Microwave doppler-based granular fertilizer flow measurement method and measurement system

Abstract

The application discloses a kind of granular fertilizer flow measurement method and measurement system based on microwave Doppler, it is related to fertilizer flow detection technical field.The method includes the following steps: microwave sensing system transmits echo signal to detect granular fertilizer, generates echo signal and carries out signal noise reduction processing to received echo signal;Granular fertilizer's average speed is obtained by frequency analysis and granular fertilizer's average concentration is obtained by power spectral density analysis to the echo signal after noise reduction respectively;The average speed of granular fertilizer and the average concentration of granular fertilizer are output after correction, and granular fertilizer flow is calculated according to granular fertilizer flow calculation model.The method has the advantages of high measurement accuracy, and detection is convenient.

Description

Technical Field

[0001] This invention relates to the field of fertilizer flow detection technology, and in particular to a method and system for measuring the flow of granular fertilizer based on microwave Doppler. Background Technology

[0002] Precision fertilization technology enables variable-rate fertilizer application based on soil nutrient requirements, significantly improving fertilizer utilization and reducing environmental pollution. Dynamic, high-precision measurement of fertilizer application is a prerequisite for implementing precision fertilization. Most chemical fertilizers are granular, but real-time, accurate measurement of their mass flow rate remains a significant challenge due to the need for non-contact detection. Since fertilizer application is difficult to evaluate visually after entering the soil, obtaining accurate dynamic fertilizer application rates in real time is crucial for evaluating the quality of fertilization operations. Existing methods for detecting granular fertilizer flow rate mainly include direct weighing, indirect detection based on the discharge shaft rotation speed, photoelectric methods, imaging methods, capacitance methods, electrostatic methods, and microwave methods. Compared to other traditional methods, the microwave method offers significant advantages such as non-contact measurement, high accuracy, wide measurement range, high reliability, and ease of integration.

[0003] In microwave Doppler measurement, fertilizer reflects microwaves emitted by a microwave sensor during its movement through the discharge pipe. Frequency and energy information from the Doppler echo signal are extracted, and the average velocity and concentration of the fertilizer are determined through power spectrum estimation. Measurement accuracy depends on factors such as the transmission frequency, fertilizer concentration, fertilizer type and distribution, and flow rate. When a large amount of fertilizer moves through the discharge pipe, the random motion and collisions between particles result in aliasing of multiple Doppler signals. Spectral aliasing, the picket fence phenomenon, and spectral leakage are the main causes of measurement errors. Frequency calculation methods such as Fast Fourier Transform (FFT) have not yet established a unified model for concentration analysis, and the relationship between echo energy and fertilizer mass flow rate has not been fully theoretically demonstrated. The mechanism for accurate fertilizer detection based on microwave Doppler technology requires further investigation.

[0004] Preliminary field trials have shown that fertilizer application rate detection is easily affected by vibration interference, which is difficult to eliminate. Field vibrations from fertilizer applicators cause a large coefficient of variation in fertilizer application rate, and vibrations generated under different speed conditions on the vehicle-mounted platform have varying effects on sensor performance. The interference factors of the vehicle-mounted vibration model are still unclear, and how to identify and suppress interference from multiple sources remains unknown. Echo signals are affected by multiple factors such as fertilizer moisture content, flow velocity, and ambient temperature. Establishing a model relating multi-source heterogeneous data to fertilizer application rate is also a key issue that needs to be considered. Summary of the Invention

[0005] The technical problem to be solved by the present invention is how to provide a high-precision microwave Doppler-based method and system for measuring the flow rate of granular fertilizer.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a method for measuring the flow rate of granular fertilizer based on microwave Doppler, comprising the following steps: The microwave sensing system transmits echo signals to detect granular fertilizer, generates echo signals, and performs signal noise reduction processing on the received echo signals; Frequency analysis and power spectral density analysis were performed on the noise-reduced echo signal. The average velocity of the granular fertilizer was obtained by frequency analysis, and the average concentration of the granular fertilizer was obtained by power spectral density analysis. The average velocity and average concentration of the granular fertilizer are obtained and then corrected. The granular fertilizer flow rate is then calculated based on the granular fertilizer flow rate calculation model.

