Cruise monitoring and early warning method based on unmanned aerial vehicle

Abstract

The invention relates to the technical field of unmanned aerial vehicle inspection, in particular to a cruise monitoring and early warning method based on an unmanned aerial vehicle, and the method comprises the steps: carrying out the temperature survey of a target region through employing the unmanned aerial vehicle based on a preset cruise path, and constructing a temperature distribution diagram of the target region; the drip irrigation amount of each drip irrigation sub-area in the target area is dynamically adjusted according to the distribution change condition of the temperature distribution diagram of the target area within a certain period of time; secondly, in the high-speed flight process of the unmanned aerial vehicle, a temperature measurement value is lower than a true value due to the fact that a temperature sensor is influenced by an airflow cooling effect, so that a flight speed compensation item is innovatively introduced to effectively counteract the sensor cooling effect caused by high-speed flight; the compensation comprises two aspects of dynamic wind speed compensation and environmental adaptability enhancement, and for the dynamic wind speed compensation, an error proportionality coefficient k and an index n are utilized to accurately quantify the nonlinear influence of the wind speed on temperature measurement.

Description

Technical Field

[0001] The present invention relates to the field of drone inspection technology, and in particular to a cruise monitoring and early warning method based on drones. Background Art

[0002] In the field of wide-area temperature monitoring, traditional methods mainly rely on fixed sensor networks or satellite remote sensing technology, which have significant defects: fixed sensors have high deployment costs and limited coverage, making it difficult to achieve dynamic mobile monitoring; satellite remote sensing is subject to long revisit cycles, low spatial resolution and meteorological interference, and cannot meet real-time requirements.

[0003] Secondly, although drone inspection technology has improved monitoring flexibility, the sensor is affected by the cooling effect of airflow during high-speed flight, causing the temperature measurement value to systematically deviate from the true value. Summary of the Invention

[0004] The purpose of the present invention is to provide a cruise monitoring and early warning method based on drones to improve the above technical problems.

[0005] In order to achieve the above objectives, the embodiments of the present application provide the following technical solutions: An embodiment of the present application provides a cruise monitoring and early warning method based on a drone, the method comprising: in response to a patrol instruction, obtaining the current cruise path information, and executing the drone cruise flight based on the cruise path information; during the flight, obtaining the temperature value on the cruise path in real time through a temperature sensor provided under the drone; constructing a temperature distribution map of the target area based on the temperature value on the cruise path, and obtaining the drip irrigation amount in the current target area; and, if the drip irrigation amount does not match the temperature distribution map of the target area, triggering a temperature anomaly early warning, so that the drip irrigation system changes the drip irrigation amount according to the temperature distribution map of the target area.

[0006] Optionally, the step of obtaining a temperature value on the cruising path in real time through a temperature sensor provided below the drone includes: Obtaining the current flight speed and temperature sensor monitoring values, and correcting the monitoring values ​​based on the current flight speed, thereby calculating the temperature value at the current cruise path point; , where is the monitoring value, is the temperature value at the current cruise path point, is the current flight speed, is the error proportional coefficient, which reflects the sensitivity of the sensor to wind speed. n is the wind speed index, which reflects the nonlinearity of the error with speed. is the temperature compensation term. When v=0, =0, output T corrected =Tmeasured , when v>0, the temperature compensation term is positive, which is used to offset the cooling effect. is the altitude compensation factor, is the humidity compensation factor.

[0007] Optionally, the altitude compensation factor is calculated as follows: , where h is the altitude, is the air density at sea level, which is the preset standard value, is the air density at the current altitude, and c is the altitude compensation index; The humidity compensation factor is calculated as follows: , where is the humidity value, is the humidity compensation factor, is the humidity sensitivity coefficient, To quantify the additional cooling effect caused by humidity, =0%, =0, =1, no humidity compensation at this time, when =100%, is the maximum value, which is the maximum compensation effect. is the saturated water vapor pressure formula, which is used to describe the nonlinear characteristics of saturated water vapor pressure changing with temperature. is an exponential function used to calculate the temperature dependence of the saturated water vapor pressure, is the saturated water vapor pressure coefficient, is the temperature offset constant.

