Crop growth multi-angle remote sensing spectrum detection device and use method thereof

Abstract

The invention discloses a crop growth multi-angle remote sensing spectrum detection device and a use method thereof in the technical field of agriculture, the crop growth multi-angle remote sensing spectrum detection device comprises an unmanned aerial vehicle, a storage battery is detachably connected to the top of the unmanned aerial vehicle, a plurality of supports are fixedly connected to the bottom of the unmanned aerial vehicle, and an organic cavity is formed in the unmanned aerial vehicle; the top of the machine cavity is provided with a plurality of incident assemblies used for collecting incident spectrums of the sun in different directions, the inner side wall of the machine cavity is fixedly connected with a control panel, the top of the control panel is fixedly connected with a processor, the bottom of the machine cavity is fixedly connected with a second motor, and an output shaft of the second motor is fixedly connected with a hollow vibration filtering rod. An electromagnet layer with magnetism is fixedly connected to the inner side wall of the vibration filtering rod, a magnet rod is arranged in the vibration filtering rod, and the magnet rod is matched with the electromagnet layer in a magnetic suspension mode. The device is scientific and reasonable, and the accuracy and the stability of spectral data are improved by designing a magnetic suspension vibration filtering structure and a multi-angle spectral acquisition function.

Description

Technical Field

[0001] The present invention belongs to the technical field of agriculture, and specifically relates to a multi-angle remote sensing spectral detection device for crop growth and its usage method. Background Art

[0002] In the agricultural field, monitoring the growth of crops is of great significance for increasing crop yields and optimizing agricultural management. Traditional methods for monitoring crop growth often rely on manual field observations or ground sensors. These methods are not only time-consuming and laborious but also difficult to achieve large-scale and high-precision monitoring. With the continuous development of remote sensing technology, unmanned aerial vehicle (UAV) remote sensing spectral detection has gradually become an important means for monitoring crop growth.

[0003] However, there are still some problems in the actual application of existing UAV remote sensing spectral detection devices. During flight, the UAV may be affected by factors such as its own structure, wind force, and air flow, resulting in vibrations of the spectral acquisition probe, which in turn affects the accuracy and stability of spectral data. At the same time, traditional spectral acquisition methods often only obtain spectral data from a single angle and are difficult to comprehensively reflect the growth situation of crops.

[0004] In summary, how to overcome the vibration impact during UAV flight and improve the accuracy and stability of spectral data has become an urgent problem for technicians in this field. Therefore, it is necessary to propose a multi-angle remote sensing spectral detection device for crop growth and its usage method. Summary of the Invention

[0005] To solve the above problems, the purpose of the present invention is to provide a multi-angle remote sensing spectral detection device for crop growth and its usage method. By designing advanced shock absorption technology and multi-angle spectral acquisition functions, the accuracy and stability of spectral data can be improved, and the growth situation of crops can be comprehensively reflected.

[0006] To achieve the above object, the technical solution of the present invention is as follows: A multi-angle remote sensing spectral detection device for crop growth includes a drone. A storage battery is detachably connected to the top of the drone. A plurality of brackets are fixedly connected to the bottom of the drone. There is a machine cavity inside the drone. An incident component for collecting solar incident spectra in different directions is opened at the top of the machine cavity. A control board is fixedly connected to the inner side wall of the machine cavity. A processor is fixedly connected to the top of the control board. A second motor is fixedly connected to the bottom of the machine cavity. The output shaft of the second motor is fixedly connected to a hollow shock-absorbing rod. An electromagnet layer with self-magnetism is fixedly connected to the inner side wall of the shock-absorbing rod. A magnet rod is arranged inside the shock-absorbing rod. The magnet rod is in magnetic suspension cooperation with the electromagnet layer. One end of the magnet rod passing through the shock-absorbing rod is fixedly connected to a third motor. A crop reflection spectral probe is fixedly connected to the output shaft of the third motor. The storage battery, the first motor, the second motor, the third motor, the electromagnet layer, the solar incident spectral probe, and the crop reflection spectral probe are all signal-connected to the processor. A probe angle adjustment module is also provided inside the processor. The probe angle adjustment module automatically calculates and adjusts the rotation angles of the first motor, the second motor, and the third motor through a motor control algorithm to adjust the orientations of the solar incident spectral probe and the crop reflection spectral probe.

[0007] After adopting the above solution, the following principle and beneficial effects are achieved:

[0008] Basic principle: Using the drone as a carrying platform, through the integration of advanced shock-absorbing technology and multi-angle spectral acquisition function, accurate monitoring of crop growth is realized. After the drone flies to the airspace above the crop area to be detected, the processor starts the operation of each component. The solar incident spectral probe can adjust the angle under the drive of the first motor to collect solar incident spectral data from different directions. At the same time, the crop reflection spectral probe can also adjust the angle under the drive of the third motor to collect the reflection spectral data of the crop. The magnet rod in the shock-absorbing rod is in magnetic suspension cooperation with the electromagnet layer, effectively reducing the influence of vibration during the flight of the drone on the spectral acquisition probe and improving the accuracy and stability of the spectral data.