[0007] Accordingly, the present invention also discloses a granular fertilizer flow measurement system based on microwave Doppler, comprising: a test bench, a fertilizer tank fixedly mounted on the upper side of the test bench, a variable fertilization unit mounted on the outlet of the fertilizer tank, the outlet of the variable fertilization unit connected to the upper end of a fertilizer conveying pipe, the lower end of the fertilizer conveying pipe extending into a fertilizer collection device, microwave sensors mounted on both sides of the lower end of the fertilizer conveying pipe, the signal output terminal of the microwave sensor connected to the signal output terminal of a data acquisition card, the data acquisition card preprocessing the signal acquired by the microwave sensor and transmitting it to a data processing terminal for calculation and processing, and the data processing terminal running the granular fertilizer flow measurement method to obtain granular fertilizer flow data; The variable fertilization unit includes an outer grooved wheel fertilizer dispenser, a servo motor, a reducer, an electric push rod, and a power supply. The fertilizer dispensing shaft of the outer grooved wheel fertilizer dispenser is connected to the servo motor through the reducer, and the electric push rod is connected to the gate of the outer grooved wheel fertilizer dispenser. The fertilizer dispensing shaft speed and fertilizer dispensing opening commands are issued by an STM32 microcontroller and implemented through control software. The power supply module is used to provide working power to the modules in the variable fertilization unit that require power.

[0008] The beneficial effects of adopting the above technical solution are as follows: The method and system use microwave Doppler technology to detect granular fertilizer flow rate, enabling non-contact detection, easy hardware integration, and high-precision measurement, thus overcoming the physical limitations of traditional sensors. The use of a wavelet method based on ensemble empirical mode decomposition and sample entropy effectively solves the problem of nonlinear signal attenuation under complex electromagnetic interference in the field, effectively avoids mode aliasing, and extracts the main signal components from noisy echo signals. This method demonstrates good denoising performance in actual data processing; the signal-to-noise ratio of the processed signal is improved by 8.485 dB, and the root mean square error is reduced by 67.7%, laying the foundation for subsequent calculation of actual granular fertilizer flow rate signals. Attached Figure Description

[0009] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0010] Figure 1 This is the main flowchart of the method described in the embodiments of the present invention; Figure 2 This is a flowchart of the process of the method described in the embodiments of the present invention; Figure 3 This is a flowchart of the combined wavelet algorithm of empirical modes and sample entropy in the method described in the embodiments of the present invention; Figure 4 This is a schematic diagram of the system described in an embodiment of the present invention; Figure 5a This is a physical image of a single microwave sensor in the system described in the embodiments of the present invention; Figure 5b This is a physical image of the integrated microwave sensor in the system described in the embodiments of the present invention; Figure 6 This is a physical image of the aluminum metal shielding box for the microwave Doppler sensor in the system described in this embodiment of the invention; Figure 7 This is a schematic diagram of the structure of the variable fertilization unit in the system described in the embodiment of the present invention; Figure 8 This is a physical image of the spiral external grooved wheel fertilizer dispenser in the system described in the embodiment of the present invention; Figure 9 This is a diagram of the data acquisition software interface in an embodiment of the present invention; Figure 10 This is "in the embodiments of the present invention" P sd - Q t Fitted curve; The components include: 1. Test bench; 2. Fertilizer tank; 3. Variable fertilization unit; 4. Fertilizer delivery pipeline; 5. Fertilizer collection device; 51. Reducer; 52. Servo motor; 53. Electric push rod; 54. External grooved wheel fertilizer dispenser; 55. Gate; 6. Integrated microwave sensor; 7. Data acquisition card; 8. Data processing terminal. Detailed Implementation

[0011] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0012] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0013] Example 1 Overall, such as Figure 1 As shown in the figure, this invention discloses a method for measuring the flow rate of granular fertilizer based on microwave Doppler, the method comprising the following steps: S1: The microwave sensing system transmits echo signals to detect granular fertilizer, generates echo signals, and performs noise reduction processing on the received echo signals; S2: Perform frequency analysis and power spectral density analysis on the noise-reduced echo signal. Obtain the average velocity of the granular fertilizer through frequency analysis and the average concentration of the granular fertilizer through power spectral density analysis. S3: After outputting the average velocity and average concentration of the granular fertilizer, correct them and calculate the granular fertilizer flow rate according to the granular fertilizer flow rate calculation model.

