An automated preparation and filling system for emulsifiable concentrate pesticides

Abstract

This invention discloses an automated formulation and filling system for emulsifiable concentrate pesticides, belonging to the field of pesticide filling technology. The invention includes selecting a target filling scheme, obtaining optimal control parameter data, optimal emulsion stability data, and emulsion stability data for each formulation and filling scheme when used with other emulsifiable concentrate pesticide formulations. This invention achieves full-process data-driven control of the formulation and filling process, effectively solving the problem of batch product non-conformity caused by response lag in traditional systems, significantly reducing material loss and production losses, while improving the accuracy and consistency of emulsifiable concentrate pesticide formulation and filling, ensuring the stability of the production process and product quality.

Description

Technical Field

[0001] This invention relates to the field of pesticide filling technology, specifically to an automated preparation and filling system for emulsifiable concentrate pesticides. Background Technology

[0002] Emulsifiable concentrate pesticides are homogeneous, transparent oily formulations made by dissolving oil-soluble pesticide active ingredients in an organic solvent and adding emulsifiers and other adjuvants. When used, they spontaneously form an oil-in-water emulsion upon the addition of water. Due to their superior efficacy, ease of processing, and strong adaptability, they remain an indispensable and important formulation in the current pesticide field. They are mainly divided into four categories: insecticides, fungicides, herbicides, and plant growth regulators. Among them, insecticide emulsifiable concentrates account for the largest proportion. Currently, emulsifiable concentrate pesticide technology has shifted from empirical formulation to precision control, with the mainstream approach being the non-ionic / anionic compound emulsification strategy.

[0003] Automated formulation and filling of emulsifiable concentrates (ECCs) is an industry trend. However, existing automated formulation and filling systems mostly use fixed preset values ​​for their operating parameters. They lack a real-time monitoring and dynamic response mechanism for component fluctuations specific to the formulation characteristics of ECCs. This makes it impossible to adjust parameters in a timely manner during the formulation and filling process. Defective products can only be detected through manual sampling after the formulation process is completed. When there are fluctuations in the emulsifier compounding ratio or changes in the type of organic solvent in the ECC formulation, the fixed high-speed shearing speed, emulsification time, and other equipment parameters cannot meet the emulsification adaptation requirements of ECCs. This can easily lead to insufficient interfacial film elastic modulus in the ECC emulsion system, which cannot effectively inhibit droplet aggregation and Ostwald ripening. Ultimately, this can cause emulsion instability, directly resulting in batches of defective ECC products. Furthermore, due to the subtle fluctuations in ECC components and the lag in system response, this problem is difficult to detect in advance, which can easily cause significant material losses and economic losses.

[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to provide an automated preparation and filling system for emulsifiable concentrate pesticides to solve the problems mentioned above.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an automated preparation and filling system for emulsifiable concentrate pesticides, comprising the following steps:

[0007] S1. Select the target configuration and filling scheme, obtain the optimal control parameter data of each formulation and filling scheme, the optimal emulsion stability data of the scheme, and the scheme stability data of the formulation type emulsion when formulating and filling other emulsifiable oil pesticides of the aforementioned formulation types.

[0008] S2. Calculate and process the error and variance of the emulsion stability data of each formulation and filling scheme with the formula type and the optimal emulsion stability data of the scheme, and generate the formulation error data and the variance data of the formulation error of the scheme with respect to the formula type respectively.

[0009] S3. Select the formulation and filling scheme with the smallest variance of the corresponding formulation type as the initial formulation and filling scheme to formulate and fill the emulsifiable concentrate pesticide, and obtain the real-time emulsion stability data of the emulsifiable concentrate pesticide to be formulated and filled.

[0010] S4. Calculate the error between the real-time emulsion stability data and the optimal emulsion stability data of the current formulation and filling scheme to generate real-time formulation error data.

[0011] Furthermore, based on the various emulsifiable concentrate pesticide formulations, the emulsion stability data and component formulation accuracy data of different control parameters were tested at each formulation and filling stage. Preliminary control parameters that optimize emulsion stability data and maximize component formulation accuracy data were obtained at each formulation and filling stage during the testing process for each formulation type.