[0008] Optionally, constructing a target area temperature distribution map based on the temperature values ​​on the cruise path includes: The altitude values ​​and corresponding temperature values ​​on the cruise path are obtained to construct a temperature distribution standard based on the altitude, and a temperature distribution map of the target area is constructed based on the altitude fluctuation of the target area.

[0009] Optionally, when the drip irrigation amount does not match the temperature distribution map of the target area, triggering a temperature abnormality warning to enable the drip irrigation system to change the drip irrigation amount according to the temperature distribution map of the target area, including: Obtaining historical temperature distribution maps of the target area generated by multiple inspections within a first time period, and obtaining time-temperature curves of multiple local irrigation areas in the target area based on the multiple historical temperature distribution maps of the target area, which are recorded as sample curves; The sample curve is decomposed empirically to obtain multiple modal functions, and then a Hilbert-Huang transform is performed based on the modal functions to obtain the Hilbert spectrum corresponding to the sample curve. The Hilbert spectrum is then integrated to obtain the corresponding marginal spectrum, and the marginal spectra are summed to obtain the drip irrigation demand control value of the sample curve. The drip irrigation demand control value is used to query the drip irrigation amount of the corresponding area in the drip irrigation reference table; The specific calculation method is: , where is the drip irrigation demand control value of the local irrigation area at time t, is the frequency, used to characterize the upper limit of integration, n is the number of mode functions, represents the function of the amplitude of the ith mode function changing with time, is the instantaneous frequency of the ith mode function, Characterizes the time-based cumulative phase, Characterizing the cosine term of the time-based cumulative phase, the above The summation range is from i=1 to n+1, including all modal function components and possible residual terms.

[0010] The beneficial effects of the present invention are: The present invention uses a drone to perform temperature surveys of a target area based on a preset cruise path, thereby constructing a temperature distribution map of the target area. The method also dynamically adjusts the drip irrigation amount of each drip irrigation sub-area in the target area based on the distribution changes of the temperature distribution map of the target area within a certain period of time. Secondly, since the temperature sensor is affected by the airflow cooling effect during the high-speed flight of the UAV, the temperature measurement value will be lower than the true value. Therefore, the present invention innovatively introduces a flight speed compensation term to effectively offset the sensor cooling effect caused by high-speed flight. The compensation includes two aspects: dynamic wind speed compensation and environmental adaptability enhancement. As for dynamic wind speed compensation, the error proportional coefficient k and exponent n are used to accurately quantify the nonlinear effect of wind speed on temperature measurement, ensuring the flight speed. When the value is >0, the compensation item actively offsets the error. In terms of enhanced environmental adaptability, a secondary correction is performed by combining the altitude compensation factor and the humidity compensation factor to eliminate geographical and meteorological interference, significantly improving the reliability of temperature data in complex environments.

[0011] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the embodiments of the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0013] Figure 1 The figure is a flow chart of a cruise monitoring and early warning method based on a drone described in an embodiment of the present invention. DETAILED DESCRIPTION

[0014] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0015] It should be noted that similar reference numerals or letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0016] Example 1:

[0017] like Figure 1 As shown, this embodiment provides a cruise monitoring and early warning method based on a drone, and the method includes step S100 and step S200.