[0014] like Figure 2 The diagram shown is a flowchart illustrating the specific processing steps of the microwave Doppler-based granular fertilizer flow measurement method. The granular fertilizer flow calculation model is as follows: According to the mass-density-volume formula, when the cross-sectional area of ​​the fertilizer discharge pipe... S granular fertilizer density ρ Given the mass flow rate of granular fertilizer flowing through the cross-section of the pipe per unit time. Q It can be defined as ; In the formula: ρ This refers to the density of granular fertilizer, expressed in kg / m³. 3 ; The velocity of the falling granular fertilizer is expressed in m / s. The concentration of granular fertilizer in the fertilizer discharge pipeline is expressed as % (%). S The cross-sectional area of ​​the fertilizer discharge pipe is expressed in meters (m²). 2 .

[0015] Microwave detection principle: A microwave sensing system establishes a static electromagnetic field within the fertilizer discharge pipeline, with the transmitter maintaining a constant geometric orientation relative to the pipeline wall. As granular fertilizer passes through, the echo signal follows a steady-state Helmholtz equation solution, forming a frequency-shift-free standing wave. Due to the Doppler effect, the electromagnetic waves reflected by the moving particles exhibit frequency shift. Simultaneously, the particles absorb electromagnetic energy, causing the echo power to attenuate. Particle falling speed. With frequency offset Positive correlation, particle concentration inside the pipeline It is positively correlated with the degree of power attenuation.

[0016] The above steps will be explained in detail below with reference to specific content: Microwave Doppler signal power spectral density estimation: For microwave Doppler sensor signals (which may contain noise and be non-stationary), the Welch method is the most suitable improvement method among periodogram methods. The core idea of ​​the Welch method is piecewise averaging and windowing, dividing the signal into overlapping segments. L Each segment is windowed, and the periodogram is calculated separately. Then, the average is used to reduce variance and suppress spectral leakage, thereby improving frequency resolution.

[0017] signal length N Segment length M Overlap ratio D (Usually 50%). The first i A segment signal can be represented as: ; In the formula: For an N-window function (such as the Hanning window), satisfying the normalization condition: ; Each segment of the periodic graph can be represented as: ; final P sd estimate: ; This method reduces the variance to 1 / L of the original periodogram through piecewise averaging, making it suitable for noisy microwave Doppler signals. It can reduce leakage through windowing and retain more data information through overlapping segments, making it suitable for real-time or offline processing, especially for long signal scenarios.

[0018] The dominant Doppler frequency shift in the echo signal of granular fertilizer By setting upper and lower frequency limits nearby, power characteristic values ​​can be obtained. .

[0019] ; By substituting the power spectrum eigenvalues ​​into the concentration-power calibration model, the average concentration can be obtained.

