Feeding method and device capable of automatically adding pig feed

Abstract

The invention discloses a feeding method and device capable of automatically adding pig raising feed, and aims to optimize feed management in the pig raising process through an automatic and intelligent technology. Comprising the following steps: monitoring environmental parameters such as temperature, humidity and air quality in a pig house in real time through an environment monitoring device, and transmitting data to a central control system; the central control system dynamically generates and adjusts a feed formula according to environmental parameters and growth stages and health conditions of pigs, and accurately mixes feed components through an automatic proportioning device. The feed trough sensor monitors the residual amount of feed in the feed trough, and when the feed is insufficient, the system automatically controls the feed conveying device to supplement the feed. In the feeding process, the central control system adjusts the feed adding frequency and the feeding amount according to real-time data, and the cleaning device is combined with the ultrasonic cleaning and nano-coating technology, so that the cleanliness and long-term stable operation of the equipment are ensured.

Description

Technical Field

[0001] The invention relates to the technical field of agriculture and animal husbandry, and in particular to a method and a device for automatically adding feed to pigs. Background Art

[0002] In the modern pig farming industry, feed management is an important factor affecting breeding efficiency and pig health. Traditional pig feed management methods usually rely on manual operations, including manual feed proportioning, manual feed addition, and equipment cleaning and maintenance. This method has many shortcomings and is difficult to meet the needs of large-scale and refined farming.

[0003] Manual operation makes it difficult to ensure the accuracy and consistency of feed ratios. In traditional methods, feed formulas are usually formulated based on experience and lack dynamic adaptability to the growth stage, health status and environmental changes of pigs, resulting in the inability of the nutritional components of the feed to accurately match the growth needs of pigs, thus affecting their growth rate and health status. In addition, manual ratios are inefficient, especially in large-scale farms, where it is difficult to quickly respond to the different nutritional needs of pigs, resulting in frequent feed waste or insufficient nutrient intake.

[0004] There are also significant deficiencies in the addition and delivery of feed. The method of artificially adding feed not only consumes a lot of manpower, but also makes it difficult to ensure the continuous supply of feed, especially during the peak period of intensive feeding of pigs, when feed may not be supplied in time. This situation not only affects the normal feeding of pigs, but may also cause scramble for food in the feed trough, leading to increased competition and pressure among pigs, which in turn affects the overall health and growth of the pig herd. In addition, the control of feed delivery is also relatively extensive, and it is difficult to make precise adjustments based on individual differences, and it is impossible to achieve differentiated feeding for special pigs.

[0005] The cleaning and maintenance issues of traditional equipment also affect breeding efficiency and food safety. If the residual feed in the feed delivery pipeline and feeding equipment is not cleaned in time, it is easy to cause feed deterioration or contamination, affecting the health of pigs. At the same time, the cleaning of equipment usually relies on manual operation, which is time-consuming and difficult to completely remove the residue, making it difficult to ensure the sanitation of the equipment. In addition, the frequency and effect of equipment maintenance are limited by the time and energy of manual operation, and the long-term stability and service life of the equipment are difficult to guarantee.

[0006] Therefore, how to provide a method and device for automatically adding pig feed is a problem that those skilled in the art need to solve urgently. Summary of the invention

[0007] One purpose of the present invention is to propose a method and device for automatically adding pig feed to feed. The present invention makes full use of environmental monitoring, data analysis, automatic control and equipment cleaning and maintenance technology, and describes in detail the full-process automation implementation method from feed formula generation, precise delivery to equipment cleaning and maintenance. It has the advantages of accurate feed management, high breeding efficiency, thorough equipment cleaning and easy maintenance.

[0008] A method and device for automatically adding feed to pigs according to an embodiment of the present invention comprises the following steps:

[0009] S1. Use an environmental monitoring device with integrated gas sensors to monitor the temperature, humidity, air quality and concentration of harmful gases in the pig house in real time, and transmit all monitoring data to the central control system;

[0010] S2. The central control system starts the built-in multi-layer enhanced genetic algorithm module based on the received environmental parameters and the growth stage and health status of the pigs. Through the adaptive optimization strategy, it dynamically generates and adjusts the feed formula suitable for the current conditions to match the formula with the environment and growth requirements.

[0011] S3, the automated proportioning device receives the feed formula generated by the central control system and controls the proportion and mixing process of each feed component. The automated proportioning device uses adaptive microfluidic control technology to dynamically achieve accurate mixing of feed components and stores the mixed feed in a central storage bin;

[0012] S4. The feed trough sensor continuously monitors the remaining feed in each feed trough in the pig house. When the feed amount is lower than the preset value, the central control system automatically activates the feed conveying device to convey the mixed feed from the central storage bin to the feed troughs in each pig house. The conveying device has an automatic unblocking function to prevent feeding interruption caused by feed blockage.

[0013] S5. The central control system analyzes the pigs’ eating behavior data and pig house environmental conditions in real time, and automatically adjusts the feed addition frequency and amount. The central control system also has a differentiated feeding function, which can be adjusted according to the special needs of individual pigs to meet the nutritional needs of different individuals.

[0014] S6. After each feed addition, the central control system automatically starts the cleaning device, which combines ultrasonic cleaning and nano-coating technology to remove residual feed in the delivery pipeline and feeding equipment through ultrasonic vibration, and uses nano-coating to prevent contaminants from adhering to maintain the cleanliness and stability of the equipment;

[0015] S7. The central control system stores all environmental monitoring data, feed formula data and pigs’ eating behavior data in the data storage module of the central control system. It also conducts a comprehensive cross-analysis of information from different data sources through a dynamic analysis method based on a multi-perspective integrated learning algorithm to generate the optimal feeding strategy, and adjusts the feed formula and feeding plan in real time to adapt to changing breeding conditions.

