Embryo screening method and device based on millimeter wave radar

Abstract

The invention discloses an embryo screening method and device based on a millimeter-wave radar, and the method comprises the steps: transmitting a frequency-modulated continuous wave by the millimeter-wave radar to irradiate an embryo egg, receiving an echo signal, and mixing the echo signal with a transmitted signal to obtain an intermediate-frequency signal; the intermediate frequency signal is sent to a computer signal processing terminal through a signal acquisition device; preprocessing the radar signal, including performing circle fitting by using a correlation optimized least square method, eliminating direct current offset, and suppressing a static clutter component by using a phasor mean cancellation algorithm; constructing a distance-angle diagram, and positioning a plurality of embryo eggs by adopting a constant false alarm rate (CFAR); phase information of a target is extracted from the preprocessed signal, the heartbeat frequency of the embryo is obtained, and the embryo incubation state is judged in real time in combination with the embryo type and incubation duration. The internal heartbeat frequency of the embryo egg can be accurately detected in real time in a non-contact mode, the incubation state of the to-be-detected embryo is judged, the detection efficiency is effectively improved, and resource consumption is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of embryo hatching, and in particular to an embryo screening method and device based on millimeter wave radar. Background Art

[0002] With the rapid development of the global poultry farming industry, my country's poultry egg production ranks first in the world, and the screening of poultry egg hatching has become increasingly important. Before poultry eggs are placed on the hatching tray, embryos need to be identified and classified, dead embryos, infertile eggs and rotten eggs need to be removed, and live embryos are left to hatch, avoiding cross contamination, effectively reducing resource consumption, and improving hatching efficiency and output quality.

[0003] In the early days, hatcheries used manual candling to inspect poultry eggs. They used a light to illuminate the top of the egg and observed the internal development of the egg, such as the shape of the air chamber and blood vessels, and selected infertile eggs, dead eggs, and rotten eggs. This operation not only has very low work efficiency and no specific quantitative criteria, but also the selection accuracy will decrease as the working time increases. If dead embryo eggs, rotten eggs, etc. are mistaken for qualified eggs and continue to be incubated, not only the space of the incubator is wasted, but also other qualified eggs will be contaminated, greatly reducing the hatching efficiency.

[0004] At present, the main detection methods for poultry egg embryo culture technology research at home and abroad are: ACG (acoustocardiogram), BCG (ballistocardiogram), ECG (electrocardiogram) and ICG (impedance-cardiogram). Among them, the ECG and ICG methods are to punch holes in the eggshell and then insert electrodes to measure the characteristic signals of live poultry egg embryos. Since the electrodes are inserted deep into the embryo, this method will damage the physiological structure of the embryo. After the test is completed, the tested poultry egg embryo will stop developing. It is an invasive measurement method and cannot meet the production needs of the hatching industry. The ACG and BCG methods are non-invasive measurement methods. The ACG method measures the sound signals emitted by live poultry egg embryos during the incubation period by placing the poultry eggs in a closed container for direct measurement; while the BCG method measures the fetal movement signals of live embryos during the incubation period by sticking magnets on the eggshells and converting the tiny movements of the magnets into induced currents through fixed electromagnetic coils to achieve measurement. The signals they extract are very weak and have very strict requirements on the test environment.

[0005] The scale of the current hatchery industry is constantly expanding, and the existing egg screening methods will be difficult to meet the scale requirements. Therefore, it is urgent to develop an automated embryo detection device to replace the manual egg screening operation to meet the needs of large-scale poultry hatcheries and improve the accuracy and efficiency of embryo egg screening. Summary of the invention

[0006] The present application discloses a millimeter wave radar-based embryo screening method and device, which realizes real-time and rapid detection of embryo development status at any position in the early stage of egg incubation, timely screening out embryo eggs such as infertile eggs and dead embryo eggs, thereby improving detection efficiency and reducing resource consumption.

[0007] The technical solution of the present invention is as follows:

[0008] In a first aspect, an embryo egg screening and detection device is provided, comprising an embryo incubation device, a millimeter wave radar motion detection device, a multi-point signal acquisition device and a computer signal processing terminal.

