Vaccination concentration confirmation method and system for animal husbandry veterinary epidemic prevention

Abstract

The invention discloses a vaccination concentration confirmation method and system for animal husbandry veterinary epidemic prevention, and relates to the technical field of vaccination concentration confirmation. The vaccination concentration confirmation method for animal husbandry and veterinary epidemic prevention comprises the following steps: acquiring vaccine light detection image data and vaccine state detection data of a set animal husbandry and veterinary epidemic prevention vaccine; analyzing a spectral concentration response characteristic value based on a pre-trained spectral concentration sensing model; vaccine state detection data of set animal husbandry and veterinary epidemic prevention vaccines are analyzed and processed to obtain state concentration induction characteristic values, and the state concentration induction characteristic values and spectral concentration response characteristic values are comprehensively processed to obtain vaccine inoculation concentration mapping values. The set animal husbandry veterinary epidemic prevention vaccine is subjected to concentration confirmation treatment based on the vaccination concentration mapping value, so that the concentration result can be kept stable under the conditions of local abnormal interference, non-uniform dilution and the like, and the reliability of vaccine concentration judgment is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of vaccine concentration confirmation technology, specifically to a method and system for confirming vaccine concentration for animal husbandry and veterinary disease prevention. Background Technology

[0002] In the process of animal husbandry and veterinary disease prevention, vaccination is a key link in ensuring the effectiveness of herd immunity in animals. In the existing disease prevention system, vaccines usually need to be artificially diluted or prepared on-site before actual vaccination. The concentration level directly affects the immunization effect and safety. If the concentration is too low, the level of antibodies produced in the animal's body will be insufficient, which may lead to immunization failure. If the concentration is too high, it is easy to cause local tissue reactions or immune stress, which may seriously affect the animal's health. At present, disease prevention personnel mostly rely on manual experience or offline chemical detection methods to confirm the vaccine concentration. This method has problems such as long detection cycle, large environmental interference, and strong subjectivity of results, making it difficult to achieve standardized on-site confirmation.

[0003] The limitations of existing technologies include at least the following problems: existing technologies have difficulty identifying optical transmission and scattering characteristics caused by changes in vaccine liquid concentration, making it difficult to detect concentration anomalies in a timely manner and affecting the effectiveness and safety of vaccination; at the same time, existing technologies lack a dynamic response mechanism for vaccine liquid under different concentration conditions, making it difficult to identify the changes in spectral response and fluid state during dilution. For slight concentration differences caused by insufficient mixing uniformity or acoustic disturbances, existing methods also have difficulty performing multi-dimensional feature decomposition and comprehensive judgment, resulting in insufficient accuracy of detection results and failing to meet the needs of rapid and standardized confirmation of vaccine concentration in livestock disease prevention sites. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method and system for confirming vaccine concentration for animal husbandry and veterinary disease prevention, which solves the problem that existing technologies are unable to jointly determine the vaccine concentration, resulting in insufficient reliability.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for confirming the concentration of vaccines used in animal husbandry and veterinary disease prevention, comprising the following steps: acquiring vaccine optical detection image data and vaccine status detection data for setting animal husbandry and veterinary disease prevention vaccines; analyzing the spectral concentration response characteristic value of the set animal husbandry and veterinary disease prevention vaccines based on a pre-trained spectral concentration perception model and in combination with the vaccine optical detection image data; parsing and processing the vaccine status detection data to obtain the status concentration sensing characteristic value of the set animal husbandry and veterinary disease prevention vaccines; analyzing the vaccine inoculation concentration mapping value based on the spectral concentration response characteristic value and the status concentration sensing characteristic value of the set animal husbandry and veterinary disease prevention vaccines; and performing concentration confirmation processing on the set animal husbandry and veterinary disease prevention vaccines based on the vaccine inoculation concentration mapping value.

[0006] Furthermore, the vaccine optical detection image data specifically includes the visible light transmittance value, near-infrared scattering value, and corresponding two-dimensional coordinates of each pixel in the vaccine optical detection image.

[0007] Further, the specific steps for analyzing and setting the spectral concentration response characteristic values ​​of livestock and veterinary vaccines are as follows: input the vaccine light detection image data of the livestock and veterinary vaccines into the pre-trained spectral concentration perception model, analyze and set the spectral concentration display feature set of the livestock and veterinary vaccines, including spectral concentration difference perception feature values, spectral transmission gradient feature values, and scattering heterogeneity feature values; based on the spectral concentration display feature set of the livestock and veterinary vaccines, analyze and set the spectral concentration response characteristic values ​​of the livestock and veterinary vaccines.

[0008] Furthermore, the specific steps for analyzing and setting the spectral concentration display feature set of livestock and veterinary vaccines are as follows: In the input layer of the spectral concentration perception model, the vaccine light detection image data for setting livestock and veterinary vaccines is received and preprocessed; in the spectral decomposition layer of the spectral concentration perception model, the vaccine light detection image data for setting livestock and veterinary vaccines is subjected to spectral decomposition processing to extract the spectral perception feature vector of setting livestock and veterinary vaccines; in the perception output layer of the spectral concentration perception model, based on the spectral perception feature vector of setting livestock and veterinary vaccines, the spectral concentration display feature set of setting livestock and veterinary vaccines is output.

[0009] Furthermore, the vaccine status detection data includes vaccine conductivity value, vaccine transmission attenuation coefficient, vaccine microfluidic impedance value, acoustic surface micro-amplitude value, and electrostatic distribution gradient value.

