Device and method for online detection and accurate regulation and control of sowing depth and sowing amount of peanut precision sowing machine

Abstract

The invention provides a device and a method for on-line detection and precise regulation and control of the sowing depth and the sowing amount of a peanut precision seeder. An ultrasonic distance measuring sensor, an optical fiber counting sensor, a double-shaft tilt angle sensor, a linear displacement sensor, a photoelectric rotary encoder and the like are used for acquiring operation information such as the seeding depth, the seeding quantity, the seeding machine tilt angle, the expansion amount of an electric cylinder telescopic mechanism, the machine tool speed and the seeding frequency of a seeding machine in real time; through digital signal processing and conversion, STM32F103ZE single-chip microcomputer processing, control algorithm optimization, on-line detection of the seeding depth and the seeding condition of the seeder, real-time adjustment of the seeding depth and real-time reseeding, real-time accurate regulation and control of peanut seeding are realized, and it is ensured that peanut seeding meets the requirements for consistency of the seeding depth and the seeding distance; meanwhile, the whole sowing process is more automatic and efficient, manual intervention is not needed, manpower and material resources are saved, and good economic benefits are achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of precision seeding, and in particular relates to an online detection and precise control device and method for the sowing depth and sowing amount of a peanut precision seeder. Background Art

[0002] Peanut is a kind of nut with abundant yield and wide range of uses. It has high nutritional value. It can not only be used as a traditional Chinese medicine, but also has certain use value in printing and dyeing, papermaking industry and other fields.

[0003] Commonly used seed drills for peanuts are divided into mechanical seed drills and air-suction seed drills. Mechanical seed drills have a high empty seed rate due to the particularity of mechanical seed removal with an external groove wheel seeding device or a duckbill seeding device, and are prone to seed squeezing, resulting in seed coat shedding or seed breakage, affecting the sowing effect. The air-suction seeding machine uses a seeding method of air pressure adsorption on the seeding disc, which can significantly reduce the problem of poor seed removal effect of traditional mechanical seeding, so the application proportion of this type of seeding machine is gradually increasing. However, the sowing depth part of the above-mentioned seeding machines generally adopts a manual adjustment control method, and the sowing depth cannot be flexibly adjusted according to changes in field terrain, resulting in uneven sowing depth; the seeding part relies on ground wheel transmission or power output shaft transmission. When encountering tire slippage and other situations, it will cause uneven sowing density and uneven sowing gaps, and it is impossible to freely adjust the sowing frequency according to agronomic requirements, resulting in reduced adaptability, and it is difficult to meet the overall needs of modern crop sowing automation and precision; in summary, the adjustment problem of sowing is an urgent problem to be solved in the current sowing industry.

[0004] In response to the above problems, the present invention improves the design of the automatic sowing depth adjustment and sowing amount adjustment of the peanut seeder, develops corresponding control technology, accurately controls peanut sowing, ensures that peanuts are planted in appropriate positions in the soil, fully utilizes nutrient and water resources, improves planting efficiency, avoids excessive use of seeds, reduces repetitive labor in the planting process, improves the yield and quality of peanuts, and improves planting benefits. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides an online detection and precise control device and method for the sowing depth and sowing amount of a peanut precision seeder. The device and method are designed to solve the problems of uneven sowing area of ​​the peanut seeder, different sowing depths required for seeds of different sizes, missed seeds during peanut seeding, uneven sowing and substandard sowing density caused by mismatch between the travel speed of the unit and the sowing frequency, etc. The device and method can respectively change the sowing depth in real time and adjust the replanting strategy to achieve timely and accurate implementation of the peanut sowing depth control and replanting strategy, ensure that the peanut sowing meets the requirements of consistency of sowing depth and seed spacing, put the seeds in the best position for sowing and growth, provide a good growth environment for crops, promote the root development and growth balance of crops, avoid competition between plants, improve the survival rate, yield and quality of plants, avoid excessive use of seeds, reduce planting costs, and save agricultural resources.

[0006] The present invention achieves the above technical objectives through the following technical means.

[0007] A device for online detection and precise control of sowing depth and sowing amount of a peanut precision seeder comprises an air-suction seeding device mounted on a frame, a furrow opener mounted in front of the air-suction seeding device, a depth-limiting wheel mounted in the rear, and a seeding tube mounted at a seeding opening; an ultrasonic distance-measuring sensor A and an ultrasonic distance-measuring sensor B are mounted at the bottom of the frame and at the front and rear ends of the furrow opener, respectively; an optical fiber counting sensor is mounted at the opening of the seeding tube below the seeding opening; a photoelectric rotary encoder is mounted on the machine drive shaft and the seeding shaft of the seeding device; a dual-axis inclination sensor is mounted on the machine; the ultrasonic distance-measuring sensor A, the ultrasonic distance-measuring sensor B, the optical fiber counting sensor and the photoelectric rotary encoder are all connected to a single-chip microcomputer; an electric cylinder telescopic mechanism and a linear displacement sensor are also mounted on the furrow opener, a servo motor is connected to the shaft of the air-suction seeding device, and the electric cylinder telescopic mechanism (13) and the servo motor are both connected to the single-chip microcomputer.

