Intelligent detection device and method for nitrogen content of fruit trees

Abstract

The application provides a fruit tree nitrogen content intelligent detection device and method, which comprises an MCU, a communication module, a collection device, a collection device, a mechanical arm device and a self-walking device, the top of the self-walking device is provided with the mechanical arm device, the mechanical arm device is provided with the collection device, one side of the mechanical arm device is provided with the collection device, the communication module, the collection device, the collection device, the mechanical arm device and the self-walking device are electrically connected with the MCU, and the communication module uploads information to the cloud. The fruit tree nitrogen content intelligent detection device and method provided by the application are accurate, high in detection efficiency, simple in operation, can realize man-machine interaction and are suitable for the detection of nitrogen elements in large-scale orchards.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent detection of nitrogen content of fruit trees, in particular to an intelligent detection device and method for nitrogen content of fruit trees. BACKGROUND

[0002] With the adjustment of rural industrial institutions, the fruit industry has gradually become a major pillar industry in promoting the development of rural economy in agricultural products, and the orchard planting area is continuously expanding. Large-scale orchard tree trace element detection has become a problem. Nitrogen is a large amount of essential element for the growth and development of fruit trees, and nitrogen element monitoring plays an important role in fruit tree management. The sixth to eighth leaves of fruit trees can best reflect the nitrogen content of fruit trees.

[0003] The mechanical arm refers to a mechanical and electronic device that imitates the functions of arm, wrist and hand, and is mainly used for grabbing or moving objects. In the orchard, it is often used for collecting fruits, leaves and the like. The operation of the mechanical arm can be automatically controlled, and the programming can be repeated.

[0004] Camera calibration is based on a series of image information collected by the camera. Four coordinate systems are established: world coordinate system, camera coordinate system, image coordinate system and pixel coordinate system. There is the following relationship between the four coordinates: the world coordinate is obtained by rigid body transformation of the camera coordinate system, and the camera coordinate is obtained by perspective projection of the image coordinate. The image coordinate is converted into the pixel coordinate through secondary conversion, which is commonly used for target leaf positioning.

[0005] The existing intelligent detection device and method for nitrogen content of fruit trees have complex operation, low detection efficiency, and are not suitable for detection of nitrogen elements in large-scale orchards. Therefore, it is necessary to design an intelligent detection device and method for nitrogen content of fruit trees. SUMMARY

[0006] The purpose of the present application is to provide an intelligent detection device and method for nitrogen content of fruit trees, which is accurate, efficient, simple to operate, can be used for human-computer interaction, and is suitable for detection of nitrogen elements in large-scale orchards.

[0007] To achieve the above purpose, the present application provides the following scheme:

[0008] An intelligent detection device for nitrogen content of fruit trees comprises an MCU, a communication module, a collection device, an acquisition device, a mechanical arm device and a self-walking device. The top of the self-walking device is provided with the mechanical arm device, the mechanical arm device is provided with the acquisition device, one side of the mechanical arm device is provided with the collection device corresponding to the acquisition device, and the communication module, collection device, acquisition device, mechanical arm device and self-walking device are electrically connected to the MCU. The communication module uploads information to the cloud;

[0009] The acquisition device is used for target leaf identification, positioning and acquisition;

[0010] The collecting device is used for collecting the leaves collected by the collecting device and detecting the nitrogen content of the leaves;

[0011] The mechanical arm device is used for driving the collecting device to move to a target position.

[0012] The self-walking device is used for driving the whole device to move.

[0013] Optionally, the self-walking device comprises a front wheel, a rear wheel, a first DC motor, a second DC motor and a device shell, the inside front side of the device shell is provided with the first DC motor, the rear side of the device shell is provided with the second DC motor, the first DC motor and the second DC motor are connected with the front wheel and the rear wheel respectively, and are used for driving the front wheel and the rear wheel to rotate, realizing self-walking, the top of the device shell is provided with the mechanical arm device and the collecting device, and the first DC motor and the second DC motor are electrically connected with the MCU.

