A machine-harvested seed cotton yield monitoring test platform and monitoring method based on microwave Doppler method

Abstract

The present application relates to the field of intelligent cotton picking machine yield monitoring, particularly to a machine-picked seed cotton yield monitoring test platform and method based on microwave Doppler method, comprising: building a machine-picked cotton microwave yield monitoring test platform; designing a microwave sensor to collect the microwave Doppler signal of seed cotton in the cotton conveying pipe; establishing a microwave loss relationship model to compensate the microwave loss caused by the moisture in the seed cotton; realizing the time-frequency conversion of the compensated microwave signal through a time-domain frequency-domain conversion algorithm; using a spectrum analysis method to estimate the power spectral density of the obtained frequency spectrum, establishing a seed cotton mass flow and power spectral density model based on a linear fitting method, and obtaining the seed cotton yield. Compared with the current machine-picked seed cotton yield monitoring method based on photoelectric sensors, the present application has the advantages of higher detection accuracy, more stable working performance, stronger anti-interference ability, and is suitable for long-term stable work in harsh environments, etc., and has good market application prospect.

Description

Technical Field

[0001] This invention relates to the field of intelligent cotton harvester yield monitoring, and in particular to an experimental platform and monitoring method for monitoring the yield of machine-harvested seed cotton based on microwave Doppler ultrasound. Background Technology

[0002] Developing online monitoring technology for machine-harvested seed cotton yield with independent intellectual property rights is fundamental to ensuring the information security of major national strategic materials, and is also key to realizing intelligent operation parameter control of domestically produced cotton harvesters. Currently, yield monitoring of domestic cotton harvesters mainly relies on photoelectric sensors. Although this method is simple to process signals, it is easily affected by ambient temperature and humidity, especially when working in fields with high humidity such as rainy days, where its measurement accuracy is too low to meet the requirements. As a non-contact method, the microwave method avoids physical contact with the cotton seed surface, thus preventing damage and contamination. Secondly, the microwave method is adaptable to different types of cotton seeds, and because microwave radiation has minimal impact on environmental factors, the measurement results are relatively stable and reliable. However, time-domain analysis of the Doppler signal obtained by the microwave method reveals severe signal aliasing, making it difficult to extract useful information. In contrast, frequency-domain analysis of the Doppler signal reveals clear frequency characteristics, allowing for rapid identification of important information such as Doppler frequency and power spectral density, thus reducing the difficulty of signal analysis. Currently, John Deere cotton harvesters in the United States have mature microwave yield measurement capabilities and have implemented them in practice. However, domestic cotton harvesters do not yet possess this function, making it difficult to meet the requirements of intelligent operation. To improve the yield measurement accuracy of domestic cotton harvesters, this invention utilizes microwave Doppler technology instead of the traditional photoelectric measurement method, enhancing detection accuracy and anti-interference capabilities. This method is more suitable for complex field environments and has a promising market prospect. Furthermore, the use of frequency domain analysis processing to acquire the Doppler signal reduces the difficulty of signal processing. Summary of the Invention

[0003] The purpose of this invention is to provide a test platform for monitoring the yield of machine-harvested seed cotton based on microwave Doppler method. This platform has a simple structure and is economical and practical. The second purpose is to provide a method for monitoring the yield of machine-harvested seed cotton based on microwave Doppler method. This method improves the detection accuracy and anti-interference ability of yield monitoring, is more suitable for complex field environments, and has good market prospects.

[0004] The above-mentioned technical problem of the present invention is solved by the following solution.

[0005] This invention relates to a test platform for monitoring the yield of machine-harvested seed cotton based on microwave Doppler. The test platform mainly includes a cotton conveying pipe (3), a cotton collection box (7), a data acquisition instrument (8), a computer (9), a DC power supply (10), and a microwave Doppler sensor (1). The microwave Doppler sensor (1) is connected to the data acquisition instrument (8) and the computer (9) via a line. The DC power supply (10) supplies power to the microwave Doppler sensor (1). The cotton conveying pipe (3) is connected to the cotton collection box (7). The microwave Doppler sensor (1) is located outside the cotton conveying pipe (3). Based on this test platform, the yield of machine-harvested seed cotton is calculated using a method for monitoring the yield of machine-harvested seed cotton based on microwave Doppler.