[0016] Optionally, the S2 specifically includes:

[0017] S21, the central control system receives the environmental parameter data transmitted by the environmental monitoring device, and simultaneously obtains the growth stage and health status data of the pigs, and transmits them as multi-dimensional input data X to the multi-layer enhanced genetic algorithm module, where x includes a set of all relevant parameters;

[0018] S22, in the multi-layer enhanced genetic algorithm module, the input multi-dimensional data x is transformed into a high-dimensional space, and the fitness function F 适应度 Calculate the initial fitness value for each feed recipe:

[0019]

[0020] Where P = {p1, p2, p m} represents the component ratio vector of the current feed formula, w i is the weight of the i-th factor, f i (x i ) is the influence function of the i-th environment or growth parameter, g i (p i ) is the effect function of feed ingredients on pig growth, θ i is the phase angle of the i-th factor, which is used to adjust the interactive effect between environmental parameters and feed ingredients, n and m are the number of environmental parameters and feed ingredients, respectively;

[0021] S23, according to the fitness value F 适应度 , the multi-layer enhanced genetic algorithm module performs genetic operations, including selection, crossover, and mutation, to optimize the feed formula:

[0022]

[0023] Among them, P 新 For the optimized feed formula, P 旧 is the current recipe, α is the learning rate of the fitness gradient, is the gradient of the fitness function relative to the proportion of feed ingredients, β is the weight coefficient of the mutation operation, and M(P) is the disturbance vector based on random mutation;

[0024] S24. After each iteration, the fitness of the generated feed formula is evaluated:

[0025]

[0026] Among them, R is the weighted average difference value of the recipe fitness, F 目标 is the expected fitness value, F 实际 (j) is the fitness value of the jth recipe currently generated, λ is the regularization parameter, ||P j -P 参考 || 2 is the Euclidean distance between the current recipe and the reference recipe, and m is the number of generated recipes;

[0027] S25. When the R value is lower than the preset threshold, the optimization process is terminated and the final feed formula is output. Otherwise, the process returns to S23 for the next round of iteration until the formula optimization meets the requirements.

[0028] S26, transmitting the finally generated feed formula to the automatic proportioning device.

[0029] Optionally, the S3 specifically includes:

[0030] S31, the automatic proportioning device receives the final generated feed formula transmitted by the central control system, and the feed formula data includes the target ratio vector P of each feed component = {p1, p2, ..., p m}, where p i represents the ratio of the i-th feed component, m is the total number of feed components, and the automatic proportioning device takes this vector as input to start the proportioning operation;

[0031] S32. The automatic proportioning device uses adaptive microfluidic control technology to control the flow rate of each feed component through a microfluidic control unit. The flow rate regulation process adopts nonlinear dynamic control:

[0032]

[0033] Among them, v i (t) is the flow rate of the ith component at time t, V 基准 is the reference flow rate, α is the flow rate adjustment parameter, p i (t) is the real-time ratio of the i-th component at time t, is the mean value of the proportion of each component, σ p is the standard deviation of the proportion of each component;

[0034] S33. The automated proportioning device uses a multiphase flow mixer to dynamically mix the components flowing through the microfluidic pipeline. The mixing process is described by the multivariable fluid dynamics equation:

[0035]

[0036] Where C(t) is the concentration of mixed feed at time t, c i (τ) is the instantaneous concentration of the i-th component at time τ, h i (τ) is the mixing efficiency function of the i-th component, which reflects the mixing effect of different components in the multiphase flow mixer, v i (τ) is the flow rate of the i-th component at time τ;

[0037] S34. The mixed feed is transported to the central storage bin through the outlet of the automatic proportioning device. The feedback control system of the automatic proportioning device monitors the uniformity of the mixed feed in real time:

[0038]

[0039] Among them, ΔC(t) is the mixed feed concentration that needs to be adjusted at time t, C 目标 is the desired mixed concentration, γ is the concentration adjustment coefficient, and η is the adjustment coefficient of the concentration change rate;

[0040] S35. After the mixing is completed, the automatic proportioning device transmits the status information of the mixed feed, including the adjustment of the final mixing concentration C(t) and the component ratio P, to the central control system, and the central control system records and stores the relevant data.

[0041] Optionally, the S4 specifically includes:

[0042] S41. The feed trough sensor monitors the remaining feed amount in each feed trough in the pig house in real time. The sensor transmits the remaining feed amount data L(t) in the feed trough as input data to the central control system. The central control system uses the received L(t) data to determine whether the current feed amount is lower than the preset feed amount threshold L 阈值 ;

[0043] S42, when the central control system determines that the amount of feed in the feed trough is lower than L according to the L(t) data 阈值 When the central control system uses the judgment result as a trigger condition, it automatically activates the feed conveying device, and the feed conveying device starts to perform the conveying operation of the final mixed feed generated by the automatic proportioning device, and conveys the feed from the central storage bin to the feed troughs of each pig house;

[0044] S43. During the conveying process, the feed conveying device dynamically adjusts the feed conveying flow rate v according to the real-time feed quantity data L(t) provided by the central control system. 输送 (t), the adjustment of flow rate depends on the real-time monitored L(t) data, so that the flow rate can be adaptively adjusted according to the current demand;

[0045] S44, the feed conveying device continuously monitors the pressure P(t) in the conveying pipeline through the pressure sensor. When the pressure P(t) exceeds the preset pressure threshold P 阈值 When the pressure reaches 0.05, the central control system automatically activates the dredging function based on the pressure data to clear the blockage in the pipeline and restore normal transportation conditions;

[0046] S45. After the feed is transported, the central control system combines the feed volume L(t) in the feed trough fed back by the sensor and the pressure data P(t) recorded during the transport process to confirm that the feed has been successfully transported as required and has reached the preset feed volume L 目标 .

[0047] Optionally, the S5 specifically includes:

[0048] S51, the central control system receives the pig house environmental condition data E(t) and the pigs' eating behavior data, as well as the pigs' eating frequency and eating amount behavior parameters in real time. The central control system combines the recorded feed amount data (L(t) in the feed trough and the pressure data P(t) during the transportation process to generate the basic strategy for current feed addition, and determines whether the current feed addition frequency and feeding amount need to be adjusted;

[0049] S52, based on the received feeding behavior data and environmental condition data, the central control system dynamically calculates the frequency f of each feed addition. 添加 (t) and the amount of delivery M 添加 (t):

[0050]

[0051]

[0052] Among them, f 基准 is the reference added frequency, κ is the frequency adjustment coefficient, ΔL(t)=L 目标 -L(t) is the difference between the amount of feed in the feed trough and the target amount of feed, M 基准 is the base release amount, λ is the release amount adjustment coefficient, E(t) is the environmental condition data at time t, E 基准 is the baseline environmental condition data;

[0053] S53, the central control system further combines the special needs of individual pigs to start the differentiated feeding function, which is based on the individual health data of the pigs. i (t) Calculate individualized feed addition frequency and amount:

[0054]

[0055] Among them, M 个体(t) is the personalized amount of pigs delivered at time t, μ is the health status adjustment coefficient, H 基准 is the baseline health status data, H i (t) represents the health status parameter set of the i-th pig at time t;

[0056] S54, after the differentiated feeding is completed, the central control system integrates the multi-dimensional data analysis module to analyze the eating behavior data E(t), environmental condition data L(t) and health status data H i (t) Perform comprehensive analysis to identify possible abnormal patterns and optimize feeding strategies, which are recorded and stored in the central data storage module.