[0020] ; In the formula: m and k For calibration parameters, Microwave Doppler signal autocorrelation frequency shift analysis: Average speed of granular fertilizer Average frequency shift of Doppler echo signal The relationship can be represented as: ; In the formula: The average speed of granular fertilizer; α The angle between the main beam axis of the Doppler chip in the microwave sensing system and the direction of particle flow; This refers to the frequency of the microwave transmission source; c This refers to the microwave emission speed; The average frequency shift of the Doppler echo signal; cycle T The Doppler frequency shift can be directly obtained by performing autocorrelation on the microwave Doppler intermediate frequency signal, avoiding the difficulty in obtaining the Doppler frequency shift under low signal-to-noise ratio conditions. The autocorrelation analysis can be expressed as follows: ; In the formula: It is the autocorrelation function; For time intervals; The degree of correlation between the values ​​at any two different times; Microwave Doppler signals are typically processed intermediate frequency (IF) signals. The process involves converting the Doppler frequency shift signal into a microwave Doppler IF signal (the IF signal can be viewed as converting the velocity and distance information contained in the high-frequency echo signal into a low-frequency signal that is easier to measure and analyze; the IF signal is the original data). The period of the main component in this IF signal is then determined. T Average speed of granular fertilizer cycle T The relationship can be represented as: ; Physical analysis of granular fertilizer velocity: The movement process of granular fertilizer is analyzed. The granular fertilizer undergoes circular motion within the discharge trough, and the height during the descent phase affects its vertical velocity. The horizontal velocity of the granular fertilizer after leaving the discharge trough is also analyzed. and vertical velocity They can be represented as follows: ; In the formula: The horizontal velocity of the granular fertilizer after it leaves the fertilizer discharge wheel; The vertical velocity of the granular fertilizer after it leaves the grooved wheel; n This refers to the rotational speed of the fertilizer discharge shaft; R The radius of the fertilizer discharge channel wheel; The angle between the granular fertilizer and the horizontal direction after it leaves the fertilizer discharge wheel.

[0021] The final falling velocity of the granular fertilizer is obtained by vector synthesis of the horizontal velocity and the vertical velocity of free fall. It can be represented as: ; In the formula: The falling height of granular fertilizer h The vertical velocity afterwards; h This refers to the falling height of the granular fertilizer; g It is the acceleration due to gravity; k It is a scaling factor; This refers to the final falling speed of the granular fertilizer.

[0022] Granular fertilizer flow echo signal processing: This application proposes a set-based empirical mode decomposition (... EEMD The composite noise reduction algorithm combining EEMD, sample entropy, and wavelet method employs a fusion architecture of EEMD, sample entropy, and wavelet to enhance signal processing capabilities. Its core process is as follows: Figure 3 As shown.

[0023] Empirical Mode Decomposition: EEMD Algorithm principle: By repeatedly feeding the original signal... Injection of white noise sequence with controllable amplitude Furthermore, by utilizing the property that noise cancels out during the averaging process, a decomposition result without mode aliasing is obtained. New signal It can be represented as: ; In the formula: It is a noise-free Doppler signal; This is a noise signal; k This is the amplification factor for the interference signal; This is a noisy signal.

[0024] Empirical mode decomposition is performed on each noisy signal. EMD ), to obtain the intrinsic mode functions ( IMF The set and a residual component will give the signal After decomposition IMF The component expression is represented as: ; In the formula: For the first i indivual IMF Quantity; This is to decompose the residual terms.

[0025] pass EEMD The decomposition process separates high-frequency noise, enabling signal denoising. The residual components represent non-periodic or trending elements in the signal. This improvement overcomes the mode aliasing problem of traditional EMD and significantly enhances decomposition accuracy.

[0026] Based on sample entropy IMF Classification: Sample entropy distinguishes noise through the following steps IMF ,mix IMF and useful IMF : (1) Construct a dimension of m vector sequence: ; (2) Define similarity: given a threshold r (generally ), calculation satisfies number of vector pairs .

[0027] ; ; (3) Calculate the entropy value: ; (4) IMF Classification: Calculate all IMF After determining the entropy value, the inflection point or a threshold is set. S y Automatically determine classification points j 0 The IMF's can be divided into noise and other characteristics. IMF Sets, Mixtures IMF Collections and useful IMF gather.

[0028] ; High sample entropy components reflect strong noise characteristics, while low entropy components carry effective signals. j The sample entropy value of each IMF is ; Wavelet thresholding for noise reduction: Multi-scale decomposition using wavelet transform decomposes the signal into coefficients of different frequency components. Then, based on the characteristics of noise on the wavelet coefficients, the influence of noise on the wavelet coefficients is eliminated, and the signal is reconstructed using inverse wavelet transform, thus achieving the purpose of noise reduction.

[0029] (1) Wavelet transform: Wavelet decomposition is performed on the noisy signal to obtain the wavelet coefficients: ; In the formula: The signal contains noise; j As a scale; k For location; These are wavelet basis functions; These are wavelet coefficients.