[0006] The microwave Doppler sensor consists of a planar array antenna microwave module and a signal conditioning circuit. The signal conditioning circuit consists of a filter circuit and an amplifier circuit. The filter circuit consists of two operational amplifiers and resistors and capacitors, and the amplifier circuit consists of one operational amplifier and resistors and capacitors.

[0007] The method for monitoring the yield of machine-harvested seed cotton based on microwave Doppler mainly includes the following steps: (1) Signal acquisition: Design a microwave Doppler sensor (1) to acquire microwave Doppler signals of seed cotton in the cotton conveying pipe (3); (2) Constructing a microwave loss model: Measure the moisture content of the experimental cotton seeds, derive the attenuation coefficient equation, obtain the relationship model between different moisture contents and microwave amplitude loss, substitute the moisture content of the experimental cotton seeds into the microwave loss model, obtain the microwave amplitude loss value, and compensate for the collected signal; (3) Signal time-frequency domain conversion: The time-frequency domain conversion algorithm is used to convert the compensated microwave signal from the time domain to the frequency domain to obtain the spectrum of the microwave signal; (4) Construct a mass flow rate model for machine-harvested cotton: The power spectral density of the above spectrum is estimated by using the spectral analysis method. The relationship model between the mass flow rate of machine-harvested cotton and the power spectral density is established by using the linear fitting method to obtain the seed cotton yield. (5) Error correction: The experiment was conducted on the microwave yield test bench for machine-harvested cotton to obtain the seed cotton mass flow rate model. The actual mass of the collected seed cotton was compared with the mass calculated by the model to perform error analysis.

[0008] The microwave Doppler sensor (1) consists of a planar array antenna microwave module with a transmission frequency range of 5GHz to 27GHz and a signal conditioning circuit. It outputs the Doppler signal in the form of a voltage. The microwave module is used to transmit and receive microwaves and convert the Doppler signal into a voltage signal. The signal conditioning circuit filters and amplifies the converted voltage signal to facilitate signal acquisition and analysis.

[0009] The specific process for establishing the microwave loss model is as follows: Since the substance flowing in the cotton conveying pipe is a complex of seed cotton, water and air, the attenuation coefficient equation is obtained as equation (2) based on the composite permeability relationship in equation (1) and the electromagnetic wave propagation equation. In the formula, V h V m V s These are the volumetric volumes of the mixture, seed cotton, and water, respectively. The relative composite permeabilities of the mixture, seed cotton, and water are given, respectively. The dielectric constant ε of water is given in the microwave frequency band. s ≈37; α is the attenuation coefficient, β is the phase shift coefficient, ω is the microwave transmission angular frequency, θ is the water loss angle, tanθ=0.0125 in the text, and the vacuum permittivity ε=8.85×10 -12 F / m, vacuum permeability μ=4π×10 -7 H / m; Then the average seed cotton moisture content is measured using equation (3): In the formula, n is the number of test groups for seed cotton, and m i,wet m is the weight of the i-th seed cotton before drying. i,dry The weight of the i-th dried seed cotton; Finally, by using equations (2) and (3) to obtain the seed cotton moisture content and performing linear regression fitting, the seed cotton moisture content and microwave loss model can be obtained as equation (4).