[0057] Optionally, the S6 specifically includes:

[0058] S61. After each feed addition is completed, the central control system receives status feedback from the conveying device, confirms that the feed addition process has ended, and automatically starts the cleaning device, which generates high-frequency vibration through an ultrasonic generator, and the frequency is set within the optimal cleaning range to form a cavitation effect on the inner wall of the conveying pipe and the feeding device to remove residual feed substances;

[0059] S62. During the cleaning process, the cleaning device monitors the quality of residual feed in the conveying pipeline in real time, and dynamically adjusts the ultrasonic power through adaptive ultrasonic power regulation technology to meet the removal requirements of different residues and optimize the cleaning effect;

[0060] S63. While completing the ultrasonic cleaning, the cleaning device automatically starts the nano-coating spraying system to spray the nano-coating on the inner wall of the conveying pipe and the feeding equipment. The nano-coating effectively prevents the attachment of future pollutants by forming a low surface energy structure and self-cleaning characteristics;

[0061] S64, the nano coating thickness control system in the cleaning device monitors the thickness of the coating in real time during the spraying process and makes dynamic adjustments according to the ultrasonic power during the cleaning process;

[0062] S65. After the cleaning and coating spraying are completed, the central control system receives feedback data from the cleaning device to confirm that the inner wall of the equipment has reached the set cleaning standard.

[0063] Optionally, the S7 specifically includes:

[0064] S71. The central control system receives and integrates the data E(t), feed formula data P(t), pig eating behavior data B(t), and cleaning equipment data C(t) from the environmental monitoring device, transmits them to the data storage module of the central control system in real time, and performs preliminary sorting and storage to form the original data set D. 原始 (t);

[0065] S72. In the data storage module, the system stores the original data set D 原始 (t) Perform preprocessing, including data denoising, standardization, and missing value filling, to generate a preprocessed multidimensional dataset D 处理 (t);

[0066] S73, the data storage module stores the preprocessed multidimensional data set D 处理 (t) Provided to the multi-perspective integrated learning algorithm module, through the integrated learning method, a comprehensive cross-analysis of data from different sources is performed to establish a correlation model between the data:

[0067]

[0068] Among them, R 关联 (i,j) represents the correlation between data source i and data source j, D i (t) and D j (t) represent the preprocessed data sets of the i-th and j-th data sources at time t, respectively, k is the kth correlation function, w k is the weight of the kth correlation function, n is the number of correlation functions used;

[0069] S74. Based on the correlation analysis, the system further uses dynamic analysis methods to generate the optimal feeding strategy S through a multi-perspective integrated learning algorithm. 优化 (t);

[0070] S75, the central control system according to the optimal feeding strategy S 优化 (t) Adjust feed formula and feeding plan in real time to match feeding strategy with current breeding conditions, and dynamically update feeding strategy through continuous monitoring and analysis of data to maintain the optimal state of feed formula;

[0071] S76. After executing the adjusted feeding plan, the central control system stores all adjustment data, analysis results and execution effect data in the data storage module to form a historical data set D 历史 , for future strategy optimization and system improvement.

[0072] Optionally, the following devices are included:

[0073] Central control system: responsible for receiving, processing and analyzing data from different sensors and subsystems, generating and optimizing feeding strategies, and adjusting the operating parameters of each subsystem in real time;

[0074] Environmental monitoring device: real-time monitoring of environmental parameters in the pig house, including temperature, humidity, and air quality, and transmits data to the central control system for optimizing feed addition strategies and adjusting the feeding environment;

[0075] Feed trough sensor: monitors the remaining feed in the feed trough, transmits feed quantity data to the central control system, and determines whether the feed addition process needs to be started;

[0076] Feed conveying device: conveys feed from the central storage bin to the feed troughs in each pig house, and dynamically adjusts the conveying speed according to the instructions of the central control system;

[0077] Automatic proportioning device: According to the feed formula generated by the central control system, the proportion of each feed component is controlled and dynamically mixed. The mixed feed is stored in the central storage bin for use by the feed conveying device;

[0078] Cleaning device: Combining ultrasonic cleaning and nano-coating technology, it cleans the conveying pipeline and the inner wall of the equipment after each feed addition, prevents the adhesion of pollutants, and maintains the cleanliness and stability of the equipment;

[0079] Data storage module: stores real-time data from various sensors and subsystems, including environmental parameters, feed volume in the feed trough, pressure data, and cleaning process data, for analysis and strategy optimization by the central control system;

[0080] User interface: allows farm managers to view the system's operating status, feeding data and analysis results in real time, and to manually adjust system parameters.

[0081] The beneficial effects of the present invention are:

[0082] The present invention utilizes a central control system combined with an environmental monitoring device and a feed trough sensor to achieve real-time monitoring and analysis of multi-dimensional data such as the pig house environment, the amount of feed in the feed trough, and the health status of pigs. The feed formula generated and dynamically adjusted based on these data can accurately match the growth needs of pigs and environmental changes, avoiding the problems of inaccurate feed ratios and unbalanced nutrition in traditional methods, thereby improving the health level and growth rate of pigs.

[0083] The present invention realizes the automation of the entire process from feed proportioning to feed delivery through an automated proportioning device and a feed conveying device, thereby reducing manpower input and operational errors. The automated system can accurately control the frequency and amount of feed delivery according to the pigs' eating behavior and the real-time situation in the feed trough, thereby ensuring the continuous supply and rational use of feed, and greatly improving the overall operational efficiency of the farm. At the same time, the central control system has a differentiated feeding function, which can adjust the frequency and amount of feed addition according to the special needs of individual pigs, thereby realizing personalized feed management. Through this precise differentiated feeding, the nutritional needs of different individuals can be met, promoting the healthy growth of the pig herd as a whole, and reducing the probability of disease occurrence and the waste of resources.

[0084] The present invention automatically completes the cleaning and maintenance of the conveying pipeline and feeding equipment by integrating an ultrasonic cleaning device and a nano-coating spraying system. Ultrasonic cleaning can completely remove residual feed materials, and the nano-coating prevents the adhesion of pollutants, thereby maintaining the long-term cleanliness and stable operation of the equipment. Compared with traditional manual cleaning, the present invention significantly reduces the risk of equipment contamination and failure, extends the service life of the equipment, and reduces maintenance costs. Through the data storage and multi-dimensional data analysis modules of the central control system, the real-time data of each link is comprehensively processed and analyzed to form a data-driven feeding strategy optimization mechanism. Through the accumulation and analysis of historical data, the system can continuously optimize various parameters in the breeding process, realize the intelligence and refinement of breeding management, and further improve economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0086] Figure 1 This is a flow chart of a method and device for automatically adding feed to pigs proposed by the present invention;

[0087] Figure 2 It is a flow chart of feed proportioning and mixing of the automatic proportioning device in the present invention;

[0088] Figure 3 This is a data processing and optimization flow chart for the data storage and multidimensional data analysis modules in the present invention. DETAILED DESCRIPTION

[0089] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention.