[0014] Optionally, the mechanical arm device comprises a first stepping motor and a mechanical arm, the bottom end of the mechanical arm is fixed on the top of the device shell, the first stepping motor is drivingly connected with the mechanical arm, and the upper part of the mechanical arm is mechanically connected with the collecting device, and the MCU is electrically connected with the first stepping motor.

[0015] Optionally, the collecting device comprises a mechanical hand, a third DC motor, a DC motor driving gear, a DC motor driven gear, a second stepping motor, a stepping motor driving gear, a stepping motor driven gear, a blade and a second camera, the MCU is electrically connected with the third DC motor, the second stepping motor and the second camera, the top of the mechanical hand is provided with the second camera, which is used for collecting the position information of the leaves; the rear end of the mechanical hand is mechanically connected with the top end of the mechanical arm; the front side of the mechanical hand is provided with the third DC motor, the output end of the third DC motor is connected with the DC motor driving gear, the DC motor driving gear is meshingly connected with two groups of DC motor driven gears, the DC motor driven gears are connected with the clamping part of the mechanical hand, and are used for driving the clamping part of the mechanical hand to clamp the leaves; the rear side of the mechanical hand is provided with the second stepping motor, the output end of the second stepping motor is provided with the stepping motor driving gear, the rear side of the mechanical hand is provided with the stepping motor driven gears on both sides, and the two groups of stepping motor driven gears are connected through a rotating shaft, the stepping motor driven gear located on one side of the stepping motor driving gear is meshingly connected with the stepping motor driving gear, and the U-shaped blade is arranged outside the two groups of stepping motor driven gears, and is used for cutting the leaves; and the second camera, the third DC motor and the second stepping motor are electrically connected with the MCU.

[0016] Optionally, the collecting device includes a collecting barrel, a display screen, an infrared sensor, a plant nutrient rapid tester and a first camera, the collecting barrel is fixed on the top of the device shell, the first camera is arranged on the outside bottom of the collecting barrel, the display screen is arranged on the middle part of the outside, the infrared sensor is arranged on the inside top, and the plant nutrient rapid tester is arranged on the inside bottom; the MCU is electrically connected with the display screen, the infrared sensor, the plant nutrient rapid tester and the first camera, the infrared sensor is used for judging whether the leaf falls or not, the first camera is used for collecting the environmental information of the self-walking path, and the display screen can be used for man-machine interaction.

[0017] An intelligent fruit tree nitrogen content detection method applied to the intelligent fruit tree nitrogen content detection device, comprising the following steps:

[0018] Step 1: collecting orchard environmental information through the first camera, planning the path according to the orchard environmental information, and moving to the position 0.3-1 meters away from the fruit tree through the self-walking device and stopping;

[0019] Step 2: collecting the image of the corresponding fruit tree through the second camera, and transmitting the collected information to the MCU;

[0020] Step 3: the MCU analyzes and processes the image information collected by the second camera, finds the position of the target leaf, plans the mechanical arm collection route by using the camera calibration technology, and generates corresponding instructions and transmits them to the mechanical arm;

[0021] Step 4: the mechanical arm executes the instructions, controls the mechanical hand to reach the target leaf position, grabs the target leaf, controls the blade to cut, after cutting, the blade is retracted, and the mechanical hand puts the leaf into the collecting device;

[0022] Step 5: the infrared sensor in the collecting device judges whether the leaf is successfully collected and transmits the result to the MCU, if successfully collected, the plant nutrient rapid tester is used for nitrogen content measurement, if not successfully collected, the leaf collection is re-performed, and the nitrogen content detection is completed;

[0023] Step 6: the nitrogen content result detected by the plant nutrient rapid tester is output to the display screen for summarizing, and the summarized result is stored to the cloud.

[0024] The application discloses the following technical effects: the fruit tree nitrogen content intelligent detection device and method provided by the application are suitable for the detection of nitrogen elements in large-scale orchards, the camera, the infrared sensor and the plant nutrient rapid tester transmit information to the MCU, after analysis and processing by the MCU, the collection device, the acquisition device, the mechanical arm device and the self-walking device reach the target fruit tree and complete a series of processes such as target leaf identification, positioning, acquisition and information feedback, and the automation of fruit tree nitrogen content detection is realized; the MCU transmits the fruit tree nitrogen content data to the display screen for display, the fruit grower can call data information through the control panel, and the current data can be uploaded to the cloud for storage, so that the information management of the orchard is facilitated. BRIEF DESCRIPTION OF DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments. Obviously, the drawings in the following description only constitute some embodiments of the application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0026] Figure 1 It is a block diagram of the nitrogen content detection system of the application.