[0010] The time-frequency conversion algorithm mentioned is DIT-FFT, and the specific algorithm is as follows: (1) Convert the microwave signal obtained by the microwave Doppler sensor (1) into a discrete digital quantity x(n), and perform a discrete Fourier transform (DFT) on it: In the formula, x(n) is a discrete digital sequence, X(k) is the Fourier transform value of x(n), and N is the number of DFT transform points. In this paper, N = 1024. Let w(n) be the rotation factor and w(n) be the window function. This paper selects the Hanning window. (2) Divide the sequence x(n) into two groups, odd and even, according to n: (3) Utilizing the reducibility of the rotation factor, perform a piecewise DFT on x(n) to obtain the DFT of the first N / 2 points: (4) Calculate the last N / 2 points of the DFT of X(k) using periodicity: The result of a single time-domain decimation of an N-point DFT is: (5) Performing a quadratic decomposition on X1(k) and X2(k) yields: Continue decomposing according to equation (15) until a single-point DFT is performed on x(n).

[0011] The spectrum analysis algorithm mentioned is the modified average periodogram method, and the specific algorithm is as follows: (1) Divide x(n) into segments with an overlap ratio α, and each segment has a length of M. Then the number of segments K is: In the formula, INT[] represents the rounding operation, and α is the overlap rate between each data segment and its adjacent data, which is generally taken as 0 < α < 1. This paper selects... (2) For the i-th data x i Adding the Hanning window w(n) to (n) gives: x i (n)=x[n+(i-1)M]w(n+(i-1)M) (12) (3) Calculate the i-th data segment x i Power spectral density of (n): In the formula, For normalization operators; (4) The power spectral density estimate P(k) is obtained by summing the power spectra of each segment and taking their average. The mass flow rate and corresponding power spectral density of seed cotton were obtained using a machine-harvested seed cotton yield monitoring test platform. The mass flow rate and corresponding power spectral density were then fitted using the least squares method to obtain a mass flow rate model for machine-harvested cotton.

[0012] The specific process for obtaining seed cotton mass flow rate and corresponding power spectral density by means of the machine-harvested seed cotton yield monitoring test platform is as follows: When the seed cotton moves through the microwave Doppler sensor (1) in the cotton conveying pipe (3), the microwave Doppler sensor (1) outputs a Doppler signal, which is collected and converted by the data acquisition instrument (8). The digital signal after digital-to-analog conversion is sent to the computer (9) for spectrum analysis, a seed cotton mass flow rate model is established, the seed cotton monitoring mass is calculated, and finally the actual seed cotton mass falling into the cotton collection box (7) and the monitored seed cotton mass mass are compared with the error analysis.

[0013] This invention emits microwaves through a microwave sensor transmitter. The microwave sensor forms a measurement field with the cotton seed pipe. When cotton seeds pass through, the emitted wave is absorbed and reflected by the cotton, causing the microwave signal to attenuate. This results in the received microwave frequency being lower than the emitted frequency, creating a signal frequency difference, i.e., the Doppler frequency. The power spectral density of the echo signal is estimated using the Doppler frequency, establishing a model of cotton seed mass flow rate and power spectral density to obtain the cotton seed flow rate. This invention not only features a simple and economical experimental setup, facilitating the verification of cotton seed monitoring methods, but also provides a highly accurate and interference-resistant monitoring method, making it more suitable for complex field environments. Bench tests have verified that the relative error between the monitored yield value and the actual yield value is 6.98%, indicating good market prospects. Attached Figure Description

[0014] Figure 1 This is a diagram showing the installation location of the microwave sensor of the present invention.

[0015] Figure 2 This is a flowchart of the production testing process of the present invention.

[0016] Figure 3 This is the microwave sensor signal conditioning circuit of the present invention.

[0017] Figure 4 This invention relates to a planar array antenna microwave module.

[0018] Figure 5 This invention relates to a microwave yield testing platform for machine-harvested cotton.

[0019] Figure 6 The diagram shows the seed cotton mass flow rate monitoring scheme of the present invention.

[0020] Figure 7 This invention provides a pneumatic conveying test model for seed cotton mass flow rate.