[0008] The method for online detection and precise control of sowing depth and sowing amount of a peanut precision seeder using the above-mentioned online detection and precise control device of sowing depth and sowing amount of a peanut precision seeder comprises the following process:

[0009] Step 1: Check the condition of the seeder;

[0010] Step 2: Start the seeder, and control the electric cylinder telescopic mechanism and the servo motor through the single chip microcomputer to maintain the initial operating state;

[0011] Step 3: Start the ultrasonic distance sensor A, ultrasonic distance sensor B, optical fiber counting sensor, photoelectric rotary encoder, dual-axis inclination sensor, and linear displacement sensor; during the movement of the seeder, in conjunction with the single-chip microcomputer, the ultrasonic distance sensor A and ultrasonic distance sensor B are used to continuously and in real time detect the distance from the frame to the ridge surface and the bottom of the ridge, and then calculate the sowing depth, the dual-axis inclination sensor is used to detect the working inclination of the seeder in real time, the optical fiber counting sensor is used to detect the seeding frequency of the air-suction seeding device, the photoelectric rotary encoder is used to respectively determine the travel speed of the seeder and the rotation speed of the seeding shaft, and the linear displacement sensor is used to detect the telescopic amount of the electric cylinder telescopic mechanism;

[0012] Step 4: The data measured by each sensor is transmitted to the single-chip microcomputer, which converts, calculates, and smoothes the signal, generates control logic, and converts it into an output signal, which is output to the electric cylinder telescopic mechanism and the servo motor respectively;

[0013] Step 5: The electric cylinder telescopic mechanism and the servo motor adjust the operating state according to the input control signal respectively; the electric cylinder telescopic mechanism adjusts the telescopic amount in real time to change the length of the furrow opener and directly adjust the sowing depth; the servo motor adjusts the speed in real time to change the speed of the air suction seed metering device and indirectly adjust the seeding frequency;

[0014] Step 6: After adjusting the operating state of the seed drill in step 5, each sensor further performs detection, generates a signal, and generates the next output signal through the single-chip microcomputer, forming a closed-loop control of the seeding operation.

[0015] Furthermore, in step 3, the specific method of using ultrasonic ranging sensor A and ultrasonic ranging sensor B to detect the distance from the frame to the ridge surface and the ridge ditch bottom and then obtain the sowing depth is as follows:

[0016] Ultrasonic distance sensor A or ultrasonic distance sensor B first calculates the distance d from the frame to the ridge surface or ridge ditch bottom using the following formula:

[0017]

[0018] Among them, v represents the propagation speed of ultrasound in the air; t represents the time required from transmitting the wave to receiving the wave;

[0019] Then the Doppler effect formula is introduced to reduce the influence of frequency offset on the ranging effect:

[0020]

[0021] Among them, f r is the received frequency; f s is the transmitting frequency; v a is the propagation speed of ultrasound in air; v ris the velocity of the ground; v s is the vertical speed of ultrasonic ranging sensor A or ultrasonic ranging sensor B;

[0022] By calculating the frequency deviation, the corrected ultrasonic propagation time is obtained:

[0023]

[0024] Among them, t corr is the corrected ultrasonic propagation time; t is the time directly measured by ultrasonic ranging sensor A or ultrasonic ranging sensor B to send and receive;

[0025] Finally, the corrected distance d' from the frame to the ridge surface or ridge bottom is:

[0026]

[0027] Ultrasonic distance measuring sensor A and ultrasonic distance measuring sensor B input the corrected measured data to the microcontroller for difference calculation to finally obtain the sowing depth.

[0028] Furthermore, in step 3, the dual-axis inclination sensor uses the principle of gravity acceleration and micro-electromechanical technology, and utilizes the directional invariance of gravity acceleration. When the object tilts, the built-in accelerometer of the dual-axis inclination sensor measures the changes in gravity components along the X, Y, and Z axes, and calculates the working inclination angle of the seed drill in real time based on the components.