[0030] (2) Thresholding: Thresholding is performed on the wavelet coefficients, and the soft thresholding method is used to remove the influence of noise on the wavelet coefficients. ; In the formula: These are the wavelet coefficients after thresholding. The threshold value is used.

[0031] (3) Wavelet reconstruction: Processed wavelet coefficients Perform inverse wavelet transform ( IDWT After denoising, IMF Component signals: ; In the formula: After noise reduction IMF Quantity; Signal reconstruction: All processed components are superimposed to obtain the final denoised signal and the final reconstructed signal. for: .

[0032] A flow prediction model is constructed based on least squares theory, using power spectrum characteristics. Mass flow rate is the independent variable. Establish a linear regression equation for the dependent variable: ; The optimal coefficients are found by minimizing the sum of squared residuals: ; ; In the formula: This represents the average output value of the microwave sensor, in units of... W ; This represents the average actual granular fertilizer flow rate, in g / min. n f For the number of times measured.

[0033] Experimental verification: After processing with this method, the signal-to-noise ratio of the echo signal is improved by 8.485 dB, and the root mean square error is reduced by 67.7% (see Table 1 for experimental data).

[0034] Table 1: Signal-to-noise ratio and root mean square error before and after denoising

[0035] Example 2 like Figure 4 As shown in the figure, this invention also discloses a granular fertilizer flow measurement system based on microwave Doppler, including a test bench 2, which provides mechanical support and a fertilizer conveying channel. A fertilizer tank 1 is fixedly installed on the upper side of the test bench 2, and a variable fertilization unit 5 is installed at the outlet of the fertilizer tank 1. The variable fertilization unit 5 can realize quantitative and controllable fertilizer output. The outlet of the variable fertilization unit 5 is connected to the upper end of the fertilizer conveying pipe 3, and the lower end of the fertilizer conveying pipe 3 extends into the fertilizer collection device 4. Integrated microwave sensors 8 are installed on both sides of the lower end of the fertilizer conveying pipe 3. The signal output terminal of the integrated microwave sensor 8 is connected to the signal output terminal of the data acquisition card 7. The data acquisition card 7 preprocesses the signal collected by the integrated microwave sensor 8 and transmits it to the data processing terminal 6 for calculation. The data processing terminal 6 runs the granular fertilizer flow measurement method and obtains the granular fertilizer flow data through calculation.

[0036] Integrated microwave sensor: Sensor selection: Through-beam type, operating frequency 24.125 Hz. GHz The microwave Doppler sensor is used as the detection unit, and its integrated structure is as follows: Figures 5a-5b As shown.

[0037] Electromagnetic shielding design: Design an aluminum metal shielding box, such as... Figure 6 As shown, it can effectively block the intrusion of external electromagnetic interference and reduce the leakage of internal echo signals, thereby ensuring the stability and signal quality of the microwave Doppler sensor in complex environments and improving the overall measurement accuracy and reliability.

[0038] Variable fertilization unit: The variable fertilization unit consists of, for example, Figure 7 As shown, the variable fertilization unit 5 includes an outer grooved wheel fertilizer applicator 53, a servo motor 51, a reducer 52, an electric push rod 55, and a power supply. The fertilizer applicator shaft of the outer grooved wheel fertilizer applicator 53 is connected to the servo motor 51 through the reducer 52. The specific structure of the outer grooved wheel fertilizer applicator 53 is as follows: Figure 8 As shown. The electric push rod 55 is connected to the gate 54 of the outer grooved wheel fertilizer dispenser 53. The commands for the fertilizer discharge shaft speed and fertilizer discharge opening are issued by the STM32 microcontroller and implemented through control software. The power module is used to provide working power to the modules in the variable fertilization unit 5 that require power.