[0027] Figure 2 It is a program flow chart of the embodiment of the application.

[0028] Figure 3 It is a structure diagram of the fruit tree nitrogen content intelligent detection device of the embodiment of the application.

[0029] Figure 4 It is a structure diagram of the acquisition device of the embodiment of the application.

[0030] Figure 5 It is a bottom view of the acquisition device of the embodiment of the application.

[0031] Figure 6 It is a schematic view of the collection device of the embodiment of the application.

[0032] The drawings show that: 1, the collection device; 2, the acquisition device; 3, the mechanical arm device; 4, the self-walking device; 5, the second DC motor; 6, the first DC motor; 7, the third DC motor; 8, the second stepping motor; 9, the stepping motor driven gear; 10, the stepping motor driving gear; 11, the DC motor driven gear; 12, the DC motor driving gear; 13, the second camera; 14, the blade; 15, the third DC motor; 16, the display screen; 17, the infrared sensor; 18, the plant nutrient rapid tester; 19, the first camera. DETAILED DESCRIPTION

[0033] Clearly, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present application.

[0034] The purpose of the present application is to provide a fruit tree nitrogen content intelligent detection device and method, which is accurate, efficient and easy to operate, and can be used for large-scale orchard nitrogen detection.

[0035] In order to make the above-mentioned purposes, characteristics and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below in combination with the drawings and specific embodiments.

[0036] As shown in Figure 3 A fruit tree nitrogen content intelligent detection device, comprising: MCU, communication module, collecting device 1, acquisition device 2, mechanical arm device 3 and self-propelled device 4, the top of the self-propelled device 4 is provided with the mechanical arm device 3, the mechanical arm device 3 is provided with the acquisition device 2, one side of the mechanical arm device 3 corresponds to the acquisition device 2 and is provided with the collecting device 1, the communication module, collecting device 1, acquisition device 2, mechanical arm device 3 and self-propelled device 4 are electrically connected with the MCU, and the communication module uploads information to the cloud;

[0037] The acquisition device 2 is used for identifying, positioning and collecting target leaves;

[0038] The collecting device 1 is used for collecting leaves collected by the acquisition device 2 and detecting the nitrogen content thereof;

[0039] The mechanical arm device 3 is used for moving the acquisition device 2 to a target position;

[0040] The self-propelled device 4 is used for moving the whole device.

[0041] The self-propelled device 4 comprises front wheels, rear wheels, a first DC motor 6, a second DC motor 5 and a device shell, the inside front side of the device shell is provided with the first DC motor 6, the back side is provided with the second DC motor 5, the first DC motor 6 and the second DC motor 5 are connected with the front wheels and the rear wheels respectively, and are used for driving the front wheels and the rear wheels to rotate, realizing self-propelled, the top of the device shell is provided with the mechanical arm device 3 and the collecting device 1, and the first DC motor 6 and the second DC motor 5 are electrically connected with the MCU.

[0042] An embodiment of the present application is that two DC motors drive two front wheels respectively, and another two DC motors drive two rear wheels respectively.

[0043] One embodiment of the present application is that the first DC motor 6 and the second DC motor 5 are connected to the front rotating shaft and the rear rotating shaft respectively, the front rotating shaft is connected to two front wheels at both ends, and the rear rotating shaft is connected to two rear wheels at both ends.

[0044] The mechanical arm device 3 comprises a first stepping motor and a mechanical arm, the bottom end of the mechanical arm is fixed to the top of the device shell, the first stepping motor is drivingly connected to the mechanical arm, the upper part of the mechanical arm is mechanically connected to the collecting device 2, and the MCU is electrically connected to the first stepping motor.