[0029] Furthermore, in step 3, when the peanut seeds fall from the seed drop tube and enter the detection range of the optical fiber counting sensor, the position of the interference fringes inside the optical fiber counting sensor changes, causing the optical path difference to change. Each time the optical fiber counting sensor detects a change in the optical path difference, the count is increased once, thereby realizing the counting detection of the peanuts; and the counting data is input into the single-chip microcomputer for signal capture, and then the seed drop frequency is calculated, and the change in the seed drop frequency is used to determine whether the seeds are missed.

[0030] Furthermore, in step 4, the single chip microcomputer data processing method is as follows:

[0031] Step 4.1: Use Kalman filter algorithm to smooth the sowing depth control logic:

[0032] The Kalman filter algorithm is divided into two steps: prediction and update. The prediction step includes state prediction and covariance prediction, and the update step includes Kalman gain calculation, state update, and covariance update. The prediction and update steps are repeated at each time step to gradually improve the accuracy of state estimation. The sowing depth data processed by the Kalman filter algorithm makes the output control signal smooth, reduces the sowing depth variance, and reduces the vibration of the electric cylinder telescopic mechanism during operation.

[0033] Step 4.2: Use the improved PID control algorithm to control the sowing frequency control logic, that is, use internal model control and model adaptive reference control to optimize the fuzzy PID control algorithm, improve the adaptability of PID control to model mismatch caused by complex and uncertain environments, improve the robustness to disturbances, and dynamically adjust the PID control parameters to improve the control performance of PID control under different working conditions, and enhance the system's ability to respond and quickly correct errors, as follows:

[0034] The control quantity calculation formula of the PID control algorithm is:

[0035]

[0036] Among them, u(t) is the output of the controller, that is, the control quantity; e(t) is the error at time t, that is, the difference between the target value and the actual value; K p is the proportional gain; K i is the integral gain; K d is the differential gain; e(τ) is the error at time τ; d represents the differential operator;

[0037] The calculation formula of internal model control IMC is:

[0038] The IMC controller C(s) and process model G(s) satisfy the following relationship:

[0039]

[0040] Among them, C(s) is the IMC controller; G(s) is the model of the controlled system; Q(s) is the IMC filter used to stabilize the controller, and its calculation formula is:

[0041]

[0042] Among them, λ is the adjustment parameter; n is the order of the filter; s is the complex frequency variable;

[0043] The control output formula is:

[0044]

[0045] Where y(s) is the system output; r(s) is the reference input;

[0046] The calculation formula of model reference adaptive control MRAC is:

[0047] Adaptive control formula:

[0048]

[0049] in, is the rate of change of the control coefficient; θ is the parameter of adaptive control; γ is the adaptive gain; y m is the output of the reference model; e(t) is the error signal, and the calculation formula is:

[0050] e(t)=y(t)-y m (t)

[0051] Among them, y(t) is the output of the system; y m (t) is the output of the reference model;

[0052] The reference model calculation formula of MRAC is:

[0053]

[0054] Where M(s) and D(s) are the transfer functions of the reference model respectively; m (s) is the output of the reference model.

[0055] The present invention has the following beneficial effects:

[0056] The peanut precision seeder sowing depth and sowing amount online detection and precise control device and method provided by the present invention utilizes ultrasonic ranging sensors, optical fiber counting sensors, biaxial inclination sensors, linear displacement sensor photoelectric rotary encoders, etc. to obtain the sowing depth, sowing amount, sowing machine inclination, electric cylinder telescopic mechanism telescopic amount, machine speed and seeding frequency and other operation information of the sowing machine in real time, and through digital signal processing conversion, STM32F103ZE single-chip microcomputer processing, optimization algorithm and control algorithm optimization, the sowing depth and seeding situation of the sowing machine are detected online, the sowing depth is adjusted in real time, and the sowing is replanted in real time, so as to realize real-time and precise control of peanut sowing, ensure that peanut sowing meets the requirements of sowing depth and seed spacing consistency, make the seeds in the best position for planting and growth, provide a good growth environment for crops, improve the survival rate, yield and quality of crops, and realize high-quality and efficient control of peanut sowing depth and sowing amount. At the same time, the whole sowing process is more automated and efficient, and no manual intervention is required, which saves manpower and material resources and has good economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a principle diagram of real-time measurement and control of sowing depth and sowing amount according to the present invention;

[0058] Figure 2 This is a flow chart of real-time measurement and control of sowing depth and sowing amount according to the present invention;

[0059] Figure 3 The principle of dual-axis tilt detection of the present invention

[0060] Figure 4 This is a schematic diagram of the optical fiber counting detection of the present invention;

[0061] Figure 5 This is a schematic diagram of the Kalman filter algorithm of the present invention;

[0062] Figure 6 This is the principle diagram of the improved PID control algorithm of the present invention;

[0063] Figure 7 This is a diagram of the sowing depth adjustment method described in the present invention.