[0090] refer to Figure 1-3 , a method and device for automatically adding pig feed to feed, comprising the following steps:

[0091] S1. Use an environmental monitoring device with integrated gas sensors to monitor the temperature, humidity, air quality and concentration of harmful gases in the pig house in real time, and transmit all monitoring data to the central control system;

[0092] S2. The central control system starts the built-in multi-layer enhanced genetic algorithm module based on the received environmental parameters and the growth stage and health status of the pigs. Through the adaptive optimization strategy, it dynamically generates and adjusts the feed formula suitable for the current conditions to match the formula with the environment and growth requirements.

[0093] S3, the automated proportioning device receives the feed formula generated by the central control system and controls the proportion and mixing process of each feed component. The automated proportioning device uses adaptive microfluidic control technology to dynamically achieve accurate mixing of feed components and stores the mixed feed in a central storage bin;

[0094] S4. The feed trough sensor continuously monitors the remaining feed in each feed trough in the pig house. When the feed amount is lower than the preset value, the central control system automatically activates the feed conveying device to convey the mixed feed from the central storage bin to the feed troughs in each pig house. The conveying device has an automatic unblocking function to prevent feeding interruption caused by feed blockage.

[0095] S5. The central control system analyzes the pigs’ eating behavior data and pig house environmental conditions in real time, and automatically adjusts the feed addition frequency and amount. The central control system also has a differentiated feeding function, which can be adjusted according to the special needs of individual pigs to meet the nutritional needs of different individuals.

[0096] S6. After each feed addition, the central control system automatically starts the cleaning device, which combines ultrasonic cleaning and nano-coating technology to remove residual feed in the delivery pipeline and feeding equipment through ultrasonic vibration, and uses nano-coating to prevent contaminants from adhering to maintain the cleanliness and stability of the equipment;

[0097] S7. The central control system stores all environmental monitoring data, feed formula data and pigs’ eating behavior data in the data storage module of the central control system. It also conducts a comprehensive cross-analysis of information from different data sources through a dynamic analysis method based on a multi-perspective integrated learning algorithm to generate the optimal feeding strategy, and adjusts the feed formula and feeding plan in real time to adapt to changing breeding conditions.

[0098] In this implementation, S2 specifically includes:

[0099] S21, the central control system receives the environmental parameter data transmitted by the environmental monitoring device, and simultaneously obtains the growth stage and health status data of the pigs, and transmits them as multi-dimensional input data X to the multi-layer enhanced genetic algorithm module, where X includes a set of all relevant parameters;

[0100] S22, in the multi-layer enhanced genetic algorithm module, the input multi-dimensional data X is transformed into a high-dimensional space, and the fitness function F is used to calculate the 适应度 Calculate the initial fitness value for each feed recipe:

[0101]

[0102] Where P = {p1, p2,, p m} represents the component ratio vector of the current feed formula, wi is the weight of the i-th factor, f i (x i ) is the influence function of the i-th environment or growth parameter, g i (p i ) is the effect function of feed ingredients on pig growth, θ i is the phase angle of the i-th factor, which is used to adjust the interactive effect between environmental parameters and feed ingredients, n and m are the number of environmental parameters and feed ingredients, respectively;

[0103] S23, according to the fitness value F 适应度 , the multi-layer enhanced genetic algorithm module performs genetic operations, including selection, crossover, and mutation, to optimize the feed formula:

[0104]

[0105] Among them, P 新 For the optimized feed formula, P 旧 is the current recipe, α is the learning rate of the fitness gradient, is the gradient of the fitness function relative to the proportion of feed ingredients, β is the weight coefficient of the mutation operation, and M(P) is the disturbance vector based on random mutation;

[0106] S24. After each iteration, the fitness of the generated feed formula is evaluated:

[0107]

[0108] Among them, R is the weighted average difference value of the recipe fitness, F 目标 is the expected fitness value, F 实际 (j) is the fitness value of the jth recipe currently generated, λ is the regularization parameter, ∥P j -P 参考 ∥ 2 is the Euclidean distance between the current recipe and the reference recipe, and m is the number of generated recipes;

[0109] S25. When the R value is lower than the preset threshold, the optimization process is terminated and the final feed formula is output. Otherwise, the process returns to S23 for the next round of iteration until the formula optimization meets the requirements.

[0110] S26, transmitting the finally generated feed formula to the automatic proportioning device.

[0111] In this implementation, S3 specifically includes:

[0112] S31, the automatic proportioning device receives the final generated feed formula transmitted by the central control system, and the feed formula data includes the target ratio vector P of each feed component = {p1, p2, ..., pm}, where p i represents the ratio of the i-th feed component, m is the total number of feed components, and the automatic proportioning device takes this vector as input to start the proportioning operation;

[0113] S32. The automatic proportioning device uses adaptive microfluidic control technology to control the flow rate of each feed component through a microfluidic control unit. The flow rate regulation process adopts nonlinear dynamic control:

[0114]

[0115] Among them, v i (t) is the flow rate of the ith component at time t, v 基准 is the reference flow rate, α is the flow rate adjustment parameter, p i (t) is the real-time ratio of the i-th component at time t, is the mean value of the proportion of each component, σ p is the standard deviation of the proportion of each component;

[0116] S33. The automated proportioning device uses a multiphase flow mixer to dynamically mix the components flowing through the microfluidic pipeline. The mixing process is described by the multivariable fluid dynamics equation:

[0117]

[0118] Where C(t) is the concentration of mixed feed at time t, c i (τ) is the instantaneous concentration of the i-th component at time τ, h i (τ) is the mixing efficiency function of the i-th component, which reflects the mixing effect of different components in the multiphase flow mixer, v i (τ) is the flow rate of the i-th component at time τ;

[0119] S34. The mixed feed is transported to the central storage bin through the outlet of the automatic proportioning device. The feedback control system of the automatic proportioning device monitors the uniformity of the mixed feed in real time:

[0120]

[0121] Among them, ΔC(t) is the mixed feed concentration that needs to be adjusted at time t, C 目标 is the desired mixed concentration, γ is the concentration adjustment coefficient, and η is the adjustment coefficient of the concentration change rate;

[0122] S35. After the mixing is completed, the automatic proportioning device transmits the status information of the mixed feed, including the adjustment of the final mixing concentration C(t) and the component ratio P, to the central control system, and the central control system records and stores the relevant data.