[0039] Data acquisition system: Hardware configuration: Employs NI my-DAQ high-speed data acquisition card, with a single-channel sampling rate of 200 Hz. kHz Nyquist, Signal-to-Noise Ratio (SNR) 74 dB @20 kHzUSB 3.0 Type-C power supply (5 V / 900 mA ), Software design: Develop a data acquisition interface based on LabVIEW, and display the echo waveform in real time via serial bus communication (e.g., ...). Figure 9 As shown in the figure, it supports data storage and preprocessing.

[0040] Granular fertilizer truck load flow test: The experimental method consisted of two parts: calibration and on-machine testing. In the calibration experiment, with the fertilizer applicator stationary, SACF 22-8-10 granular fertilizer was filled into the fertilizer tank. The step size was set to 5 r / min, and the speed of the fertilizer discharge shaft motor was adjusted from 20 r / min to 50 r / min, a total of seven speed levels. The Doppler microwave sensor module was fixed 50 cm from the fertilizer discharge port at a 78° angle. The discharge shaft speed and running time were first set to 60 s, and the microwave Doppler sensor and signal acquisition equipment were simultaneously turned on for a data acquisition time of 60 seconds. s The sampling frequency is 1024. Hz .

[0041] Calibration test: To ensure the accuracy of the measurement results, the experiment needs to be repeated five times. Throughout the calibration process, the tractor remains stationary, and fertilizer is continuously discharged from the fertilizer delivery pipe. When the fertilizer discharge shaft stops rotating after a preset time, the data acquisition equipment also stops collecting data simultaneously. Subsequently, data is collected using an accuracy of 0.01... g An electronic balance was used to weigh the particles in the collection device. The fitted curves of power spectral density and particle flow rate were obtained as follows: Figure 10 As shown.

[0042] On-machine testing: Data acquisition was conducted while the fertilizer applicator was traveling at a stable speed. The fertilizer, microwave sensor settings, and data acquisition card settings were consistent with the calibration test. During the test, the tractor's speed was varied by adjusting its gears to maintain a stable travel speed. Three gears were selected. km / h 4.5 km / h and 5.5 km / h The experiment was conducted, and at least five sets of measurements were repeated. The obtained fertilizer excretion measurement data are shown in Table 2.

[0043] Table 2: Analysis of Experimental Data on Vehicle-Mounted Granular Fertilizer Operation

[0044] In summary, the method described in this application, employing microwave Doppler technology, achieves non-contact detection, easy hardware integration, and high-precision measurement, overcoming the physical limitations of traditional sensors. The use of a combined wavelet method based on ensemble empirical mode decomposition and sample entropy effectively addresses the problem of nonlinear signal attenuation under complex electromagnetic interference in the field, effectively avoiding mode aliasing and extracting the main signal components from noisy echo signals. This method demonstrates excellent denoising performance in practical data processing; the signal-to-noise ratio of the processed signal is improved by 8.485 dB, and the root mean square error is reduced by 67.7%, laying a solid foundation for subsequent calculations of actual granular fertilizer flow signals.

[0045] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0046] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0047] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units, etc., and are not limited to these.

[0048] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0049] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for measuring the flow rate of granular fertilizer based on microwave Doppler, characterized in that... Includes the following steps: The microwave sensing system transmits echo signals to detect granular fertilizer, generates echo signals, and performs signal noise reduction processing on the received echo signals; Frequency analysis and power spectral density analysis were performed on the noise-reduced echo signal. The average velocity of the granular fertilizer was obtained by frequency analysis, and the average concentration of the granular fertilizer was obtained by power spectral density analysis. The average velocity and average concentration of the granular fertilizer are obtained and then corrected. The granular fertilizer flow rate is then calculated based on the granular fertilizer flow rate calculation model.

2. The method for measuring the flow rate of granular fertilizer based on microwave Doppler as described in claim 1, characterized in that, The method for power spectral density analysis includes the following steps: signal length N Segment length M Overlap ratio D , No. i The segment signal is represented as: ； In the formula: It is an N-window function that satisfies the normalization condition: ; Each segment of the periodic graph can be represented as: ； final P sd estimate: ； The dominant Doppler frequency shift in the echo signal of granular fertilizer By setting upper and lower frequency limits nearby, power characteristic values ​​can be obtained. : ； Substituting the power spectrum eigenvalues ​​into the concentration-power calibration model yields the average concentration: ； In the formula: m and k These are calibration parameters.