[0064] In the figure: 1-frame; 2-machine drive shaft; 3-ultrasonic distance sensor A; 4-servo motor; 5-air suction seed metering device; 6-ultrasonic distance sensor B; 7-STM32F103ZE type single chip microcomputer; 8-seed drop tube; 9-optical fiber counting sensor; 10-dual-axis inclination sensor; 11-photoelectric rotary encoder; 12-linear displacement sensor; 13-electric cylinder telescopic mechanism; 14-ditch opener; 15-seed; 16-depth limiting wheel. DETAILED DESCRIPTION

[0065] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments, but the protection scope of the present invention is not limited thereto.

[0066] like Figure 1 As shown, the online detection and precise control device of sowing depth and sowing amount of the peanut precision seeder of the present invention comprises a frame 1, a machine transmission shaft 2, a dual-axis inclination sensor 10, an air suction seeding device 5, a seed dropping tube 8, a furrow opener 14, a depth limiting wheel 16, a photoelectric rotary encoder 11, an optical fiber counting sensor 9, an ultrasonic ranging sensor A3, an ultrasonic ranging sensor B6, an STM32F103ZE type single chip microcomputer 7, a servo motor 4, a linear displacement sensor 12, and an electric cylinder telescopic mechanism 13.

[0067] like Figure 1As shown, with the traveling direction as the positive direction, a furrow opener 14 is installed at the corresponding position in front of the air-suction seed metering device 5, a limited depth wheel 16 is installed at the corresponding position in the rear, and a seed drop tube 8 is installed at the seeding port; the ultrasonic distance sensor A3 and the ultrasonic distance sensor B6 are installed downward at the bottom of the frame 1, and are respectively located at the front and rear ends of the furrow opener 14. The optical fiber counting sensor 9 is installed below the seeding port of the air-suction seed metering device 5 and at the mouth of the seed drop tube 8 to detect the seed drop frequency; the photoelectric rotary encoder 11 is respectively installed on the machine transmission shaft 2 and the seeding shaft of the seed metering device to respectively detect the traveling speed of the machine and the rotation speed of the seeding shaft; the dual-axis inclination sensor 10 is installed on the machine to respectively detect the pitch angle when the machine is traveling. The ultrasonic distance sensor A3, the ultrasonic distance sensor B6, the optical fiber counting sensor 9 and the photoelectric rotary encoder 11 are all connected to the STM32F103ZE single-chip computer 7. The furrow opener 14 is also equipped with an electric cylinder telescopic mechanism 13 and a linear displacement sensor 12 . The shaft of the air suction seed metering device 5 is connected to a servo motor 4 . The electric cylinder telescopic mechanism 13 and the servo motor 4 are both connected to a STM32F103ZE single chip microcomputer 7 .

[0068] The sowing depth measurement and control part and the missed sowing detection and reseeding part of the measurement and control device are respectively equipped with different detection and control equipment, and are both connected to the STM32F103ZE type single chip computer 7.

[0069] Reference Figure 2 The method for online detection and precise control of sowing depth and sowing amount of peanut precision seeder using the above-mentioned online detection and precise control device of sowing depth and sowing amount of peanut precision seeder includes a preparation stage, a detection stage, and a control stage. The specific process is as follows:

[0070] Preparation stage, implementation of preparatory work before peanut planter operation:

[0071] Step 1: Check the condition of the peanut precision seeder to ensure that the seeder can meet the conditions for peanut precision seeding;

[0072] Step 2: Start the seed drill, and control the electric cylinder telescopic mechanism 13 and the servo motor 4 through the STM32F103ZE type single chip microcomputer 7 to maintain the initial operating state.

[0073] Detection stage: Detection equipment operation and operation information collection:

[0074] Step 3: Start the ultrasonic distance sensor A3, the ultrasonic distance sensor B6, the optical fiber counting sensor 9, the photoelectric rotary encoder 11, the biaxial tilt sensor 10, and the linear displacement sensor 12; during the movement of the seeder, cooperate with the STM32F103ZE single chip computer 7, continuously and in real time detect the distance from the frame 1 to the ridge surface and the bottom of the ridge ditch through the ultrasonic distance sensor A3 and the ultrasonic distance sensor B6, detect the working inclination of the seeder in real time through the biaxial tilt sensor 10, detect the sowing frequency of the air suction seeding device 5 through the optical fiber counting sensor 9, respectively measure the travel speed of the seeder and the rotation speed of the seeding shaft through the photoelectric rotary encoder 11, and detect the telescopic amount of the electric cylinder telescopic mechanism 13 through the linear displacement sensor 12;