[0018] Step S100: In response to the inspection instruction, obtain the current cruise path information, and execute the UAV cruise flight based on the cruise path information. During the flight, obtain the temperature value on the cruise path in real time through the temperature sensor provided under the UAV; The specific implementation method of obtaining the temperature value on the cruising path in real time through the temperature sensor installed under the drone is as follows: Step S110: obtaining the current flight speed and the monitoring value of the temperature sensor, and correcting the monitoring value based on the current flight speed, thereby calculating the temperature value at the current cruising path point; , where is the monitoring value, is the temperature value at the current cruise path point, is the current flight speed, is the error proportional coefficient, which reflects the sensitivity of the sensor to wind speed. n is the wind speed index, which reflects the nonlinearity of the error with speed. is the temperature compensation term. When v=0, =0, the output Tcorrected=Tmeasured, when v>0, the temperature compensation term is positive, which is used to offset the cooling effect. is the altitude compensation factor, is the humidity compensation factor; The calculation method of the above altitude compensation factor is: , where h is the altitude, is the air density at sea level, which is the preset standard value, is the air density at the current altitude, and c is the altitude compensation index; The humidity compensation factor is calculated as follows: , where is the humidity value, is the humidity compensation factor, is the humidity sensitivity coefficient, To quantify the additional cooling effect caused by humidity, =0%, =0, =1, no humidity compensation at this time, when =100%, is the maximum value, which is the maximum compensation effect. is the saturated water vapor pressure formula, which is used to describe the nonlinear characteristics of saturated water vapor pressure changing with temperature. is an exponential function used to calculate the temperature dependence of the saturated water vapor pressure, is the saturated water vapor pressure coefficient, is the temperature offset constant.

[0019] Step S200: construct a target area temperature distribution map based on the temperature values ​​on the cruise path, obtain the drip irrigation amount in the current target area, and trigger a temperature anomaly warning when the drip irrigation amount does not match the target area temperature distribution map, so that the drip irrigation system changes the drip irrigation amount according to the target area temperature distribution map.

[0020] The specific implementation method of triggering a temperature anomaly warning when the drip irrigation amount does not match the target area temperature distribution map is as follows: Obtaining historical temperature distribution maps of the target area generated by multiple inspections within a first time period, and obtaining time-temperature curves of multiple local irrigation areas in the target area based on the multiple historical temperature distribution maps of the target area, which are recorded as sample curves; The sample curve is decomposed by empirical mode to obtain multiple modal functions, and then a Hilbert transform is performed based on the modal function to obtain the Hilbert spectrum corresponding to the sample curve, which is then integrated to obtain the corresponding marginal spectrum, and the marginal spectrum is summed to obtain the drip irrigation demand control value of the sample curve. The drip irrigation demand control value can be understood in disguise as the cumulative amount of heat in a certain period of time. The cumulative heat value serves as a reference value for the drip irrigation amount during this period. The correlation between the cumulative heat value and the drip irrigation amount is not linear, but is obtained through a large number of experimental tests and recorded in the drip irrigation comparison table. The drip irrigation demand control value is used to query the drip irrigation amount of the corresponding area in the drip irrigation comparison table; The specific calculation method is: , where is the drip irrigation demand control value of the local irrigation area at time t, is the frequency, used to characterize the upper limit of integration, n is the number of mode functions, represents the function of the amplitude of the ith mode function changing with time, is the instantaneous frequency of the ith mode function, Characterizes the time-based cumulative phase, Characterizing the cosine term of the time-based cumulative phase, the above The summation range is from i=1 to n+1, including all modal function components and possible residual terms.

[0021] In this embodiment, a temperature survey of a target area is performed using a drone based on a preset cruising path, thereby constructing a temperature distribution map of the target area. The drip irrigation amount of each drip irrigation sub-area in the target area is dynamically adjusted according to the distribution change of the temperature distribution map of the target area within a certain period of time. Secondly, since the temperature sensor is affected by the airflow cooling effect during the high-speed flight of the UAV, the temperature measurement value will be lower than the true value. Therefore, the present invention innovatively introduces a flight speed compensation term to effectively offset the sensor cooling effect caused by high-speed flight. The compensation includes two aspects: dynamic wind speed compensation and environmental adaptability enhancement. As for dynamic wind speed compensation, the error proportional coefficient k and exponent n are used to accurately quantify the nonlinear effect of wind speed on temperature measurement, ensuring the flight speed. When the value is >0, the compensation item actively offsets the error. In terms of enhanced environmental adaptability, a secondary correction is performed by combining the altitude compensation factor and the humidity compensation factor to eliminate geographical and meteorological interference, significantly improving the reliability of temperature data in complex environments.