[0021] The numbers in the diagram are as follows: 1 is the microwave Doppler sensor, 2 is the angle between the target's direction of motion and the axis of the Doppler chip's main beam, 3 is the cotton conveyor, 4 is the test cotton, 5 is the speed of the test cotton, 6 is the direction of the test cotton, 7 is the cotton collection box, 8 is the data acquisition instrument, 9 is the computer, and 10 is the DC power supply. Detailed Implementation

[0022] To provide a better understanding of the technical means, structural features, objectives, and effects of this invention, a detailed description is provided below in conjunction with specific embodiments and accompanying drawings: like Figures 1-6As shown, in a specific embodiment of the present invention, a microwave yield measurement test platform for machine-harvested cotton is used to monitor the yield of seed cotton. The test platform for monitoring the yield of machine-harvested seed cotton based on microwave Doppler mainly includes a cotton conveying pipe (3), a cotton collection box (7), a data acquisition instrument (8), a computer (9), a DC power supply (10), and a microwave Doppler sensor (1). The microwave Doppler sensor (1) is connected to the data acquisition instrument (8) and the computer (9) through a line. The DC power supply (10) supplies power to the microwave Doppler sensor (1). The cotton conveying pipe (3) is connected to the cotton collection box (7). The microwave Doppler sensor (1) is located outside the cotton conveying pipe (3).

[0023] The microwave Doppler sensor consists of a planar array antenna microwave module and a signal conditioning circuit. The signal conditioning circuit consists of a filter circuit and an amplifier circuit. The filter circuit consists of two operational amplifiers and resistors and capacitors, and the amplifier circuit consists of one operational amplifier and resistors and capacitors.

[0024] Based on this test platform, a method for monitoring machine-harvested seed cotton yield using microwave Doppler ultrasound was employed to calculate seed cotton yield. The main steps include: (1) Signal acquisition: A microwave Doppler sensor (1) was designed to acquire the microwave Doppler signal of the seed cotton in the cotton conveying pipe (3). The microwave transmission frequency is 24.125 GHz. (2) Constructing a microwave loss model: Measure the moisture content of the experimental cotton seeds, derive the attenuation coefficient equation, obtain the relationship model between different moisture contents and microwave amplitude loss, substitute the moisture content of the experimental cotton seeds into the microwave loss model, obtain the microwave amplitude loss value, and compensate for the collected signal; (3) Signal time-frequency domain conversion: The DIT-FFT algorithm is used to convert the compensated microwave signal from the time domain to the frequency domain to obtain the spectrum of the microwave signal; (4) Construct a mass flow rate model for machine-harvested cotton: The power spectral density of the above spectrum is estimated using the modified periodogram method, and a relationship model between the mass flow rate and power spectral density of machine-harvested cotton is established based on the least squares method; seed cotton yield is obtained; (5) Error correction: A microwave yield measurement test bench for machine-harvested cotton was built. The seed cotton mass flow rate model was obtained through the experiment. The actual mass of the collected seed cotton and the mass calculated by the model were compared to perform error analysis.

[0025] In the aforementioned method for monitoring the yield of machine-harvested seed cotton based on microwave Doppler, the microwave Doppler sensor (1) consists of a planar array antenna microwave module with a transmission frequency of 24.125 GHz and a signal conditioning circuit, which outputs the Doppler signal in the form of voltage. The microwave module is used to transmit and receive microwaves and convert the Doppler signal into a voltage signal. The signal conditioning circuit filters and amplifies the converted voltage signal to facilitate signal acquisition and analysis.