[0075] The specific detection methods of each sensor are as follows:

[0076] Using ultrasonic sensing to detect the sowing depth:

[0077] By using ultrasonic sensing, through multi-source information fusion, multiple ultrasonic sensing modules are placed at appropriate positions of the precision seeder, and the ultrasonic sensing modules are driven to transmit and receive high-frequency sound waves to the ground to respectively detect the distance from the frame 1 to the ridge surface and the ridge ditch bottom in real time, avoid the influence of medium and low-frequency sound wave signals in the working environment, and use the multi-source sensing characteristics of the detection module to reduce detection errors and improve detection accuracy;

[0078] The distance d from the frame 1 to the ridge surface (or ridge bottom) is calculated as follows:

[0079]

[0080] Among them, v represents the propagation speed of ultrasound in the air; t represents the time required from transmitting the wave to receiving the wave;

[0081] The Doppler effect formula is introduced to reduce the influence of frequency offset on ranging effect:

[0082]

[0083] Among them, f r is the received frequency; f s is the transmitting frequency; v a is the propagation speed of ultrasound in air; v r is the velocity of the ground (since the ground is used as a reference, v r =0m / s); v s is the vertical speed of ultrasonic ranging sensor A3 (or ultrasonic ranging sensor B6);

[0084] By calculating the frequency deviation, the corrected ultrasonic propagation time is obtained:

[0085]

[0086] Among them, t corr is the corrected ultrasonic propagation time; t is the time directly measured by the ultrasonic ranging sensor A3 (or ultrasonic ranging sensor B6) from sending to receiving;

[0087] Finally, the distance d′ from the frame 1 to the ridge surface (or ridge ditch bottom) after correction is obtained:

[0088]

[0089] The ultrasonic distance measuring sensor A3 and the ultrasonic distance measuring sensor B6 input the corrected measured data to the STM32F103ZE microcontroller 7 for difference calculation to finally obtain the sowing depth.

[0090] Use dual-axis inclination sensing to detect the inclination of the seed drill during operation:

[0091] The dual-axis inclination posture detection method is used to detect the inclination state of the frame 1 in real time during operation, avoid the influence of the seeder tilt on the sowing depth detection, and reduce the detection error. The principle is as follows Figure 3 As shown;

[0092] The dual-axis inclination sensor 10 uses the principle of gravity acceleration and micro-electromechanical (MEMS) technology, and takes advantage of the directional invariance of gravity acceleration. When an object tilts, the dual-axis inclination sensor 10 has a built-in accelerometer to measure the changes in gravity components along the X, Y, and Z axes, and calculates the object's inclination in real time based on the components. The gravity acceleration g can be decomposed into three components along the X, Y, and Z axes in three-dimensional space, namely g x , g y , g z ;

[0093] In three-dimensional space, the inclination of an object has two main angles, namely pitch and roll;

[0094] The pitch angle θ is used to describe the inclination angle of an object around the X-axis, which is expressed by the gravity component g along the X-axis. x And the total gravity g is calculated:

[0095]

[0096] Roll Angle Used to describe the inclination angle of an object around the Y axis, using the gravity component g along the Y axis y And the total gravity g is calculated:

[0097]

[0098] Among them, g x , gy , g z are the gravity components along the X-axis, Y-axis, and Z-axis respectively.

[0099] Use fiber optic sensing to detect seeding operation conditions:

[0100] The optical fiber counting sensor is used to judge the information of peanut seeds 15, and the photoelectric signal changes generated by the optical fiber detection port during peanut seeding are used to determine the missing seed information, so as to realize the real-time and accurate detection of missing seeds;

[0101] Detection principle Figure 4 As shown, when the peanut seeds 15 enter the detection range of the optical fiber counting sensor 9, the position of the interference fringes inside the optical fiber counting sensor 9 changes, causing the optical path difference to change:

[0102]

[0103] Where ΔL is the optical path difference, Δx is the position of the interference fringes, and λ is the wavelength of light.

[0104] Each time the optical fiber counting sensor 9 detects a change in the optical path difference, the count is increased, thereby realizing the counting and detection function for peanuts; and the counting data is input into the STM32F103ZE microcontroller 7 for signal capture to calculate the seed drop frequency, and whether seeds are missed is determined by the change in the seed drop frequency.