[0123] In this implementation, S4 specifically includes:

[0124] S41. The feed trough sensor monitors the remaining feed amount in each feed trough in the pig house in real time. The sensor transmits the remaining feed amount data L(t) in the feed trough as input data to the central control system. The central control system uses the received L(t) data to determine whether the current feed amount is lower than the preset feed amount threshold L 阈值 ;

[0125] S42, when the central control system determines that the amount of feed in the feed trough is lower than L according to the L(t) data 阈值 When the central control system uses the judgment result as a trigger condition, it automatically activates the feed conveying device, and the feed conveying device starts to perform the conveying operation of the final mixed feed generated by the automatic proportioning device, and conveys the feed from the central storage bin to the feed troughs of each pig house;

[0126] S43. During the conveying process, the feed conveying device dynamically adjusts the feed conveying flow rate v according to the real-time feed quantity data L(t) provided by the central control system. 输送 (t), the adjustment of flow rate depends on the real-time monitored L(t) data, so that the flow rate can be adaptively adjusted according to the current demand;

[0127] S44, the feed conveying device continuously monitors the pressure P(t) in the conveying pipeline through the pressure sensor. When the pressure P(t) exceeds the preset pressure threshold P 阈值 When the pressure reaches 0.05, the central control system automatically activates the dredging function based on the pressure data to clear the blockage in the pipeline and restore normal transportation conditions;

[0128] S45. After the feed is transported, the central control system combines the feed volume L(t) in the feed trough fed back by the sensor and the pressure data P(t) recorded during the transport process to confirm that the feed has been successfully transported as required and has reached the preset feed volume L 目标 .

[0129] In this implementation manner, S5 specifically includes:

[0130] S51, the central control system receives the pig house environmental condition data E(t) and the pigs' eating behavior data, as well as the pigs' eating frequency and eating amount behavior parameters in real time. The central control system combines the recorded feed amount data (L(t) in the feed trough and the pressure data P(t) during the transportation process to generate the basic strategy for current feed addition, and determines whether the current feed addition frequency and feeding amount need to be adjusted;

[0131] S52, based on the received feeding behavior data and environmental condition data, the central control system dynamically calculates the frequency f of each feed addition. 添加(t) and the amount of delivery M 添加 (t):

[0132]

[0133]

[0134] Among them, f 基准 is the reference added frequency, κ is the frequency adjustment coefficient, ΔL(t)=L 目标 -L(t) is the difference between the amount of feed in the feed trough and the target amount of feed, M 基准 is the base release amount, λ is the release amount adjustment coefficient, E(t) is the environmental condition data at time t, E 基准 is the baseline environmental condition data;

[0135] S53, the central control system further combines the special needs of individual pigs to start the differentiated feeding function, which is based on the individual health data of the pigs. i (t) Calculate individualized feed addition frequency and amount:

[0136]

[0137] Among them, M 个体 (t) is the personalized amount of pigs delivered at time t, μ is the health status adjustment coefficient, H 基准 is the baseline health status data, H i (t) represents the health status parameter set of the i-th pig at time t;

[0138] S54, after the differentiated feeding is completed, the central control system integrates the multi-dimensional data analysis module to analyze the eating behavior data E(t), environmental condition data L(t) and health status data H i (t) Perform comprehensive analysis to identify possible abnormal patterns and optimize feeding strategies, which are recorded and stored in the central data storage module.

[0139] In this implementation manner, S6 specifically includes:

[0140] S61. After each feed addition is completed, the central control system receives status feedback from the conveying device, confirms that the feed addition process has ended, and automatically starts the cleaning device, which generates high-frequency vibration through an ultrasonic generator, and the frequency is set within the optimal cleaning range to form a cavitation effect on the inner wall of the conveying pipe and the feeding device to remove residual feed substances;

[0141] S62. During the cleaning process, the cleaning device monitors the quality of residual feed in the conveying pipeline in real time, and dynamically adjusts the ultrasonic power through adaptive ultrasonic power regulation technology to meet the removal requirements of different residues and optimize the cleaning effect;

[0142] S63. While completing the ultrasonic cleaning, the cleaning device automatically starts the nano-coating spraying system to spray the nano-coating on the inner wall of the conveying pipe and the feeding equipment. The nano-coating effectively prevents the attachment of future pollutants by forming a low surface energy structure and self-cleaning characteristics;

[0143] S64, the nano coating thickness control system in the cleaning device monitors the thickness of the coating in real time during the spraying process and makes dynamic adjustments according to the ultrasonic power during the cleaning process;

[0144] S65. After the cleaning and coating spraying are completed, the central control system receives feedback data from the cleaning device to confirm that the inner wall of the equipment has reached the set cleaning standard.

[0145] In this implementation manner, the S7 specifically includes:

[0146] S71. The central control system receives and integrates the data E(t), feed formula data P(t), pig eating behavior data B(t), and cleaning equipment data C(t) from the environmental monitoring device, transmits them to the data storage module of the central control system in real time, and performs preliminary sorting and storage to form the original data set D. 原始 (t);

[0147] S72. In the data storage module, the system stores the original data set D 原始 (t) Perform preprocessing, including data denoising, standardization, and missing value filling, to generate a preprocessed multidimensional dataset D 处理 (t);

[0148] S73, the data storage module stores the preprocessed multidimensional data set D 处理 (t) Provided to the multi-perspective integrated learning algorithm module, through the integrated learning method, a comprehensive cross-analysis of data from different sources is performed to establish a correlation model between the data:

[0149]

[0150] Among them, R 关联 (i,j) represents the correlation between data source i and data source j, D i (t) and D j (t) represent the preprocessed data sets of the i-th and j-th data sources at time t, respectively, k is the kth correlation function, w kis the weight of the kth correlation function, n is the number of correlation functions used;

[0151] S74. Based on the correlation analysis, the system further uses dynamic analysis methods to generate the optimal feeding strategy S through a multi-perspective integrated learning algorithm. 优化 (t);

[0152] S75, the central control system according to the optimal feeding strategy S 优化 (t) Adjust feed formula and feeding plan in real time to match feeding strategy with current breeding conditions, and dynamically update feeding strategy through continuous monitoring and analysis of data to maintain the optimal state of feed formula;

[0153] S76. After executing the adjusted feeding plan, the central control system stores all adjustment data, analysis results and execution effect data in the data storage module to form a historical data set D 历史 , for future strategy optimization and system improvement.