[0010] Furthermore, the specific steps for obtaining the state concentration sensing characteristic values ​​of the set animal and veterinary disease prevention vaccine are as follows: Based on the vaccine state detection data of the set animal and veterinary disease prevention vaccine, analyze the state concentration mapping characteristic set of the set animal and veterinary disease prevention vaccine, including the concentration polarization response characteristic value and the acoustic flow concentration response characteristic value; Based on the state concentration mapping characteristic set of the set animal and veterinary disease prevention vaccine, analyze the state concentration sensing characteristic value of the set animal and veterinary disease prevention vaccine.

[0011] Furthermore, the specific steps for analyzing and setting the state concentration mapping feature set of livestock and veterinary vaccines are as follows: Based on the set vaccine conductivity value and electrostatic distribution gradient value of livestock and veterinary vaccines, analyze and set the concentration polarization response feature value of livestock and veterinary vaccines; based on the set vaccine transmission attenuation coefficient value, vaccine microfluidic impedance value, and acoustic surface micro-amplitude value of livestock and veterinary vaccines, analyze and set the acoustic flow concentration response feature value of livestock and veterinary vaccines.

[0012] Furthermore, the specific formula for calculating the mapping value of the vaccination concentration for livestock and veterinary disease prevention vaccines is as follows: ;in, , , The steps are as follows: setting the vaccination concentration mapping value, spectral concentration response characteristic value, and state concentration sensing characteristic value for livestock and veterinary disease prevention vaccines. , , The coefficients are, in order, the spectral concentration adjustment coefficient, the state concentration adjustment coefficient, and the synergistic adjustment coefficient stored in the database.

[0013] Furthermore, the specific steps for confirming the concentration of livestock and veterinary vaccines based on the vaccine concentration mapping value are as follows: compare the vaccine concentration mapping value of the livestock and veterinary vaccines with the preset vaccine concentration mapping range; and confirm the concentration of the livestock and veterinary vaccines based on the comparison results.

[0014] A vaccine concentration confirmation system for animal husbandry and veterinary disease prevention includes: a data acquisition module for acquiring vaccine optical detection image data and vaccine status detection data for setting animal husbandry and veterinary disease prevention vaccines; a spectral concentration detection module for analyzing the spectral concentration response characteristic values ​​of the set animal husbandry and veterinary disease prevention vaccines based on a pre-trained spectral concentration perception model and combined with the vaccine optical detection image data; a vaccine status concentration analysis module for parsing and processing the vaccine status detection data of the set animal husbandry and veterinary disease prevention vaccines to obtain the status concentration sensing characteristic values ​​of the set animal husbandry and veterinary disease prevention vaccines; a comprehensive concentration perception module for analyzing the vaccine inoculation concentration mapping value of the set animal husbandry and veterinary disease prevention vaccines based on the spectral concentration response characteristic values ​​and the status concentration sensing characteristic values; and a concentration confirmation feedback module for performing concentration confirmation processing on the set animal husbandry and veterinary disease prevention vaccines based on the vaccine inoculation concentration mapping value.

[0015] The present invention has the following beneficial effects:

[0016] (1) The method for confirming the concentration of vaccines for animal husbandry and veterinary disease prevention improves the accuracy of concentration confirmation by jointly analyzing the vaccine optical detection image data and the vaccine status detection data. The spectral concentration response characteristic value is used to capture the changes in optical transmission and scattering response of the vaccine liquid under different concentration states, and participates in the analysis of the vaccine concentration mapping value together with the state concentration sensing characteristic value. This enables the concentration assessment process to have multi-dimensional self-correction capabilities, so that the concentration results can remain stable under local abnormal interference, uneven dilution, etc., thereby significantly improving the reliability of vaccine concentration determination.

[0017] (2) The method for confirming the concentration of vaccines for animal husbandry and veterinary disease prevention introduces a pre-trained spectral concentration sensing model, constructs a dual-band spectral deconstruction layer using visible light transmittance and near-infrared scattering, and achieves high-resolution extraction of optical features through three types of indicators: spectral concentration difference sensing features, spectral transmission gradient features, and scattering heterogeneity features. The model can adaptively learn the nonlinear variation law of spectral distribution under different concentration conditions, thereby accurately reflecting the correspondence between liquid dilution and light scattering changes, and generating spectral concentration response feature values ​​to achieve dynamic identification of vaccine liquid concentration, thereby improving the accuracy of vaccine concentration determination.

[0018] (3) The vaccine concentration confirmation system for animal husbandry and veterinary disease prevention achieves intelligent processing of the entire chain of vaccine concentration detection through hierarchical collaboration between modules. The system can simultaneously collect vaccine optical detection image data and vaccine status detection data. The spectral concentration detection module performs feature deconstruction and concentration response analysis, while the vaccine status concentration analysis module extracts the status concentration sensing feature value. The comprehensive concentration sensing module fuses and maps the multi-source features to generate a vaccine concentration mapping value. The concentration confirmation feedback module automatically outputs the concentration level and processing suggestions based on the comparison results of the mapping value, realizing an automatic closed loop of concentration detection, judgment and feedback, thereby achieving rapid confirmation of vaccine concentration and helping to improve the safety of disease prevention operations.

[0019] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0020] Figure 1 This is a flowchart of a method for confirming the concentration of vaccines used in animal husbandry and veterinary disease prevention according to the present invention.

[0021] Figure 2 This is a flowchart illustrating the specific steps involved in analyzing and setting the spectral concentration response characteristic values ​​of livestock and veterinary vaccines in a method for confirming vaccine concentration for livestock and veterinary disease prevention according to the present invention.

