CN116337014A - Processing method of unmanned aerial vehicle aerial photogrammetry data - Google Patents
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Abstract
The invention belongs to the technical field of unmanned aerial vehicle aerial photography, and particularly relates to a processing method of unmanned aerial vehicle aerial photography measurement data, which comprises unmanned aerial vehicle position deviation correction analysis, front strategy analysis before aerial photography and data transmission quality analysis.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle aerial photography, in particular to a processing method of unmanned aerial vehicle aerial photography measurement data.
Background
The unmanned aerial vehicle is an unmanned aerial vehicle which is controlled by a radio remote control device or an onboard computer program control system, the unmanned aerial vehicle is simple in structure and low in use cost, has great effects on emergency and early warning of sudden matters, the unmanned aerial vehicle aerial photography takes the unmanned aerial vehicle as an aerial platform, the onboard remote sensing device acquires information, the computer is used for processing image information and making images according to certain precision requirements, and the unmanned aerial vehicle aerial photography measurement data mainly refer to body condition detection data of the unmanned aerial vehicle before and after aerial photography;
at present, when aerial photography of an unmanned aerial vehicle is carried out, the unmanned aerial vehicle is mainly controlled manually to move and shoot, effective processing of relevant measurement data is difficult to carry out, position correction of the unmanned aerial vehicle at a distribution control point cannot be carried out automatically, pre-strategy analysis cannot be carried out before aerial photography to judge whether the aerial photography environment condition and the unmanned aerial vehicle condition are normal, clarity of shot images and operation safety of the unmanned aerial vehicle are difficult to ensure, and data transmission condition of the unmanned aerial vehicle cannot be detected and analyzed, so that follow-up maintenance and supervision of the unmanned aerial vehicle are not facilitated;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide a processing method of unmanned aerial vehicle aerial photogrammetry data, which solves the problems that the prior art cannot automatically correct the position of an unmanned aerial vehicle at a distribution control point and cannot perform front strategy analysis before aerial photography, the clarity of shot images and the operation safety of the unmanned aerial vehicle are difficult to ensure, the data transmission condition of the unmanned aerial vehicle cannot be detected and analyzed, and the follow-up maintenance and supervision are not facilitated.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a processing method of unmanned aerial vehicle aerial photogrammetry data comprises the following steps:
firstly, arranging a plurality of photographing control points in a required photographing area by an aerial photographing control platform, marking the photographing control points as analysis control points i, i= {1,2, …, n }, wherein n represents the number of the photographing control points and n is a natural number greater than 1, and transmitting the longitude, the latitude and the height of the analysis control points i to corresponding unmanned aerial vehicles;
step two, the corresponding unmanned aerial vehicle enters a corresponding analysis and control point i according to a preset flight track route, the unmanned aerial vehicle is subjected to position deviation correction analysis through an unmanned aerial vehicle position deviation correction analysis module, an unmanned aerial vehicle correction signal or an unmanned aerial vehicle in-place qualified signal is sent to an aerial photography control platform through analysis, the aerial photography control platform sends a correction instruction to the corresponding unmanned aerial vehicle after receiving the unmanned aerial vehicle correction signal, and the unmanned aerial vehicle automatically carries out position correction after receiving the corresponding correction instruction;
analyzing the unmanned aerial vehicle corresponding to the photographing control point i through a photographing front-end decision module after the position correction of the corresponding unmanned aerial vehicle is completed, judging whether front-end preparation operation of the corresponding unmanned aerial vehicle is qualified through analysis, generating a front-end preparation unqualified signal and sending the front-end preparation unqualified signal to an aerial photographing control platform if the front-end preparation operation is unqualified, and stopping aerial photographing measurement of the unmanned aerial vehicle after the aerial photographing control platform receives the front-end preparation unqualified signal; otherwise, the next step is carried out;
fourth, the camera shooting mechanism corresponding to the unmanned aerial vehicle carries out aerial shooting at the corresponding analysis and control point i, the shooting image, shooting time, shooting position, shooting environment information and unmanned aerial vehicle shooting condition information are packaged into a data folder, and the corresponding data folder is sent to a data storage module in an aerial shooting control platform for storage;
and fifthly, after the transmission of the corresponding data folder is completed, the photographic transmission quality analysis module carries out transmission quality analysis on the current data transmission, generates a transmission quality unqualified signal or a transmission quality qualified signal through the transmission quality analysis, and sends the transmission quality unqualified signal or the transmission quality unqualified signal to the aerial photographic control platform.
Further, the specific operation process of the unmanned aerial vehicle deviation correction analysis module comprises the following steps:
the corresponding unmanned aerial vehicle enters a corresponding analysis and control point i according to a preset flight track route to obtain the actual longitude, the actual latitude and the actual height of the corresponding unmanned aerial vehicle, the actual longitude of the unmanned aerial vehicle and the longitude of the analysis and control point i are subjected to difference calculation before shooting, the absolute value is taken to obtain a longitude position difference coefficient, the actual latitude of the unmanned aerial vehicle and the latitude of the analysis and control point i are subjected to difference calculation, the absolute value is taken to obtain a latitude position difference coefficient, and the actual height of the unmanned aerial vehicle and the height of the analysis and control point i are subjected to difference calculation to obtain a height position difference coefficient; and if at least one of the longitude potential difference coefficient, the latitude potential difference coefficient and the altitude potential difference coefficient of the corresponding unmanned aerial vehicle exceeds a corresponding preset threshold value, generating an unmanned aerial vehicle correction signal.