[0154] In this embodiment, the following devices are included:

[0155] Central control system: responsible for receiving, processing and analyzing data from different sensors and subsystems, generating and optimizing feeding strategies, and adjusting the operating parameters of each subsystem in real time;

[0156] Environmental monitoring device: real-time monitoring of environmental parameters in the pig house, including temperature, humidity, and air quality, and transmits data to the central control system for optimizing feed addition strategies and adjusting the feeding environment;

[0157] Feed trough sensor: monitors the remaining feed in the feed trough, transmits feed quantity data to the central control system, and determines whether the feed addition process needs to be started;

[0158] Feed conveying device: conveys feed from the central storage bin to the feed troughs in each pig house, and dynamically adjusts the conveying speed according to the instructions of the central control system;

[0159] Automatic proportioning device: According to the feed formula generated by the central control system, the proportion of each feed component is controlled and dynamically mixed. The mixed feed is stored in the central storage bin for use by the feed conveying device;

[0160] Cleaning device: Combining ultrasonic cleaning and nano-coating technology, it cleans the conveying pipeline and the inner wall of the equipment after each feed addition, prevents the adhesion of pollutants, and maintains the cleanliness and stability of the equipment;

[0161] Data storage module: stores real-time data from various sensors and subsystems, including environmental parameters, feed volume in the feed trough, pressure data, and cleaning process data, for analysis and strategy optimization by the central control system;

[0162] User interface: allows farm managers to view the system's operating status, feeding data and analysis results in real time, and to manually adjust system parameters.

[0163] Embodiment 1:

[0164] In order to verify the feasibility of the present invention in implementation, the present invention is applied to a large pig farm, which raises thousands of pigs. In the breeding process, there are problems such as feed waste, inaccurate feed management, unbalanced nutrition intake of pigs, and difficulty in cleaning and maintaining equipment. In order to improve breeding efficiency, reduce feed waste, and ensure the healthy growth of pigs, the pig farm introduced the automatic pig feed addition feeding method and related devices of the present invention.

[0165] In this scenario, the manager of the pig farm realizes the full process automation of feed management by installing the system described in the present invention, including a central control system, an environmental monitoring device, a feed trough sensor, a feed conveying device, an automatic proportioning device, a cleaning device and a data storage module. The environmental monitoring device monitors the temperature, humidity, air quality and other environmental parameters in the pig house in real time, and transmits these data to the central control system. At the same time, the feed trough sensor monitors the remaining feed in each feed trough. After receiving these data, the central control system dynamically generates the most suitable feed formula according to the growth stage and health status of the pigs and the current environmental conditions. After receiving the feed formula, the automatic proportioning device accurately controls the proportion of each feed component and performs dynamic mixing. The mixed feed is automatically transported to the feed trough of each pig house through the feed conveying device.

[0166] In actual application, every morning, the central control system automatically analyzes the feed consumption of the previous day and the eating behavior of the pigs, and generates a feed delivery strategy for the day. At 8 a.m., the system starts the feed addition program, and the automatic proportioning device starts to mix the feed according to the generated formula and delivers the feed to the feed trough in the pig house through the conveying pipeline. The feed trough sensor monitors the amount of feed in the feed trough in real time. When it detects that the feed is insufficient, the central control system will automatically trigger the program to add feed again to ensure that the pigs have sufficient feed supply at any time.

[0167] Before using the automatic pig feed feeding system of the present invention, the feed waste rate of the pig farm was as high as 12%. Due to uneven feed delivery, some pigs did not get enough nutrition, resulting in slow growth and a long breeding cycle. At the same time, due to incomplete equipment cleaning, feed often remained in the feed delivery pipeline and feeding equipment, resulting in frequent equipment failures, requiring at least 4 shutdowns per month for maintenance.

[0168] After the introduction of the invention, after a six-month application test, the feed waste rate dropped significantly to 3%, the average growth rate of pigs increased by 15%, and the breeding cycle was shortened by about 10 days. At the same time, the efficiency of equipment cleaning and maintenance was greatly improved, the number of monthly maintenance times was reduced to 1, and the equipment failure rate was reduced by 70%. The system's cleaning device automatically cleans the delivery pipeline and the inner wall of the equipment after each feed addition through ultrasonic cleaning and nano-coating spraying, ensuring the cleanliness of the equipment and long-term stable operation.

[0169] Data analysis based on a one-month cycle shows that after adopting the present invention, feed utilization has increased by about 18%. Feed consumption has dropped from 25 tons per month to 21 tons, while the average weight growth rate of pigs has increased from 0.8 kg per day to 1 kg. This series of data proves that the present invention not only solves the problems of feed waste and inaccurate management, but also significantly improves the growth rate and health level of pigs, and ultimately greatly improves the economic benefits of the farm. The differentiated feeding function has also been fully verified in practice. The system can adjust the feed formula and amount according to the special health needs of individual pigs, reducing the imbalance caused by individual differences in the pig herd. The data shows that after using the system, the weight growth rate of pigs in poor health increased by about 12%, their health status improved significantly, and the incidence rate decreased by 20%.

[0170] Table 1 Comparative analysis of various indicators before and after the application of the present invention in pig farms

[0171]

[0172]

[0173] It can be seen from the data in the above table that after applying the automated and intelligent feed management system of the present invention, all operating indicators of the pig farm have been significantly improved. The feed waste rate dropped from 12% to 3%, a reduction of 75%, indicating that the system is very effective in reducing feed waste and improving feed utilization. The average growth rate of pigs increased from 0.8 kg / day to 1.0 kg / day, an increase of 25%, which shows that the system can better meet the nutritional needs of pigs and promote their growth. In terms of the breeding cycle, due to the increase in the growth rate of pigs, the overall breeding cycle was shortened from about 150 days to about 140 days, a reduction of 10 days. This change means that the farm can complete a breeding cycle faster, thereby improving overall production efficiency. At the same time, although the growth rate and health of pigs have improved, the monthly feed consumption has decreased from 25 tons to 21 tons, a decrease of 4 tons, which further proves the advantage of the system in the efficient use of feed resources. Equipment maintenance efficiency has also been significantly improved. The equipment failure rate and cleaning and maintenance times were reduced from 4 times per month to 1 time per month, indicating that the system's automated measures for equipment cleaning and maintenance effectively extended the service life of the equipment, reduced the frequency of failures, and significantly reduced the cost of equipment maintenance. Overall, these data show that the present invention significantly improves the operational efficiency of pig farms, reduces costs, and improves the health and growth performance of pigs.

[0174] In summary, the present invention is significantly superior to the existing technology in terms of the accuracy of feed management, improvement of breeding efficiency, realization of personalized feeding, high efficiency of equipment cleaning and maintenance, and data-driven intelligent management. It effectively solves many problems in traditional breeding methods and achieves the goals of improving breeding efficiency, reducing costs and ensuring the health of pigs.