[0026] In the microwave Doppler-based method for monitoring the yield of machine-harvested seed cotton, the process of establishing the microwave loss model is as follows: Since the substance flowing in the cotton conveying pipe is a complex of seed cotton, water and air, the attenuation coefficient equation is obtained as equation (2) based on the composite permeability relationship in equation (1) and the electromagnetic wave propagation equation. In the formula, V h V m V s These are the volumetric volumes of the mixture, seed cotton, and water, respectively. The relative composite permeabilities of the mixture, seed cotton, and water are given, respectively. The dielectric constant ε of water is given in the microwave frequency band. s ≈37; α is the attenuation coefficient, β is the phase shift coefficient, ω is the microwave transmission angular frequency, θ is the water loss angle, tanθ=0.0125 in the text, and the vacuum permittivity ε=8.85×10 -12 F / m, vacuum permeability μ=4π×10 -7 H / m. Then, the moisture content of the experimental seed cotton was measured using a moisture meter, and the average seed cotton moisture content was calculated using formula (3). The moisture content of the experimental seed cotton is shown in Table 1. In the formula, n is the number of test groups for seed cotton, and m i,wet m is the weight of the i-th seed cotton before drying. i,dry The weight of the i-th dried seed cotton is given.

[0027] Table 1. Moisture content of seed cotton in the experiment 1 0.403 0.391 2.98 2 0.424 0.413 2.59 3 0.358 0.348 2.80 4 0.493 0.479 2.84 5 0.394 0.382 3.05 6 0.459 0.440 4.14 7 0.406 0.393 3.20 8 0.306 0.297 2.94 9 0.401 0.393 2.00 10 0.360 0.350 2.77

[0028] Table 1 shows that the average moisture content of the seed cotton used in the tabletop test was 2.93%. Combining Table 1 and Equation (2), the relationship between microwave amplitude attenuation and moisture content is shown in Table 2.

[0029] Table 2 Relationship between microwave amplitude attenuation and water content 24.125 5 0.961 24.125 8 1.537 24.125 10 1.922 24.125 12 2.306 24.125 15 2.883

[0030] Table 2 yields the fitting equation for microwave loss and moisture content, with a coefficient of determination R² of 1:

[0031] With an average moisture content of 2.93% for seed cotton, substituting this into equation (23) reveals that the microwave amplitude that needs to be compensated is 0.563 dB.

[0032] In the aforementioned method for monitoring the yield of machine-harvested seed cotton based on microwave Doppler, the power spectral density estimation method—the modified periodogram method—specifically refers to: (1) Divide x(n) into segments with an overlap ratio α, and each segment has a length of M. Then the number of segments K is: In the formula, INT[] represents the rounding operation, and α is the overlap rate between each data segment and its adjacent data, which is generally taken as 0 < α < 1. This paper selects... (2) For the i-th data x i Adding the Hanning window w(n) to (n) gives: x i (n)=x[n+(i-1)M]w(n+(i-1)M) (6) (3) Calculate the i-th data segment x i Power spectral density of (n) In the formula, This is the normalization operator. (4) The power spectral density estimate P(k) is obtained by summing the power spectra of each segment and taking their average.

[0033] The power spectral density of different mass flow rates is obtained by using the modified periodogram method, and then the mass flow rate and the corresponding power spectral density are fitted by the least squares method to obtain the mass flow rate model of machine-harvested cotton.

[0034] In the aforementioned method for monitoring the yield of machine-harvested seed cotton based on microwave Doppler, the specific process for obtaining the seed cotton mass flow rate and corresponding power spectral density using the machine-harvested seed cotton yield monitoring test platform is as follows: When the seed cotton moves through the microwave Doppler sensor (1) in the cotton conveying pipe (3), the microwave Doppler sensor (1) outputs a Doppler signal, which is collected and converted by the data acquisition instrument (8). The digital signal after digital-to-analog conversion is sent to the computer (9) for spectrum analysis, a seed cotton mass flow rate model is established, the seed cotton monitoring mass is calculated, and finally, the actual seed cotton mass falling into the cotton collection box (7) and the monitored seed cotton mass mass are compared for error analysis. Figure 5 Based on the test bench, an experiment was designed to acquire model data. The specific experiment was as follows: Five mass flow rates ranging from 30 to 70 g were set, and seed cotton was transported using a 1800W small fan at a wind speed of 15 m / s. Each group of experiments was repeated three times. The measured seed cotton power spectral density and corresponding mass flow rates are shown in Table 7.