[0022] Figure 3 This is a block diagram of a vaccine concentration confirmation system for animal husbandry and veterinary disease prevention according to the present invention. Detailed Implementation

[0023] Please see Figure 1 This invention provides a technical solution: a method for confirming the concentration of vaccines used in animal husbandry and veterinary disease prevention, comprising the following steps: acquiring vaccine optical detection image data and vaccine status detection data of a designated animal husbandry and veterinary disease prevention vaccine (such as a swine fever vaccine); analyzing the spectral concentration response feature value of the designated animal husbandry and veterinary disease prevention vaccine based on a pre-trained spectral concentration sensing model and in combination with the vaccine optical detection image data; parsing and processing the vaccine status detection data of the designated animal husbandry and veterinary disease prevention vaccine to obtain the status concentration sensing feature value of the designated animal husbandry and veterinary disease prevention vaccine; analyzing the vaccine inoculation concentration mapping value of the designated animal husbandry and veterinary disease prevention vaccine based on the spectral concentration response feature value and the status concentration sensing feature value; and performing concentration confirmation processing on the designated animal husbandry and veterinary disease prevention vaccine based on the vaccine inoculation concentration mapping value.

[0024] The vaccine optical detection image data specifically includes the visible light transmittance value, near-infrared scattering value, and corresponding two-dimensional coordinates of each pixel in the vaccine optical detection image.

[0025] Specifically, such as Figure 2 As shown, the specific steps for analyzing and setting the spectral concentration response characteristic values ​​of livestock and veterinary vaccines are as follows: Input the vaccine light detection image data of the livestock and veterinary vaccines into the pre-trained spectral concentration perception model, analyze and set the spectral concentration display feature set of the livestock and veterinary vaccines, including spectral concentration difference perception feature values, spectral transmission gradient feature values, and scattering heterogeneity feature values; Based on the spectral concentration display feature set of the livestock and veterinary vaccines, analyze and set the spectral concentration response characteristic values ​​of the livestock and veterinary vaccines.

[0026] The specific formula for calculating the spectral concentration response characteristic value of livestock and veterinary vaccines is as follows: ;in, To define the spectral concentration response characteristic values ​​for livestock and veterinary vaccines, To establish spectral concentration difference sensing characteristic values ​​for livestock and veterinary vaccines, These are the concentration sensing adjustment coefficients stored in the database. To determine the spectral transmission gradient characteristic values ​​for livestock and veterinary vaccines, The transmission gradient adjustment coefficients are stored in the database. To define the scattering heterogeneity characteristic values ​​of livestock and veterinary vaccines, The scattering heterogeneity adjustment coefficients are stored in the database. .

[0027] It needs to be explained that the concentration sensing adjustment coefficients stored in the database Transmission gradient adjustment coefficient Scattering heterogeneity adjustment coefficient The acquisition steps are as follows: Obtain the spectral concentration difference sensing characteristic values, spectral transmission gradient characteristic values, and scattering heterogeneity characteristic values ​​of this type of livestock and veterinary disease prevention vaccine from several historical data. Extract the mean values ​​of the spectral concentration difference sensing characteristics, spectral transmission gradient characteristics, and scattering heterogeneity characteristics respectively, and sum them to obtain the concentration response sum value. Ratio the mean values ​​of the spectral concentration difference sensing characteristics, spectral transmission gradient characteristics, and scattering heterogeneity characteristics to the concentration response sum value, and use the corresponding results as the concentration difference sensing adjustment coefficient. Transmission gradient adjustment coefficient Scattering heterogeneity adjustment coefficient .

[0028] The specific steps for analyzing and setting the spectral concentration display feature set of animal husbandry and veterinary disease prevention vaccines are as follows: In the input layer of the spectral concentration perception model, the vaccine light detection image data of the animal husbandry and veterinary disease prevention vaccines is received and preprocessed. Specifically, the vaccine light detection image data is subjected to optical noise suppression processing, such as using the median filtering method to smooth and correct local abnormal light intensity points, and using bilateral filtering to maintain the light intensity gradient information of the edge region to eliminate random high-frequency noise. The transmittance value and scattering value of all pixels are normalized and mapped to the [0, 1] interval to eliminate the global brightness deviation caused by the difference in light source intensity and image exposure.

[0029] In the spectral deconstruction layer of the spectral concentration sensing model, the spectral decomposition processing is performed on the vaccine photodetection image data of the designated livestock and veterinary vaccines to extract the spectral sensing feature vector of the designated livestock and veterinary vaccines. Specifically, this involves reading the visible light transmittance and near-infrared scattering rate of each pixel in the designated vaccine photodetection image, and using each pixel as a processing unit to establish a corresponding dual-band optical response pair. Then, spectral response difference analysis is performed to obtain the spectral difference amplitude (i.e., the absolute value of the difference between the visible light transmittance and near-infrared scattering rate of the pixel) and the spectral response ratio (i.e., the difference between the visible light transmittance and near-infrared scattering rate of the pixel) of each dual-band optical response pair. The ratio of visible light transmittance to near-infrared scattering of the pixel was calculated, and the average spectral difference amplitude and average spectral response ratio of all dual-band optical response pairs were statistically analyzed. These values ​​were then standardized, and the average spectral difference amplitude and average spectral response ratio of the standardized values ​​were weighted to extract spectral concentration sensing features. These features are used to characterize the degree of cross-band spectral response difference of the vaccine solution at the current concentration. When the vaccine solution concentration is high, the transmittance of the visible light channel decreases significantly, and the scattering of the near-infrared channel increases, resulting in a greater difference in optical response between the two bands, and the feature is correspondingly increased.

