aerial vehicle, carries a wide-angle, long-focus and thermal imaging function camera, and automatically cruises the inspection area under the control of the flight control module.

[0072] In specific embodiments, the remote data analysis and flight management system includes a data communication module, a data storage module, a flight task calculation module, a flight task manual correction module and a route planning module;

[0073] The data communication module is in communication connection with a data cleaning processing module of the edge computing unit and a flight command communication module of the unmanned airport unit respectively, and is used for receiving the processed data sent by the edge computing unit and sending control command data to the flight task calculation module, the flight task manual correction module and the route planning module;

[0074] The data storage module is used for storing the cruise task obtained by the flight task calculation module;

[0075] The flight task manual correction module is used for manually correcting the flight task;

[0076] The route planning module is used for setting the unmanned aerial vehicle cruise route:

[0077] The flight task calculation module is used for judging the forest fire danger weather grade of different weather conditions, special holidays or different seasons according to the processed data received by the data communication module every day, and formulating the cruise task of the unmanned aerial vehicle according to the forest fire danger weather grade:

[0078] S21: extracting the processed data, the data being the temperature T, relative humidity r and wind speed value V at 14 o'clock of the day before the inspection day; RH

[0079] S22: determining the number of days M with continuous precipitation less than the precipitation threshold value from the processed data, the precipitation threshold value being 1 mm in the embodiment, and the calculation being performed according to the national regulation method;

[0080] S23: calculating the precipitation R within 24 hours of the inspection day and the day before; t

[0081] S24: calculating the minimum thickness H of snow within 24 hours of the inspection day and the day before; t

[0082] S25: calculating the forest fire danger weather index FFDI according to the data obtained from S21-S24, as shown in formula (9),

[0083] I FFDI =(f(V)+f(T)+f(r RH )+f(M))×C t ×C h (9)

[0084] Wherein, I FFDI represents the forest fire danger weather index, f(V) represents the wind speed weather factor index function, f(r RH ) represents the rainfall weather factor index function, f(T) represents the temperature weather factor index function, and f(M) represents the drought weather factor index function, and the weather factor index functions are all national set values; ​​​

[0085] C t represents a precipitation correction coefficient, R t C is equal to 0 when R t is greater than or equal to a preset value; R t C is equal to 1 when R t is less than the preset value; C h represents a snow correction coefficient, H t C is equal to 0 when H h is greater than or equal to a preset value; H t C is equal to 1 when H h is less than the preset value; in the embodiment, when 24h precipitation R t ≥1mm, C t =0; when R t <1mm, C t =1; when 24h snow depth H t ≥1mm, C h =0; when H t <1mm, C h =1;

[0086] The forest fire weather is divided into five levels, as shown in Table 1,

[0087] Table 1 Forest fire weather levels

[0088] FFDI Forest fire weather class [0，38) Low risk [38，47) Lower risk [47，66) Higher risk [66，73) High risk [73，47) Very high risk

[0089] S26: judging the level to which the calculated forest fire weather index I FFDI belongs, calculating the daily inspection frequency according to the forest fire weather index I FFDI and the date D of the day of inspection, the inspection frequency X t is calculated, as shown in formula (10),

[0090] X t = f I +f h +f s (10)

[0091] f I is the five inspection frequencies set according to the levels of forest fire weather, as shown in formula (11),

[0092]

[0093] f h is the inspection frequency calculated according to whether it is a special holiday, as shown in formula (12),

[0094]

[0095] Special holidays include Tomb-Sweeping Day, Ghost Festival, Spring Festival, etc.

[0096] f s The number of inspections is calculated according to whether it is a special season, as shown in formula (13),

[0097]

[0098] The special seasons are spring and autumn.

[0099] S27: Calculate the inspection time point according to the number of inspections;

[0100] S271: Set the inspection start time T s point and the inspection end time T e point; in this embodiment, it is from 4 am to 8 pm;

[0101] S272: Calculate the inspection time, as shown in formula (14),

[0102]

[0103] Where K represents the Kth inspection, T s represents the start inspection time point, T e represents the end inspection time point, X t represents the number of inspections, and Round is the rounding function, and f(K) represents the Kth inspection time point.

[0104] S28: Formulate the cruise task according to the flight task parameters pre-set by the route planning module, such as formulating the cruise task according to the inspection route, inspection equipment, and return condition.