[0012] Furthermore, the optimal control parameter data for the proposed scheme are obtained through the following steps:

[0013] For each formulation and filling scheme, the automated formulation and filling equipment is controlled to formulate and fill the corresponding emulsifiable concentrate pesticide according to the corresponding control parameters; the data on the change of emulsion stability over time, the corresponding component formulation accuracy data, and the production energy consumption data when the emulsion stability meets the qualified threshold are obtained during the formulation and filling process of the automated formulation and filling equipment, and the scheme emulsion stability change data, scheme component formulation accuracy data, and scheme production energy consumption data are generated respectively.

[0014] Based on the emulsion stability variation data, formulation accuracy data, and production energy consumption data of each formulation and filling scheme, an objective function is constructed that simultaneously satisfies the constraints of maximizing the emulsion stability variation data, maximizing the formulation accuracy data, and minimizing the production energy consumption data. The control parameters corresponding to each formulation type are then solved to generate the optimal control parameter data for each formulation and filling scheme.

[0015] Furthermore, the optimal emulsion stability data for the proposed solution is obtained through the following steps:

[0016] For each formulation and filling scheme, the automated formulation and filling equipment is controlled to formulate and fill the corresponding emulsifiable concentrate pesticide according to the optimal control parameter data of the corresponding scheme, obtain the corresponding emulsion stability data, and generate the optimal emulsion stability data of the corresponding scheme.

[0017] Furthermore, the stability data of the formulated emulsion is obtained through the following steps:

[0018] For each formulation and filling scheme, the automated formulation and filling equipment is controlled to formulate and fill emulsifiable concentrate pesticides of other formulation and filling schemes according to the optimal control parameter data of the corresponding scheme; the emulsion stability data of each formulation type of emulsifiable concentrate pesticide is obtained, and the corresponding scheme-to-formulation emulsion stability data is generated respectively.

[0019] Furthermore, S2 includes the following steps:

[0020] S2.1. For each formulation and filling scheme, the first and second derivatives of the emulsion stability data of the formulation type and the optimal emulsion stability data of the scheme are respectively obtained to obtain the change rate characteristics of the formulation stability of the emulsion of the scheme with respect to the formulation type, the change acceleration characteristics of the formulation stability of the emulsion of the scheme with respect to the formulation type, the change rate characteristics of the optimal emulsion stability of the scheme, and the change acceleration characteristics of the optimal emulsion stability of the scheme. The formulation feature vector of the scheme with respect to the formulation type and the optimal formulation feature vector of the scheme are generated.

[0021] S2.2 Calculate the error vector between the formulation feature vector of all schemes of this preparation and filling scheme and the optimal formulation feature vector of the scheme, and generate the formulation error vector of the scheme to the formulation type.

[0022] S2.3 Calculate the error norm of the formulation error vector for each scheme to generate formulation error data for each scheme.

[0023] S2.4. For all schemes based on the same formulation and filling scheme, calculate the error variance of the formulation type and generate the scheme formulation error variance data.

[0024] Furthermore, S3 includes the following steps:

[0025] S3.1 Compare the variance data of the formulation error of all formulation and filling schemes with the formula type, and obtain the scheme with the smallest variance data of the formulation error of the formula type.

[0026] S3.2 Set the preparation and filling scheme corresponding to the smallest scheme type formulation error variance data as the initial preparation and filling scheme;

[0027] S3.3 The automated preparation and filling equipment prepares and fills the emulsifiable concentrate pesticide according to the optimal control parameter data of the initial preparation and filling scheme, and obtains the real-time emulsion stability data of the emulsifiable concentrate pesticide to be prepared and filled.

[0028] Furthermore, S4 includes the following steps:

[0029] S4.1 Obtain the optimal emulsion stability data for the current formulation and filling scheme;

[0030] S4.2 Calculate the error between the real-time emulsion stability data and the optimal emulsion stability data of the current formulation and filling scheme, and generate real-time formulation error data.