[0030] Read the visible light transmittance value of each pixel in the vaccine light detection image. Using each pixel as the center, construct a local neighborhood pixel set for that center pixel (i.e., select pixels adjacent to the center pixel in the vertical, horizontal, and lateral directions). For each center pixel, calculate the absolute difference in transmittance values ​​between the center pixel and its left and right adjacent pixels, and take the arithmetic mean to obtain the horizontal transmittance variation amplitude value of the center pixel in the horizontal direction. Similarly, obtain the vertical transmittance variation amplitude value of the center pixel in the vertical direction, and average it with the horizontal transmittance variation amplitude value to obtain the local transmittance variation intensity value of the pixel. Then, use a sliding window of a preset size (e.g., a 5x5 pixel area) to sequentially... The image is traversed by sliding across the entire image. Within each sliding window, the average value of the local transmission change intensity of all pixels in the window is calculated to obtain the local average transmission gradient value of that sliding window. The overall average value of the local average transmission gradient values ​​of all sliding windows is calculated to obtain the global average transmission gradient value of the entire image. The standard deviation of the local average transmission gradient values ​​of all sliding windows is calculated to obtain the transmission gradient dispersion value. This value is then weighted with the global average transmission gradient value to extract the spectral transmission gradient feature, which is used to characterize the uniformity of the transmission distribution of the current vaccine solution in the visible light channel. When the concentration of the vaccine solution increases, the liquid's ability to absorb light increases, and the light attenuation during the transmission process intensifies, resulting in a significant difference in transmittance between adjacent pixels, and this feature increases accordingly.

[0031] The near-infrared scattering rate value of each pixel in the vaccine photodetector image is read. Based on a preset-sized sliding analysis window (e.g., a 5x5 pixel region), the sliding analysis window is moved sequentially across the entire near-infrared channel image in a sliding traversal manner. When the window slides to each pixel, that pixel is taken as the current window center pixel. For each sliding analysis window, the average scattering rate of all pixels within the corresponding sliding analysis window is calculated, and the average of the squared differences between the scattering rate of all pixels within the corresponding sliding analysis window and the corresponding average scattering rate is extracted to obtain the local scattering variance value of the corresponding sliding analysis window, forming a local variance matrix for the entire image. After completing the full image traversal, all local scattering variance values ​​are averaged to obtain the average scattering variance value of the entire image, which is used as the scattering heterogeneity feature value to characterize the non-uniformity of the scattering distribution of the vaccine liquid in the near-infrared channel, reflecting the degree of heterogeneity in the distribution of suspended particles within the liquid. Its value increases with increasing liquid concentration and decreases with liquid dilution. The spectral concentration difference sensing feature, spectral transmission gradient feature, and scattering heterogeneity feature are concatenated into a spectral sensing feature vector.

[0032] In the perception output layer of the spectral concentration perception model, based on the spectral perception feature vector of the set animal and veterinary disease prevention vaccine, the spectral concentration display feature set of the set animal and veterinary disease prevention vaccine is output. Specifically, the spectral concentration perception feature, spectral transmission gradient feature, and scattering heterogeneity feature in the spectral perception feature vector of the set animal and veterinary disease prevention vaccine are activated by the Sigmoid function to obtain the spectral concentration perception feature value, spectral transmission gradient feature value, and scattering heterogeneity feature value between 0 and 1.

[0033] The pre-training steps for the spectral concentration sensing model are as follows:

[0034] A labeled dataset was obtained, which consists of several sets of optical detection image data of livestock and veterinary vaccine samples with different concentrations and corresponding ground truth labels. The labeled dataset was formed by a combination of experimental sampling and manual annotation. Each set of samples includes optical detection image data of the vaccine sample in the visible light channel and near-infrared channel, as well as the corresponding true concentration value of the sample (obtained by standardized chemical detection or dilution factor determination) to ensure that the model can learn the true distribution law of optical response under different concentrations.

[0035] During the data acquisition process, light detection images were acquired under multiple angles and exposure conditions for each group of samples to cover the range of changes in light intensity, container thickness, and liquid volume, thereby enhancing the diversity and robustness of the dataset. After acquisition, the images were preprocessed with uniform size adjustment, illumination normalization, and noise suppression to maintain consistent pixel distribution across samples. Subsequently, the preprocessed dataset was divided into training, validation, and test sets proportionally, for example, 80% for training, 10% for validation, and 10% for testing. The input to the training samples was vaccine light detection image data (including visible light transmittance matrix and near-infrared scattering matrix), and the output was the true concentration label.

[0036] During the model training phase, the spectral deconstruction layer, feature stitching layer, and perception output layer of the spectral concentration perception model are the main training components. Forward propagation is used to calculate the spectral concentration feature values ​​predicted by the model, and the error between the predicted output and the true concentration label is used as the loss function. The loss function can be in the form of mean squared error (MSE) to measure the deviation between the predicted concentration and the true concentration. The weight parameters in the model are updated through the backpropagation algorithm, and the overall loss value is minimized using optimization algorithms (such as the Adam optimizer or RMSprop optimizer). Hyperparameters such as learning rate, batch size, and number of iterations are gradually adjusted to improve the model's ability to distinguish and generalize between samples of different concentrations.

[0037] During training, the spectral concentration sensing model automatically learns the spectral differences of samples with different concentrations through a combination of multi-layer convolution and nonlinear activation. These differences include variations in transmission levels, scattering distribution patterns, and nonlinear response relationships of dual-band coupling features. The validation set is used to evaluate the model's fitting performance on unseen samples, while the test set is used to ultimately evaluate the model's concentration recognition accuracy and stability, ensuring that the features output by the model are consistent with the true concentration trend.

