Pseudosciaena crocea feed processing and mixing method and device

Abstract

The invention provides a large yellow croaker feed processing and mixing method and device. The method provided by the invention comprises the following steps: determining a growth stage of the large yellow croaker; determining formula data of the large yellow croaker based on the growth stage; the intelligent control system determines processing parameters of the processing mixing system based on the formula data; the change state of the raw materials in the processing and mixing system is monitored in real time based on a sensor; the intelligent control system optimizes formula data of the pseudosciaena crocea and processing parameters of the processing and mixing system in real time according to the change state; and processing and mixing according to the formula data and the processing parameters of the processing and mixing system to obtain the large yellow croaker feed. According to the method and device provided by the invention, the formula data and the corresponding processing parameters are adjusted in time according to the growth stage and actual requirements of the large yellow croaker, accurate feeding of the feed for the large yellow croaker is realized, and growth and health of the large yellow croaker are guaranteed.

Description

Technical Field

[0001] The present application relates to the technical field of aquaculture, and in particular to a method and device for processing and mixing large yellow croaker feed. Background Art

[0002] Since yellow croaker has different nutritional requirements at different growth stages, special yellow croaker feed can provide appropriate protein, fat, vitamins and minerals according to its growth stage to ensure its healthy growth. In addition, with the development of feed technology, the process, formula and raw material selection of feed manufacturing are constantly innovating, and providing yellow croaker with better quality feed for yellow croaker farming has become a problem that must be solved.

[0003] The traditional yellow croaker feed processing and mixing method is based on fixed formula data to process yellow croaker feed. It is unable to adjust the formula data and corresponding processing parameters in time according to the growth stage and actual needs of the yellow croaker. In addition, the fixed formula data relies on experience, which may lead to unbalanced nutritional components of the yellow croaker feed, affect the growth and health of the yellow croaker, and cause feed waste.

[0004] Therefore, there is an urgent need for a method to timely adjust the formula data and corresponding processing parameters according to the growth stage and actual needs of large yellow croaker, so as to achieve accurate feeding of large yellow croaker feed and ensure the growth and health of large yellow croaker. Summary of the invention

[0005] In view of this, the present application provides a large yellow croaker feed processing and mixing method and device, which are used to timely adjust the formula data and corresponding processing parameters according to the growth stage and actual needs of the large yellow croaker, so as to achieve accurate feeding of the large yellow croaker feed and ensure the growth and health of the large yellow croaker.

[0006] Specifically, the present application is implemented through the following technical solutions: The first aspect of the present application provides a large yellow croaker feed processing and mixing method, the method comprising: Determine the growth stage of large yellow croaker; Determine the formula data of large yellow croaker based on the growth stage; the formula data includes the ratio of different raw materials and the size of different raw materials, and different growth stages correspond to different nutritional requirements; The intelligent control system determines the processing parameters of the processing and mixing system based on the formula data; wherein the processing and mixing system at least includes a grinding system and a mixing system, the order of raw materials entering the grinding system is determined according to the ratio in the formula data, and the grinding processing parameters of the grinding system are determined according to the size in the formula data; the mixing processing parameters of the mixing system are determined according to the ratio; Real-time monitoring of the changing state of the raw materials in the processing and mixing system based on sensors; The intelligent control system optimizes the recipe data of large yellow croaker and the processing parameters of the processing and mixing system in real time according to the changing state; Processing and mixing are carried out according to the formula data and the processing parameters of the processing and mixing system to obtain large yellow croaker feed.

[0007] The second aspect of the present application provides a large yellow croaker feed processing and mixing device, the device comprising an intelligent control system and a processing and mixing system connected to each other; wherein: The intelligent control system is used to determine the formula data of the large yellow croaker based on the growth stage of the large yellow croaker; the formula data includes the ratio of different raw materials and the size of different raw materials, and different growth stages correspond to different nutritional requirements; The intelligent control system is further used to determine the processing parameters of the processing and mixing system based on the formula data; wherein the processing and mixing system at least includes a grinding system and a mixing system, the order of raw materials entering the grinding system is determined according to the ratio in the formula data, and the grinding processing parameters of the grinding system are determined according to the size in the formula data; the mixing processing parameters of the mixing system are determined according to the ratio; The processing and mixing system is used to process and mix based on the formula data and the processing parameters to obtain large yellow croaker feed; The intelligent control system is also used to monitor the changing state of the raw materials in the processing and mixing system in real time based on sensors, and optimize the formula data and the processing parameters in real time based on the changing state.