[0105] Control phase: Receiving and processing of detection signals and generating control actions:

[0106] Step 4: The data measured by each sensor in step 3 is transmitted to the STM32F103ZE type single chip microcomputer 7, which converts, calculates, and smoothes the signal, generates control logic, and converts it into an output signal, which is output to the electric cylinder telescopic mechanism 13 and the servo motor 4 respectively; the data processing method of the STM32F103ZE type single chip microcomputer 7 is as follows:

[0107] Step 4.1: Use Kalman filter algorithm to smooth the sowing depth control logic:

[0108] Reference Figure 5 , The Kalman filter algorithm is mainly divided into two steps: prediction and update. The prediction step includes state prediction and covariance prediction; the state prediction is as follows:

[0109]

[0110] The covariance prediction is as follows:

[0111]

[0112] in, is the predicted value of the state vector; A is the state transfer matrix; is the state estimate at the previous moment; B is the control input matrix; u k is the control input; is the prediction error covariance matrix; Q is the process noise covariance matrix;

[0113] The update steps include Kalman gain calculation, state update, and covariance update;

[0114] Kalman gain calculation:

[0115]

[0116] Status Update:

[0117]

[0118] And covariance update:

[0119]

[0120] Among them, K k is the Kalman gain; H is the observation matrix; is the observed value; R is the measurement noise covariance matrix; I is the identity matrix; is the updated state estimate; P k is the updated error covariance matrix;

[0121] The two steps of prediction and updating are repeated at each time step, gradually improving the accuracy of state estimation;

[0122] The sowing depth data processed by the Kalman filter algorithm can make the output control signal smoother, reduce the variance of the sowing depth, and reduce the vibration of the electric cylinder telescopic mechanism 13 during operation, thereby increasing the service life and improving the operation effect.

[0123] Step 4.2: Reference Figure 6 , use the improved PID control algorithm to control the sowing frequency control logic:

[0124] The control quantity calculation formula of the PID control algorithm is:

[0125]

[0126] Among them, u(t) is the output of the controller, that is, the control quantity; e(t) is the error at time t, that is, the difference between the target value and the actual value; K p is the proportional gain; K i is the integral gain; K d is the differential gain; e(τ) is the error at time τ; d represents the differential operator.

[0127] The fuzzy PID control algorithm is optimized by using internal model control (IMC) and model adaptive reference control (MRAC) to improve the adaptability of PID control to model mismatch caused by complex and uncertain environments, improve the robustness to disturbances, and dynamically adjust PID control parameters to improve the control performance of PID control under different working conditions, and enhance the system response and ability to quickly correct errors, as follows:

[0128] The calculation formula of internal model control IMC is:

[0129] The IMC controller C(s) and process model G(s) satisfy the following relationship:

[0130]

[0131] Among them, C(s) is the IMC controller; G(s) is the model of the controlled system; Q(s) is the IMC filter used to stabilize the controller, and its calculation formula is:

[0132]

[0133] Among them, λ is the adjustment parameter; n is the order of the filter; s is the complex frequency variable;

[0134] The control output formula is:

[0135]

[0136] Where y(s) is the system output; r(s) is the reference input;

[0137] The calculation formula of model reference adaptive control MRAC is:

[0138] Adaptive control formula:

[0139]

[0140] in, is the rate of change of the control coefficient; θ is the parameter of adaptive control, i.e., the control parameter; γ is the adaptive gain; y m is the output of the reference model; e(t) is the error signal, and the calculation formula is:

[0141] e(t)=y(t)-y m (t)

[0142] Among them, y(t) is the output of the system; y m (t) is the output of the reference model;

[0143] The reference model calculation formula of MRAC is:

[0144]

[0145] Where M(s) and D(s) are the transfer functions of the reference model respectively; m (s) is the output of the reference model, where the variable s is because the output is represented in the Laplace transform domain and s is a complex frequency variable.

[0146] Fuzzy PID converts the input signal of PID control into a fuzzy set ("negative large", "negative small", "zero", "positive small", "positive large"), defines fuzzy rules and uses a fuzzy inference system to convert the fuzzy control quantity into a specific PID gain adjustment quantity, thereby adjusting the three types of integrals and improving the PID control effect.

[0147] Step 5: The electric cylinder telescopic mechanism 13 and the servo motor 4 adjust their operating states according to the input control signal; the electric cylinder telescopic mechanism 13 adjusts the telescopic amount in real time to change the length of the furrow opener 14 and directly adjust the sowing depth; the servo motor 4 adjusts the speed in real time to change the speed of the air suction seeding device 5 and indirectly adjust the seeding frequency; the specific adjustment principle is as follows Figure 7 As shown;

[0148] Step 6: After the above control mechanism adjusts the working state of the seed drill, each sensor further performs detection, generates a signal, and generates the next output signal through the STM32F103ZE type single chip microcomputer 7, forming a closed-loop control of the seeding operation.