[0038] Once the model's errors on the validation and test sets converge and stabilize, the parameters of the finally trained spectral concentration sensing model are saved. This parameter set is used in the subsequent actual detection stage.

[0039] In this implementation scheme, a spectral concentration sensing model is introduced to perform in-depth analysis of vaccine optical detection image data. This enables multidimensional decomposition of the optical characteristics of the vaccine liquid and high-precision construction of the concentration response, allowing for comprehensive capture of optical behavior differences caused by vaccine concentration changes across different spectral channels. Secondly, by extracting spectral concentration sensing features, spectral transmission gradient features, and scattering heterogeneity features from the visible and near-infrared channels respectively, the model can simultaneously perceive transmission, scattering, and spatial distribution inhomogeneity, achieving full-domain quantitative expression of dilution, particle suspension state, and light energy attenuation. Furthermore, the introduction of standardization and Sigmoid activation mechanisms effectively eliminates differences in light source conditions, container thickness, and imaging brightness, ensuring the stability of feature value calculation. Finally, this step transforms the vaccine optical detection image data into a spectral response feature set, thereby achieving a mappable conversion of optical information to concentration parameters, significantly improving the accuracy and anti-interference capability of vaccine concentration detection.

[0040] Specifically, vaccine status detection data includes vaccine conductivity value, vaccine (ultrasound) transmission attenuation coefficient, vaccine microfluidic impedance value, acoustic surface micro-amplitude value, and electrostatic distribution gradient value.

[0041] The vaccine conductivity value is the ability of ions and soluble chemical components in the vaccine liquid to conduct electricity. It is calculated by simultaneously applying alternating electric field signals to both sides of the outer wall of a sealed container and synchronously detecting the induced current response generated by the liquid inside the container. The conductivity value is calculated in real time based on the amplitude ratio and phase difference of the input voltage and the induced current (i.e., after applying the alternating electric field signal, the waveforms of the voltage signal at the input end and the current signal at the induction end are recorded in real time; amplitude extraction and phase alignment processing are performed on the two sets of signals respectively, and the ratio of the effective value of the input voltage to the effective value of the induced current is calculated to obtain the AC impedance modulus; at the same time, by comparing the phase difference of the two sets of signals, the ratio of the real part to the imaginary part of the impedance is determined, and the impedance modulus and phase difference are converted into equivalent conductivity). The conductivity value reflects the ion migration ability and solute concentration in the vaccine liquid in real time. The higher the concentration, the lower the conductivity value.

[0042] The vaccine (ultrasound) transmission attenuation coefficient is the degree of energy loss of sound waves inside the vaccine liquid. It can be determined by synchronously transmitting and receiving short pulse ultrasound signals, recording the amplitude of the transmitted signal and the amplitude of the received signal in real time, calculating the ratio of the two amplitudes and taking the logarithm as the vaccine transmission attenuation coefficient value.

[0043] The vaccine microfluidic impedance value is the instantaneous flow resistance of the vaccine liquid under micro-pressure disturbance, reflecting the viscosity and intermolecular friction characteristics of the liquid. When the liquid concentration is high, the fluidity decreases and the impedance increases. It can be obtained by applying a micro-amplitude air pressure pulse to the outside of the container at the moment of detection, and at the same time using the built-in pressure detection element to collect the pressure change curve over time in real time; recording the time required for the pressure to drop to a certain proportion of the initial value (e.g., drop to 1 / e), and dividing this time constant by the applied pulse amplitude to obtain the normalized impedance value, which is used as the vaccine microfluidic impedance value.

[0044] The acoustic surface micro-amplitude value is the dynamic response capability of the vaccine liquid surface to acoustic excitation, reflecting the coupling effect of liquid viscosity damping and surface tension. When the vaccine concentration is high, the internal energy dissipation is large and the vibration transmission is weak. It can be detected by applying a short-time acoustic excitation signal (such as a frequency range of 500Hz to 5kHz) to the outer wall of the container during detection, and using a miniature piezoelectric vibration sensor to synchronously collect the position change of the liquid surface reflection point; extract the difference between the maximum and minimum displacements within one acoustic cycle, and use the result as the acoustic surface micro-amplitude value.

[0045] The electrostatic gradient value reflects the uniformity of charge distribution in the vaccine liquid within the container. As the concentration of the vaccine liquid increases, the density of solute molecules or ions increases, enhancing intermolecular polarization coupling and causing uneven electric field distribution in local areas, thus increasing the electrostatic gradient. This can be achieved by distributing potential detection points at multiple spatial locations on the outer wall of the container during detection. Each detection point can be composed of capacitively coupled potential sensors for non-contact acquisition of instantaneous potential signals from the container surface. When the vaccine liquid is stationary, due to the interaction between internal molecular polarization and the external electric field, minute potential differences are generated at different locations on the container surface. Instantaneous potential values ​​from all potential detection points are simultaneously acquired within the same detection cycle, and the corresponding local potential gradient is calculated based on the potential difference between any two adjacent detection points. The average local potential gradient values ​​across all detection points are then used as the electrostatic gradient value.