[0035] Table 3 Power spectral density and corresponding mass flow rate data for pneumatic conveying tests

[0036] Linear fitting was performed on the data in Table 3 to obtain the relationship between seed cotton mass flow rate and power spectral density under pneumatic conveying, as shown in the figure below. Figure 7 As shown, the fitting equation is: y=(7.14101×10 -5 )x 3 -0.01801x 2 +1.66782x-0.05117 (9)

[0037] To verify the accuracy of the model, in Figure 5 The power spectral density of any mass of seed cotton was measured on the test bench. Substituting it into equation (9), the measured value, actual value and average error rate of the pneumatically conveyed seed cotton were obtained as shown in Table 4.

[0038] Table 4. Measured values, actual values, and error rate of pneumatic conveying test

[0039] As shown in Table 4, the average error rate of the seed cotton mass flow rate model is 6.98%, which is low and has a certain degree of accuracy.

[0040] This invention emits microwaves through a microwave sensor transmitter. The microwave sensor forms a measurement field with the cotton seed pipe. When cotton seed passes through, the emitted wave is absorbed and reflected by the cotton seed, and the microwave signal attenuates, causing the microwave frequency received by the sensor to be lower than the emitted frequency. This results in a signal frequency difference, i.e., the Doppler frequency. The power spectral density of the echo signal is estimated by estimating the Doppler frequency, and a model of cotton seed mass flow rate and power spectral density is established to obtain the cotton seed flow rate.

[0041] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A method for monitoring the yield of machine-harvested seed cotton based on microwave Doppler ultrasound, characterized in that, Includes the following steps: (1) Signal acquisition: The microwave Doppler signal generated by the moving seed cotton in the cotton conveying pipe (3) is acquired by using the microwave Doppler sensor (1) located outside the cotton conveying pipe (3); (2) Constructing and compensating for microwave loss: Measure the moisture content of the experimental cotton seeds, establish a relationship model between different moisture contents and microwave amplitude loss, input the collected cotton seed moisture content into the model to obtain the microwave amplitude loss value, and perform amplitude compensation on the signal collected in step (1). (3) Signal time-frequency domain conversion: The compensated time-domain microwave signal is converted into a frequency-domain signal through a time-frequency domain conversion algorithm to obtain the spectrum of the microwave signal; (4) Constructing a mass flow rate model for machine-harvested cotton: The power spectral density of the spectrum is estimated by using the spectral analysis method. The relationship model between the mass flow rate of machine-harvested cotton and the power spectral density is established by using the linear fitting method, thereby obtaining the seed cotton yield.

2. The method according to claim 1, characterized in that, The specific process of establishing the microwave loss model in step (2) includes: obtaining the attenuation coefficient equation based on the composite permeability relationship of the complex composed of seed cotton, moisture, and air in the cotton conveying pipe and the electromagnetic wave propagation equation; measuring the moisture content of different seed cotton samples and the corresponding microwave attenuation values; and obtaining a quantitative relationship model between seed cotton moisture content and microwave loss through linear regression fitting. The specific process of establishing the microwave loss model is as follows: Since the substance flowing in the cotton conveying pipe is a complex of seed cotton, water and air, the attenuation coefficient equation is obtained as equation (2) based on the composite permeability relationship in equation (1) and the electromagnetic wave propagation equation. In the formula, These are the volumetric volumes of the mixture, seed cotton, and water, respectively. The relative composite permeability of the mixture, seed cotton, and water, respectively, and the dielectric constant of water in the microwave band. ; The attenuation coefficient is... The phase shift coefficient, The microwave transmission angular frequency, For the water loss angle, in the text vacuum permittivity Vacuum permeability ; Then the average seed cotton moisture content is measured using equation (3): In the formula, To test the number of groups of seed cotton, The weight of the i-th seed cotton before drying. The weight of the i-th dried seed cotton; Finally, by using equations (2) and (3) to obtain the seed cotton moisture content and performing linear regression fitting, the seed cotton moisture content and microwave loss model can be obtained as equation (4).