[0031] Furthermore, a preset error threshold is retrieved and compared with real-time configuration error data for analysis: it is determined whether the real-time formulation error data is less than the set error threshold. If so, the current formulation and filling scheme is set as the final formulation and filling scheme; if not, the formulation error vectors of all schemes for all formulation and filling schemes are collected to generate a set of formulation error vectors for all schemes for all formulation and filling schemes. Based on the real-time emulsion stability data and the optimal emulsion stability data of the current formulation and filling scheme, the error vector of the current formulation and filling scheme for emulsifiable concentrate pesticide formulation and filling is calculated, and a real-time formulation error vector is generated. Based on the nearest neighbor algorithm, the formulation error vector of the scheme for the formulation type most similar to the real-time formulation error vector is searched in the set of formulation error vectors for the scheme for the formulation type, and the corresponding formulation and filling scheme adjustment data is generated. The automated formulation and filling equipment performs formulation and filling of emulsifiable concentrate pesticides with a set test duration according to the optimal control parameter data of the formulation and filling scheme adjustment data, and obtains and updates the real-time emulsion stability data.

[0032] The beneficial effects of this invention are:

[0033] 1. This invention establishes a real-time monitoring and dynamic response mechanism for emulsion component fluctuations. It can collect emulsion stability data and perform error analysis in real time during the formulation and filling process. When there are fluctuations in the emulsifier compounding ratio or solvent type replacement, the algorithm can search for and match the optimal formulation and filling scheme and dynamically adjust the equipment control parameters. This effectively solves the problems of emulsion instability such as insufficient interfacial film elastic modulus and droplet coalescence caused by the inability of fixed shear speed and emulsification time to adapt to changes in emulsion formulation. It avoids emulsion instability caused by insufficient formulation adaptability from the root.

[0034] 2. This invention precisely classifies emulsifiable concentrate pesticide formulations, generates corresponding formulation and filling schemes by combining multiple sets of control parameters, and optimizes and dynamically iterates the schemes through error and variance calculations. This replaces the traditional manual sampling and testing mode, realizing full-process data-driven management and control of the formulation and filling process. It effectively solves the problem of batch product non-conformity caused by the slow response of traditional systems, significantly reduces material loss and production losses, and improves the accuracy and consistency of emulsifiable concentrate pesticide formulation and filling, ensuring the stability of the production process and product quality. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a flowchart of the system steps of the present invention;

[0037] Figure 2 This is a flowchart illustrating the system framework of the present invention.

[0038] Figure 3 This is a flowchart illustrating the trend of data analysis in this invention. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] Example 1: Please refer to Figures 1-3 As shown, this embodiment is an automated preparation and filling system for emulsifiable concentrate pesticides, including the following steps:

[0041] Based on the formulation type of emulsifiable concentrate pesticides, multiple sets of control parameters are set to generate multiple formulation and filling schemes. Each formulation type corresponds to the ratio of active ingredient, organic solvent, and emulsifier in the emulsifiable concentrate pesticide, as well as the type of organic solvent. The control parameters are obtained by testing the shear speed, emulsification time, component metering ratio, and raw material feeding rate of the automated formulation and filling equipment under different shearing, stirring, and metering feeding conditions.

[0042] S1. Select the target configuration and filling scheme, obtain the optimal control parameter data of each formulation and filling scheme, the optimal emulsion stability data of the scheme, and the scheme stability data of the formulation type emulsion when formulating and filling other emulsifiable oil pesticides of the aforementioned formulation types.

[0043] Based on the mainstream formulations of emulsifiable concentrate pesticides, several core formulation types were selected. Each formulation type corresponds to a fixed ratio of active ingredient, organic solvent, emulsifier, and solvent type, and is labeled as formulation type F1-F6.

[0044] The four core control parameters of the automated formulation and filling equipment were tested: shear speed, emulsification time, component metering ratio, and raw material feeding rate. Based on the requirements of the emulsification process of emulsifiable concentrate pesticides, the control range of shear speed was determined to be 2000-10000 rpm, the control range of emulsification time was 0.5-3 hours, the deviation of component metering ratio was controlled within ±0.5%, and the raw material feeding rate was controlled within 50-200 L / hour.