[0046] The specific steps to obtain the state concentration sensing characteristic value of the set animal and veterinary disease prevention vaccine are as follows: Based on the vaccine state detection data of the set animal and veterinary disease prevention vaccine, analyze the state concentration mapping characteristic set of the set animal and veterinary disease prevention vaccine, including the concentration polarization response characteristic value and the acoustic flow concentration response characteristic value; Based on the state concentration mapping characteristic set of the set animal and veterinary disease prevention vaccine, analyze the state concentration sensing characteristic value of the set animal and veterinary disease prevention vaccine, specifically: perform weighted processing on the concentration polarization response characteristic value and the acoustic flow concentration response characteristic value of the set animal and veterinary disease prevention vaccine to obtain the state concentration sensing characteristic value of the set animal and veterinary disease prevention vaccine.

[0047] It should be noted that in this implementation example, the weight coefficients of each parameter in the weighted processing can be obtained using sample entropy weighting. Taking the weighted processing of obtaining the state concentration sensing feature value as an example, for instance, the concentration polarization response feature value and acoustic flow concentration response feature value of several historical livestock and veterinary vaccines are obtained, and their corresponding information entropy values ​​are extracted respectively. Then, their corresponding information entropy values ​​are transformed using the reciprocal suppression mapping function f(x)=1 / (1+x), such as 1 / (1+information entropy value of concentration polarization response feature value), and summed to obtain the information entropy sum value. The corresponding transformed information entropy values ​​are then compared with the information entropy sum value to obtain the weight coefficients corresponding to each parameter.

[0048] The specific steps for analyzing and setting the state concentration mapping feature set of livestock and veterinary vaccines are as follows: Based on the set vaccine conductivity value and electrostatic distribution gradient value of livestock and veterinary vaccines, analyze the concentration polarization response feature value of the set livestock and veterinary vaccines. Specifically, the set vaccine conductivity value and electrostatic distribution gradient value of livestock and veterinary vaccines are standardized (i.e., units are removed and their values ​​are mapped to between 0 and 1). The standardized set vaccine conductivity value and electrostatic distribution gradient value of livestock and veterinary vaccines are weighted. In this weighting process, the standardized vaccine conductivity value is transformed using the reciprocal suppression mapping function f(x)=1 / (1+x), such as 1 / (1+standardized vaccine conductivity value), to obtain the concentration polarization response feature value of the set livestock and veterinary vaccines, which is used to characterize the degree of electrical energy response of the vaccine liquid under the current concentration conditions, that is, the change in the equivalent electric field strength formed by the restriction of ion migration and molecular polarization coupling in the liquid.

[0049] Based on the predetermined transmission attenuation coefficient, microfluidic impedance, and acoustic surface micro-amplitude of livestock and veterinary vaccines, the acoustic flux concentration response characteristic values ​​of the predetermined livestock and veterinary vaccines are analyzed. Specifically, the transmission attenuation coefficient, microfluidic impedance, and acoustic surface micro-amplitude of the predetermined livestock and veterinary vaccines are standardized (i.e., units are removed and their values ​​are mapped to the range of 0-1). The standardized transmission attenuation coefficient, microfluidic impedance, and acoustic surface micro-amplitude of the predetermined livestock and veterinary vaccines are then weighted. In this weighted processing, the standardized acoustic surface micro-amplitude value is transformed using the reciprocal suppression mapping function f(x)=1 / (1+x), such as 1 / (1+standardized acoustic surface micro-amplitude value), to obtain the acoustic flow concentration response characteristic value of the set animal husbandry and veterinary disease prevention vaccine. This characteristic value is used to characterize the comprehensive influence of the vaccine liquid on the internal energy dissipation and sound wave transmission capability of the liquid under the current concentration conditions. When the concentration of the vaccine liquid increases, the energy attenuation of the system increases and the overall response weakens. The acoustic flow concentration response characteristic value increases monotonically with the increase of concentration.

[0050] In this implementation scheme, through in-depth deconstruction of vaccine status detection data, multi-channel comprehensive analysis and concentration response mapping of vaccine liquid are achieved, enabling multi-dimensional identification of the concentration confirmation process, including conductivity and acoustic flow. For example, concentration polarization response features are extracted through conductivity and electrostatic distribution gradient, reflecting changes in electrical energy distribution caused by restricted ion migration and molecular polarization coupling. Acoustic flow concentration response features are extracted through transmission attenuation coefficient, microfluidic impedance, and acoustic surface micro-amplitude, capturing concentration-sensitive changes in dynamic characteristics such as liquid viscosity, acoustic impedance, and energy attenuation. Secondly, the introduction of standardized and reciprocal suppression mapping functions allows parameters of different dimensions to participate in fusion at a unified scale, eliminating calculation biases caused by differences in units and amplitudes. Furthermore, the sample entropy weighting method is used to determine the weights of each parameter, enabling the model to automatically identify the most discriminative physical signal, thereby improving the adaptability and stability of concentration feature extraction. Finally, this step achieves coupled response characterization of vaccine liquid concentration, allowing the concentration assessment process to simultaneously reflect the true response state of the liquid, enabling rapid identification of vaccine concentration, and significantly improving the accuracy of concentration confirmation.

[0051] Specifically, the formula for calculating the mapping value of the vaccination concentration for livestock and veterinary disease prevention vaccines is as follows: ;in, To set the vaccination concentration mapping value for livestock and veterinary vaccines, To define the spectral concentration response characteristic values ​​for livestock and veterinary vaccines, These are the spectral concentration adjustment coefficients stored in the database. To set the state concentration sensing characteristic value for livestock and veterinary vaccines, These are the state concentration adjustment coefficients stored in the database. These are the coordination coefficients stored in the database.

