An unmanned aerial vehicle-based cruise monitoring and early warning method

Abstract

The present application relates to the technical field of unmanned aerial vehicle inspection, in particular to a cruise monitoring and early warning method based on unmanned aerial vehicle, the present application uses unmanned aerial vehicle to perform temperature survey on target area based on preset cruise path, and then constructs temperature distribution map of target area, and dynamically adjusts drip irrigation amount of each drip irrigation sub-area in target area according to distribution change of temperature distribution map of target area within a certain time; secondly, during high-speed flight of unmanned aerial vehicle, temperature sensor is affected by air flow cooling effect, so that temperature measurement value is lower than real value, therefore, the present application innovatively introduces flight speed compensation term, which is used to effectively offset sensor cooling effect caused by high-speed flight, and the compensation includes two aspects of dynamic wind speed compensation and environmental adaptability enhancement, as for dynamic wind speed compensation, error proportion coefficient k and index n are used to accurately quantify nonlinear influence of wind speed on temperature measurement.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle inspection, in particular to a cruise monitoring and early warning method based on unmanned aerial vehicles. BACKGROUND

[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, limited coverage, and are difficult to achieve dynamic mobile monitoring; satellite remote sensing is subject to long revisit cycles, low spatial resolution, and weather interference, and cannot meet real-time requirements.

[0003] Secondly, although the unmanned aerial vehicle inspection technology improves the monitoring flexibility, the sensor is affected by the airflow cooling effect when flying at high speed, resulting in systematic deviation of the temperature measurement value from the true value. SUMMARY

[0004] The present application aims to provide a cruise monitoring and early warning method based on unmanned aerial vehicles to improve the above technical problems.

[0005] To achieve the above purpose, the embodiments of the present application provide the following technical solutions:

[0006] The embodiments of the present application provide a cruise monitoring and early warning method based on unmanned aerial vehicles, which comprises: in response to an inspection instruction, obtaining the cruise path information of this time, and executing unmanned aerial vehicle cruise flight based on the cruise path information; during flight, obtaining the temperature value on the cruise path in real time through the temperature sensor arranged below the unmanned aerial vehicle; constructing a target area temperature distribution map based on the temperature value on the cruise path, and obtaining the drip irrigation amount in the current target area; and triggering a temperature anomaly early warning in the case that 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.

[0007] Optionally, the temperature value on the cruise path is obtained in real time by the temperature sensor arranged below the unmanned aerial vehicle, comprising:

[0008] obtaining the current flight speed and the monitoring value of the temperature sensor, and correcting the monitoring value based on the current flight speed, and then calculating the temperature value at the current cruise path point;

[0009] , wherein, is the monitoring value, is the temperature value at the current cruise path point, is the current flight speed, is the error proportion coefficient, reflecting the sensitivity of the sensor to the wind speed, n is the index of the wind speed, reflecting the nonlinearity degree of the error with the speed change, 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 an altitude compensation factor, is a humidity compensation factor.

[0010] Optionally, the altitude compensation factor is calculated as follows:

[0011] where h is the altitude, is the air density at sea level, and c is a preset standard value, is the current air density at the altitude, and c is the altitude compensation index;

[0012] The humidity compensation factor is calculated as follows:

[0013] where is the humidity value, is the humidity compensation factor, is the humidity sensitivity coefficient, is used to quantify the additional cooling effect caused by humidity, when = 0%, = 0, = 1, at which there is no humidity compensation, = 100%, is the maximum value, at which the maximum compensation effect is achieved, is the saturation vapor pressure formula, which is used to describe the nonlinear characteristics of the saturation vapor pressure with temperature, is an exponential function, which is used to calculate the temperature dependence of the saturation vapor pressure, is the saturation vapor pressure coefficient, is the temperature offset constant.

[0014] Optionally, a target area temperature distribution map is constructed based on the temperature values on the cruise path, including:

[0015] The altitude values and corresponding temperature values on the cruise path are obtained to construct a temperature distribution standard based on altitude, and a target area temperature distribution map is constructed based on the altitude fluctuations of the target area.

[0016] Optionally, in the case where the drip irrigation amount does not match the target area temperature distribution map, a temperature anomaly warning is triggered to make the drip irrigation system change the drip irrigation amount according to the target area temperature distribution map, including:

[0017] Obtaining a historical target area temperature distribution map generated by multiple inspections in a first time period, and obtaining a time-temperature curve of multiple local irrigation areas in the target area based on the multiple historical target area temperature distribution maps, denoted as a sample curve;

[0018] A plurality of modal functions are obtained by empirical mode decomposition of the sample curve, and then a Hilbert spectrum corresponding to the sample curve is obtained based on the modal functions by Hilbert-Huang transformation, and then the Hilbert spectrum is integrated to obtain a corresponding marginal spectrum, and the marginal spectrum is summed to obtain a drip irrigation demand quantity reference value of the sample curve, which is used to query the drip irrigation quantity of the corresponding area in the drip irrigation reference table;

[0019] Wherein, the specific calculation method is: , wherein is the drip irrigation demand quantity reference value of the local irrigation area at time t, is the frequency, used to represent the upper limit of integration, and n is the number of modal functions, represents the amplitude of the i-th modal function as a function of time, is the instantaneous frequency of the i-th modal function, represents the cumulative phase based on time, represents the cosine term of the cumulative phase based on time, and the above The summation range of i is from 1 to n+1, including all modal function components and possible residual terms.