[0009] Beneficial effects:

[0010] 1. Both the incident component and the crop reflection spectral probe designed in the present invention have the angle adjustment function, and can realize the collection of solar incident spectra and crop reflection spectra in different directions. This multi-angle spectral acquisition method can more comprehensively reflect the growth situation of crops and provide strong support for precision agriculture management.

[0011] 2. Through the magnetic suspension shock-absorbing technology, the present invention effectively reduces the influence of vibration during the flight of the drone on the spectral acquisition probe, thereby improving the accuracy and stability of the spectral data. This is crucial for subsequent spectral data analysis and crop growth assessment.

[0012] 3. The device of the present invention realizes the coordinated control of each component through a processor, and can adjust the angle of the spectral acquisition probe and the flight path of the drone according to actual needs. This design enhances the flexibility and adaptability of the system, enabling it to be applicable to the growth monitoring of different crops, at different growth stages, and under different environmental conditions.

[0013] Furthermore, the incident component includes a number of incident holes, all of which are opened on the top of the machine cavity. The inner side walls of the incident holes are fixedly connected with first motors, and the output shafts of the first motors are fixedly connected with solar incident spectral probes.

[0014] Beneficial effects: Through multiple incident holes and corresponding solar incident spectral probes, the present invention can simultaneously collect solar incident spectral data from multiple directions. This comprehensive data acquisition method helps to more accurately understand the distribution characteristics of the solar spectrum in different directions, providing richer information for subsequent crop growth analysis.

[0015] Furthermore, tilt sensors are fixedly connected inside the solar incident spectral probe, the machine cavity, and the crop reflection spectral probe, and vibration sensors are fixedly connected inside the solar incident spectral probe and the crop reflection spectral probe. The tilt sensors and vibration sensors are signal-connected to the processor.

[0016] Beneficial effects: Through the real-time monitoring and adjustment of the tilt sensors, it can ensure that the spectral data is collected at the correct angle, thereby improving the accuracy of the data. This is crucial for subsequent spectral data analysis and crop growth assessment, as accurate data can provide more reliable analysis results. The vibration sensors can real-time monitor the vibration conditions of the solar incident spectral probe and the crop reflection spectral probe when collecting spectral data. When the vibration exceeds a certain threshold, the processor can take corresponding measures to reduce the impact of vibration on spectral data acquisition, such as by adjusting the flight attitude of the drone or activating a shock absorption mechanism, etc.

[0017] Furthermore, a GPS sensor is provided inside the control board, and the GPS sensor is signal-connected to the processor.

[0018] Beneficial effects: The GPS sensor can provide real-time accurate position information of the drone, including longitude, latitude, and altitude, etc. This enables the drone to accurately fly to the designated crop monitoring area, ensuring the pertinence and effectiveness of spectral data acquisition.

[0019] Furthermore, a GPS positioning module is provided inside the processor. The GPS positioning module is used to real-time obtain the position information and attitude information of the drone through the tilt sensors and the GPS sensor, and send the position information and attitude information to the processor.

[0020] Further, a flight control module is provided inside the processor. The flight control module is used to control the flight path and altitude of the drone according to the position information and attitude information of the GPS positioning module, and at the same time adjust the flight attitude of the drone.

[0021] Further, the motor control algorithm calculates the orientation angle based on the preset spectral acquisition requirements and the position information and attitude information obtained in real time by the GPS positioning module, converts the calculated orientation angle into the rotation angle or number of steps of the first motor, the second motor, and the third motor, and plans the rotation speed of the first motor, the second motor, and the third motor according to the flight speed and attitude change of the drone. During the rotation of the first motor, the second motor, and the third motor, the inclination sensor is used to monitor the orientation angle of the solar incident spectral probe and the crop reflection spectral probe in real time, compare it with the target angle, and use the PID control algorithm to adjust the rotation speed and direction of the first motor, the second motor, and the third motor according to the error size to achieve closed-loop control.

[0022] Further, the processor is also provided with a data processing module. The data processing module is used to perform denoising and calibration operations on the spectral data collected by the solar incident spectral probe and the crop reflection spectral probe.

[0023] Further, the processor is also provided with a wireless communication module. The wireless communication module is used to transmit the collected spectral data to the remote service platform in real time.