[0105] S29: Store the cruise task to the data storage module, and at the same time, send the flight task to the flight control module of the unmanned airport unit through the data communication module.

[0106] In this embodiment, the flight task manual correction module is a management function based on B / S architecture. Through this function, the prevention and control personnel can manually correct the inspection task and synchronize the unmanned airport unit. The route planning module is a management function based on B / S architecture. Through this function, the prevention and control personnel can manually pre-set the flight route of the unmanned aerial vehicle based on GIS, satellite map image, elevation data, and three-dimensional map model, and send the inspection route to the flight control module. The data storage module is a Mysql relational database, which stores the meteorological factor data, route data, and inspection task data after processing and analysis.

[0107] The remote data analysis and flight management system further comprises a special date and season setting module, through which special dates requiring increased inspection intensity, such as the Spring Festival, Tomb-Sweeping Day, etc., and special seasons, such as spring and autumn, are set, and the set dates are sent to the data storage module for formulating inspection tasks;

[0108] The remote data analysis and flight management system can process and analyze meteorological data again, and automatically generate unmanned aerial vehicle cruise tasks under different weather conditions or in different seasons by using the data, so as to achieve the purpose of controlling unmanned aerial vehicle automatic cruise, and automatically increase the cruise intensity in special seasons and holidays, meet the actual inspection requirements, and make forest fire prevention more efficient and intelligent.

[0109] In specific embodiments, the edge computing unit comprises a data receiving module, a data caching module and a data cleaning and processing module;

[0110] The data receiving module is connected with the meteorological collection device, and is used for receiving meteorological factor data collected by the meteorological collection device;

[0111] The data caching module is connected with the data receiving module, and is used for saving the meteorological factor data received by the data receiving module;

[0112] The data cleaning and processing module is connected with the data caching module, and is used for cleaning and processing the saved meteorological factor data to obtain processed data;

[0113] S31, extracting meteorological factor data, and using a limit symbol filtering algorithm to denoise the meteorological factor data, as shown in formula (15),

[0114]

[0115] Wherein, Y represents a sampling value, k represents the Kth data extracted, Y(k) represents the kth sampling value, Y(k-1) represents the last sampling value, and ΔY represents a sampling deviation threshold;

[0116] The limit symbol filtering subtracts two adjacent sampling values, obtains the absolute value increment, and then compares it with the sampling deviation threshold ΔY, if it is less than or equal to the sampling deviation ΔY, the current sampling value Y(k) is taken, if it is greater than the sampling deviation threshold ΔY, the last sampling value Y(k-1) is taken as the current sampling value, and the cached data is updated;

[0117] S32, every 1 hour, the data cleaning and processing module extracts meteorological factor data temperature T, atmospheric relative humidity r RH , wind speed V, rainfall R t and snow depth H t , k=1, 2, 3...60;

[0118] S33, calculate the de-noised per-minute sampling average value, as shown in formula (16),

[0119]

[0120] wherein T represents the per-minute sampling average value, and n represents the number of data extracted within 1 minute;

[0121] S34, send the calculated data to the remote data analysis and flight management system, and the data format is ID, meteorological factor type name, meteorological factor type symbol, meteorological factor collection time, and meteorological factor value (with 1 decimal point retained).

[0122] In the embodiment, the data receiving module is electrically connected with the meteorological data collection device, collects meteorological factor data every 1 minute through RS485 protocol, and saves the data in the data cache module; the data cache module uses Redis as a data cache database; the data cache module is connected with the data cleaning processing module; an edge computing unit is arranged, which can save and de-noise and clean the collected data to obtain more accurate data.

[0123] In specific embodiments, the unmanned airport unit comprises a flight command communication module, a flight control module, and an unmanned airport device;

[0124] The flight command communication module is connected with the data cache module and the remote data analysis and flight management system, and is used for receiving data from the data cache module and control commands and data synchronization commands from the remote data analysis and flight management system;

[0125] The flight control module is used for controlling the unmanned airport and the unmanned aerial vehicle operation, sets a timer according to the set cruise task, and controls the unmanned aerial vehicle to cruise according to the following steps when the time reaches the set time:

[0126] S41, extract real-time meteorological factor data from the data cache module of the meteorological data collection device;

[0127] S42, determine whether the current unmanned aerial vehicle takeoff condition is met according to the meteorological factor data, and the takeoff condition requires that the wind speed and the 24-hour rainfall are both less than a threshold value, and the takeoff determination is shown in formula (17),