3. The method for measuring the flow rate of granular fertilizer based on microwave Doppler as described in claim 1, characterized in that, The method for obtaining the average velocity of granular fertilizer by frequency analysis of the noise-reduced echo signal includes the following steps: Average speed of granular fertilizer Average frequency shift of Doppler echo signal The relationship is represented as: ； In the formula: The average speed of granular fertilizer; α The angle between the main beam axis of the Doppler chip in the microwave sensing system and the direction of particle flow; This refers to the frequency of the microwave transmission source; c This refers to the microwave emission speed; The average frequency shift of the Doppler echo signal; The period T is directly obtained by autocorrelation analysis of the microwave Doppler intermediate frequency signal, avoiding the difficulty in obtaining the Doppler frequency shift under low signal-to-noise ratio conditions. The autocorrelation analysis is expressed as follows: ； In the formula: It is the autocorrelation function; For time intervals; The degree of correlation between the values ​​at any two different times; Microwave Doppler signals are processed intermediate frequency signals, converting the Doppler frequency shift signal into the period of the main component in the microwave Doppler intermediate frequency signal. T Average speed of granular fertilizer cycle T The relationship is represented as: 。 4. The method for measuring the flow rate of granular fertilizer based on microwave Doppler as described in claim 1, characterized in that, The final falling speed of the granular fertilizer was obtained using the following method: The movement process of granular fertilizer is analyzed. The granular fertilizer undergoes circular motion in the discharge trough. The height of the descent phase affects the vertical velocity of the granular fertilizer, while the horizontal velocity of the granular fertilizer after leaving the discharge trough is also analyzed. and vertical velocity They are represented as follows: ； In the formula: The horizontal velocity of the granular fertilizer after it leaves the grooved wheel; The vertical velocity of the granular fertilizer after it leaves the grooved wheel; n This refers to the rotational speed of the fertilizer discharge shaft; R The radius of the fertilizer discharge channel wheel; The angle between the granular fertilizer and the horizontal direction after it leaves the grooved wheel; The final falling velocity of the granular fertilizer is obtained by vector synthesis of the horizontal velocity and the vertical velocity of free fall. It can be represented as: ； In the formula: The falling height of granular fertilizer h The vertical velocity afterwards; h This refers to the falling height of the granular fertilizer; g It is the acceleration due to gravity; k It is a scaling factor; This refers to the final falling speed of the granular fertilizer.

5. The method for measuring the flow rate of granular fertilizer based on microwave Doppler as described in claim 1, characterized in that, The methods for signal noise reduction processing include the following steps: The original signal is input into several denoising units for processing. Each denoising unit includes a white noise addition module, an empirical mode decomposition module, an IMF classification module based on sample entropy, and a wavelet threshold denoising module. The original signal is processed by the corresponding modules in the denoising unit in sequence and then cross-correlation and frequency combination analysis are performed. The processed signal is then reconstructed to obtain the denoised signal.

6. The method for measuring the flow rate of granular fertilizer based on microwave Doppler as described in claim 5, characterized in that, The processing method of the Empirical Mode Decomposition (EMD) module includes the following steps: By repeatedly sending the original signal Injection of white noise sequence with controllable amplitude By utilizing the property that noise cancels out during the averaging process, a decomposition result without mode mixing is obtained, and a new signal is generated. Represented as: ； In the formula: Noise-free Doppler signal; Noise signals; k Interference signal amplification factor; Noisy signals; Empirical mode decomposition is performed on each noisy signal. EMD Obtain the intrinsic mode functions IMF The set and a residual component will give the signal After decomposition IMF The components are represented as: In the formula: No. i indivual IMF Quantity; Decompose the residual terms.