[0045] The stability data and formulation accuracy data of emulsions under different control parameters at each stage of raw material mixing, high-speed shearing, constant temperature emulsification, and finished product filling were tested. The preliminary control parameters that optimize the emulsion stability and formulation accuracy at each stage of each formulation type were obtained. Based on different combinations of preliminary control parameters, 8 sets of control parameters were generated for each formulation type F1-F6, resulting in a total of 48 sets of control parameters. 48 formulation and filling schemes were generated, denoted as schemes P1-P48.

[0046] To accurately match the relationship between shear rotation speed and emulsion emulsification effect, a shear emulsification dynamic equation is constructed with reference to the basic equations of fluid mechanics. ,in, Expressed as shear stress, it represents the shear force exerted by the equipment on the emulsion mixture. Expressed as the dynamic viscosity of an emulsifiable concentrate mixture, it changes with the type of organic solvent and the ratio of emulsifier; It is expressed as shear rate, which is positively correlated with the shearing speed of the equipment. The higher the shearing speed, the greater the shear rate. Based on the dynamic viscosity of the emulsion oil mixture, a suitable shear rate can be initially matched, and then the initial value of the shearing speed can be determined, avoiding blind testing and improving the rationality of control parameter settings.

[0047] The optimal control parameter data, optimal emulsion stability data, and emulsion stability data for different formulation types of the scheme were obtained separately. The specific process is as follows:

[0048] The optimal control parameter data of the scheme is obtained, and the automated preparation and filling equipment is controlled to prepare and fill the corresponding F1-F6 formula types of emulsifiable oil according to the control parameters of P1-P48. The emulsion stability change data over time is collected through the online emulsion stability detection module, the formulation accuracy data is collected through the metering pump sensor, and the production energy consumption data is collected through the electricity meter.

[0049] The above data is normalized, and a multi-objective optimization objective function is constructed. ,in, It is represented as a combination of control parameters constructed from shear speed, emulsification time, metering ratio, and feed rate; This is expressed as a comprehensive value for emulsion stability, calculated from interfacial tension, Zeta potential, and particle size distribution with weights of 0.3, 0.4, and 0.3, respectively. A larger value for S indicates better emulsion stability. The higher the precision of the formulation, the better; N is the unit production energy consumption; α, β, and γ are weighting coefficients, set to 0.4, 0.4, and 0.2 respectively according to the requirements of emulsifiable concentrate production process, and α+β+γ=1.

[0050] The preset constraints are retrieved: shearing speed ranges from 2000 to 10000 rpm, emulsification time ranges from 0.5 to 3 hours, metering ratio deviation ≤ ±0.5%, feed rate ranges from 50 to 200 L / h, interfacial tension ranges from 15 to 20 mN / m, absolute value of Zeta potential ≥ 28 mV, D5 ranges from 0.7 to 1.3 μm, and D90 ≤ 2.0 μm. The particle swarm optimization algorithm is used to solve for the minimum value of the objective function F(X), and the corresponding combination of control parameters is the optimal control parameter data of the scheme.

[0051] Based on the optimal control parameter data obtained from the above solution, the control equipment prepares and fills the emulsion of the corresponding formulation type, collects the interfacial tension, Zeta potential, and particle size distribution data after the emulsion stabilizes, and calculates the comprehensive value of emulsion stability, which is the optimal emulsion stability data of the solution.

[0052] Based on the optimal control parameter data of each scheme, the control equipment formulates and fills the remaining 5 types of emulsions, and collects the comprehensive value of emulsion stability corresponding to each type of formulation, which is the emulsion stability data of the scheme for the formulation type.