[0024] Beneficial effects:

[0025] 1. By integrating the GPS positioning module, the flight control module, the probe angle adjustment module, the data processing module, and the wireless communication module, the processor realizes a highly integrated design. This design not only simplifies the system structure but also improves the intelligent level of the system. The processor can automatically adjust the flight path, altitude, flight attitude, and the orientation of the spectral probe according to the position information and attitude information of the drone obtained in real time, thereby ensuring the accuracy and stability of spectral data acquisition.

[0026] 2. The probe angle adjustment module can accurately calculate and adjust the rotation angle of the motor according to the preset spectral acquisition requirements and the position information and attitude information obtained in real time, so as to ensure that the solar incident spectral probe and the crop reflection spectral probe always maintain the best acquisition angle. The probe angle adjustment module can also monitor the data of the vibration sensor in real time. When the vibration exceeds the preset threshold, it automatically energizes the electromagnet layer to further reduce the influence of vibration on spectral data acquisition.

[0027] 3. The data processing module can perform preprocessing, denoising, and calibration operations on the collected spectral data, thereby improving the accuracy and reliability of the data. The wireless communication module can then transmit the processed spectral data to the remote service platform in real time, facilitating subsequent data analysis and decision-making by the user.

[0028] A method for using a multi-angle remote sensing spectral detection device for crop growth vigor includes the following steps:

[0029] Step 1, start the drone: Fly the drone above the crop area to be detected and start the solar incident spectral detection probe and the crop reflection spectral probe.

[0030] Step 2, adjust the probe angles: Adjust the rotation of the first motor, the second motor, and the third motor through the motor control algorithm in the processor so that the solar incident spectral probe and the crop reflection spectral probe are respectively aligned with the sun and the crop for spectral data collection.

[0031] Step 3, collect spectral data: Obtain spectral data using the solar incident spectral probe and the crop reflection spectral probe. The spectral data includes solar incident spectral data and crop reflection spectral data.

[0032] Step 4, transmit spectral data: Transmit the collected solar incident spectral data and crop reflection spectral data to the remote server or mobile device in real time.

[0033] Step 5, analyze spectral data: Process and analyze the solar incident spectral data and crop reflection spectral data on the remote server. By extracting key spectral features reflecting the crop growth status from the crop reflection spectral data, the key spectral features including the normalized difference vegetation index and the leaf area index, and then combining with the growth cycle and physiological characteristics of the crop, monitor the growth trend and changes of the crop by comparing the solar incident spectra and crop reflection spectral data at different time periods, and finally evaluate the crop growth vigor.

[0034] Step 6, multi-angle collection: Adjust the flight path of the drone, the angles of the solar incident spectral probe and the crop reflection spectral probe, and collect spectral data at different angles until the operation of the entire detection area is completed.

[0035] Beneficial effects:

[0036] 1. By using the multi-angle remote sensing spectral detection device, this method can collect the solar incident spectral data and reflection spectral data of crops in real time and accurately. These data can reflect key information such as the growth status, chlorophyll content, and water status of the crops, thereby realizing the precise monitoring of crop growth vigor. Transmitting the spectral data to the remote server or mobile device in real time enables decision-makers to quickly obtain the crop growth status information and make corresponding agricultural management measures in a timely manner, improving the timeliness of monitoring.

[0037] 2. By analyzing spectral data, this method can extract key spectral features reflecting the growth status of crops, such as the Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI). These features can provide a scientific basis for agricultural resource management, such as precision fertilization, irrigation, pest control, etc. Combining the growth cycle and physiological characteristics of crops, by comparing spectral data at different time periods, the growth trend and changes of crops can be monitored, providing precise support for agricultural decision-making.

[0038] 3. This method combines unmanned aerial vehicle (UAV) technology and remote sensing spectral detection technology to achieve remote and real-time monitoring of crop growth. This intelligent monitoring method can reduce manual intervention and improve the automation level of agricultural production. By continuously optimizing and adjusting the UAV flight path and probe angle, comprehensive coverage of the detection area can be achieved, improving the efficiency and accuracy of data collection. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 Isometric view of an embodiment of the present invention.

[0040] Figure 2 Side view of an embodiment of the present invention.

[0041] Figure 3 Lateral sectional view of the shock-absorbing rod in an embodiment of the present invention.

[0042] Figure 4 Top view of an embodiment of the present invention.

[0043] Figure 5 Bottom view of an embodiment of the present invention.

[0044] Figure 6 Flowchart of the method in an embodiment of the present invention.