Further, if the longitude potential difference coefficient, the latitude potential difference coefficient and the altitude potential difference coefficient corresponding to the unmanned aerial vehicle do not exceed the corresponding preset threshold values, performing difference calculation on the preset longitude potential difference coefficient threshold value and the longitude potential difference coefficient to obtain a longitude threshold difference value, performing difference calculation on the preset latitude potential difference coefficient threshold value and the latitude potential difference coefficient to obtain a latitude threshold difference value, and performing difference calculation on the preset altitude potential difference coefficient threshold value and the altitude potential difference coefficient to obtain an altitude threshold difference value;
and carrying out numerical calculation on the longitude threshold difference value, the latitude threshold difference value and the height threshold difference value to obtain a in-place distribution unqualified coefficient, generating an unmanned aerial vehicle correction signal if the in-place distribution unqualified coefficient does not exceed a preset in-place distribution unqualified coefficient threshold value, generating an unmanned aerial vehicle in-place qualified signal if the in-place distribution unqualified coefficient exceeds a preset in-place distribution unqualified coefficient threshold value, transmitting the unmanned aerial vehicle correction signal and the in-place unmanned aerial vehicle qualified signal to a corresponding unmanned aerial vehicle through an aerial photography management and control platform, and carrying out position correction after the corresponding unmanned aerial vehicle receives the unmanned aerial vehicle correction signal.
Further, the specific operation process of the photographing front-end decision module comprises the following steps:
the method comprises the steps of obtaining an environment decision value of an unmanned aerial vehicle at a corresponding analysis and control point i through photographic environment detection analysis, comparing the environment decision value with a preset environment decision threshold value, generating a pre-preparation unqualified signal if the environment decision value exceeds the preset environment decision threshold value, obtaining vibration frequency, vibration amplitude and levelness of the corresponding unmanned aerial vehicle at the corresponding analysis and control point i if the environment decision value does not exceed the preset environment decision threshold value, calculating the vibration frequency, vibration amplitude and levelness to obtain an organism decision value, comparing the organism decision value with the preset organism decision threshold value, and generating a pre-preparation unqualified signal if the organism decision value exceeds the preset organism decision threshold value.
Further, the specific analysis process of the photographic environment detection analysis is as follows:
acquiring illumination brightness data of a corresponding unmanned aerial vehicle at a corresponding analysis and control point i, calling a preset shooting proper illumination brightness range, carrying out average value calculation on the maximum value and the minimum value of the preset shooting proper illumination brightness range to acquire an optimal brightness value, carrying out difference value calculation on the illumination brightness data and the optimal brightness value, taking an absolute value to acquire brightness deviation data, acquiring wind speed data and air visibility data of the corresponding unmanned aerial vehicle at the corresponding analysis and control point i, and carrying out numerical calculation on the brightness deviation data, the wind speed data and the air visibility data to acquire an environment decision value.
Further, if the body decision value does not exceed the preset body decision threshold, acquiring temperatures corresponding to a plurality of positions in the unmanned aerial vehicle, summing the temperatures at the plurality of positions in the unmanned aerial vehicle, taking an average value to acquire a body temperature average value, marking the position with the temperature exceeding the preset temperature threshold as Wen Yidian, acquiring the number of temperature abnormal points, calculating the ratio of the number of the temperature abnormal points to the number of the positions for temperature acquisition to generate a bad temperature point occupation ratio, acquiring a noise decibel value corresponding to the unmanned aerial vehicle, calculating the body temperature average value, the bad temperature point occupation ratio and the noise decibel value, acquiring a body operation condition value, comparing the body operation condition value with the preset body operation condition threshold, and generating an unmanned aerial vehicle early warning signal if the body operation condition value exceeds the preset body operation condition threshold.
Further, if the machine body operation condition value does not exceed the preset machine body operation condition threshold value, a plurality of detection time periods are set, power consumption of the unmanned aerial vehicle is obtained in the corresponding detection time periods, power consumption of the plurality of detection time periods is summed and averaged to obtain a power consumption average value of the unmanned aerial vehicle, power consumption of the plurality of detection time periods is calculated in variance to obtain a power consumption fluctuation value of the unmanned aerial vehicle, the power consumption average value of the unmanned aerial vehicle and the power consumption fluctuation value of the unmanned aerial vehicle are respectively compared with a preset power consumption average value range of the unmanned aerial vehicle and a preset power consumption fluctuation threshold value of the unmanned aerial vehicle, if the power consumption average value of the unmanned aerial vehicle is not in the preset power consumption average value range of the unmanned aerial vehicle or the power consumption fluctuation value of the unmanned aerial vehicle exceeds the preset power consumption fluctuation threshold value of the unmanned aerial vehicle, an unmanned aerial vehicle early warning signal is generated, and otherwise the unmanned aerial vehicle early warning signal is not generated.
Further, the specific operation process of the photographic transmission quality analysis module comprises:
after the corresponding unmanned aerial vehicle's camera shooting mechanism finishes the corresponding analysis and control point i aerial shooting image, send the data file folder to the aerial shooting management and control platform, obtain corresponding unmanned aerial vehicle at the corresponding analysis and control point i carry out data transmission's beginning time and end time, carry out difference calculation and obtain the transmission duration value with beginning time, and obtain the memory value that corresponds data file folder and occupy, carry out ratio calculation and obtain data transmission efficiency coefficient with the memory value that corresponds data file folder occupy, if data transmission efficiency coefficient does not surpass the data transmission efficiency threshold value of predetermineeing, then generate transmission quality disqualification signal.