[0008] The large yellow croaker feed processing and mixing method and device provided by the present application, in the first aspect, by being equipped with an intelligent control system, the intelligent control system can determine the formula data of the large yellow croaker and the processing parameters of the processing and mixing system according to the determined growth stage of the large yellow croaker, and perform processing and mixing based on the formula data and processing parameters. In this way, the large yellow croaker feed obtained by processing and mixing is nutritionally balanced, and can meet the needs of large yellow croaker at different growth stages. Compared with the traditional large yellow croaker feed processing and mixing method, which processes large yellow croaker feed based on fixed formula data, the present application will not cause feed waste, and ensure the growth and health of large yellow croaker. In the second aspect, by integrating multiple sensors in the processing and mixing system, multiple sensors monitor the changing state of raw materials in the processing and mixing system in real time, and the intelligent control system optimizes the formula data of large yellow croaker and the processing parameters of the processing and mixing system by analyzing and predicting the changing state monitored by the sensors. In this way, the formula data and processing parameters can be adjusted in real time and more accurately, so that the large yellow croaker feed obtained by processing and mixing can better meet the needs of large yellow croaker at different growth stages, reduce feed waste, improve production efficiency, and reduce costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1A flow chart of a large yellow croaker feed processing and mixing method provided in Example 1 of the present application; Figure 2 This is a schematic diagram of the structure of the large yellow croaker feed processing and mixing device provided in Example 2 of the present application. DETAILED DESCRIPTION

[0010] Exemplary embodiments will now be described in detail, examples of which are shown in the accompanying drawings. The implementations described in the following exemplary embodiments are not intended to represent all implementations consistent with the present application.

[0011] The terms used in this application are only for the purpose of describing specific embodiments and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in this article refers to and includes any or all possible combinations of one or more associated listed items.

[0012] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0013] Specific embodiments are given below to introduce the technical solution of the present application in detail.

[0014] Figure 1 This is a flow chart of the large yellow croaker feed processing and mixing method provided in Example 1 of this application. Figure 1 , the method provided in this embodiment may include: S101. Determine the growth stage of large yellow croaker.

[0015] Specifically, the growth stages of large yellow croaker characterize the physiological characteristics and demand changes of large yellow croaker during different development and growth processes, and different growth stages correspond to different nutritional requirements. The growth stages of large yellow croaker generally include the juvenile stage, the seedling stage and the adult stage. Among them, the juvenile stage has a weak ability to adapt to the environment, relies on high-energy and easily digestible feeds, and requires high protein (about 40-50%) and fat. In the seedling stage, large yellow croaker begins to gradually adapt to the water environment, begins to eat a variety of feeds, and slightly reduces the demand for protein (about 35-45%). In the adult stage, the digestibility and palatability requirements of the feed are improved, the growth rate gradually slows down, and the demand for protein is reduced to 30-40%. The demand for fat and vitamins is still important.

[0016] For example, the protein requirement in the feed for juvenile fish (corresponding to the initial weight of 12.8 grams for yellow croaker) is 48.3%, the protein requirement in the feed for fry (corresponding to the initial weight of 137.9 grams for yellow croaker) is 44.8%, and the protein requirement in the feed for adult fish (corresponding to the initial weight of 194.1 grams for yellow croaker) is 42.7%. The protein requirement for yellow croaker in the feed gradually decreases as the fish grows. As the fish matures, the protein requirement, which is the main nutrient in the feed, also gradually decreases.

[0017] In specific implementation, since large yellow croakers at different growth stages may show different body colors and spots (especially at the juvenile and adult stages), and the change rates of body length and weight of large yellow croakers at different growth stages are different (faster at the juvenile stage and slower at the adult stage), the growth stage of large yellow croakers can be determined by regularly measuring their body length and weight and observing their body color and spots.

[0018] Optionally, a camera can be installed in the intelligent control system to take photos of large yellow croaker, and the growth stage of large yellow croaker can be automatically identified through image recognition. The identification result of large yellow croaker can be directly obtained through the large model. On the other hand, the body color and spot features can also be extracted to obtain the first identification result, obtain the preliminary result of the growth stage, calculate the body length change rate and weight change rate of adjacent images, correct the first identification result based on the body length change rate and weight change rate, and obtain the accurate growth stage. Optionally, the large yellow croaker boundary is located in the captured image, the neighborhood area at a first distance outside the large yellow croaker boundary is determined, the first color within the large yellow croaker boundary and the second color within the neighborhood area are respectively identified, the large yellow croaker correction color is obtained based on the difference between the first color and the second color, and the color of the large yellow croaker in the correction color recognition image is identified. The area within the boundary is used as the second image, and the basic pixel color in the second image is identified, wherein the color of each pixel in the second image is determined, the color corresponding to the pixel with the most identical colors is the basic pixel color, the pixels corresponding to the colors different from the basic pixel color in the second image are connected to the adjacent pixels, and if the connection forms a closed shape, it is regarded as the identification target, and the identification target is a spot. All the identification targets in the second image are extracted, and the spot features such as color, size and shape of the identification targets are identified. The preliminary result of the growth stage is obtained according to the color and spot features of the large yellow croaker in the identified image.

[0019] Furthermore, the body length change rate and weight change rate of adjacent images are calculated, the boundary of the large yellow croaker is located in the captured image, the longest line connecting any two points of the large yellow croaker boundary is taken as the body length, the body length value is calculated, the area of ​​the large yellow croaker is calculated based on the large yellow croaker boundary, and the weight of the large yellow croaker is estimated; the body length values ​​of adjacent images are calculated, and if the body length value change of adjacent images is greater than or equal to a threshold, the two images are determined to be target images, the weight of the large yellow croaker in the target image is estimated respectively, the weight change rate and the body length change rate are calculated, and the preliminary result is corrected according to the weight change rate and the body length change rate to obtain the final correction result of the growth stage.