[0045] As shown in Figure 4 and Figure 5 The collecting device 2 comprises a mechanical hand, a third DC motor 157, a DC motor driving gear 12, a DC motor driven gear 11, a second stepping motor 8, a stepping motor driving gear 10, a stepping motor driven gear 9, a blade 14 and a second camera 13, the MCU is electrically connected to the third DC motor 157, the second stepping motor 8 and the second camera 13, the top of the mechanical hand is provided with the second camera 13 for collecting the position information of the blade; the rear end of the mechanical hand is mechanically connected to the top end of the mechanical arm; the front side of the mechanical hand is provided with the third DC motor 157, the output end of the third DC motor 157 is connected to the DC motor driving gear 12, the DC motor driving gear 12 is meshingly connected to two groups of DC motor driven gears 11, the DC motor driven gears 11 are connected to the clamping part of the mechanical hand for driving the clamping part of the mechanical hand to clamp the blade; the rear side of the mechanical hand is provided with the second stepping motor 8, the output end of the second stepping motor 8 is provided with the stepping motor driving gear 10, the rear side of the mechanical hand is provided with the stepping motor driven gears 9 on both sides, two groups of stepping motor driven gears 9 are connected through rotating shafts, the stepping motor driven gear 9 on one side of the stepping motor driving gear 10 is meshingly connected to the stepping motor driving gear 10, and the U-shaped blade 14 is arranged outside the two groups of stepping motor driven gears 9 for cutting the blade; the second camera 13, the third DC motor 157 and the second stepping motor 8 are electrically connected to the MCU.

[0046] As shown in Figure 6As shown, the collecting device 1 includes a collecting barrel, a display screen 16, an infrared sensor 17, a plant nutrient rapid tester 18 and a first camera 19, the collecting barrel is fixed on the top of the device shell, the first camera 19 is arranged on the outside bottom of the collecting barrel, the display screen 16 is arranged on the middle part of the outside, the infrared sensor 17 is arranged on the inside top, and the plant nutrient rapid tester 18 is arranged on the inside bottom; the MCU is electrically connected with the display screen 16, the infrared sensor 17, the plant nutrient rapid tester 18 and the first camera 19, the infrared sensor 17 is used for judging whether the leaf falls or not, the first camera 19 is used for collecting the environmental information of the self-walking path, and the display screen 16 can be used for man-machine interaction. After the nitrogen content data of the fruit tree leaf is analyzed and processed by the MCU, the current regional nitrogen content data is displayed and compared on the LED display screen 16, and the fruit grower can retrieve the nitrogen content data of the orchard or part of the region through the control panel, and the data can be uploaded to the cloud through the communication module, so that the information management of the orchard is facilitated.

[0047] An embodiment of the application is that the MCU selects Raspberry Pi 4B, compared with common 51 single-chip microcomputer and STM32 and other embedded microcontrollers, Raspberry Pi can not only complete the same IO pin control, but also can run the corresponding operating system, can complete more complex task management and scheduling, can support the development of upper-layer application, and provides wider application space for developers.

[0048] The first camera 19 selects RPiCamera(M) camera, which is used for collecting the environmental information of the walking path of the self-walking device 4, has 5 million pixels, 200-degree diagonal field of view, supports video recording and only has 0.25 inch size, and meets the requirements of orchard path exploration. The second camera 13 selects RPiCamera(B) camera, which is used for collecting the position of the fruit tree leaf in the orchard, the leaf for nitrogen content detection is the seventh leaf from outside to inside of the fruit tree layer, and the position data of the leaf is transmitted to the MCU after collection. The camera has a 60.6-degree diagonal field of view, a 6mm focal length and supports focusing, and meets the requirements of leaf position recognition in the orchard.

[0049] The plant nutrient rapid tester 18 selects TST-4N rapid tester, which can quickly determine all parameters of the leaf, has a USB interface for data transmission, meets the detection requirements, the infrared sensor 17 selects Tai Bang E3Z-LS61-BGS square infrared sensor 17, which is used to judge whether the leaf falls into the collecting device 1 after the collecting device 2 executes the command of collecting the leaf, and transmits the judgment result to the MCU. The sensor has a detection distance of 1m and can be adjusted, has small volume and strong anti-interference ability, and meets the requirements of leaf detection.