[0045] Reference numerals in the drawings of the specification include: 1. Unmanned aerial vehicle; 2. Storage battery; 3. Bracket; 4. Solar incident spectral probe; 5. Processor; 6. Machine cavity; 7. Control board; 8. Second motor; 9. Third motor; 10. Inclination sensor; 11. Crop reflection spectral probe; 12. Shock-absorbing rod; 13. Electromagnet layer; 14. Magnet rod; 15. First motor; 16. Incident hole. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] The following is a further detailed description through specific embodiments:

[0047] Embodiment 1

[0048] Basically as shown in the attached Figures 1 - 5As shown: A multi-angle remote sensing spectral detection device for crop growth includes a drone 1. The drone 1 serves as the platform for the entire detection device. The drone 1 provides flexible aerial operation capabilities, enabling wide-ranging and efficient collection of spectral data. A battery 2 is detachably connected to the top of the drone 1. A number of brackets 3 are fixedly connected to the bottom of the drone 1 by bolts. There is a machine cavity 6 inside the drone 1. An incident component for collecting solar incident spectra from different directions is opened at the top of the machine cavity 6. The incident component includes a number of incident holes 16. All the incident holes 16 are opened at the top of the machine cavity 6. The inner side walls of the incident holes 16 are all embedded with first motors 15. The output shafts of the first motors 15 are fixedly connected with solar incident spectral probes 4 by screws. The incident holes 16 are exquisitely designed. With the precise control of the first motors 15, the solar incident spectral probes 4 can flexibly adjust the angles to comprehensively capture solar spectral information.

[0049] The inner side wall of the machine cavity 6 is fixedly connected with a control board 7 by bolts. A GPS sensor is provided inside the control board 7. A processor 5 is fixedly connected to the top of the control board 7 by bolts. A second motor 8 is fixedly connected to the bottom of the machine cavity 6 by bolts. The output shaft of the second motor 8 is fixedly connected with a hollow shock-absorbing rod 12 by bolts. An electromagnet layer 13 with its own magnetism is embedded in the inner side wall of the shock-absorbing rod 12. A magnet rod 14 is arranged inside the shock-absorbing rod 12. The magnet rod 14 is in magnetic suspension cooperation with the electromagnet layer 13. One end of the magnet rod 14 passing through the shock-absorbing rod 12 is fixedly connected with a third motor 9 by bolts. A crop reflection spectral probe 11 is fixedly connected to the output shaft of the third motor 9 by bolts. Inclinometers 10 are fixedly connected to the solar incident spectral probes 4, the machine cavity 6, and the crop reflection spectral probe 11 by bolts. Vibration sensors are embedded in both the solar incident spectral probes 4 and the crop reflection spectral probe 11. The second motor 8 drives the shock-absorbing rod 12, effectively reducing the vibration interference during the collection process of the crop reflection spectral probe 11 and improving the data quality. The magnetic suspension cooperation between the electromagnet layer 13 and the magnet rod 14 realizes the stable suspension and fine adjustment of the crop reflection spectral probe 11, improving the accuracy and stability of spectral data collection.

[0050] The inclinometers 10, vibration sensors, GPS sensor, battery 2, first motors 15, second motor 8, third motor 9, electromagnet layer 13, solar incident spectral probes 4, and crop reflection spectral probe 11 are all signal-connected to the processor 5. The following modules are provided inside the processor 5:

[0051] A GPS positioning module for real-time obtaining of the position information and attitude information of the drone 1 through the inclinometers 10 and the GPS sensor and sending the position information and attitude information to the processor 5.

[0052] The flight control module is used to control the flight path and altitude of the drone 1 based on the position information and attitude information of the GPS positioning module, and at the same time adjust the flight attitude of the drone 1.

[0053] The probe angle adjustment module is used to automatically calculate and adjust the rotation angles of the first motor 15, the second motor 8, and the third motor 9 according to the motor control algorithm to adjust the orientations of the solar incident spectrum probe 4 and the crop reflection spectrum probe 11. At the same time, it judges whether the vibration data of the vibration sensor exceeds a preset threshold, and when it exceeds the threshold, it energizes the electromagnet layer 13.

[0054] The probe angle adjustment module reads the preset spectral acquisition requirements in the processor 5, including the optimal acquisition angle range of the solar incident spectrum, the optimal acquisition height and angle of the crop reflection spectrum, etc. It obtains the current GPS position, flight altitude, flight speed, pitch angle, yaw angle, roll angle, etc. of the drone.

[0055] According to the current time, location, and date, use the solar position algorithm to calculate the precise position of the sun in the sky, including the azimuth angle and altitude angle. According to the solar position information and the preset optimal acquisition angle range of the solar incident spectrum, calculate the optimal orientation angle of the solar incident spectrum probe 4. Perceive the change of the drone attitude through a number of tilt sensors 10, and perform real-time correction on the calculated orientation angle, and adjust the rotation of the first motor to ensure that the solar incident spectrum probe 4 always points to the sun.