[0053] S2. The error and variance of the two types of emulsion stability data obtained are calculated. First-order and second-order derivatives are performed on the emulsion stability data for the specific formulation type and the optimal emulsion stability data for the specific scheme, respectively. The first-order derivative result represents the rate of change of emulsion stability, characterizing how quickly the emulsion stability changes over time. The second-order derivative result represents the acceleration characteristic of the change in emulsion stability, characterizing the trend of the rate of change in emulsion stability. The two features are combined sequentially to obtain the formulation feature vector for the specific scheme type. And the optimal configuration feature vector of the scheme ,in, , This represents the velocity and acceleration characteristics of the scheme relative to the formulation type. , The velocity and acceleration characteristics represent the optimal solution.

[0054] Calculate the error vector between the two eigenvectors using the Euclidean distance formula. ,in, This is represented as a formulation error vector for the scheme relative to the recipe type, where each element in the vector is the error value of the corresponding feature;

[0055] The L2 norm of the formulation error vector is calculated to obtain the scalar form of the formulation error data for the formula type. The formula is as follows: ,in, This is represented as preparation error data. The smaller the value, the smaller the deviation between the formulation effect and the optimal effect for other formulation types;

[0056] The variance of the formulation error data for all formulation types under the same formulation and filling scheme is calculated to obtain the variance data of the formulation error for each formulation type. The formula is as follows: ,in, This is represented as the variance data of the preparation error; This represents the total number of recipe types; This represents the preparation error data for the i-th type of recipe; It represents the average value of all preparation error data for this scheme; the smaller D is, the smaller the fluctuation of the preparation effect of this scheme on different formulation types, and the stronger its adaptability.

[0057] Example 2: S3 selects the initial formulation and filling scheme and obtains real-time emulsion stability data. The formulation error variance data D of 48 formulation and filling schemes from P1 to P48 are compared, and the formulation and filling scheme corresponding to the minimum value of the formulation error variance data D is selected and recorded as the initial formulation and filling scheme.

[0058] The automated formulation and filling equipment is controlled based on the optimal control parameter data from several types of schemes. The actual emulsifiable concentrate pesticide to be formulated and filled is tested for 30 minutes. The interfacial tension, zeta potential, and particle size distribution data are collected in real time through the online emulsion stability detection module. The comprehensive value of emulsion stability is calculated, which is the real-time emulsion stability data.

[0059] S4. Retrieve the optimal emulsion stability data from step S2 and mark it as... , and the real-time emulsion stability data obtained in step S3, are marked as Calculate the real-time preparation error data according to the absolute error formula, based on the formula. ,in, This is represented as real-time preparation error data, in this embodiment. The possible value is 0.18. A preset error threshold is retrieved, which can be 0.15. This threshold is obtained based on historical data analysis and is adjusted according to real-time error data. If the error exceeds the error threshold, the solution needs to be adjusted.

[0060] Based on a pre-defined matching scheme database, adjustment data is generated and iterative optimization is performed. The formulation error vectors of all schemes from P1 to P48 are collected to generate a set U of formulation error vectors. This is based on real-time emulsion stability data. , and optimal emulsion stability data of the solution The differentiation and vector calculation methods in step S2 were verified to obtain the real-time configuration error vector. ;

[0061] Based on the K-nearest neighbor algorithm, K can be 3, to analyze the real-time preparation error vector. The Euclidean distances with all vectors in the error vector set U are used to select the three vectors with the smallest distances, which correspond to three formulation and filling schemes. The scheme with the smallest variance in formulation error is selected as the matching formulation and filling scheme.

[0062] The optimal control parameter data of the matching formulation and filling scheme is retrieved as the adjustment data for the formulation and filling scheme. The control equipment performs 30 minutes of formulation and filling of emulsifiable concentrate of formulation type F4 based on this data, re-collects and updates the real-time emulsion stability data, and recalculates the real-time formulation error data. After one adjustment, the new real-time formulation error data ΔE=0.09 is obtained, which is less than the set error threshold of 0.15. Therefore, the final formulation and filling scheme is determined, and the equipment performs subsequent automated formulation and filling of emulsifiable concentrate pesticides according to the optimal control parameters of this scheme.