[0050] The first and second direct current motors 6 and 5 are selected from DSEM-J direct current servo motors, the third direct current motor 157 is selected from an 8430 brushless direct current motor, and the first and second stepping motors 8 are selected from 86 stepping motors.

[0051] As shown in Figure 1 and Figure 2 After the first camera 19 collects the road condition information, the information is transmitted to the MCU, which plans the path and drives the first and second direct current motors 6 and 5 to make the device reach the designated row of fruit trees. After the second camera 13 collects the position information of the seventh leaf, the information is sent to the MCU, which sends a signal to the first stepping motor. The mechanical arm reaches the target leaf after being driven by the first stepping motor. After the mechanical arm reaches the designated position, the MCU sends a signal to the third direct current motor 157 and the second stepping motor 8 to collect the leaf. The third direct current motor 157 controls the mechanical hand to hold the leaf, and the second stepping motor 8 controls the blade 14 to cut the petiole. After cutting, the third direct current motor 157 controls the mechanical hand to put the leaf into the collection device 1. The infrared sensor 17 inside the collection device 1 judges whether the leaf has fallen into it. If the collection is successful, the mechanical arm is retracted, and the next collection is performed. If the collection is unsuccessful, the previous command is repeated, and the collection is re-performed.

[0052] A fruit tree nitrogen content intelligent detection method is applied to the fruit tree nitrogen content intelligent detection device, and includes the following steps:

[0053] Step 1: Collect the orchard environment information through the first camera 19, plan the path according to the orchard environment information, and move the self-walking device 4 to stop at a distance of 0.3-1 meters from the fruit tree.

[0054] Step 2: Collect the image of the corresponding fruit tree through the second camera 13, and transmit the collected information to the MCU.

[0055] Step 3: The MCU analyzes and processes the image information collected by the second camera 13, finds the position of the seventh leaf, plans the collection route of the mechanical arm using camera calibration technology, and generates corresponding instructions and transmits them to the mechanical arm.

[0056] Step 4: The mechanical arm executes the instructions, controls the mechanical hand to reach the target leaf position, grabs the target leaf, controls the blade 14 to cut, retracts the blade 14 after cutting, and puts the leaf into the collection device 1.

[0057] Step 5: The infrared sensor in the collection device 1 judges whether the leaf is successfully collected and transmits the result to the MCU. If the collection is successful, the nitrogen content is measured by the plant nutrient rapid tester 18. If the collection is not successful, the leaf collection is re-performed, and the nitrogen content detection is completed.

[0058] Step 6: The nitrogen content detected by the plant nutrient rapid tester 18 is output to the display screen 16 for summarization, and the summarized results are stored in the cloud.

[0059] The fruit tree nitrogen content intelligent detection device and method provided by the application is suitable for detection of nitrogen elements in large-scale orchards. The camera, infrared sensor and plant nutrient rapid tester transmit information to the MCU. After analysis and processing by the MCU, the collection device, acquisition device, mechanical arm device and self-walking device reach the target fruit tree and complete a series of processes such as target leaf recognition, positioning, acquisition and information feedback, realizing the automation of fruit tree nitrogen content detection. The MCU transmits the fruit tree nitrogen content data to the display screen for display. The fruit grower can call data information through the control panel and upload the current data to the cloud for storage, so as to realize information management of the orchard.

[0060] The principles and implementation modes of the application are described by applying specific examples in this paper. The above examples are only used to help understand the method and core idea of the application. For those skilled in the art, according to the idea of the application, the specific implementation mode and application range can be changed. In summary, the content of the specification should not be understood as a limitation of the application.