[0056] According to the preset optimal acquisition height and angle of the crop reflection spectrum, as well as the current flight altitude and attitude information of the drone 1, calculate the optimal orientation angle of the crop reflection spectrum probe 11. Considering the crop distribution and terrain changes, further identify and locate the crops through image processing or machine learning algorithms to further optimize the orientation of the crop reflection spectrum probe 11. During the process of adjusting the orientation of the crop reflection spectrum probe 11, monitor the data of the vibration sensor in real time. If the vibration data exceeds the preset threshold, immediately energize the electromagnet layer 13, and use magnetic levitation technology to stabilize the probe position and reduce the impact of vibration on spectral acquisition.

[0057] According to the optimal orientation angle calculated by the probe angle adjustment module, control the rotation of the first motor, the second motor, and the third motor through the motor control algorithm, so that the solar incident spectrum probe 4 and the crop reflection spectrum probe 11 always face the preset orientation.

[0058] The motor control algorithm converts the calculated optimal orientation angle into the rotation angle or number of steps of the motor. According to the flight speed and attitude change of the drone 1, plan the rotation speed of the first motor 15, the second motor 8, and the third motor 9 to ensure the smooth adjustment of the probe.

[0059] For the first motor 15, it is responsible for adjusting the orientation of the solar incident spectrum probe 4. According to the calculated optimal solar orientation angle and the current orientation angle of the probe, the angle difference to be rotated is calculated.

[0060] For the second motor 8 and the third motor 9, they are jointly responsible for adjusting the orientation of the crop reflection spectrum probe 11. According to the calculated optimal acquisition height, angle of the crop and the position information of the current crop reflection spectrum probe 11, the height that the second motor 8 needs to adjust and the angle that the third motor 9 needs to rotate are calculated. According to the flight speed and attitude change of the drone, as well as the distance between the current position and the target position of the probe, the rotation speeds of the second motor 8 and the third motor 9 are planned. When planning the speed, the response time, moment of inertia and load conditions of the second motor 8 and the third motor 9 are considered to ensure the smooth adjustment of the probe.

[0061] During the speed planning process, optimization algorithms are adopted, such as speed curve smoothing processing, acceleration limit, etc., to further improve the adjustment accuracy and stability of the probe. During the rotation of the second motor 8 and the third motor 9, the orientation angle of the crop reflection spectrum probe 11 is real-time monitored by the tilt sensor 10, compared with the target angle, and the rotation speed and direction of the second motor 8 and the third motor 9 are adjusted according to the error size to achieve closed-loop control. The closed-loop control algorithm adopts the PID control algorithm to improve the adjustment accuracy and stability of the probe.

[0062] The data processing module is used to perform denoising and calibration operations on the spectral data collected by the solar incident spectrum probe 4 and the crop reflection spectrum probe 11.

[0063] The wireless communication module is used to transmit the collected spectral data to the remote service platform in real time through 5G communication.

[0064] Specific implementation steps:

[0065] First, start the drone 1. After the drone 1 is started, the GPS positioning module, flight control module, probe angle adjustment module, data processing module, and wireless communication module in the processor 5 are initialized to prepare for receiving and executing instructions. The operator commands the drone 1 to fly above the crop area to be detected through the remote processor 5 or a preset flight plan. The flight control module adjusts the flight path, height and attitude of the drone 1 according to the position information and attitude information provided by the GPS positioning module to ensure that the drone 1 hovers stably above the crop area.

[0066] The probe angle adjustment module calculates and adjusts the rotation angles of the first motor 15, the second motor 8, and the third motor 9 according to the preset spectral acquisition requirements and the position information and attitude information obtained in real time. The rotation of the first motor 15 adjusts the orientation of the solar incident spectral probe 4 so that it can accurately receive the solar incident spectra from different directions. The rotation of the second motor 8 adjusts the overall orientation of the shock-absorbing rod 12 and the crop reflection spectral probe 11, while the rotation of the third motor 9 further fine-tunes the specific angle of the crop reflection spectral probe 11 so that it can accurately align with the crops for collecting reflection spectral data.

[0067] An example of the probe adjustment process is as follows: At 10 am, over a certain farmland at 30° north latitude and 114° east longitude, the solar position algorithm calculates that the azimuth angle of the sun in the sky at this time is 75° and the altitude angle is 45°. The preset optimal acquisition angle range for the solar incident spectra is azimuth angle 70 - 80° and altitude angle 40 - 50°. The current orientation angle of the solar incident spectral probe 4 is azimuth angle 60° and altitude angle 30°. Therefore, the probe angle adjustment module calculates that the required angle difference to be adjusted is azimuth angle 75 - 60 = 15°, and altitude angle 45 - 30 = 15°. Subsequently, the first motor 15 starts to rotate, and based on the calculated angle difference and the flight speed and attitude changes of the unmanned aerial vehicle, a suitable rotation speed and acceleration are planned to ensure that the solar incident spectral probe 4 is smoothly and accurately adjusted to the optimal orientation angle.