[0149] The embodiments are preferred implementations of the present invention, but the present invention is not limited to the above-mentioned implementations. Any obvious improvements, substitutions or modifications that can be made by those skilled in the art without departing from the essential content of the present invention belong to the protection scope of the present invention.

Claims

1. A device for online detection and precise control of sowing depth and sowing amount of a peanut precision seeder, characterized in that: The invention comprises an air-suction seed metering device (5) mounted on a frame (1), wherein a furrow opener (14) is mounted in front of the air-suction seed metering device (5), a limited depth wheel (16) is mounted in the rear, and a seed drop tube (8) is mounted at the seed discharge port; an ultrasonic distance measuring sensor A (3) and an ultrasonic distance measuring sensor B (6) are mounted at the bottom of the frame (1) and at the front and rear ends of the furrow opener (14); an optical fiber counting sensor (9) is mounted at the mouth of the seed drop tube (8) below the seed discharge port; a machine transmission shaft (2) and a seed discharge shaft of the seed metering device A photoelectric rotary encoder (11) is installed on each of the two devices; a dual-axis tilt sensor (10) is installed on the machine; an ultrasonic distance sensor A (3), an ultrasonic distance sensor B (6), an optical fiber counting sensor (9) and a photoelectric rotary encoder (11) are all connected to a single-chip microcomputer; an electric cylinder telescopic mechanism (13) and a linear displacement sensor (12) are also installed on the furrow opener (14); a servo motor (4) is connected to the shaft of the air suction seed metering device (5); and the electric cylinder telescopic mechanism (13) and the servo motor (4) are both connected to the single-chip microcomputer.

2. A method for online detection and precise control of sowing depth and sowing amount of a peanut precision seeder using the device for online detection and precise control of sowing depth and sowing amount of a peanut precision seeder according to claim 1, characterized in that: The process includes the following: Step 1: Check the condition of the seeder; Step 2: Start the seed drill, and control the electric cylinder telescopic mechanism (13) and the servo motor (4) through the single chip microcomputer to maintain the initial operation state; Step 3: Start the ultrasonic distance sensor A (3), the ultrasonic distance sensor B (6), the optical fiber counting sensor (9), the photoelectric rotary encoder (11), the biaxial tilt sensor (10), and the linear displacement sensor (12); during the movement of the seed drill, the ultrasonic distance sensor A (3) and the ultrasonic distance sensor B (6) are used in conjunction with the single chip microcomputer to continuously and in real time detect the distance from the frame (1) to the ridge surface and the bottom of the ridge, thereby calculating the sowing depth, and the biaxial tilt sensor (10) is used to detect the working tilt angle of the seed drill in real time, and the optical fiber counting sensor (9) is used to detect the seed dropping frequency of the air suction seeding device (5), and the photoelectric rotary encoder (11) is used to respectively measure the travel speed of the seed drill and the rotation speed of the seeding shaft, and the linear displacement sensor (12) is used to detect the telescopic amount of the electric cylinder telescopic mechanism (13); Step 4: The data measured by each sensor is transmitted to the single chip microcomputer, which converts, calculates and smoothes the signal, generates control logic, and converts it into an output signal, which is output to the electric cylinder telescopic mechanism (13) and the servo motor (4) respectively; Step 5: The electric cylinder telescopic mechanism (13) and the servo motor (4) adjust their operating states according to the input control signal respectively; the electric cylinder telescopic mechanism (13) adjusts the telescopic amount in real time to change the length of the furrow opener (14) and directly adjust the sowing depth; the servo motor (4) adjusts the rotation speed in real time to change the rotation speed of the air suction seeding device (5) and indirectly adjust the seeding frequency; Step 6: After adjusting the operating state of the seed drill in step 5, each sensor further performs detection, generates a signal, and generates the next output signal through the single-chip microcomputer, forming a closed-loop control of the seeding operation.