Further, if the data transmission efficiency coefficient exceeds a preset data transmission efficiency threshold, performing difference calculation on the data transmission efficiency coefficient and the preset data transmission efficiency threshold to obtain a transmission efficiency threshold difference value, obtaining data transmission speeds of a plurality of detection time points in the transmission process, performing variance calculation on the data transmission speeds of the plurality of detection time points to obtain a transmission speed fluctuation coefficient, performing numerical calculation on the transmission efficiency threshold difference value and the transmission speed fluctuation coefficient to obtain a transmission quality coefficient, if the transmission quality coefficient exceeds the preset transmission quality coefficient threshold, generating a transmission quality qualified signal, and otherwise, generating a transmission quality disqualification signal.
Further, the aerial photography supervision platform is in communication connection with the unmanned aerial vehicle supervision terminal, the aerial photography supervision platform sends the data folder to the unmanned aerial vehicle supervision terminal, and the unmanned aerial vehicle correction signal or the unmanned aerial vehicle in-place qualified signal, the pre-preparation unqualified signal, the unmanned aerial vehicle early warning signal and the transmission quality unqualified signal or the transmission quality qualified signal are sent to the unmanned aerial vehicle supervision terminal.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the unmanned aerial vehicle position deviation correction analysis module, position deviation correction analysis is carried out on the corresponding unmanned aerial vehicle, an unmanned aerial vehicle correction signal or an unmanned aerial vehicle in-place qualified signal is sent to the aerial photography control platform, and the unmanned aerial vehicle is enabled to automatically carry out position correction after receiving the unmanned aerial vehicle correction signal, so that position analysis and automatic correction adjustment before aerial photography of the unmanned aerial vehicle are realized; the unmanned aerial vehicle corresponding to the photographing control point i is subjected to environment decision analysis and organism decision analysis through the photographing front-end decision module to judge whether front-end preparation operation of the corresponding unmanned aerial vehicle is qualified or not, so that aerial photographing measurement of the unmanned aerial vehicle is stopped in time, aerial photographing effects are further guaranteed, whether operation abnormality exists in the corresponding unmanned aerial vehicle is judged through analysis, follow-up timely maintenance and overhaul of the unmanned aerial vehicle by corresponding supervision personnel are facilitated, and potential safety hazards existing in the corresponding unmanned aerial vehicle are reduced;
2. according to the invention, the current data transmission is subjected to transmission quality analysis through the photographic transmission quality analysis module, the transmission quality unqualified signal or the transmission quality unqualified signal is generated, the transmission quality unqualified signal or the transmission quality unqualified signal is sent to the aerial photography control platform, and the transmission quality unqualified signal or the transmission quality unqualified signal is sent to the unmanned aerial vehicle supervision terminal through the aerial photography control platform, so that the supervision personnel can know the data transmission condition in time, and the supervision personnel can conveniently and correspondingly carry out targeted maintenance and overhaul subsequently, so that the stability and the high efficiency of the subsequent data transmission of the corresponding unmanned aerial vehicle are ensured.
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For the convenience of those skilled in the art, the present invention will be further described with reference to the accompanying drawings;
FIG. 1 is a flow chart of the method of the present invention;
fig. 2 is a system block diagram of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one:
as shown in fig. 1, the processing method of the unmanned aerial vehicle aerial photogrammetry data provided by the invention comprises the following steps:
firstly, arranging a plurality of photographing control points in a required photographing area by an aerial photographing control platform, marking the photographing control points as analysis control points i, i= {1,2, …, n }, wherein n represents the number of the photographing control points and n is a natural number greater than 1, and transmitting the longitude, the latitude and the height of the analysis control points i to corresponding unmanned aerial vehicles;
step two, the corresponding unmanned aerial vehicle enters a corresponding analysis and control point i according to a preset flight track route, the unmanned aerial vehicle is subjected to position deviation correction analysis through an unmanned aerial vehicle position deviation correction analysis module, an unmanned aerial vehicle correction signal or an unmanned aerial vehicle in-place qualified signal is sent to an aerial photography control platform through analysis, the aerial photography control platform sends a correction instruction to the corresponding unmanned aerial vehicle after receiving the unmanned aerial vehicle correction signal, and the unmanned aerial vehicle automatically carries out position correction after receiving the corresponding correction instruction;
analyzing the unmanned aerial vehicle corresponding to the photographing control point i through a photographing front-end decision module after the position correction of the corresponding unmanned aerial vehicle is completed, judging whether front-end preparation operation of the corresponding unmanned aerial vehicle is qualified through analysis, generating a front-end preparation unqualified signal and sending the front-end preparation unqualified signal to an aerial photographing control platform if the front-end preparation operation is unqualified, and stopping aerial photographing measurement of the unmanned aerial vehicle after the aerial photographing control platform receives the front-end preparation unqualified signal; otherwise, the next step is carried out;
fourth, the camera shooting mechanism corresponding to the unmanned aerial vehicle carries out aerial shooting at the corresponding analysis and control point i, the shooting image, shooting time, shooting position, shooting environment information and unmanned aerial vehicle shooting condition information are packaged into a data folder, and the corresponding data folder is sent to a data storage module in an aerial shooting control platform for storage;
and fifthly, after the transmission of the corresponding data folder is completed, the photographic transmission quality analysis module carries out transmission quality analysis on the current data transmission, generates a transmission quality unqualified signal or a transmission quality qualified signal through the transmission quality analysis, and sends the transmission quality unqualified signal or the transmission quality unqualified signal to the aerial photographic control platform.