[0068] For the adjustment of the crop reflection spectral probe 11, the preset optimal acquisition height is 10 m and the optimal acquisition angle is a depression angle of 30°. The current flight height of the unmanned aerial vehicle is 12 m and the pitch angle is 0°. Considering the crop distribution and terrain changes, the crops are identified and located through an image processing algorithm, and it is found that the crops are mainly concentrated 5 m in front of the unmanned aerial vehicle and the terrain is relatively flat. Therefore, the probe angle adjustment module calculates that the required height difference for the second motor 8 to be adjusted is 10 - 12 = -2 m, that is, to lower the height by 2 m, and the angle that the third motor 9 needs to rotate is 30°, that is, to rotate from the horizontal position to a depression angle of 30°. Similarly, based on the flight speed and attitude changes of the unmanned aerial vehicle, the rotation speeds and accelerations of the second motor 8 and the third motor 9 are planned to ensure that the crop reflection spectral probe 11 can be smoothly and accurately adjusted to the optimal orientation angle and height.

[0069] During the adjustment process, the inclination sensor 10 monitors the orientation angle of the probe in real time and compares it with the target angle. If there is an error, the rotation speed and direction of the motor are adjusted according to the PID control algorithm to achieve closed-loop control. At the same time, the vibration sensor monitors the vibration condition of the probe in real time. If during the adjustment process, the vibration data of the solar incident spectral probe 4 exceeds the preset threshold, the probe angle adjustment module immediately energizes the electromagnet layer 13 to increase the same-sex repulsive force between the electromagnet layer 13 and the magnet rod 14, and uses the magnetic levitation principle to reduce the influence of vibration on spectral data acquisition.

[0070] When the attitude of the unmanned aerial vehicle 1 changes, by repeating the above probe adjustment process, both the solar incident spectral probe 4 and the crop reflection spectral probe 11 can accurately and stably face the preset optimal acquisition angle and height, providing a strong guarantee for subsequent spectral data acquisition.

[0071] The solar incident spectral probe 4 and the crop reflection spectral probe 11 start to collect spectral data. The data processing module performs preprocessing, denoising, and calibration operations on the collected spectral data to improve the accuracy and reliability of the data.

[0072] The wireless communication module transmits the processed spectral data to the remote service platform in real time. Operators or data analysts can view and analyze the spectral data on the remote service platform in real time, providing a scientific basis for crop growth assessment. According to the preset acquisition plan or the requirements of real-time analysis, the flight path of the unmanned aerial vehicle 1 and the angles of the solar incident spectral probe 4 and the crop reflection spectral probe 11 are adjusted for multi-angle acquisition. Repeat the above steps until the operation of the entire detection area is completed.

[0073] When the unmanned aerial vehicle 1 completes all preset acquisition tasks, the operator instructs the unmanned aerial vehicle 1 to return to the take-off point or the designated landing position. On the remote service platform, the collected spectral data is further analyzed and processed to extract the key spectral features reflecting the crop growth status and evaluate the crop growth situation.

[0074] Embodiment 2

[0075] Basically as shown in the appendix Figure 6 The difference from the above embodiment is that a method for using a multi-angle remote sensing spectral detection device for crop growth includes the following steps:

[0076] Step 1, start the unmanned aerial vehicle 1: Fly the unmanned aerial vehicle 1 above the crop area to be detected and start the solar incident spectral detection probe and the crop reflection spectral probe 11.

[0077] Step 2, Probe Angle Adjustment: Adjust the rotation of the first motor 15, the second motor 8, and the third motor 9 through the motor control algorithm in the processor 5, so that the solar incident spectrum probe 4 and the crop reflection spectrum probe 11 are respectively aligned with the sun and the crop, and spectral data collection is performed.

[0078] Step 3, Collect Spectral Data: Obtain spectral data using the solar incident spectrum probe 4 and the crop reflection spectrum probe 11. The spectral data includes solar incident spectral data and crop reflection spectral data.

[0079] Step 4, Transmit Spectral Data: Transmit the collected solar incident spectral data and crop reflection spectral data to a remote server or a mobile device in real time.

[0080] Step 5, Analyze Spectral Data: Process and analyze the solar incident spectral data and crop reflection spectral data on the remote server. By extracting key spectral features reflecting the growth status of the crop from the crop reflection spectral data, the key spectral features include the normalized difference vegetation index and the leaf area index, and then combining with the growth cycle and physiological characteristics of the crop, by comparing the solar incident spectra and crop reflection spectral data at different time periods, monitor the growth trend and changes of the crop, and finally evaluate the growth condition of the crop.