Claims

1. An intelligent detection device for nitrogen content in fruit trees, characterized in that, include: The system includes an MCU, a communication module, a collection device, a data acquisition device, a robotic arm device, and a self-propelled device. The robotic arm device is mounted on the top of the self-propelled device, and the data acquisition device is mounted on the robotic arm device. The collection device is mounted on one side of the robotic arm device corresponding to the data acquisition device. The communication module, the collection device, the data acquisition device, the robotic arm device, and the self-propelled device are electrically connected to the MCU. The communication module uploads information to the cloud. The acquisition device is used to identify, locate, and acquire data on the target blade; The collection device is used to collect the leaves collected by the collection device and detect their nitrogen content; The robotic arm is used to move the data acquisition device to the target location. The self-propelled device is used to drive the entire device to move; The self-propelled device includes a front wheel, a rear wheel, a first DC motor, a second DC motor, and a device housing. The first DC motor is located on the front side of the interior of the device housing, and the second DC motor is located on the rear side. The first DC motor and the second DC motor are respectively connected to the front wheel and the rear wheel to drive the front wheel and the rear wheel to rotate and achieve self-propelled movement. The top of the device housing is equipped with a robotic arm device and a collecting device. The first DC motor and the second DC motor are electrically connected to the MCU. The robotic arm device includes a first stepper motor and a robotic arm. The bottom end of the robotic arm is fixed to the top of the device housing. The first stepper motor drives and connects to the robotic arm. The upper part of the robotic arm is mechanically connected to the data acquisition device. The MCU is electrically connected to the first stepper motor. The data acquisition device includes a robotic arm, a third DC motor, a DC motor drive gear, a DC motor driven gear, a second stepper motor, a stepper motor drive gear, a stepper motor driven gear, a blade, and a second camera. The MCU is electrically connected to the third DC motor, the second stepper motor, and the second camera. The second camera is mounted on the top of the robotic arm for acquiring the blade's position information. The rear end of the robotic arm is mechanically connected to the top of the robotic arm. The third DC motor is mounted on the front side of the robotic arm, and its output is connected to the DC motor drive gear. The DC motor drive gear meshes with two sets of DC motor driven gears. The driven gear is connected to the gripping part of the robot arm to drive the gripping part of the robot arm to grip the blade; the second stepper motor is provided on the rear side of the robot arm, the output end of the second stepper motor is provided with the stepper motor drive gear, the driven gears of the stepper motor are provided on both sides of the rear side of the robot arm, and the two sets of driven gears are connected by a rotating shaft. The driven gear of the stepper motor located on one side of the stepper motor drive gear meshes with the stepper motor drive gear, and U-shaped blades are provided on the outer side of the two sets of driven gears for cutting the blade; the second camera, the third DC motor and the second stepper motor are electrically connected to the MCU; The collection device includes a collection bucket, a display screen, an infrared sensor, a plant nutrient rapid tester, and a first camera. The collection bucket is fixed to the top of the device housing. The first camera is located at the bottom outer side of the collection bucket, the display screen is located at the middle outer side, the infrared sensor is located at the top inner side, and the plant nutrient rapid tester is located at the bottom inner side. The MCU is electrically connected to the display screen, the infrared sensor, the plant nutrient rapid tester, and the first camera. The infrared sensor is used to determine whether a leaf has fallen in, the first camera is used to collect environmental information about the self-walking path, and the display screen can be used for human-computer interaction.

2. A method for intelligent detection of nitrogen content in fruit trees, applied to the intelligent detection device for nitrogen content in fruit trees as described in claim 1, characterized in that, Includes the following steps: Step 1: Collect orchard environmental information through the first camera, plan a path based on the orchard environmental information, and move to a distance of 0.3 to 1 meter from the fruit tree using a self-propelled device; Step 2: Capture images of the corresponding fruit trees using the second camera and transmit the captured information to the MCU; Step 3: The MCU analyzes and processes the image information captured by the second camera, locates the position of the target blade, plans the acquisition route of the robotic arm using camera calibration technology, and generates corresponding instructions to transmit to the robotic arm. Step 4: The robotic arm executes the command, controls the robotic arm to reach the target blade position, grasps the target blade, controls the blade to cut, and after the cutting is completed, retracts the blade and the robotic arm puts the blade into the collection device; Step 5: The infrared sensor in the collection device determines whether the leaf has been successfully collected and transmits the result to the MCU. If the collection is successful, the nitrogen content is measured by the plant nutrient rapid tester. If the collection is unsuccessful, the leaf is collected again to complete the nitrogen content detection. Step 6: Output the nitrogen content results detected by the plant nutrient rapid tester to the display screen for summary, and store the summary results in the cloud.

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