[0175] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for automatically adding feed to pigs, characterized in that: The steps include: S1. Use an environmental monitoring device with integrated gas sensors to monitor the temperature, humidity, air quality and concentration of harmful gases in the pig house in real time, and transmit all monitoring data to the central control system; S2. The central control system starts the built-in multi-layer enhanced genetic algorithm module based on the received environmental parameters and the growth stage and health status of the pigs. Through the adaptive optimization strategy, it dynamically generates and adjusts the feed formula suitable for the current conditions to match the formula with the environment and growth requirements. S3, the automatic proportioning device receives the feed formula generated by the central control system and controls the proportion and mixing process of each feed component, wherein the automatic proportioning device adopts adaptive microfluidic control technology to dynamically achieve the mixing of feed components and stores the mixed feed in the central storage bin; S4. The feed trough sensor continuously monitors the remaining feed in each feed trough in the pig house. When the feed amount is lower than the preset value, the central control system automatically activates the feed conveying device to convey the mixed feed from the central storage bin to the feed troughs in each pig house. The conveying device has an automatic unblocking function to prevent feeding interruption caused by feed blockage. S5. The central control system analyzes the pigs’ eating behavior data and pig house environmental conditions in real time, and automatically adjusts the feed addition frequency and amount. The central control system also has a differentiated feeding function, which can be adjusted according to the special needs of individual pigs to meet the nutritional needs of different individuals. S6. After each feed addition, the central control system automatically starts the cleaning device, which combines ultrasonic cleaning and nano-coating technology to remove residual feed in the delivery pipeline and feeding equipment through ultrasonic vibration, and uses nano-coating to prevent contaminants from adhering to maintain the cleanliness and stability of the equipment; S7. The central control system stores all environmental monitoring data, feed formula data and pigs’ eating behavior data in the data storage module of the central control system. It also conducts a comprehensive cross-analysis of information from different data sources through a dynamic analysis method based on a multi-perspective integrated learning algorithm to generate the optimal feeding strategy, and adjusts the feed formula and feeding plan in real time to adapt to changing breeding conditions.

2. The method for automatically adding feed to pigs according to claim 1, characterized in that: The S2 specifically includes: S21, the central control system receives the environmental parameter data transmitted by the environmental monitoring device, and simultaneously obtains the growth stage and health status data of the pigs, and transmits them as multi-dimensional input data X to the multi-layer enhanced genetic algorithm module, where X includes a set of all relevant parameters; S22, in the multi-layer enhanced genetic algorithm module, the input multi-dimensional data X is transformed into a high-dimensional space, and the fitness function F is used to calculate the 适应度 Calculate the initial fitness value for each feed recipe: Where P = {p1, p2,, p m } represents the component ratio vector of the current feed formula, w i is the weight of the i-th factor, f i (x i ) is the influence function of the i-th environment or growth parameter, g i (p i ) is the effect function of feed ingredients on pig growth, θ i is the phase angle of the i-th factor, which is used to adjust the interactive effect between environmental parameters and feed ingredients, n and m are the number of environmental parameters and feed ingredients, respectively; S23, according to the fitness value F 适应度 , the multi-layer enhanced genetic algorithm module performs genetic operations, including selection, crossover, and mutation, to optimize the feed formula: Among them, P 新 For the optimized feed formula, P 旧 is the current recipe, α is the learning rate of the fitness gradient, is the gradient of the fitness function relative to the proportion of feed ingredients, β is the weight coefficient of the mutation operation, and M(P) is the disturbance vector based on random mutation; S24. After each iteration, the fitness of the generated feed formula is evaluated: Among them, R is the weighted average difference value of the recipe fitness, F 目标 is the expected fitness value, F 实际 (j) is the fitness value of the jth recipe currently generated, λ is the regularization parameter, ∥P j -P 参考 ∥ 2 is the Euclidean distance between the current recipe and the reference recipe, and m is the number of generated recipes; S25. When the R value is lower than the preset threshold, the optimization process is terminated and the final feed formula is output. Otherwise, the process returns to S23 for the next round of iteration until the formula optimization meets the requirements. S26, transmitting the finally generated feed formula to the automatic proportioning device.

3. The method for automatically adding feed to pigs according to claim 1, characterized in that: The S3 specifically includes: S31, the automatic proportioning device receives the final generated feed formula transmitted by the central control system, and the feed formula data includes the target ratio vector P of each feed component = {p1, p2, ..., p m }, where p i represents the ratio of the i-th feed component, m is the total number of feed components, and the automatic proportioning device takes this vector as input to start the proportioning operation; S32. The automatic proportioning device uses adaptive microfluidic control technology to control the flow rate of each feed component through a microfluidic control unit. The flow rate regulation process adopts nonlinear dynamic control: Among them, v i (t) is the flow rate of the ith component at time t, v 基准 is the reference flow rate, α is the flow rate adjustment parameter, p i (t) is the real-time ratio of the i-th component at time t, is the mean value of the proportion of each component, σ p is the standard deviation of the proportion of each component; S33. The automated proportioning device uses a multiphase flow mixer to dynamically mix the components flowing through the microfluidic pipeline. The mixing process is described by the multivariable fluid dynamics equation: Where C(t) is the concentration of mixed feed at time t, c i (τ) is the instantaneous concentration of the i-th component at time τ, h i (τ) is the mixing efficiency function of the i-th component, which reflects the mixing effect of different components in the multiphase flow mixer, v i (τ) is the flow rate of the i-th component at time τ; S34. The mixed feed is transported to the central storage bin through the outlet of the automatic proportioning device. The feedback control system of the automatic proportioning device monitors the uniformity of the mixed feed in real time: Among them, ΔC(t) is the mixed feed concentration that needs to be adjusted at time t, C 目标 is the desired mixed concentration, γ is the concentration adjustment coefficient, and η is the adjustment coefficient of the concentration change rate; S35. After the mixing is completed, the automatic proportioning device transmits the status information of the mixed feed, including the adjustment of the final mixing concentration C(t) and the component ratio P, to the central control system, and the central control system records and stores the relevant data.

4. The method for automatically adding feed to pigs according to claim 1, characterized in that: The S4 specifically includes: S41. The feed trough sensor monitors the remaining feed amount in each feed trough in the pig house in real time. The sensor transmits the remaining feed amount data L(t) in the feed trough as input data to the central control system. The central control system uses the received L(t) data to determine whether the current feed amount is lower than the preset feed amount threshold L 阈值 ; S42, when the central control system determines that the amount of feed in the feed trough is lower than L according to the L(t) data 阈值 When the central control system uses the judgment result as a trigger condition, it automatically activates the feed conveying device, and the feed conveying device starts to perform the conveying operation of the final mixed feed generated by the automatic proportioning device, and conveys the feed from the central storage bin to the feed troughs of each pig house; S43. During the conveying process, the feed conveying device dynamically adjusts the feed conveying flow rate v according to the real-time feed quantity data L(t) provided by the central control system. 输送 (t), the adjustment of flow rate depends on the real-time monitored L(t) data, so that the flow rate can be adaptively adjusted according to the current demand; S44, the feed conveying device continuously monitors the pressure P(t) in the conveying pipeline through the pressure sensor. When the pressure P(t) exceeds the preset pressure threshold P 阈值 When the pressure reaches 0.05, the central control system automatically activates the dredging function based on the pressure data to clear the blockage in the pipeline and restore normal transportation conditions; S45. After the feed is transported, the central control system combines the feed volume L(t) in the feed trough fed back by the sensor and the pressure data P(t) recorded during the transport process to confirm that the feed has been successfully transported as required and has reached the preset feed volume L 目标 .