[0052] It needs to be explained that the spectral concentration adjustment coefficients stored in the database State concentration adjustment coefficient The acquisition steps are as follows: Obtain the spectral concentration response characteristic values ​​and state concentration sensing characteristic values ​​of this type of livestock and veterinary disease prevention vaccine from several historical data. Extract the mean values ​​of the spectral concentration response characteristics and state concentration sensing characteristics respectively, and sum them to obtain a comprehensive concentration sum value. Ratio the mean values ​​of the spectral concentration response characteristics and state concentration sensing characteristics to the comprehensive concentration sum value, and use the corresponding results as the spectral concentration adjustment coefficient. State concentration adjustment coefficient .

[0053] Coordination coefficients stored in the database The acquisition steps are as follows: Obtain the spectral concentration response characteristic values ​​and state concentration sensing characteristic values ​​of this type of livestock and veterinary disease prevention vaccine from several historical data, extract the correlation value between the two based on the Pearson correlation coefficient, and use it as the co-regulation coefficient. .

[0054] The specific steps for confirming the concentration of livestock and veterinary vaccines based on the vaccine concentration mapping value are as follows: The vaccine concentration mapping value is compared with a preset vaccine concentration mapping range. Based on the comparison result, the concentration of the livestock and veterinary vaccines is confirmed and judged. Specifically: If the vaccine concentration mapping value is lower than the lower limit of the preset vaccine concentration mapping range, the vaccine is considered to be diluted too much and the concentration of active ingredients is insufficient, generating a low-concentration label and suggesting reconfiguration; if the vaccine concentration mapping value is within the preset vaccine concentration mapping range, the vaccine concentration is considered acceptable, and vaccination is recommended; if the vaccine concentration mapping value is higher than the upper limit of the preset vaccine concentration mapping range, the vaccine concentration is considered too high, which may lead to an excessively strong immune response in animals, generating a high-concentration label and suggesting standard dilution or disposal.

[0055] In this implementation scheme, by introducing the joint calculation of spectral concentration response characteristic values ​​and state concentration sensing characteristic values, the concentration assessment simultaneously incorporates both optical and physical information sources. This ensures stable results even under conditions of optical anomalies, temperature disturbances, or sensing errors. Secondly, the ratio-based determination of the spectral concentration adjustment coefficient and the state concentration adjustment coefficient guarantees that it can adaptively adjust based on historical samples, matching the concentration characteristic distribution of different vaccine types without relying on fixed thresholds. Furthermore, the co-regulation coefficient, extracted through Pearson correlation, reflects the linear correlation between optical and state characteristics. Finally, based on the dynamic comparison of the concentration mapping value with the upper and lower limits of the interval, automatic judgment and graded prompts can be achieved, ensuring that the inoculation solution is used within the standard concentration range, avoiding immunization failure caused by low concentrations or stress reactions caused by high concentrations, thereby constructing a highly accurate concentration confirmation system.

[0056] Please see Figure 3 This invention provides a technical solution: a vaccine concentration confirmation system for animal husbandry and veterinary disease prevention, comprising: a data acquisition module for acquiring vaccine optical detection image data and vaccine status detection data for setting animal husbandry and veterinary disease prevention vaccines; a spectral concentration detection module for analyzing the spectral concentration response characteristic value of the set animal husbandry and veterinary disease prevention vaccine based on a pre-trained spectral concentration perception model and combined with the vaccine optical detection image data; a vaccine status concentration analysis module for parsing and processing the vaccine status detection data of the set animal husbandry and veterinary disease prevention vaccine to obtain the status concentration sensing characteristic value of the set animal husbandry and veterinary disease prevention vaccine; a comprehensive concentration perception module for analyzing the vaccine inoculation concentration mapping value of the set animal husbandry and veterinary disease prevention vaccine based on the spectral concentration response characteristic value and the status concentration sensing characteristic value; and a concentration confirmation feedback module for performing concentration confirmation processing on the set animal husbandry and veterinary disease prevention vaccine based on the vaccine inoculation concentration mapping value.

[0057] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0058] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for confirming the concentration of a vaccine for livestock and animal epidemic prevention, characterized by, The method comprises the following steps: Obtain the vaccine light detection image data and the vaccine state detection data of the set livestock veterinarian epidemic prevention vaccine; Based on the pre-trained spectrum concentration perception model, and combined with the vaccine light detection image data of the set livestock veterinarian epidemic prevention vaccine, analyze the spectrum concentration response characteristic value of the set livestock veterinarian epidemic prevention vaccine; The state concentration sensing characteristic value of the set livestock veterinarian epidemic prevention vaccine is obtained by analyzing the state concentration sensing characteristic value of the set livestock veterinarian epidemic prevention vaccine. Based on the spectrum concentration response characteristic value and the state concentration sensing characteristic value of the set livestock veterinarian epidemic prevention vaccine, analyze the vaccination concentration mapping value of the set livestock veterinarian epidemic prevention vaccine. Based on the vaccination concentration mapping value, the concentration of the set livestock veterinarian epidemic prevention vaccine is confirmed.

2. The method for confirming the vaccination concentration for livestock and animal medical quarantine according to claim 1, characterized by, The vaccine light detection image data is specifically the visible light transmittance value, near-infrared scattering rate value and corresponding two-dimensional coordinates of each pixel point in the vaccine light detection image.