The aerial photography supervision platform is in communication connection with the unmanned aerial vehicle supervision terminal, and sends the data folder to the unmanned aerial vehicle supervision terminal, and sends unmanned aerial vehicle correction signals or unmanned aerial vehicle in-place qualified signals, pre-preparation unqualified signals, unmanned aerial vehicle early warning signals or transmission quality unqualified signals to the unmanned aerial vehicle supervision terminal.
Embodiment two:
as shown in fig. 2, the difference between the present embodiment and embodiment 1 is that the aerial photography control platform is in communication connection with the unmanned aerial vehicle deviation correction analysis module, and the specific operation process of the unmanned aerial vehicle deviation correction analysis module is as follows:
the corresponding unmanned aerial vehicle enters a corresponding analysis and control point i according to a preset flight track route to obtain the actual longitude, the actual latitude and the actual height of the corresponding unmanned aerial vehicle, the actual longitude of the unmanned aerial vehicle and the longitude of the analysis and control point i are subjected to difference calculation before shooting, an absolute value is taken to obtain a longitude potential difference coefficient JCi, the actual latitude of the unmanned aerial vehicle and the latitude of the analysis and control point i are subjected to difference calculation, an absolute value is taken to obtain a latitude potential difference coefficient WCi, and the actual height of the unmanned aerial vehicle and the height of the analysis and control point i are subjected to difference calculation to obtain a height potential difference coefficient GCi;
respectively carrying out numerical comparison on a longitude potential difference coefficient JCi, a latitude potential difference coefficient WCi and a height potential difference coefficient GCi with a preset longitude potential difference coefficient threshold value, a preset latitude potential difference coefficient threshold value and a preset height potential difference coefficient threshold value, and generating an unmanned plane correction signal if at least one of the longitude potential difference coefficient JCi, the latitude potential difference coefficient WCi and the height potential difference coefficient GCi of the corresponding unmanned plane exceeds the corresponding preset threshold value; if the longitude potential difference coefficient JCi, the latitude potential difference coefficient WCi and the altitude potential difference coefficient GCi of the corresponding unmanned aerial vehicle do not exceed the corresponding preset threshold values, performing difference calculation on the preset longitude potential difference coefficient threshold value and the longitude potential difference coefficient to obtain a longitude threshold value JYi, performing difference calculation on the preset latitude potential difference coefficient threshold value and the latitude potential difference coefficient to obtain a latitude threshold difference value WYi, and performing difference calculation on the preset altitude potential difference coefficient threshold value and the altitude potential difference coefficient to obtain an altitude threshold difference value GYi;
numerical calculation is carried out through a formula bwi=a1× JYi +a2×wyi+a3× GYi and substituted into a longitude threshold difference value JYi, a latitude threshold difference value WYi and a altitude threshold difference value GYi, and a control in-place disqualification coefficient BWi of the corresponding unmanned aerial vehicle at a corresponding analysis control point i is obtained through the numerical calculation; wherein a1, a2 and a3 are preset weight coefficients, and the values of a1, a2 and a3 are all larger than zero; the numerical value of the in-place unqualified coefficient BWI is in a proportional relation with the longitude threshold difference value JYi, the latitude threshold difference value WYi and the altitude threshold difference value GYi, and the smaller the numerical value of the in-place unqualified coefficient BWI is, the more the current control position of the corresponding unmanned plane deviates from the corresponding analysis control point i;
and comparing the in-place control disqualification coefficient BWI with a preset in-place control disqualification coefficient threshold value which is recorded and stored in advance, generating an unmanned aerial vehicle correction signal if the in-place control disqualification coefficient BWI does not exceed the preset in-place control disqualification coefficient threshold value, generating an unmanned aerial vehicle in-place qualification signal if the in-place control disqualification coefficient BWI exceeds the preset in-place control disqualification coefficient threshold value, transmitting the unmanned aerial vehicle correction signal and the unmanned aerial vehicle in-place qualification signal to a corresponding unmanned aerial vehicle through an aerial photography management and control platform, carrying out position correction after the corresponding unmanned aerial vehicle receives the unmanned aerial vehicle correction signal, and preparing the corresponding unmanned aerial vehicle for aerial photography after the unmanned aerial vehicle in-place qualification signal is received, so that the position analysis and automatic correction and adjustment before aerial photography of the unmanned aerial vehicle are realized, and the subsequent aerial photography effect and accuracy are ensured.