7. The method for measuring the flow rate of granular fertilizer based on microwave Doppler as described in claim 5, characterized in that, Sample entropy distinguishes noise through the following steps IMF ,mix IMF and useful IMF : Construct a dimension of m Vector sequence: ； Define similarity: given a threshold r The calculation satisfies number of vector pairs ; ； ； Calculate the entropy value: ； High sample entropy components reflect strong noise characteristics, while low entropy components carry effective signals. j The sample entropy value of each IMF is ; IMF Classification: Calculate all IMF After determining the entropy value, the inflection point or a threshold is set. S y Automatically determine classification points j 0 The IMF's data is divided into three sets: noise, etc. IMF Sets, Mixtures IMF Collections and useful IMF gather: 。 8. The method for measuring the flow rate of granular fertilizer based on microwave Doppler as described in claim 5, characterized in that, The wavelet thresholding denoising and signal reconstruction method includes the following steps: Wavelet transform: Performing wavelet decomposition on a noisy signal to obtain wavelet coefficients: ； In the formula: The signal contains noise; j As a scale; k For location; These are wavelet basis functions; These are wavelet coefficients; Thresholding: Thresholding is performed on the wavelet coefficients, using a soft thresholding method to remove the influence of noise on the wavelet coefficients. ； In the formula: These are the wavelet coefficients after thresholding. For threshold; Wavelet reconstruction: Processed wavelet coefficients Perform inverse wavelet transform ( IDWT After denoising, IMF Component signals: ； In the formula: After noise reduction IMF Quantity; All processed components are superimposed to obtain the final denoised signal and the final reconstructed signal. for: 。 9. The method for measuring the flow rate of granular fertilizer based on microwave Doppler as described in claim 5, characterized in that, The calculation model for the granular fertilizer flow rate is as follows: When the cross-sectional area of ​​the fertilizer discharge pipe S granular fertilizer density ρ Given the mass flow rate of granular fertilizer flowing through the cross-section of the pipe per unit time. Q Defined as: ； In the formula: ρ This refers to the density of granular fertilizer; The average velocity of the granular fertilizer is expressed in m / s. This represents the average concentration of granular fertilizer, expressed in % (%). S The cross-sectional area of ​​the fertilizer discharge pipe is expressed in meters (m²). 2 ; A flow prediction model is constructed based on least squares theory, using power spectrum characteristics. The actual flow rate of granular fertilizer is the independent variable. Establish a linear regression equation for the dependent variable: ； The optimal coefficients are obtained by minimizing the sum of squared residuals: ； ； In the formula: This represents the average output value of the microwave sensor, in units of... W ; This represents the average actual flow rate of granular fertilizer, in g / min. n f For the number of times measured.

10. A granular fertilizer flow measurement system based on microwave Doppler, characterized in that... include: Test bench (2), on the upper side of the test bench (2) is a fertilizer box (1), the outlet of the fertilizer box (1) is provided with a variable fertilizer unit (5), the outlet of the variable fertilizer unit (5) is connected to the upper end of the fertilizer conveying pipe (3), the lower end of the fertilizer conveying pipe (3) extends into the fertilizer collection device (4), the lower ends of the fertilizer conveying pipe (3) are provided with integrated microwave sensors (8) on both sides, the signal output end of the integrated microwave sensor (8) is connected to the signal output end of the data acquisition card (7), the data acquisition card (7) preprocesses the signal collected by the integrated microwave sensor (8) and transmits it to the data processing terminal (6) for calculation and processing, the data processing terminal (6) runs the granular fertilizer flow measurement method as described in any one of claims 1-9, and obtains granular fertilizer flow data after calculation; The variable fertilization unit (5) includes an outer grooved wheel fertilizer dispenser (53), a servo motor (51), a reducer (52), an electric push rod (55), and a power supply. The fertilizer discharge shaft of the outer grooved wheel fertilizer dispenser (53) is connected to the servo motor (51) through the reducer (52), and the electric push rod (55) is connected to the gate (54) of the outer grooved wheel fertilizer dispenser (53). The fertilizer discharge shaft speed and fertilizer discharge opening command are both issued by the STM32 microcontroller and the command is implemented through the control software. The power supply module is used to provide working power to the modules in the variable fertilization unit (5) that need to be powered.

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