5. The method for automatically adding feed to pigs according to claim 1, characterized in that: The S5 specifically includes: S51, the central control system receives the pig house environmental condition data E(t) and the pigs' eating behavior data, as well as the pigs' eating frequency and eating amount behavior parameters in real time. The central control system combines the recorded feed amount data (L(t) in the feed trough and the pressure data P(t) during the transportation process to generate the basic strategy for current feed addition, and determines whether the current feed addition frequency and feeding amount need to be adjusted; S52, based on the received feeding behavior data and environmental condition data, the central control system dynamically calculates the frequency f of each feed addition. 添加 (t) and the amount of delivery M 添加 (t): Among them, f 基准 is the reference added frequency, κ is the frequency adjustment coefficient, ΔL(t)=L 目标 -L(t) is the difference between the amount of feed in the feed trough and the target amount of feed, M 基准 is the base release amount, λ is the release amount adjustment coefficient, E(t) is the environmental condition data at time t, E 基准 is the baseline environmental condition data; S53, the central control system further combines the special needs of individual pigs to start the differentiated feeding function, which is based on the individual health data of the pigs. i (t) Calculate individualized feed addition frequency and amount: Among them, M 个体 (t) is the personalized amount of pigs delivered at time t, μ is the health status adjustment coefficient, H 基准 is the baseline health status data, H i (t) represents the health status parameter set of the i-th pig at time t; S54, after the differentiated feeding is completed, the central control system integrates the multi-dimensional data analysis module to analyze the eating behavior data E(t), environmental condition data L(t) and health status data H i (t) Perform comprehensive analysis to identify possible abnormal patterns and optimize feeding strategies, which are recorded and stored in the central data storage module.

6. The method for automatically adding feed to pigs according to claim 1, characterized in that: The S6 specifically includes: S61. After each feed addition is completed, the central control system receives status feedback from the conveying device, confirms that the feed addition process has ended, and automatically starts the cleaning device, which generates high-frequency vibration through an ultrasonic generator, and the frequency is set within the optimal cleaning range to form a cavitation effect on the inner wall of the conveying pipe and the feeding device to remove residual feed substances; S62. During the cleaning process, the cleaning device monitors the quality of residual feed in the conveying pipeline in real time, and dynamically adjusts the ultrasonic power through adaptive ultrasonic power regulation technology to meet the removal requirements of different residues and optimize the cleaning effect; S63. While completing the ultrasonic cleaning, the cleaning device automatically starts the nano-coating spraying system to spray the nano-coating on the inner wall of the conveying pipe and the feeding equipment. The nano-coating effectively prevents the attachment of future pollutants by forming a low surface energy structure and self-cleaning characteristics; S64, the nano coating thickness control system in the cleaning device monitors the thickness of the coating in real time during the spraying process and makes dynamic adjustments according to the ultrasonic power during the cleaning process; S65. After the cleaning and coating spraying are completed, the central control system receives feedback data from the cleaning device to confirm that the inner wall of the equipment has reached the set cleaning standard.

7. The method for automatically adding feed to pigs according to claim 1, characterized in that: The S7 specifically includes: S71. The central control system receives and integrates the data E(t), feed formula data P(t), pig eating behavior data B(t) and cleaning equipment data C(t) from the environmental monitoring device, transmits them to the data storage module of the central control system in real time, and performs preliminary sorting and storage to form the original data set D. 原始 (t); S72. In the data storage module, the system stores the original data set D 原始 (t) Perform preprocessing, including data denoising, standardization, and missing value filling, to generate a preprocessed multidimensional dataset D 处理 (t); S73, the data storage module stores the preprocessed multidimensional data set D 处理 (t) Provided to the multi-perspective integrated learning algorithm module, through the integrated learning method, a comprehensive cross-analysis of data from different sources is performed to establish a correlation model between the data: Among them, R 关联 (i,j) represents the correlation between data source i and data source j, D i (t) and D j (t) represent the preprocessed data sets of the i-th and j-th data sources at time t, respectively, k is the kth correlation function, w k is the weight of the kth correlation function, n is the number of correlation functions used; S74. Based on the correlation analysis, the system further uses dynamic analysis methods to generate the optimal feeding strategy S through a multi-perspective integrated learning algorithm. 优化 (t); S75, the central control system according to the optimal feeding strategy S 优化 (t) Adjust feed formula and feeding plan in real time to match feeding strategy with current breeding conditions, and dynamically update feeding strategy through continuous monitoring and analysis of data to maintain the optimal state of feed formula; S76. After executing the adjusted feeding plan, the central control system stores all adjustment data, analysis results and execution effect data in the data storage module to form a historical data set D 历史 , for future strategy optimization and system improvement.

8. An automatic feeding device for pig feed, characterized in that: Includes the following devices: Central control system: responsible for receiving, processing and analyzing data from different sensors and subsystems, generating and optimizing feeding strategies, and adjusting the operating parameters of each subsystem in real time; Environmental monitoring device: real-time monitoring of environmental parameters in the pig house, and transmission of data to the central control system for optimizing feed addition strategies and adjusting the feeding environment; Feed trough sensor: monitors the remaining feed in the feed trough, transmits feed quantity data to the central control system, and determines whether the feed addition process needs to be started; Feed conveying device: conveys feed from the central storage bin to the feed troughs in each pig house, and dynamically adjusts the conveying speed according to the instructions of the central control system; Automatic proportioning device: According to the feed formula generated by the central control system, the proportion of each feed component is controlled and dynamically mixed. The mixed feed is stored in the central storage bin for use by the feed conveying device; Cleaning device: Combining ultrasonic cleaning and nano-coating technology, it cleans the conveying pipeline and the inner wall of the equipment after each feed addition, prevents the adhesion of pollutants, and maintains the cleanliness and stability of the equipment; Data storage module: stores real-time data from various sensors and subsystems for central control system analysis and strategy optimization; User interface: allows farm managers to view the system's operating status, feeding data and analysis results in real time, and to manually adjust system parameters.

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