Embodiment III:
as shown in fig. 2, the difference between the present embodiment and embodiments 1 and 2 is that the aerial photography control platform is in communication connection with a photography front-end decision module, and the specific operation process of the photography front-end decision module is as follows:
acquiring illumination brightness data of a corresponding unmanned aerial vehicle at a corresponding analysis and control point i, calling a preset shooting proper illumination brightness range, carrying out average value calculation on the maximum value and the minimum value of the preset shooting proper illumination brightness range to acquire an optimal brightness value, carrying out difference value calculation on the illumination brightness data and the optimal brightness value, taking an absolute value to acquire brightness deviation data LPi, and acquiring wind speed data and air visibility data of the corresponding unmanned aerial vehicle at the corresponding analysis and control point i, wherein the wind speed data and the air visibility data are respectively marked as FSi and NJi; the air visibility data is a data value representing the visibility of a corresponding area, and the smaller the dust concentration and the fog concentration in the air of the current area, the larger the area visibility is;
calculating the values of the brightness deviation data LPi, the wind speed data FSi and the air visibility data NJi through an environment decision analysis formula hci=b1+b2+fsi+b3/NJi, and obtaining an environment decision value HCi corresponding to the analysis control point i after the numerical calculation; wherein b1, b2 and b3 are preset weight coefficients, b1 is more than 1 and b2 is more than 3; the magnitude of the environmental decision value HCi is in a direct proportion relation with the brightness deviation data LPi and the wind speed data FSi and in an inverse proportion relation with the air visibility data NJi, and the larger the magnitude of the environmental decision value HCi is, the worse the environmental condition of the current corresponding analysis and distribution point i for aerial photography is, and the more unsuitable the aerial photography is currently performed;
comparing the environmental decision value HCi with a preset environmental decision threshold value which is input and stored in advance, generating a pre-preparation unqualified signal if the environmental decision value HCi exceeds the preset environmental decision threshold value, and acquiring the vibration frequency, the vibration amplitude and the levelness of the corresponding unmanned aerial vehicle at the corresponding analysis control point i and marking the vibration frequency, the vibration amplitude and the levelness as ZPi, ZFi and SPI respectively if the environmental decision value HCi does not exceed the preset environmental decision threshold value; the levelness is a data value which corresponds to the deviation angle of the unmanned aerial vehicle in aerial photography, and the smaller the deviation angle of the unmanned aerial vehicle in aerial photography is, the smaller the value of the levelness is, so that the aerial photography effect is improved;
numerical calculation is performed on the vibration frequency ZPi, the vibration amplitude ZFi and the levelness SPi through a formula JCi =up1× ZPi +up2× ZFi +up3×spi to obtain an organism decision value JCi, wherein up1, up2 and up3 are preset weight coefficients, and 0 < up1 < up2 < up3; and, the smaller the numerical value of the organism decision value JCi is, the more stable the corresponding unmanned aerial vehicle operates at present; the body decision value JCi is compared with a preset body decision threshold value which is recorded and stored in advance, and if the body decision value JCi exceeds the preset body decision threshold value, a pre-preparation unqualified signal is generated.
If the body decision value JCi does not exceed the preset body decision threshold, acquiring temperatures at a plurality of positions in the corresponding unmanned aerial vehicle, summing the temperatures at the plurality of positions in the unmanned aerial vehicle, taking an average value to acquire a machine temperature average value WJi, marking the position with the temperature exceeding the preset temperature threshold as Wen Yidian, acquiring the number of temperature abnormal points, calculating the ratio of the number of the temperature abnormal points to the number of the positions for temperature acquisition to generate a bad temperature point occupation value WZi, and acquiring a noise decibel value YBi generated by the corresponding unmanned aerial vehicle;
calculating the machine temperature average value WJi, the bad temperature point occupation ratio WZi and the noise decibel value YBi according to a formula JKi =th1× WJi +th2× WZi +th3× YBi to obtain a machine body operating condition value JKi, wherein th1, th2 and th3 are preset weight coefficients, th2 > th1 > th3 > 0, and the numerical value of the machine body operating condition value JKi is in direct proportion to the machine temperature average value WJi, the bad temperature point occupation ratio WZi and the noise decibel value YBi; comparing the machine body operating condition value JKi with a preset machine body operating condition threshold value which is recorded and stored in advance, and generating an unmanned aerial vehicle early warning signal if the machine body operating condition value JKi exceeds the preset machine body operating condition threshold value;
if the machine body operating condition value JKi does not exceed the preset machine body operating condition threshold, a plurality of detection time periods are set, power consumption of the unmanned aerial vehicle is obtained in the corresponding detection time periods, the power consumption of the plurality of detection time periods is summed and averaged to obtain the power consumption average value HDi of the unmanned aerial vehicle, the power consumption of the plurality of detection time periods is subjected to variance calculation to obtain the power consumption fluctuation value HBi of the unmanned aerial vehicle, the power consumption average value HDi of the unmanned aerial vehicle and the power consumption fluctuation value HBi of the unmanned aerial vehicle are respectively subjected to numerical comparison with a preset power consumption average value range of the unmanned aerial vehicle and a preset power consumption fluctuation threshold of the unmanned aerial vehicle which are recorded and stored in advance, if the power consumption average value HDi of the unmanned aerial vehicle is not in the preset power consumption average value range of the unmanned aerial vehicle or the power consumption fluctuation value HBi of the unmanned aerial vehicle exceeds the preset power consumption fluctuation threshold of the unmanned aerial vehicle, an unmanned aerial vehicle early warning signal is generated, and otherwise the unmanned aerial vehicle early warning signal is not generated.
The unmanned aerial vehicle is subjected to pre-decision analysis before aerial photography operation of the analysis control point i through a pre-decision module, a pre-preparation unqualified signal, an unmanned aerial vehicle early warning signal or no signal is generated through pre-decision analysis, the pre-preparation unqualified signal or the unmanned aerial vehicle early warning signal is sent to an aerial photography control platform, the aerial photography control platform sends a corresponding signal to an unmanned aerial vehicle supervision terminal, aerial photography of the corresponding analysis control point i should be suspended in time when the unmanned aerial vehicle supervision terminal receives the pre-preparation unqualified signal, aerial photography of the corresponding analysis control point i can be suspended when the unmanned aerial vehicle early warning signal is received, or overhaul and maintenance of the unmanned aerial vehicle can be conducted in time after the current aerial photography is finished, and potential safety hazards of the corresponding unmanned aerial vehicle are reduced.