[0009] The embryo incubation device is composed of an incubation box and an egg fixing container, which is used to accommodate multiple embryo eggs and provide a suitable incubation environment;

[0010] The millimeter wave radar motion detection device is composed of a millimeter wave radar sensor, a mechanical arm bracket and a sliding guide rail. The millimeter wave radar sensor is used to send an adjustable frequency continuous wave FMCW to the inside of the embryo egg, receive an echo signal and mix it with the transmitted signal; the mechanical arm bracket is used to adjust the millimeter wave radar sensor so that it is facing the center of the embryo egg incubation device; the sliding guide rail is used to make the millimeter wave radar move along the sliding guide rail, thereby realizing the detection and screening of the embryo eggs inside all embryo incubation devices on the moving path.

[0011] The multi-point signal acquisition device is used to receive data sent by the radar and send it to the computer signal processing terminal;

[0012] The computer signal processing terminal is used to receive radar data, perform signal processing, separate embryo vital sign information and interference signals in the data, and amplify and extract the heartbeat signal of the internal embryo.

[0013] In a second aspect, a detection method for embryo screening is provided, comprising the following steps:

[0014] Control the millimeter wave radar sensor to send frequency-adjustable continuous wave FMCW into the embryo egg, receive the echo signal and mix it with the transmitted signal to obtain an intermediate frequency signal;

[0015] The mixed intermediate frequency signal data is sent to a computer signal processing terminal for signal processing through a signal acquisition device;

[0016] Preprocessing the radar signal includes: performing distance-FFT and angle-FFT on each chirp of the radar signal to convert the time domain data into frequency domain data; using the least square method optimized by correlation to perform circle fitting on the radar data to eliminate the DC offset; using the phasor mean cancellation algorithm to suppress the static clutter component in the radar data; constructing a distance-angle diagram to perform two-dimensional positioning of multiple embryos in the detection area, and using the constant false alarm rate CFAR algorithm to determine the number and position of embryo eggs in the detection area;

[0017] Extracting phase information from the preprocessed frequency domain signal includes: extracting the phase information at the maximum position after the distance-FFT through the phase inverse tangent, and unwrapping the phase to ensure the continuity of the phase change; calculating the phase difference of the extracted phase to enhance the heartbeat signal of the embryo.

[0018] Furthermore, an 8th-order IIR bandpass filter is used to extract the embryonic heartbeat signal, a time-domain peak-finding algorithm is used to find the peak of the heartbeat signal, and the frequency of the peak is calculated to obtain the embryonic heartbeat frequency.

[0019] Furthermore, by collecting and calculating the number of heartbeats per minute of the embryo, the survival status of the embryo being tested is determined according to the incubation time of the embryo egg being tested and the type of the embryo being tested.

[0020] The present invention provides a non-contact detection for embryo screening based on millimeter wave radar, which can effectively detect the heartbeat information inside the embryo egg, so as to detect whether the embryo is alive, solve the problem of interference and potential damage to the embryo caused by traditional manual detection methods, reduce costs and improve detection efficiency, meet the needs of existing large-scale hatcheries, and have great practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The working principle of the embryo screening method based on millimeter wave radar in an embodiment of the present invention;

[0022] Figure 2 A flowchart of preprocessing the radar data in an embodiment of the present invention;

[0023] Figure 3 The figure is a flow chart of least squares circle fitting for correlation optimization in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The following embodiments of the technical solution of the present invention are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and are therefore only used as examples, and cannot be used to limit the protection scope of the present invention.

[0025] In order to solve the problems that existing embryo egg detection equipment requires non-contact detection, and that embryo egg detection in hatcheries has low accuracy and detection efficiency, the present application provides an embryo egg screening method and device based on millimeter wave radar, which realizes real-time and rapid detection of the development status of embryo eggs in any position in the early stage of incubation, and timely screening out embryo eggs such as unsperm eggs and dead embryo eggs, thereby improving hatching efficiency and reducing resource consumption.