[0063] The formulation types of emulsifiable concentrate pesticides are classified according to the type of active pharmaceutical ingredient, the type of organic solvent, and the ratio of emulsifier. The active pharmaceutical ingredient includes insecticides, fungicides, herbicides, and plant growth regulators. The types of organic solvents include traditional aromatic solvents and environmentally friendly bio-based solvents. The ratio of emulsifier is the ratio of nonionic emulsifier to anionic emulsifier.

[0064] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

[0065] This embodiment addresses the issues of emulsion instability and batch product defects caused by fluctuations in formulation components (emulsifier mixing ratio, solvent type replacement, etc.) and fixed equipment parameters during the automated preparation and filling of emulsifiable concentrate pesticides. Based on the control methods described in the aforementioned claims, and considering the physicochemical properties of emulsifiable concentrate pesticides and the operating conditions of the automated preparation and filling equipment, specific preparation and filling control measures are implemented to achieve dynamic parameter adjustment under fluctuations in emulsifiable concentrate components, ensuring emulsion stability and preparation and filling quality. In this embodiment, emulsion stability is comprehensively evaluated using three indicators: interfacial tension, Zeta potential, and emulsion particle size distribution (D50, D90). Component preparation accuracy is defined as the deviation between the actual measured ratios of technical grade pesticide, organic solvent, and emulsifier and the preset formulation. Production energy consumption is the electrical energy consumed per unit time when the equipment achieves qualified emulsion stability.

[0066] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. An automated preparation and filling system for emulsifiable concentrate pesticides, characterized in that, Includes the following steps: S1. Select the target configuration and filling scheme, obtain the optimal control parameter data of each formulation and filling scheme, the optimal emulsion stability data of the scheme, and the scheme stability data of the formulation type emulsion when formulating and filling other emulsifiable oil pesticides of the aforementioned formulation types. S2. Calculate and process the error and variance of the emulsion stability data of each formulation and filling scheme with the formula type and the optimal emulsion stability data of the scheme, and generate the formulation error data and the variance data of the formulation error of the scheme with respect to the formula type respectively. S3. Select the formulation and filling scheme with the smallest variance of the corresponding formulation type as the initial formulation and filling scheme to formulate and fill the emulsifiable concentrate pesticide, and obtain the real-time emulsion stability data of the emulsifiable concentrate pesticide to be formulated and filled. S4. Calculate the error between the real-time emulsion stability data and the optimal emulsion stability data of the current formulation and filling scheme to generate real-time formulation error data.

2. The automated preparation and filling system for emulsifiable concentrate pesticides according to claim 1, characterized in that, Based on the various emulsifiable concentrate pesticide formulations, different control parameters were tested at each formulation and filling stage to obtain the emulsion stability data and component formulation accuracy data for each formulation type.

3. The automated preparation and filling system for emulsifiable concentrate pesticides according to claim 1, characterized in that, The optimal control parameter data for the proposed scheme are obtained through the following steps: For each formulation and filling scheme, the automated formulation and filling equipment is controlled to formulate and fill the corresponding emulsifiable concentrate pesticide according to the corresponding control parameters; the data on the change of emulsion stability over time, the corresponding component formulation accuracy data, and the production energy consumption data when the emulsion stability meets the qualified threshold are obtained during the formulation and filling process of the automated formulation and filling equipment, and the scheme emulsion stability change data, scheme component formulation accuracy data, and scheme production energy consumption data are generated respectively. Based on the emulsion stability variation data, formulation accuracy data, and production energy consumption data of each formulation and filling scheme, an objective function is constructed that simultaneously satisfies the constraints of maximizing the emulsion stability variation data, maximizing the formulation accuracy data, and minimizing the production energy consumption data. The control parameters corresponding to each formulation type are then solved to generate the optimal control parameter data for each formulation and filling scheme.

4. The automated preparation and filling system for emulsifiable concentrate pesticides according to claim 1, characterized in that, The optimal emulsion stability data for the proposed solution were obtained through the following steps: For each formulation and filling scheme, the automated formulation and filling equipment is controlled to formulate and fill the corresponding emulsifiable concentrate pesticide according to the optimal control parameter data of the corresponding scheme, obtain the corresponding emulsion stability data, and generate the optimal emulsion stability data of the corresponding scheme.