Embodiment four:
as shown in fig. 2, the difference between this embodiment and embodiments 1,2, and 3 is that the aerial photography control platform is communicatively connected to the photography transmission quality analysis module, and the specific operation procedure of the photography transmission quality analysis module is as follows:
after the aerial image of the corresponding analysis and control point i is finished, the image pickup mechanism of the corresponding unmanned aerial vehicle sends the data folder to the aerial image management and control platform, obtains the starting time and the ending time of data transmission of the corresponding unmanned aerial vehicle at the corresponding analysis and control point i, calculates the difference between the ending time and the starting time to obtain a transmission time length value, obtains the memory value occupied by the corresponding data folder, calculates the ratio of the memory value occupied by the corresponding data folder to the transmission time length value to obtain a data transmission efficiency coefficient CXi, compares the data transmission efficiency coefficient CXi with a preset data transmission efficiency threshold value which is input and stored in advance, and generates a transmission quality disqualification signal if the data transmission efficiency coefficient CXi does not exceed the preset data transmission efficiency threshold value;
if the data transmission efficiency coefficient exceeds a preset data transmission efficiency threshold, performing difference calculation on the preset data transmission efficiency threshold and the data transmission efficiency coefficient to obtain a transmission efficiency threshold difference YCi, obtaining data transmission speeds of a plurality of detection time points in the transmission process, performing variance calculation on the data transmission speeds of the plurality of detection time points to obtain a transmission speed fluctuation coefficient CBi, wherein the smaller the value of the transmission speed fluctuation coefficient CBi is, the more stable the data transmission efficiency is, performing numerical calculation on the transmission efficiency threshold difference YCi and the transmission speed fluctuation coefficient CBi through a formula ZLI=eu1× YCi +eu2/(CBi+0.845), and obtaining a transmission quality coefficient ZLI after numerical calculation; wherein, eu1 and eu2 are preset proportional coefficients, and 1 < eu2;
it should be noted that, the value of the transmission quality coefficient ZLi is in a proportional relationship with the transmission efficiency threshold difference YCi, and in an inverse relationship with the value of the transmission speed fluctuation coefficient CBi, the larger the value of the transmission efficiency threshold difference YCi is, the smaller the value of the transmission speed fluctuation coefficient CBi is, the larger the value of the transmission quality coefficient ZLi is, which indicates that the transmission efficiency is higher and the transmission efficiency is more stable; and carrying out numerical comparison on the transmission quality coefficient ZLI and a preset transmission quality coefficient threshold value which is recorded and stored in advance, if the transmission quality coefficient ZLI exceeds the preset transmission quality coefficient threshold value, generating a transmission quality qualified signal, and if the transmission quality coefficient ZLI does not exceed the preset transmission quality coefficient threshold value, generating a transmission quality unqualified signal.
After the transmission of the corresponding data folder is completed, the current data transmission is subjected to transmission quality analysis through the photographing transmission quality analysis module, a transmission quality unqualified signal or a transmission quality qualified signal is generated through the transmission quality analysis, the transmission quality unqualified signal or the transmission quality unqualified signal is sent to the aerial photographing management and control platform, and the transmission quality unqualified signal or the transmission quality unqualified signal is sent to the unmanned aerial vehicle supervision terminal through the aerial photographing management and control platform, so that supervision personnel can know the data transmission condition in time, and the corresponding supervision personnel can conveniently and pointedly maintain and overhaul the unmanned aerial vehicle, so that the stability and the high efficiency of the subsequent data transmission of the corresponding unmanned aerial vehicle are guaranteed.