[0026] The present application discloses an embryo egg screening and detection device, comprising an embryo incubation device, a millimeter wave radar motion detection device, a multi-point signal acquisition device and a computer signal processing terminal, wherein the embryo incubation device is composed of an incubation box and an embryo egg fixing container; the millimeter wave radar motion detection device is composed of a millimeter wave radar sensor, a mechanical arm bracket and a sliding guide rail, wherein the mechanical arm bracket is used to adjust the millimeter wave radar sensor so that it faces the center of the embryo incubation device; the sliding guide rail is used to move the millimeter wave radar along the sliding guide rail, thereby realizing the detection and screening of embryo eggs inside all embryo incubation devices on the moving path; the multi-point signal acquisition device is used to receive data sent by the radar and send it to the computer signal processing terminal; the computer signal processing terminal is used to receive radar data, perform signal processing,

[0027] The working principle of the embryo screening method based on millimeter wave radar provided by the present invention is as follows: Figure 1 As shown:

[0028] The embryo eggs to be screened are placed in the embryo incubation device; after the embryo eggs are placed, the millimeter wave radar sensor moves along the sliding guide rail. When the millimeter wave radar sensor detects that the number of embryo eggs entering the detection area reaches a threshold, the millimeter wave radar sensor stops moving and detects each embryo egg in the detection area. When the detection is completed, the millimeter wave radar sensor continues to move and detects the embryo eggs in the next detection area.

[0029] Furthermore, the millimeter wave radar sensor is configured in a one-transmit-four-receive mode, transmitting a frequency modulated continuous wave FMCW with a predetermined frequency of 30 GHz to 300 GHz and a frame number of 400 frames to irradiate the embryo eggs and receive the echo signal, and the echo signal and the transmission signal are mixed to obtain an intermediate frequency signal.

[0030] The electromagnetic wave irradiates the eggs through the frequency range and can penetrate the eggshells of different types of eggs, thereby detecting the status of embryonic development. The eggs include but are not limited to chicken eggs, duck eggs, goose eggs and bird eggs. The eggshell thickness of different poultry is different. The design of the millimeter wave radar motion detection device fully takes these differences into account. In order to adapt to these differences, the millimeter wave radar system is optimized in the frequency range of 30GHz to 100GHz, and the appropriate frequency band is selected to ensure that the electromagnetic wave can effectively penetrate various eggshells and provide sufficient resolution to detect embryonic development. The millimeter wave radar sensor uses a high frequency band to ensure that it can penetrate thicker eggshells (such as duck eggs and goose eggs) and provide a higher spatial resolution; for thinner eggshells (such as bird eggs), a lower frequency band can meet the penetration requirements. For chicken eggs, duck eggs, goose eggs and bird eggs, the frequency ranges are selected as 60GHz to 100GHz, 50GHz to 90GHz, 40GHz to 80GHz and 30GHz to 60GHz, respectively, to optimize the penetration and signal detection effect, and ensure that the embryonic development can be accurately monitored. The system is also set to a frame rate of 400 frames to ensure that data is fully collected during the detection process, thereby improving the detection accuracy of embryonic development.

[0031] The frequency modulated continuous pulses emitted by the millimeter wave radar sensor can be expressed as:

[0032]

[0033] Among them, A Tx is the amplitude of the transmitted signal, K slope is the sawtooth wave slope, f c is the center frequency of the radar transmitting signal, is the initial phase of the transmitted signal.

[0034] The expression of the echo signal received by the millimeter wave radar sensor is:

[0035]

[0036] Among them A Rx is the amplitude of the echo signal, τ is the delay of the radar echo signal;

[0037] The intermediate frequency signal is obtained by mixing the received echo signal and the transmitted signal and then low-pass filtering. The expression of the intermediate frequency signal is:

[0038] S IF (t) = S Tx (t)×S * Rx (t) = A Tx A Rx exp[j(πK slope tτ-πKslope τ 2 +2πf c τ)]

[0039] Its frequency f IF =2πK slope τ, phase

[0040] Furthermore, the intermediate frequency signal is sent through the signal acquisition device to the computer signal processing terminal for processing. The specific processing process is as follows:

[0041] 1. Preprocessing the radar data to remove DC offset and suppress noise interference of clutter on target echo;

[0042] 2. Perform distance-FFT and angle-FFT on the pre-processed signal, use CFAR constant false alarm rate to perform 2D target recognition, and determine the embryo egg target in the area;

[0043] 3. Extract the phase information of the embryo egg target in the area and calculate the phase difference between adjacent range bins

[0044] 4. Use sliding average filtering to remove impulse noise, and use an 8th-order IIR bandpass filter to extract the heartbeat component of the embryo to obtain the number of heartbeats of the embryo per minute;

[0045] The specific steps include:

[0046] Step 1 includes the following: using the least square method with correlation optimization to perform circular fitting on the radar data to remove the DC offset; using the phasor mean cancellation algorithm to remove the static clutter component in the radar data. The specific steps are as follows:

[0047] Extract the complex data of each range gate from the radar data, map the complex data points of each range gate to the complex plane, use the real part as the horizontal coordinate and the imaginary part as the vertical coordinate to obtain a set of discrete complex plane points. In order to remove the DC component, perform the least squares fitting on these points and establish a circle fitting model. The position (x, y) of the center of the circle and the radius of the circle are solved by least squares fitting. The coordinates of the center of the circle represent the average DC offset of the complex signal. The formula for least squares circle fitting is as follows:

[0048]

[0049] Where k1 and k2 are the coordinates of the center of the circle (x, y), k3 is the radius of the circle, and n is the total number of data points in the current range gate. i ,y i), the goal is to minimize the error function: minimize the distance difference between all data points and the fitted circle, that is, the radius and center of the fitted circle can best represent the data points. By minimizing this error function, the optimal estimate of the center and radius can be obtained.

[0050] On the basis of least squares circle fitting for each range gate, the Pearson correlation coefficient is further used to calculate the correlation of the complex data of adjacent range gates. The calculation formula of the Pearson correlation coefficient is as follows:

[0051]

[0052] Where r is the Pearson correlation coefficient, a i and b i are the complex data points of adjacent range gates, and is the sample mean of the two. If the Pearson correlation coefficient between adjacent range gates is high, the fitting centers of the two range gates are replaced by the mean of the least square fitting centers of the two adjacent range gates. This method can effectively reduce the redundant calculation errors caused by the high consistency between adjacent range gates and improve the smoothness and overall consistency of the fitting results.

[0053] The coordinates of the center of the circle obtained by fitting are used as the offset value, which is subtracted from the original complex data to move the center of the circle to the origin (0,0) on the complex plane, effectively removing the DC component in the radar echo signal and introducing the correlation calculation of adjacent range gates, thereby improving the accuracy of target detection and parameter estimation and enhancing the radar system's ability to detect targets.

[0054] The distance from the stationary target to the radar antenna is constant, and the time delay of the stationary target on each beam of received pulses is also constant. By averaging all received pulses, a reference received pulse can be obtained. Then, by subtracting the reference received pulse from each beam of received pulse, the result of phasor mean cancellation can be obtained, thereby suppressing the interference of static clutter components.

[0055] Step 2 comprises the following contents: performing distance-FFT and angle-FFT on the sampling point data on each chirp of the preprocessed radar data to obtain a distance-angle matrix, and preliminarily estimating the orientations of multiple embryo egg targets.

[0056] The 2D-CFAR algorithm is used to realize multi-target detection of embryo eggs. A sliding window is defined to evaluate its local background noise characteristics, including detection unit, protection unit and reference unit. The signal strength of the reference unit is statistically analyzed to estimate the background noise characteristics of the area where the current detection unit is located. Combined with the preset false alarm probability threshold, the dynamic detection threshold is calculated by the formula: T = α·μ, where α is a proportional factor determined according to the false alarm probability (PFA), and μ is the background noise statistic of the reference unit. If the signal strength of the detection unit is greater than the threshold T, the detection unit is determined to be a target point.