[0128]

[0129] wherein V represents the current wind speed value, the unit is meter per second, v represents the set wind speed threshold value, t represents the current time, which is accurate to minutes, R represents the set rainfall threshold value, and R trepresents 24-hour rainfall; fly represents take-off conditions, when fly=1, it represents that it is possible to take off; when fly=0, it represents that it is impossible to take off; in this embodiment, the wind speed is below 12 meters per second, and the 24-hour rainfall is not more than 100 millimeters;

[0130] S43, when the weather factor data meets the take-off conditions, the unmanned aerial vehicle is controlled to take off and perform the cruising task according to the set cruising task and cruising route;

[0131] The unmanned airport device is used to provide an intelligent airport for the unmanned aerial vehicle.

[0132] In this embodiment, the flight command communication module is used to receive control commands and data synchronization commands from a remote data analysis and flight management system. The control commands include operation control of the unmanned airport and operation control of the unmanned aerial vehicle; the data synchronization commands mainly include route data synchronization and flight plan data synchronization.

[0133] The flight control module mainly includes two parts of work. One part of work is to control the opening and closing of the cabin door of the unmanned airport, the clamping and loosening of the push rod, the charging and closing of the unmanned aerial vehicle, the take-off, landing, hovering, flight of the unmanned aerial vehicle, and the control of the camera holder, etc. according to the control commands. The other part of work is to synchronize the route data and flight plan data to the remote controller of the unmanned aerial vehicle according to the data synchronization commands.

[0134] The unmanned airport device mainly includes the unmanned airport, the additional remote controller of the unmanned aerial vehicle, and the router, etc., to control the unmanned aerial vehicle and provide network.

[0135] The unmanned airport unit is set to be able to receive flight commands of the unmanned aerial vehicle and control the unmanned aerial vehicle, so as to realize the cruising task.