3. The method according to claim 1, characterized in that, The time-frequency domain conversion algorithm in step (3) is the time-decimation fast Fourier transform (DIT-FFT) algorithm; the spectrum analysis algorithm in step (4) is the modified average periodogram method.

4. A microwave Doppler-based experimental platform for monitoring the yield of machine-harvested seed cotton, used to implement the method according to any one of claims 1 to 3, characterized in that: It mainly includes a cotton conveying pipe (3), a cotton collection box (7), a data acquisition instrument (8), a computer (9), a DC power supply (10), and a microwave Doppler sensor (1); the microwave Doppler sensor (1) is connected to the data acquisition instrument (8) and the computer (9) through a line, the DC power supply (10) supplies power to the microwave Doppler sensor (1), and the cotton conveying pipe (3) is connected to the cotton collection box (7); the microwave Doppler sensor (1) is located outside the cotton conveying pipe (3); the computer (9) is equipped with instructions for executing steps (2) to (4) of claim 1.

5. The test platform according to claim 4, characterized in that, The microwave Doppler sensor (1) consists of a planar array antenna microwave module with a transmission frequency range of 5GHz to 27GHz and a signal conditioning circuit. The signal conditioning circuit consists of a filter circuit and an amplifier circuit. The filter circuit consists of two operational amplifiers and resistors and capacitors, and the amplifier circuit consists of one operational amplifier and resistors and capacitors.

6. The method according to claim 1, characterized in that, The microwave Doppler sensor (1) consists of a planar array antenna microwave module with a transmission frequency range of 5GHz to 27GHz and a signal conditioning circuit, which outputs the Doppler signal in the form of voltage.

7. The method according to claim 1, characterized in that, The specific process of obtaining the seed cotton mass flow rate and corresponding power spectral density by means of the machine-harvested seed cotton yield monitoring test platform in step (4) is as follows: when the seed cotton moves through the microwave Doppler sensor (1) in the cotton conveying pipe (3), the microwave Doppler sensor (1) outputs a Doppler signal, which is collected and converted by the data acquisition instrument (8). The digital signal after digital-to-analog conversion is sent to the computer (9) for spectrum analysis, a seed cotton mass flow rate model is established, the seed cotton monitoring quality is calculated, and finally the actual seed cotton quality falling into the cotton collection box (7) and the monitored seed cotton quality are compared with the error analysis.

8. The method according to claim 1, characterized in that, The time-frequency domain conversion algorithm in step (3) specifically includes: (1) Convert the microwave signal obtained by the microwave Doppler sensor (1) into discrete digital quantity. Perform a Discrete Fourier Transform (DFT) on it: In the formula, It is a discrete number sequence. for Fourier transform value, In this paper, N=1024, representing the number of DFT transform points. For rotation factor, For window functions, this paper selects the Hanning window. ; (2) Change the sequence according to Divided into two groups: odd and even. (3) Utilizing the reducibility of the twitch factor, for Perform a piecewise DFT to obtain the DFT of the first N / 2 points: (4) Using periodicity to find The last N / 2 point DFT: The result of a single time-domain decimation of an N-point DFT is: (5) and A second decomposition yields: Continue decomposing according to equation (15) to Continue until a single-point DFT is performed.

9. The method according to claim 1, characterized in that, The modified average period chart method in step (4) specifically includes: (1) With overlap rate If the segments are divided into segments, each of length M, then the number of segments K is: In the formula, This indicates the rounding operation. The overlap rate between each data segment and its adjacent data is typically taken as... This article selects ; (2) For the data at the i-th end Plus Hanning windows The following is: (3) Calculate the i-th segment of data Power spectral density: In the formula, For normalization operators; (4) The power spectral density estimate is obtained by summing the power spectra of each segment and taking their average. :

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