[0057] Step 3 includes the following: extracting the phase information of the embryo egg target in the region by using the phase inverse tangent; due to the inverse tangent operation, the phase is generally limited to between -π and π. When some values ​​in the actual phase exceed this interval, phase wrapping will occur, so it is necessary to perform phase unwrapping calculation on the extracted phase. Whenever the phase difference between consecutive values ​​is greater than or less than ±π, the unwrapped phase is obtained by subtracting 2π from the phase.

[0058] A phase difference operation is performed on the phase after unwrapping, and a phase difference operation is performed on the phase after unwrapping by subtracting continuous phase values. The specific formula is: D(i)=φ(i)-φ(i-1), wherein φ(i) is the phase value of the current point, φ(i-1) is the phase value of the previous point, and D(i) is the phase difference value; this is achieved by continuously subtracting the unwrapping phase of the current sampling point from the previous sampling point; this will help to enhance the heartbeat signal and eliminate the phase drift existing in the hardware receiver, eliminate the interference of clutter on the embryo's life signal, and obtain a signal of the embryo's vital signs containing the heartbeat.

[0059] Step 4 includes the following contents: adopting sliding average filtering, selecting a window size of 5, and filtering out high-frequency noise in the phase difference signal.

[0060] An IIR bandpass filter is used on the phase difference signal after sliding average filtering to filter out other signals and extract the heartbeat-related frequency components from the phase signal; due to differences in the incubation process of different poultry eggs, the time when the embryonic heartbeat frequency and intensity reach their peak values ​​on different days is also different. Therefore, for different types of eggs, the stopband and passband cutoff frequencies of the bandpass filter need to be adjusted according to their respective incubation characteristics in order to accurately extract the embryonic heartbeat signal. For example, the heartbeat frequency and intensity of chicken eggs, duck eggs, and goose eggs reach their peak values ​​at different times. Adaptively selecting different filter frequency ranges can help to more accurately monitor and analyze embryonic development.

[0061] Perform FFT on the bandpass filtered signal, traverse the positive frequency part of the spectrum, find the frequency component with the largest amplitude, and set a threshold. If the amplitude is greater than the threshold, it is considered that there is a valid heartbeat signal in the current frequency component, and the heartbeats per minute of the embryo are calculated, recorded as BPM1. Use the time domain peak detection algorithm to detect the peak of the embryo heartbeat signal and calculate its heartbeats per minute, recorded as BPM2. Perform mean processing on BPM1 and BPM2, and finally obtain the accurate heartbeats per minute of the embryo.

[0062] The survival status of the detected embryo is determined based on the precise number of heartbeats per minute of the embryo, the hatching time of the detected embryo, and the type of the detected embryo for subsequent screening.

[0063] At present, the egg embryo detection technology generally adopts manual detection, which has very low work efficiency and no specific quantitative criteria, and the selection accuracy will also decrease with the increase of working time; the detection method for the egg embryo culture technology research in China is currently mainly an invasive measurement method, which has strict requirements for the test environment. In view of the above problems, the present invention proposes a new solution, which includes an embryo incubation device, a millimeter wave radar motion detection device, a multi-point signal acquisition device and a computer signal processing terminal. The present invention can realize non-contact detection of the incubation status of various egg embryos, can effectively improve the accuracy and efficiency of detection, solve the interference and potential damage problems of traditional manual detection methods to embryo eggs, and reduce costs, meet the needs of existing large-scale hatcheries, and have great practical value.

[0064] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention is described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for embryo screening based on millimeter wave radar, characterized in that: The following steps are involved: S1: Control the millimeter wave radar sensor to send frequency modulated continuous wave FMCW to the inside of the embryo egg, receive the echo signal and mix it with the transmitted signal to obtain an intermediate frequency signal; S2: The mixed intermediate frequency signal data is sent to the signal processing terminal through the signal acquisition device for signal processing; S3: preprocessing the collected radar data; S4: extracting target phase information from the signal preprocessed in S3; S5: for the heartbeat component after the bandpass filtering in S4, a time domain peak finding algorithm is used to find the peak of the embryonic heartbeat signal, and the frequency of the peak is calculated to obtain the embryonic heartbeat frequency; S6: According to the embryo heartbeat frequency described in S5, combined with the hatching time of the embryo and the type of the embryo, the survival status of the embryo is determined.