[0136] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A forest fire prevention unmanned aerial vehicle automatic patrol system based on meteorological factors, characterized in that, The application relates to a meteorological data acquisition device, an unmanned airport and edge computing device, a remote data analysis and flight management system and an unmanned aerial vehicle. The meteorological data acquisition device is used for collecting meteorological factor data under different meteorological conditions, special holidays or different seasons in real time, wherein the meteorological factor data includes but is not limited to temperature, air humidity, wind speed, rainfall and snow thickness. The unmanned airport and edge computing device comprises an edge computing unit and an unmanned airport unit, the edge computing unit is used for receiving meteorological factor data and processing the meteorological factor data to obtain processed data, and the unmanned airport unit is used for controlling an unmanned aerial vehicle to cruise in a patrol area. The remote data analysis and flight management system is used for receiving the processed data, analyzing the processed data, judging a forest fire danger meteorological grade under different meteorological conditions, special holidays or different seasons, formulating different unmanned aerial vehicle cruising tasks according to the forest fire danger meteorological grade, and sending the unmanned aerial vehicle cruising tasks to the unmanned airport unit. The remote data analysis and flight management system comprises a data communication module, a data storage module, a flight task calculation module, a flight task manual correction module and a route planning module. The data communication module is used for receiving the processed data sent by the edge computing unit and sending control command data to the flight task calculation module, the flight task manual correction module and the route planning module. The data storage module is used for storing the cruising tasks obtained by the flight task calculation module. The flight task calculation module is used for judging a forest fire danger meteorological grade under different meteorological conditions, special holidays or different seasons according to the processed data received by the data communication module every day, formulating unmanned aerial vehicle cruising tasks according to the forest fire danger meteorological grade, and the specific steps are as follows: S22: determining the number M of days with continuous rainfall less than a rainfall threshold value from the processed data; S21: extract the processed data, which is the temperature T, relative humidity RH and wind speed value V at 14:00 of the day before the inspection day ; S25: calculating a forest fire danger meteorological index FFDI according to the data obtained from S21-S24, as shown in formula (1), S23: Calculate the inspection day and the previous day within 24 hours of precipitation ; S24: Calculate the minimum snow depth in the 24 hours before the day of the inspection ; S27: calculating a patrol time point according to the patrol frequency, （1） wherein, represents a forest fire danger meteorological index, represents a wind speed factor meteorological index function, represents a temperature factor meteorological index function, represents a drought meteorological factor index function, represents a precipitation correction coefficient, greater than or equal to a preset value is 0; less than a preset value is 1; represents a snow cover correction coefficient, greater than or equal to a preset value is 0; less than a preset value is 1; The forest fire danger weather is divided into five grades, and the value of the calculated forest fire danger weather index is judged to belong to which grade ; S26: According to the forest fire weather index and the date D of the day of the inspection, the number of inspections per day is calculated, the number of inspections As shown in equation (2), （2） Five kinds of patrol frequency are set according to the grades of forest fire danger weather; For the number of inspections calculated according to whether it is a special holiday or not, as shown in Equation (3), （3） The number of inspections is calculated according to whether it is a special season, as shown in equation (4). （4） S272: calculating a patrol time according to formula (5), S271: Set the start time of the inspection point, the end time of the inspection point; S28: formulating a cruising task according to flight task parameters preset by the route planning module; （5） Wherein, K represents the Kth inspection, represents the starting inspection time point, represents the inspection time point, represents the inspection number, and Round is the rounding function, represents the Kth inspection time point; S29: storing the cruising task into the data storage module, and simultaneously sending the flight task to a flight control module of the unmanned airport unit through the data communication module; The flight task manual correction module is used for manually correcting the flight task. The route planning module is used for setting an unmanned aerial vehicle patrol route. The unmanned aerial vehicle automatically executes the cruising task according to the control command of the unmanned airport unit, and automatically cruises in the patrol area. The edge computing unit comprises a data receiving module, a data caching module and a data cleaning and processing module. 2.The forest fire prevention unmanned aerial vehicle automatic patrol system based on meteorological factors of claim 1, wherein The data receiving module is connected with the meteorological acquisition device and is used for receiving meteorological factor data collected by the meteorological acquisition device. The data caching module is connected with the data receiving module and is used for saving the meteorological factor data received by the data receiving module. ​ The data cleaning processing module is connected with the data cache module and is used for cleaning and processing the saved meteorological factor data to obtain processed data. 3.The forest fire prevention unmanned aerial vehicle automatic patrol system based on meteorological factors of claim 1, wherein The unmanned airport unit comprises a flight command communication module, a flight control module and an unmanned airport device. The flight command communication module is used for receiving data from the data cache module and control commands and data synchronization commands from a remote data analysis and flight management system. The flight control module is used for controlling the unmanned airport and the unmanned aerial vehicle. The unmanned airport device is used for providing an intelligent airport for the unmanned aerial vehicle. 4.The forest fire prevention unmanned aerial vehicle automatic patrol system based on meteorological factors of claim 3, wherein, The flight control module sets a timer according to a set cruise mission, and when the time of the timer is reached, the unmanned aerial vehicle flight control module controls the unmanned aerial vehicle to perform the cruise mission according to the following steps: S41. Real-time meteorological factor data is extracted from the data cache module of the meteorological data acquisition device. S42. Whether the current has the take-off condition of the unmanned aerial vehicle is judged according to the meteorological factor data. The take-off condition requires that the wind speed and the 24-hour rainfall are less than the threshold value. The take-off determination is shown in formula (6), （6） wherein, represents the current wind speed value in meters per second, represents the set wind speed threshold, represents the current time, accurate to the minute, represents the set rainfall threshold, represents the 24-hour rainfall; represents the takeoff condition, when = 1, it represents that it can take off; when it represents that it cannot take off; S43. When the meteorological factor data meets the take-off condition, the unmanned aerial vehicle is controlled to take off and perform the cruise mission according to the set cruise mission and cruise route. 5.The forest fire prevention unmanned aerial vehicle automatic patrol system based on meteorological factors of claim 2, wherein The steps of cleaning and processing the meteorological factor data by the data cleaning processing module comprise: S31. The meteorological factor data is extracted, and a limit symbol filtering algorithm is used to denoise the meteorological factor data, as shown in formula (7), （7） wherein, represents a sample value, represents the extracted first data, represents the first sample value, represents the last sample value, represents a sample deviation threshold value; S32. The sampling average value of each minute after denoising is calculated, as shown in formula (8), （8） wherein, represents the sample average per minute, represents the number of times the data is extracted within 1 minute; S33. The calculated data is sent to the remote data analysis and flight management system. The data format is ID, meteorological factor type name, meteorological factor type symbol, meteorological factor collection time and meteorological factor value.

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