[0081] Step 6, Multi-angle Collection: Adjust the flight path of the drone 1, the angles of the solar incident spectrum probe 4 and the crop reflection spectrum probe 11, and collect spectral data at different angles until the operation of the entire detection area is completed.

[0082] Specific implementation steps:

[0083] First, according to the size, shape, and geographical location of the corn field, formulate the flight path and altitude of the drone 1. At the same time, determine the time points for spectral data collection, such as morning, noon, or evening, to obtain spectral data under different lighting conditions. Establish a data processing and analysis platform on the remote server, prepare a database for receiving and storing spectral data, and software tools for extracting key spectral features and evaluating the growth condition of the crop.

[0084] Take off the drone 1 above the corn field and ensure its stable hover. Then start the solar incident spectrum detection probe and the crop reflection spectrum probe 11 through the processor 5. According to the preset collection plan, adjust the rotation of the first motor 15, the second motor 8, and the third motor 9 through the motor control algorithm in the processor 5, so that the solar incident spectrum probe 4 is aligned with the sun and the crop reflection spectrum probe 11 is aligned with the corn field.

[0085] As the drone 1 flies and the probe is adjusted, the solar incident spectrum probe 4 and the crop reflection spectrum probe 11 start to collect spectral data. These data include solar incident spectral data and the reflection spectral data of the corn field. The collected spectral data is transmitted to the remote server in real time through the wireless communication module of the drone 1. The operator can view the received spectral data in real time on the remote server and conduct a preliminary inspection on it.

[0086] On the remote server, the received spectral data is further processed and analyzed. By extracting key spectral features such as the normalized difference vegetation index NDVI and the leaf area index LAI, the growth condition of the corn is evaluated. At the same time, combined with the growth cycle and physiological characteristics of the corn, the spectral data of different time periods is compared to monitor the growth trend and changes of the corn. In order to more comprehensively understand the growth condition of the corn field, the flight path of the drone 1 and the angle of the probe are adjusted to collect spectral data from multiple angles. This can ensure full coverage of the entire corn field and obtain more information about the crop growth condition. According to the results of the spectral data analysis, decision-making support is provided for agricultural production. For example: if it is found that the growth of the corn in certain areas is poor, management measures such as fertilization, irrigation or pest control can be adjusted in a timely manner.

[0087] The above are only embodiments of the present invention. Common knowledge such as specific structures and characteristics known in the art are not described in detail here. Those of ordinary skill in the art know all the common general technical knowledge in the technical field to which the invention belongs before the application date or priority date, can know all the existing technologies in this field, and have the ability to apply conventional experimental means before this date. Those of ordinary skill in the art can, under the inspiration given in this application, complete and implement this solution in combination with their own abilities. Some typical well-known structures or well-known methods should not become an obstacle for those of ordinary skill in the art to implement this application. It should be noted that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can still be made, and these should also be regarded as the protection scope of the present invention, and these will not affect the implementation effect of the present invention and the practicality of the patent. The protection scope required by this application should be based on the content of its claims, and the specific implementation manners described in the specification can be used to explain the content of the claims.

Claims

1. A multi-angle remote sensing spectral detection device for crop growth conditions, comprising a drone (1), a storage battery (2) is detachably connected to the top of the drone (1), and a plurality of brackets (3) are fixedly connected to the bottom of the drone (1), characterized in that: The unmanned aerial vehicle (1) is internally provided with an engine cavity (6). At the top of the engine cavity (6), there is an incident component for collecting solar incident spectra from different directions. On the inner side wall of the engine cavity (6), a control board (7) is fixedly connected. On the top of the control board (7), a processor (5) is fixedly connected. At the bottom of the engine cavity (6), a second motor (8) is fixedly connected. The output shaft of the second motor (8) is fixedly connected with a hollow shock-absorbing rod (12). On the inner side wall of the shock-absorbing rod (12), a self-magnetic electromagnet layer (13) is fixedly connected. Inside the shock-absorbing rod (12), a magnet rod (14) is provided. The magnet rod (14) is in magnetic suspension cooperation with the electromagnet layer (13). One end of the magnet rod (14) passing through the shock-absorbing rod (12) is fixedly connected with a third motor (9). On the output shaft of the third motor (9), a crop reflection spectrum probe (11) is fixedly connected. The battery (2), the first motor (15), the second motor (8), the third motor (9), the electromagnet layer (13), the solar incident spectrum probe (4), and the crop reflection spectrum probe (11) are all in signal connection with the processor (5). Inside the processor (5), there is also a probe angle adjustment module. The probe angle adjustment module automatically calculates and adjusts the rotation angles of the first motor (15), the second motor (8), and the third motor (9) through a motor control algorithm to adjust the orientations of the solar incident spectrum probe (4) and the crop reflection spectrum probe (11).