[0020] The beneficial effects of the present application are:

[0021] The present application uses a unmanned aerial vehicle to perform temperature survey of a target area based on a preset cruise path, and then constructs a target area temperature distribution map, and dynamically adjusts the drip irrigation quantity of each drip irrigation sub-area in the target area according to the distribution change of the target area temperature distribution map within a certain time;

[0022] Secondly, since the temperature sensor is affected by the cooling effect of the airflow during high-speed flight, the temperature measurement value will be lower than the true value, therefore, the present application innovatively introduces a flight speed compensation term to effectively offset the sensor cooling effect caused by high-speed flight, which includes dynamic wind speed compensation and environmental adaptability enhancement. In terms of dynamic wind speed compensation, the non-linear influence of wind speed on temperature measurement is accurately quantified by using error proportion coefficient k and index n, to ensure that the compensation term actively offsets the error when the flight speed >0; In terms of environmental adaptability enhancement, a secondary correction is performed in combination with an altitude compensation factor and a humidity compensation factor to eliminate geographical and meteorological interference, and significantly improve the reliability of temperature data in complex environments.

[0023] 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

[0024] 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.

[0025] 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

[0026] 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.

[0027] 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.

[0028] Example 1:

[0029] 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.

[0030] 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;

[0031] 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:

[0032] 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;

[0033] , 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;

[0034] The calculation method of the above altitude compensation factor is:

[0035] , 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;

[0036] The humidity compensation factor is calculated as follows:

[0037] , 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 a saturation vapor pressure formula used to describe the nonlinear characteristics of the saturation vapor pressure with temperature, is an exponential function used to calculate the temperature dependence of the saturation vapor pressure, is a saturation vapor pressure coefficient, is a temperature offset constant.

[0038] Step S200, based on the temperature value on the cruise path, a target area temperature distribution map is constructed, and the drip irrigation amount in the current target area is obtained, and in the case that the drip irrigation amount does not match the target area temperature distribution map, a temperature anomaly warning is triggered, so that the drip irrigation system changes the drip irrigation amount according to the target area temperature distribution map.

[0039] Among them, the specific implementation mode of the above-mentioned in the case that the drip irrigation amount does not match the target area temperature distribution map, triggering a temperature anomaly warning, so that the drip irrigation system changes the drip irrigation amount according to the target area temperature distribution map is:

[0040] Obtain the historical target area temperature distribution map generated by multiple inspections in the first time period, and based on the multiple historical target area temperature distribution maps, obtain the time-temperature curve of multiple local irrigation areas in the target area, denoted as sample curve;

[0041] The sample curve is decomposed by empirical mode decomposition to obtain multiple modal functions, and then the Hilbert transform is performed based on the modal functions to obtain the Hilbert spectrum corresponding to the sample curve, and then the integral is performed to obtain the corresponding marginal spectrum, and the sum of the marginal spectrum is obtained. The drip irrigation demand amount reference value of the sample curve, which can be understood as the cumulative heat amount in a certain period of time, which is used as a reference value for the drip irrigation amount in this period of time, wherein the correlation between the heat cumulative value and the drip irrigation amount is not linear, but is tested and recorded in the drip irrigation reference table through a large number of experiments. The drip irrigation demand amount reference value is used to query the drip irrigation amount of the corresponding area in the drip irrigation reference table;

[0042] Wherein, the specific calculation method is: , wherein is the drip irrigation demand amount reference value of the local irrigation area at time t, is the frequency, used to represent the upper limit of the integral, and n is the number of modal functions, represents the amplitude of the i-th modal function as a function of time, is the instantaneous frequency of the i-th modal function, represents the cumulative phase based on time, represents the cosine term of the cumulative phase based on time, and the above The sum range of the above is i=1 to n+1, which includes all modal function components and possible residual terms.

[0043] In the embodiment, the unmanned aerial vehicle is used to perform temperature survey on the target area based on a preset cruise path, to construct a temperature distribution map of the target area, and to dynamically adjust the drip irrigation amount of each drip irrigation sub-area in the target area according to the distribution change of the temperature distribution map of the target area within a certain time.

[0044] Secondly, since the temperature sensor is affected by the airflow cooling effect during high-speed flight of the unmanned aerial vehicle, the temperature measurement value is lower than the true value, therefore, the flight speed compensation term is introduced innovatively to effectively offset the sensor cooling effect caused by high-speed flight, the compensation includes dynamic wind speed compensation and environmental adaptability enhancement, as for the dynamic wind speed compensation, the error proportion coefficient k and the index n are used to accurately quantify the nonlinear influence of wind speed on temperature measurement, to ensure that the compensation term actively offsets the error when the flight speed is greater than 0; as for the environmental adaptability enhancement, the altitude compensation factor and the humidity compensation factor are combined for secondary correction, to eliminate geographical and meteorological interference, and to significantly improve the reliability of temperature data in complex environments. >0 when the flight speed is greater than 0; as for the environmental adaptability enhancement, the altitude compensation factor and the humidity compensation factor are combined for secondary correction, to eliminate geographical and meteorological interference, and to significantly improve the reliability of temperature data in complex environments.

[0045] The above only describes the preferred embodiments of the present application and is not used to limit the present application, for those skilled in the art, the present application can have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

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 ​​along 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, so that the drip irrigation system changes the drip irrigation amount according to the temperature distribution map of the target area. Secondly, the temperature value on the cruising path is obtained in real time by a temperature sensor provided under the drone, including: 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; Secondly, 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.

2. The cruise monitoring and early warning method based on drone according to claim 1 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.

3. The cruise monitoring and early warning method based on drone according to claim 2 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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