[0022] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A cruise monitoring and early warning method based on drones, characterized in that: The method comprises: In response to the inspection instruction, the cruise path information is obtained, and the UAV cruise flight is performed based on the cruise path information. During the flight, the temperature value along the cruise path is obtained in real time through the temperature sensor located under the UAV; Based on the temperature values ​​on the cruise path, a temperature distribution map of the target area is constructed, and the drip irrigation amount in the current target area is obtained. If the drip irrigation amount does not match the temperature distribution map of the target area, a temperature anomaly warning is triggered to enable the drip irrigation system to change the drip irrigation amount according to the temperature distribution map of the target area.

2. The cruise monitoring and early warning method based on drone according to claim 1 is characterized in that: The method of obtaining the temperature value on the cruising path in real time by using a temperature sensor provided under the drone includes: Obtaining the current flight speed and temperature sensor monitoring values, and correcting the monitoring values ​​based on the current flight speed, thereby calculating the temperature value at the current cruise path point; , where is the monitoring value, is the temperature value at the current cruise path point, is the current flight speed, is the error proportional coefficient, which reflects the sensitivity of the sensor to wind speed. n is the wind speed index, which reflects the nonlinearity of the error with speed. is the temperature compensation term. When v=0, =0, output T corrected =T measured , when v>0, the temperature compensation term is positive, which is used to offset the cooling effect. is the altitude compensation factor, is the humidity compensation factor.

3. The cruise monitoring and early warning method based on drone according to claim 2 is characterized in that: The altitude compensation factor is calculated as follows: , where h is the altitude, is the air density at sea level, which is the preset standard value. is the air density at the current altitude, and c is the altitude compensation index; The humidity compensation factor is calculated as follows: , where is the humidity value, is the humidity compensation factor, is the humidity sensitivity coefficient, To quantify the additional cooling effect caused by humidity, =0%, =0, =1, no humidity compensation at this time, when =100%, is the maximum value, which is the maximum compensation effect. is the saturated water vapor pressure formula, which is used to describe the nonlinear characteristics of saturated water vapor pressure changing with temperature. is an exponential function used to calculate the temperature dependence of the saturated water vapor pressure, is the saturated water vapor pressure coefficient, is the temperature offset constant.

4. The cruise monitoring and early warning method based on drone according to claim 3 is characterized in that: Construct a temperature distribution map of the target area based on the temperature values ​​along the cruise path, including: The altitude values ​​and corresponding temperature values ​​on the cruise path are obtained to construct a temperature distribution standard based on the altitude, and a temperature distribution map of the target area is constructed based on the altitude fluctuation of the target area.

5. The cruise monitoring and early warning method based on drone according to claim 4 is characterized in that: When the drip irrigation volume does not match the target area temperature distribution map, a temperature anomaly warning is triggered to enable the drip irrigation system to change the drip irrigation volume according to the target area temperature distribution map, including: Obtaining historical temperature distribution maps of the target area generated by multiple inspections within a first time period, and obtaining time-temperature curves of multiple local irrigation areas in the target area based on the multiple historical temperature distribution maps of the target area, which are recorded as sample curves; The sample curve is decomposed empirically to obtain multiple modal functions, and then a Hilbert-Huang transform is performed based on the modal functions to obtain the Hilbert spectrum corresponding to the sample curve. The Hilbert spectrum is then integrated to obtain the corresponding marginal spectrum, and the marginal spectra are summed to obtain the drip irrigation demand control value of the sample curve. The drip irrigation demand control value is used to query the drip irrigation amount of the corresponding area in the drip irrigation reference table; The specific calculation method is: , where is the drip irrigation demand control value of the local irrigation area at time t, is the frequency, used to characterize the upper limit of integration, n is the number of mode functions, represents the function of the amplitude of the ith mode function changing with time, is the instantaneous frequency of the ith mode function, Characterizes the time-based cumulative phase, Characterizing the cosine term of the time-based cumulative phase, the above The summation range is from i=1 to n+1, including all modal function components and possible residual terms.

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