The working principle of the invention is as follows: when the unmanned aerial vehicle position deviation correction analysis module is used, the corresponding unmanned aerial vehicle is subjected to position deviation correction analysis, an unmanned aerial vehicle correction signal or an unmanned aerial vehicle in-place qualified signal is sent to the aerial photography control platform, the unmanned aerial vehicle is automatically subjected to position correction after the unmanned aerial vehicle correction signal is received, position analysis and automatic correction adjustment before aerial photography of the unmanned aerial vehicle are realized, and the subsequent aerial photography effect is ensured; the unmanned aerial vehicle corresponding to the photographing control point i is subjected to environment decision analysis and organism decision analysis through the photographing front-end decision making module so as to judge whether front-end preparation operation of the corresponding unmanned aerial vehicle is qualified, if the front-end preparation operation is unqualified, a front-end preparation unqualified signal is generated, the aerial photographing control platform stops carrying out aerial photographing measurement of the unmanned aerial vehicle after receiving the front-end preparation unqualified signal, further the aerial photographing effect is guaranteed, whether the corresponding unmanned aerial vehicle is abnormal in operation is judged through analysis, an unmanned aerial vehicle early warning signal is generated when the operation abnormality is judged to exist, the follow-up timely maintenance and overhaul of the unmanned aerial vehicle by corresponding supervision personnel are facilitated, and the potential safety hazards existing in the corresponding unmanned aerial vehicle are reduced.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation. The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (10)
1. The processing method of the unmanned aerial vehicle aerial photogrammetry data is characterized by comprising the following steps of:
firstly, arranging a plurality of photographing control points in a required photographing area by an aerial photographing control platform, marking the photographing control points as analysis control points i, and transmitting the longitude, latitude and height of the analysis control points i to a corresponding unmanned aerial vehicle;
step two, the corresponding unmanned aerial vehicle enters a corresponding analysis and control point i according to a preset flight track route, the unmanned aerial vehicle is subjected to position deviation correction analysis through an unmanned aerial vehicle position deviation correction analysis module, an unmanned aerial vehicle correction signal or an unmanned aerial vehicle in-place qualified signal is sent to an aerial photography control platform through analysis, the aerial photography control platform sends a correction instruction to the corresponding unmanned aerial vehicle after receiving the unmanned aerial vehicle correction signal, and the unmanned aerial vehicle automatically carries out position correction after receiving the corresponding correction instruction;
analyzing the unmanned aerial vehicle corresponding to the photographing control point i through a photographing front-end decision module after the position correction of the corresponding unmanned aerial vehicle is completed, judging whether front-end preparation operation of the corresponding unmanned aerial vehicle is qualified through analysis, generating a front-end preparation unqualified signal and sending the front-end preparation unqualified signal to an aerial photographing control platform if the front-end preparation operation is unqualified, and stopping aerial photographing measurement of the unmanned aerial vehicle after the aerial photographing control platform receives the front-end preparation unqualified signal; otherwise, the next step is carried out;
fourth, the camera shooting mechanism corresponding to the unmanned aerial vehicle carries out aerial shooting at the corresponding analysis and control point i, the shooting image, shooting time, shooting position, shooting environment information and unmanned aerial vehicle shooting condition information are packaged into a data folder, and the corresponding data folder is sent to a data storage module in an aerial shooting control platform for storage;
and fifthly, after the transmission of the corresponding data folder is completed, the photographic transmission quality analysis module carries out transmission quality analysis on the current data transmission, generates a transmission quality unqualified signal or a transmission quality qualified signal through the transmission quality analysis, and sends the transmission quality unqualified signal or the transmission quality unqualified signal to the aerial photographic control platform.
2. The method for processing unmanned aerial vehicle aerial photogrammetry data according to claim 1, wherein the specific operation process of the unmanned aerial vehicle misalignment correction analysis module comprises:
the corresponding unmanned aerial vehicle enters a corresponding analysis and control point i according to a preset flight track route to obtain the actual longitude, the actual latitude and the actual height of the corresponding unmanned aerial vehicle, the actual longitude of the unmanned aerial vehicle and the longitude of the analysis and control point i are subjected to difference calculation before shooting, the absolute value is taken to obtain a longitude position difference coefficient, the actual latitude of the unmanned aerial vehicle and the latitude of the analysis and control point i are subjected to difference calculation, the absolute value is taken to obtain a latitude position difference coefficient, and the actual height of the unmanned aerial vehicle and the height of the analysis and control point i are subjected to difference calculation to obtain a height position difference coefficient; and if at least one of the longitude potential difference coefficient, the latitude potential difference coefficient and the altitude potential difference coefficient of the corresponding unmanned aerial vehicle exceeds a corresponding preset threshold value, generating an unmanned aerial vehicle correction signal.
3. The method for processing the aerial photogrammetry data of the unmanned aerial vehicle according to claim 2, wherein if the longitude potential difference coefficient, the latitude potential difference coefficient and the altitude potential difference coefficient of the corresponding unmanned aerial vehicle do not exceed the corresponding preset threshold values, the longitude threshold difference value is obtained by performing difference calculation on the preset longitude potential difference coefficient threshold value and the longitude potential difference coefficient, the latitude threshold difference value is obtained by performing difference calculation on the preset latitude potential difference coefficient threshold value and the latitude potential difference coefficient, and the altitude threshold difference value is obtained by performing difference calculation on the preset altitude potential difference coefficient threshold value and the altitude potential difference coefficient;
and carrying out numerical calculation on the longitude threshold difference value, the latitude threshold difference value and the height threshold difference value to obtain a in-place distribution unqualified coefficient, generating an unmanned aerial vehicle correction signal if the in-place distribution unqualified coefficient does not exceed a preset in-place distribution unqualified coefficient threshold value, generating an unmanned aerial vehicle in-place qualified signal if the in-place distribution unqualified coefficient exceeds a preset in-place distribution unqualified coefficient threshold value, transmitting the unmanned aerial vehicle correction signal and the in-place unmanned aerial vehicle qualified signal to a corresponding unmanned aerial vehicle through an aerial photography management and control platform, and carrying out position correction after the corresponding unmanned aerial vehicle receives the unmanned aerial vehicle correction signal.
4. The method for processing aerial photogrammetry data of an unmanned aerial vehicle according to claim 1, wherein the specific operation process of the pre-photography decision module comprises:
the method comprises the steps of obtaining an environment decision value of an unmanned aerial vehicle at a corresponding analysis and control point i through photographic environment detection analysis, comparing the environment decision value with a preset environment decision threshold value, generating a pre-preparation unqualified signal if the environment decision value exceeds the preset environment decision threshold value, obtaining vibration frequency, vibration amplitude and levelness of the corresponding unmanned aerial vehicle at the corresponding analysis and control point i if the environment decision value does not exceed the preset environment decision threshold value, calculating the vibration frequency, vibration amplitude and levelness to obtain an organism decision value, comparing the organism decision value with the preset organism decision threshold value, and generating a pre-preparation unqualified signal if the organism decision value exceeds the preset organism decision threshold value.