3. The method for confirming the vaccination concentration for livestock and animal medical quarantine according to claim 2, characterized by, The specific steps of analyzing the spectrum concentration response characteristic value of the set livestock veterinarian epidemic prevention vaccine are as follows: The vaccine light detection image data of the set livestock veterinarian epidemic prevention vaccine is input into the pre-trained spectrum concentration perception model to analyze the spectrum concentration display characteristic set of the set livestock veterinarian epidemic prevention vaccine, including the spectrum concentration difference perception characteristic value, the spectrum transmittance gradient characteristic value and the scattering heterogeneity characteristic value. Based on the spectrum concentration display characteristic set of the set livestock veterinarian epidemic prevention vaccine, analyze the spectrum concentration response characteristic value of the set livestock veterinarian epidemic prevention vaccine.

4. The method for confirming the vaccination concentration for livestock and animal medical epidemic prevention according to claim 3, characterized in that, The specific steps of analyzing the spectrum concentration display characteristic set of the set livestock veterinarian epidemic prevention vaccine are as follows: In the input layer of the spectrum concentration perception model, the vaccine light detection image data of the set livestock veterinarian epidemic prevention vaccine is received and preprocessed; In the spectrum deconstruction layer of the spectrum concentration perception model, the vaccine light detection image data of the set livestock veterinarian epidemic prevention vaccine is subjected to spectrum decomposition processing to extract the spectrum perception feature vector of the set livestock veterinarian epidemic prevention vaccine; In the perception output layer of the spectrum concentration perception model, based on the spectrum perception feature vector of the set livestock veterinarian epidemic prevention vaccine, the spectrum concentration display characteristic set of the set livestock veterinarian epidemic prevention vaccine is output.

5. The method for confirming the vaccination concentration for livestock and animal medical epidemic prevention according to claim 1, characterized in that, The vaccine state detection data includes vaccine conductivity value, vaccine transmittance attenuation coefficient, vaccine micro-flow impedance value, acoustic surface micro-amplitude value and electrostatic distribution gradient value.

6. The method for confirming the vaccination concentration for livestock and animal medical epidemic prevention according to claim 5, characterized in that, The specific steps of obtaining the state concentration sensing characteristic value of the set livestock veterinarian epidemic prevention vaccine are as follows: Based on the vaccine state detection data of the set livestock veterinarian epidemic prevention vaccine, analyze the state concentration mapping characteristic set of the set livestock veterinarian epidemic prevention vaccine, including the concentration polarization response characteristic value and the acoustic flow concentration response characteristic value. Based on the state concentration mapping characteristic set of the set livestock veterinarian epidemic prevention vaccine, analyze the state concentration sensing characteristic value of the set livestock veterinarian epidemic prevention vaccine.

7. The method for confirming the concentration of vaccination for livestock veterinary epidemic prevention according to claim 6, characterized in that, The specific steps of analyzing the state concentration mapping characteristic set of the set livestock veterinarian epidemic prevention vaccine are as follows: Based on the vaccine conductivity value and the electrostatic distribution gradient value of the set livestock veterinarian epidemic prevention vaccine, analyze the concentration polarization response characteristic value of the set livestock veterinarian epidemic prevention vaccine. Based on the set of livestock and veterinary epidemic prevention vaccine vaccine transmission attenuation coefficient value, vaccine micro flow impedance value, sound surface micro amplitude value, the sound flow concentration response characteristic value of the set of livestock and veterinary epidemic prevention vaccine is analyzed.

8. The method for confirming the vaccination concentration for livestock and animal medical epidemic prevention according to claim 1, characterized in that, The specific formula for calculating the vaccination concentration mapping value of the set of livestock and veterinary epidemic prevention vaccine is as follows: ； Wherein, , , The vaccination concentration mapping value, the spectral concentration response characteristic value, and the state concentration induction characteristic value of the set livestock veterinarian epidemic prevention vaccine are sequentially, , , The spectral concentration adjustment coefficient, the state concentration adjustment coefficient, and the synergistic adjustment coefficient stored in the database are sequentially.

9. The method for confirming the vaccination concentration for livestock and animal medical epidemic prevention according to claim 1, characterized in that, The specific steps for concentration confirmation processing of the set of livestock and veterinary epidemic prevention vaccine based on the vaccination concentration mapping value are as follows: The vaccination concentration mapping value of the set of livestock and veterinary epidemic prevention vaccine is compared with the preset vaccination concentration mapping interval; Based on the comparison processing result, the concentration confirmation judgment processing of the set of livestock and veterinary epidemic prevention vaccine is carried out.

10. A vaccine inoculation concentration confirmation system for livestock and veterinary epidemic prevention, applying the vaccine inoculation concentration confirmation method for livestock and veterinary epidemic prevention according to any one of claims 1-9, characterized in that, It includes: The data acquisition module is used to acquire the vaccine light detection image data and the vaccine state detection data of the set of livestock and veterinary epidemic prevention vaccine; The spectral concentration detection module is used to analyze the spectral concentration response characteristic value of the set of livestock and veterinary epidemic prevention vaccine based on the pre-trained spectral concentration perception model and combined with the vaccine light detection image data of the set of livestock and veterinary epidemic prevention vaccine; The vaccine state concentration analysis module is used to analyze the vaccine state detection data of the set of livestock and veterinary epidemic prevention vaccine to obtain the state concentration sensing characteristic value of the set of livestock and veterinary epidemic prevention vaccine; The comprehensive concentration perception module is used to analyze the vaccination concentration mapping value of the set of livestock and veterinary epidemic prevention vaccine based on the spectral concentration response characteristic value and the state concentration sensing characteristic value of the set of livestock and veterinary epidemic prevention vaccine; The concentration confirmation feedback module is used to carry out concentration confirmation processing of the set of livestock and veterinary epidemic prevention vaccine based on the vaccination concentration mapping value.

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