3. The method for online detection and precise control of sowing depth and sowing amount of a peanut precision seeder according to claim 2, characterized in that: In step 3, the specific method of using the ultrasonic distance measuring sensor A (3) and the ultrasonic distance measuring sensor B (6) to detect the distance from the frame (1) to the ridge surface and the ridge ditch bottom and then obtain the sowing depth is as follows: The ultrasonic distance sensor A (3) or the ultrasonic distance sensor B (6) first calculates the distance d from the frame (1) to the ridge surface or the ridge ditch bottom using the following formula: Among them, v represents the propagation speed of ultrasound in the air; t represents the time required from transmitting the wave to receiving the wave; Then the Doppler effect formula is introduced to reduce the influence of frequency offset on the ranging effect: Among them, f r is the received frequency; f s is the transmitting frequency; v a is the propagation speed of ultrasound in air; v r is the velocity of the ground; v s is the vertical speed of ultrasonic ranging sensor A (3) or ultrasonic ranging sensor B (6); By calculating the frequency deviation, the corrected ultrasonic propagation time is obtained: Among them, t corr is the corrected ultrasonic propagation time; t is the time directly measured by the ultrasonic ranging sensor A (3) or the ultrasonic ranging sensor B (6) from sending to receiving; Finally, the distance d′ from the corrected frame (1) to the ridge surface or ridge ditch bottom is obtained as: The ultrasonic distance measuring sensor A (3) and the ultrasonic distance measuring sensor B (6) input the corrected measured data into the single chip microcomputer for difference calculation to finally obtain the sowing depth.

4. The method for online detection and precise control of sowing depth and sowing amount of a peanut precision seeder according to claim 2, characterized in that: In step 3, the dual-axis inclination sensor (10) uses the principle of gravity acceleration and micro-electromechanical technology, and utilizes the directional invariance of gravity acceleration. When the object tilts, the built-in accelerometer of the dual-axis inclination sensor (10) measures the changes in gravity components along the X, Y, and Z axes, and calculates the working inclination of the seed drill in real time based on the components.

5. The method for online detection and precise control of sowing depth and sowing amount of a peanut precision seeder according to claim 2, characterized in that: In step 3, when the peanut seeds (15) fall from the seed dropping tube (8) and enter the detection range of the optical fiber counting sensor (9), the position of the interference fringes inside the optical fiber counting sensor (9) changes, causing the optical path difference to change. Each time the optical fiber counting sensor (9) detects a change in the optical path difference, the count is increased once, thereby realizing the counting detection of the peanuts. The counting data is input into the single chip microcomputer for signal capture, and then the seed dropping frequency is calculated, and whether the seeds are missed is judged by the change in the seed dropping frequency.

6. The method for online detection and precise control of sowing depth and sowing amount of a peanut precision seeder according to claim 2, characterized in that: In step 4, the single chip computer data processing method is as follows: Step 4.1: Use Kalman filter algorithm to smooth the sowing depth control logic: The Kalman filter algorithm is divided into two steps: prediction and update. The prediction step includes state prediction and covariance prediction, and the update step includes Kalman gain calculation, state update, and covariance update. The prediction and update steps are repeated at each time step to gradually improve the accuracy of state estimation. The sowing depth data processed by the Kalman filter algorithm is used to smooth the output control signal, reduce the sowing depth variance, and reduce the vibration of the electric cylinder telescopic mechanism (13) during operation. Step 4.2: Use the improved PID control algorithm to control the sowing frequency control logic, that is, use internal model control and model adaptive reference control to optimize the fuzzy PID control algorithm, improve the adaptability of PID control to model mismatch caused by complex and uncertain environments, improve the robustness to disturbances, and dynamically adjust the PID control parameters to improve the control performance of PID control under different working conditions, and enhance the system's ability to respond and quickly correct errors.

7. The method for online detection and precise control of sowing depth and sowing amount of a peanut precision seeder according to claim 2, characterized in that: In step 4.2, the specific method of improving the PID control algorithm is as follows: The control quantity calculation formula of the PID control algorithm is: Among them, u(t) is the output of the controller, that is, the control quantity; e(t) is the error at time t, that is, the difference between the target value and the actual value; K p is the proportional gain; K i is the integral gain; K d is the differential gain; e(τ) is the error at time τ; d represents the differential operator; The calculation formula of internal model control IMC is: The IMC controller C(s) and process model G(s) satisfy the following relationship: Among them, C(s) is the IMC controller; G(s) is the model of the controlled system; Q(s) is the IMC filter used to stabilize the controller, and its calculation formula is: Among them, λ is the adjustment parameter; n is the order of the filter; s is the complex frequency variable; The control output formula is: Where y(s) is the system output; r(s) is the reference input; The calculation formula of model reference adaptive control MRAC is: Adaptive control formula: in, is the rate of change of the control coefficient; θ is the parameter of adaptive control; γ is the adaptive gain; y m is the output of the reference model; e(t) is the error signal, and the calculation formula is: e(t)=y(t)-y m (t) Among them, y(t) is the output of the system; y m (t) is the output of the reference model; The reference model calculation formula of MRAC is: Where M(s) and D(s) are the transfer functions of the reference model respectively; m (s) is the output of the reference model.

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