5. The method for processing aerial photogrammetry data of an unmanned aerial vehicle according to claim 4, wherein the specific analysis process of the photographic environment detection analysis is as follows:
acquiring illumination brightness data of a corresponding unmanned aerial vehicle at a corresponding analysis and control point i, calling a preset shooting proper illumination brightness range, carrying out average value calculation on the maximum value and the minimum value of the preset shooting proper illumination brightness range to acquire an optimal brightness value, carrying out difference value calculation on the illumination brightness data and the optimal brightness value, taking an absolute value to acquire brightness deviation data, acquiring wind speed data and air visibility data of the corresponding unmanned aerial vehicle at the corresponding analysis and control point i, and carrying out numerical calculation on the brightness deviation data, the wind speed data and the air visibility data to acquire an environment decision value.
6. The method for processing unmanned aerial vehicle aerial photogrammetry data according to claim 4, wherein if the body decision value does not exceed a preset body decision threshold, temperatures corresponding to a plurality of positions inside the unmanned aerial vehicle are obtained, the temperatures corresponding to the plurality of positions inside the unmanned aerial vehicle are summed and averaged to obtain a body temperature average value, the positions with the temperatures exceeding the preset temperature threshold are marked as Wen Yidian, the number of abnormal temperature points is obtained, the number of abnormal temperature points is calculated by means of the ratio of the number of the abnormal temperature points to the number of the positions with the temperature acquisition to generate a poor temperature point occupation value, the noise decibel value corresponding to the unmanned aerial vehicle is obtained, the body operation value is obtained after the body temperature average value, the poor temperature point occupation value and the noise decibel value are calculated by means of numerical values, the body operation value is compared with the preset body operation threshold, and if the body operation value exceeds the preset body operation threshold, an unmanned aerial vehicle early warning signal is generated.
7. The method for processing unmanned aerial vehicle aerial photogrammetry data according to claim 6, wherein if the machine body operating condition value does not exceed a preset machine body operating condition threshold, a plurality of detection periods are set, power consumption of the unmanned aerial vehicle in the corresponding detection period is obtained, power consumption of the unmanned aerial vehicle in the corresponding detection period is summed and averaged to obtain a power consumption average value of the unmanned aerial vehicle, power consumption of the detection periods is calculated and variance of the power consumption of the detection periods is calculated to obtain a power consumption fluctuation value of the unmanned aerial vehicle, the power consumption average value of the unmanned aerial vehicle and the power consumption fluctuation value of the unmanned aerial vehicle are respectively compared with a preset power consumption average value range of the unmanned aerial vehicle and a preset power consumption fluctuation threshold of the unmanned aerial vehicle, if the power consumption average value of the unmanned aerial vehicle is not in the preset power consumption average value range of the unmanned aerial vehicle or the power consumption fluctuation value of the unmanned aerial vehicle exceeds the preset power consumption fluctuation threshold of the unmanned aerial vehicle, an unmanned aerial vehicle early warning signal is generated, and otherwise the unmanned aerial vehicle early warning signal is not generated.
8. The method for processing aerial photogrammetry data of an unmanned aerial vehicle according to claim 7, wherein the specific operation process of the photogrammetric mass analysis module comprises:
after the corresponding unmanned aerial vehicle's camera shooting mechanism finishes the corresponding analysis and control point i aerial shooting image, send the data file folder to the aerial shooting management and control platform, obtain corresponding unmanned aerial vehicle at the corresponding analysis and control point i carry out data transmission's beginning time and end time, carry out difference calculation and obtain the transmission duration value with beginning time, and obtain the memory value that corresponds data file folder and occupy, carry out ratio calculation and obtain data transmission efficiency coefficient with the memory value that corresponds data file folder occupy, if data transmission efficiency coefficient does not surpass the data transmission efficiency threshold value of predetermineeing, then generate transmission quality disqualification signal.
9. The method for processing aerial photogrammetry data of an unmanned aerial vehicle according to claim 8, wherein if the data transmission efficiency coefficient exceeds a preset data transmission efficiency threshold, the data transmission efficiency coefficient and the preset data transmission efficiency threshold are subjected to difference calculation to obtain a transmission efficiency threshold value, the data transmission speeds of a plurality of detection time points in the transmission process are obtained, the data transmission speeds of the plurality of detection time points are subjected to variance calculation to obtain a transmission speed fluctuation coefficient, the transmission efficiency threshold value and the transmission speed fluctuation coefficient are subjected to numerical calculation to obtain a transmission quality coefficient, if the transmission quality coefficient exceeds the preset transmission quality coefficient threshold value, a transmission quality qualified signal is generated, and otherwise, a transmission quality disqualification signal is generated.
10. The method for processing aerial photogrammetry data of an unmanned aerial vehicle according to claim 1, wherein the aerial photogrammetry platform is in communication connection with the unmanned aerial vehicle supervision terminal, the aerial photogrammetry supervision platform sends the data folder to the unmanned aerial vehicle supervision terminal, and sends the unmanned aerial vehicle correction signal or the unmanned aerial vehicle in-place qualification signal, the pre-preparation failure signal, the unmanned aerial vehicle early warning signal, and the transmission quality failure signal or the transmission quality qualification signal to the unmanned aerial vehicle supervision terminal.
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