5. The automated preparation and filling system for emulsifiable concentrate pesticides according to claim 1, characterized in that, The method obtains stability data for formulation-type emulsions through the following steps: For each formulation and filling scheme, the automated formulation and filling equipment is controlled to formulate and fill emulsifiable oil pesticides of other formulation and filling schemes according to the optimal control parameter data of the corresponding scheme. Obtain emulsion stability data for various formulation types of emulsifiable concentrate pesticides, and generate corresponding scheme pair formulation type emulsion stability data.

6. The automated preparation and filling system for emulsifiable concentrate pesticides according to claim 1, characterized in that, S2 includes the following steps: S2.

1. For each formulation and filling scheme, the first and second derivatives of the emulsion stability data of the formulation type and the optimal emulsion stability data of the scheme are respectively obtained to obtain the change rate characteristics of the formulation stability of the emulsion of the scheme with respect to the formulation type, the change acceleration characteristics of the formulation stability of the emulsion of the scheme with respect to the formulation type, the change rate characteristics of the optimal emulsion stability of the scheme, and the change acceleration characteristics of the optimal emulsion stability of the scheme. The formulation feature vector of the scheme with respect to the formulation type and the optimal formulation feature vector of the scheme are generated. S2.2 Calculate the error vector between the formulation feature vector of all schemes of this preparation and filling scheme and the optimal formulation feature vector of the scheme, and generate the formulation error vector of the scheme to the formulation type. S2.3 Calculate the error norm of the formulation error vector for each scheme to generate formulation error data for each scheme. S2.

4. For all schemes based on the same formulation and filling scheme, calculate the error variance of the formulation type and generate the scheme formulation error variance data.

7. The automated preparation and filling system for emulsifiable concentrate pesticides according to claim 1, characterized in that, S3 includes the following steps: S3.1 Compare the variance data of the formulation error of all formulation and filling schemes with the formula type, and obtain the scheme with the smallest variance data of the formulation error of the formula type. S3.2 Set the preparation and filling scheme corresponding to the smallest scheme type formulation error variance data as the initial preparation and filling scheme; S3.3 The automated preparation and filling equipment prepares and fills the emulsifiable concentrate pesticide according to the optimal control parameter data of the initial preparation and filling scheme, and obtains the real-time emulsion stability data of the emulsifiable concentrate pesticide to be prepared and filled.

8. The automated preparation and filling system for emulsifiable concentrate pesticides according to claim 6, characterized in that, S4 includes the following steps: S4.1 Obtain the optimal emulsion stability data for the current formulation and filling scheme; S4.2 Calculate the error between the real-time emulsion stability data and the optimal emulsion stability data of the current formulation and filling scheme, and generate real-time formulation error data.

9. The automated preparation and filling system for emulsifiable concentrate pesticides according to claim 8, characterized in that, The system retrieves a preset error threshold and compares it with real-time configuration error data for analysis: it determines whether the real-time formulation error data is less than the set error threshold. If so, the current formulation and filling scheme is set as the final formulation and filling scheme; if not, it collects the formulation error vectors of all formulation and filling schemes for all formula types, generating a set of formulation error vectors for each scheme. Based on the real-time emulsion stability data and the optimal emulsion stability data of the current formulation and filling scheme, it calculates the error vector of the current formulation and filling scheme for emulsifiable concentrate pesticide formulation and filling, generating a real-time formulation error vector. Based on the nearest neighbor algorithm, the formula type formulation error vector that is most similar to the real-time formulation error vector is searched in the set of formulation error vectors of the formula type of the scheme, and the corresponding formulation and filling scheme is generated to adjust the formulation and filling scheme. The automated formulation and filling equipment adjusts the optimal control parameters based on the formulation and filling scheme to formulate and fill emulsifiable oil pesticides for a set test duration, and acquires and updates real-time emulsion stability data.

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