2. The multi-angle remote sensing spectral detection device for crop growth trend according to claim 1, wherein: The incident component includes a number of incident holes (16). The number of incident holes (16) are all opened at the top of the engine cavity (6). On the inner side walls of the incident holes (16), first motors (15) are fixedly connected. The output shafts of the first motors (15) are all fixedly connected with solar incident spectrum probes (4).

3. The crop growth multi-angle remote sensing spectral detection device according to claim 2, wherein: Inclinometers (10) are fixedly connected inside the solar incident spectrum probe (4), the engine cavity (6), and the crop reflection spectrum probe (11). Vibration sensors are fixedly connected inside the solar incident spectrum probe (4) and the crop reflection spectrum probe (11). The inclinometers (10) and the vibration sensors are in signal connection with the processor (5).

4. The crop growth multi-angle remote sensing spectral detection device according to claim 3, wherein: A GPS sensor is provided inside the control board (7). The GPS sensor is in signal connection with the processor (5).

5. The crop growth multi-angle remote sensing spectral detection device according to claim 4, characterized in that: A GPS positioning module is provided inside the processor (5). The GPS positioning module is used to obtain the position information and attitude information of the unmanned aerial vehicle (1) in real time through the inclinometer (10) and the GPS sensor, and send the position information and attitude information to the processor (5).

6. The crop growth multi-angle remote sensing spectral detection device according to claim 5, characterized in that: A flight control module is provided inside the processor (5). The flight control module is used to control the flight path and altitude of the unmanned aerial vehicle (1) according to the position information and attitude information of the GPS positioning module, and at the same time adjust the flight attitude of the unmanned aerial vehicle (1).

7. The crop growth multi-angle remote sensing spectral detection device according to claim 6, characterized in that: The motor control algorithm calculates the orientation angle according to the preset spectral acquisition requirements and the position and attitude information obtained in real time by the GPS positioning module, converts the calculated orientation angle into the rotation angle or number of steps of the first motor (15), the second motor (8) and the third motor (9), and plans the rotation speed of the first motor (15), the second motor (8) and the third motor (9) according to the flight speed and attitude change of the unmanned aerial vehicle (1). During the rotation of the first motor (15), the second motor (8) and the third motor (9), the orientation angles of the solar incident spectral probe (4) and the crop reflection spectral probe (11) are monitored in real time by the inclination sensor (10), compared with the target angle, and the rotation speed and direction of the first motor (15), the second motor (8) and the third motor (9) are adjusted according to the error magnitude by using the PID control algorithm to achieve closed-loop control.

8. The crop growth multi-angle remote sensing spectral detection device according to claim 7, characterized in that: The processor (5) is also provided with a data processing module, and the data processing module is used to perform denoising and calibration operations on the spectral data collected by the solar incident spectral probe (4) and the crop reflection spectral probe (11).

9. The crop growth multi-angle remote sensing spectral detection device according to claim 8, wherein: The processor (5) is also provided with a wireless communication module, and the wireless communication module is used to transmit the collected spectral data to the remote service platform in real time.

10. A method for using a multi-angle remote sensing spectral detection device for crop growth, characterized in that: It includes the following steps: Step 1, start the unmanned aerial vehicle (1): Fly the unmanned aerial vehicle (1) above the crop area to be detected, and start the solar incident spectral detection probe and the crop reflection spectral probe (11); Step 2, probe angle adjustment: Adjust the rotation of the first motor (15), the second motor (8) and the third motor (9) through the motor control algorithm in the processor (5) to align the solar incident spectral probe (4) and the crop reflection spectral probe (11) with the sun and the crop respectively for spectral data acquisition; Step 3, collect spectral data: Obtain spectral data by using the solar incident spectral probe (4) and the crop reflection spectral probe (11), and the spectral data includes solar incident spectral data and crop reflection spectral data; Step 4, transmit spectral data: Transmit the collected solar incident spectral data and crop reflection spectral data to the remote server or mobile device in real time; Step 5, analyze spectral data: Process and analyze the solar incident spectral data and crop reflection spectral data on the remote server, extract the key spectral features reflecting the crop growth status from the crop reflection spectral data, and the key spectral features include the normalized difference vegetation index and the leaf area index. Then, combined with the growth cycle and physiological characteristics of the crop, by comparing the solar incident spectral and crop reflection spectral data at different time periods, monitor the growth trend and changes of the crop, and finally evaluate the crop growth situation; Step 6, multi-angle acquisition: Adjust the flight path of the unmanned aerial vehicle (1) and the angles of the solar incident spectral probe (4) and the crop reflection spectral probe (11), and collect spectral data at different angles until the operation of the entire detection area is completed.

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