2. The embryo screening method based on millimeter wave radar according to claim 1, characterized in that: In the step S3, preprocessing the radar data includes the following steps: S31: Perform distance-FFT and angle-FFT on each chirp of the radar signal to convert the time domain data into frequency domain data; S32: Using the least square method, performing circle fitting on the radar data to eliminate the DC offset; S33: using a phasor mean cancellation algorithm to suppress static clutter components in radar data; S34: construct a distance-angle diagram, perform two-dimensional positioning of multiple embryo eggs in the detection area, and use a constant false alarm rate CFAR algorithm to determine the number and position of embryo eggs in the detection area.

3. The embryo screening method based on millimeter wave radar according to claim 2, characterized in that: The step of using the least square method to perform circle fitting on radar data includes: S321: extracting the complex data of each range gate from the radar data, mapping the complex data points of each range gate onto the complex plane, using the real part as the abscissa and the imaginary part as the ordinate, to obtain a set of discrete complex plane points; S323: performing least squares fitting on the complex data points of each range gate to establish a circle fitting model; solving the position (x, y) of the center of the circle and the radius of the circle by least squares fitting; S323: on the basis of performing least squares circle fitting on each range gate, further performing correlation calculation on complex data of adjacent range gates using Pearson correlation coefficient; S324: If the Pearson correlation coefficient between adjacent range gates is high, the fitting centers of the two range gates are replaced by the mean of the least square fitting centers of the two adjacent range gates; S325: The center coordinates obtained by fitting are used as offset values, and the offset is subtracted from the original complex data to remove the DC component in the radar echo signal.

4. The embryo screening method based on millimeter wave radar according to claim 3, characterized in that: The formula for least squares circle fitting is as follows: Where k1 and k2 are the coordinates of the center of the circle (x, y), k3 is the radius of the circle, and n is the total number of data points in the current range gate. i ,y i ), the goal is to minimize the error function: minimize the distance difference from all data points to the fitted circle, that is, the radius and center of the fitted circle can best represent the data points; by minimizing the error function, the optimal estimate of the center and radius can be obtained.

5. The embryo screening method based on millimeter wave radar according to claim 4, characterized in that: The Pearson correlation coefficient calculation formula is as follows: Where r is the Pearson correlation coefficient, a i and b i are the complex data points of adjacent range gates, and is the sample mean of the two. If the Pearson correlation coefficient between adjacent range gates is high, the fitting centers of the two range gates are replaced by the mean of the least squares fitting centers of the two adjacent range gates.

6. An embryo screening device based on millimeter wave radar, characterized in that: The method for implementing any one of claims 1 to 5 comprises: an embryo incubation device, a millimeter wave radar motion detection device, a multi-point signal acquisition device and a signal processing terminal; the millimeter wave radar motion detection device is composed of a millimeter wave radar sensor, a mechanical arm bracket and a sliding guide rail, the mechanical arm bracket is used to adjust the millimeter wave radar sensor so that it faces the center of the embryo incubation device; the sliding guide rail is used to move the millimeter wave radar along the sliding guide rail, thereby realizing the detection and screening of embryo eggs inside all embryo incubation devices on the moving path.

7. The embryo screening device based on millimeter wave radar according to claim 6, characterized in that: The embryo screening device selects the corresponding electromagnetic wave frequency range to optimize the penetration ability and signal quality according to the eggshell thickness of different types of poultry eggs and the characteristics of the incubation process.

8. The embryo screening device based on millimeter wave radar according to claim 7, characterized in that: For chicken eggs, duck eggs, goose eggs and bird eggs, the frequency ranges are selected as 60 GHz to 100 GHz, 50 GHz to 90 GHz, 40 GHz to 80 GHz and 30 GHz to 60 GHz, respectively.

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