[0020] The method provided by the present application, in the first aspect, can directly obtain the preliminary results of the growth stage of large yellow croaker through the combination of large model and image recognition, greatly reducing manual participation and significantly improving the automation level of growth stage recognition. In addition, the preliminary results are corrected in combination with body length and weight changes, making the recognition results more accurate and reducing recognition errors. In addition to direct model recognition, the appearance characteristics such as body color and spots and the dynamic characteristics of body length and weight changes are also introduced. The comprehensive use of these multi-dimensional features can help the detection system to analyze the growth state of large yellow croaker more carefully, and is particularly suitable for identifying relatively small stage changes. In the second aspect, the correction color is calculated based on the difference in color inside and outside the boundary to adapt to the color deviation under different shooting conditions. At the same time, the change rate of physical characteristics such as body length and weight is used as a correction means to alleviate the interference of factors such as ambient light and angle on recognition accuracy, and adapt to a wider range of application scenarios. Using the body length and weight change rate of adjacent images as the basis for correction, dynamic monitoring of the growth stage can be achieved, the growth state of large yellow croaker can be reflected in real time, and it can be adjusted in time, especially in feeding management and feed formula adjustment. It can play a guiding role.

[0021] S102. Determine recipe data for large yellow croaker based on the growth stage; the recipe data includes ratios of different raw materials and sizes of different raw materials, and different growth stages correspond to different nutritional requirements.

[0022] Specifically, the formula data of large yellow croaker records the raw materials used to process and manufacture large yellow croaker feed, including the ratio of different raw materials and the sizes of different raw materials.

[0023] In a specific implementation, the formula data of large yellow croaker is determined based on the growth stage, including: determining the nutritional requirements of large yellow croaker based on the growth stage of large yellow croaker; the nutritional requirements include nutrients of different components; determining raw materials for providing nutrients based on the nutrients; determining the ratio and size of different raw materials based on the nutrients provided by the raw materials and the nutritional requirements.

[0024] Specifically, combined with the above description, the nutritional requirements of large yellow croaker are different at different growth stages. Nutrients of different components mainly include protein, carbohydrates and functional substances. The energy supply raw materials corresponding to nutrients of different components are different. The raw materials corresponding to protein are fish meal, soybean meal, and chlorella powder. The raw materials corresponding to carbohydrates are sweet potato powder, gluten powder, and barley flour. The raw materials corresponding to functional substances are astaxanthin and phospholipids.

[0025] In specific implementation, the corresponding nutritional requirements of the large yellow croaker are determined based on the determined growth stage of the large yellow croaker (for example, when the large yellow croaker is in the juvenile stage, it needs high protein and fat; when the large yellow croaker is in the fry stage, it needs high protein and appropriate fat and vitamins; when the large yellow croaker is in the adult stage, it needs high protein, fat and other nutrients). Furthermore, the corresponding raw materials are determined according to the nutrients included in the nutritional requirements of the large yellow croaker. The proportion and size of each raw material are determined based on the nutrients that each raw material can provide (protein provides amino acids, carbohydrates and fats provide energy, and functional substances provide trace elements and vitamins) and the total nutrients required by the large yellow croaker at the growth stage.

[0026] The method provided in the present application can improve the body color of large yellow croaker, reduce the fishy smell and control the muscle fat content by adding natural pigments such as astaxanthin and functional ingredients such as phospholipids to large yellow croaker feed. The addition of these ingredients makes the large yellow croaker feed more in line with the growth needs and market requirements of large yellow croaker.

[0027] S103, the intelligent control system determines the processing parameters of the processing and mixing system based on the recipe data; wherein the processing and mixing system includes at least a grinding system and a mixing system, the sequence of raw materials entering the grinding system is determined according to the ratio in the recipe data, and the grinding processing parameters of the grinding system are determined according to the size in the recipe data; the mixing processing parameters of the mixing system are determined according to the ratio.

[0028] Specifically, the processing and mixing system is used to process and mix the raw materials in the formula data to obtain large yellow croaker feed. The processing and mixing system includes a grinding system and a mixing system. The grinding system grinds the raw materials based on the raw material sequence and grinding processing parameters. The raw material sequence is determined according to the ratio of different raw materials in the formula data, and the grinding processing parameters are determined according to the sizes of different raw materials in the formula data. The mixing system mixes the raw materials ground by the grinding system based on the mixing processing parameters, and the mixing processing parameters are determined according to the ratio of different raw materials in the formula data.

[0029] In specific implementation, the intelligent control system determines the raw material sequence of the grinding system based on the ratio of different raw materials in the recipe data, and determines the grinding processing parameters of the grinding system and the mixing processing parameters of the mixing system based on the sizes of different raw materials in the recipe data. Further, the raw material sequence of the grinding system and the grinding processing parameters of the grinding system are determined as the processing parameters of the grinding system, the mixing processing parameters of the mixing system are determined as the processing parameters of the mixing system, and the processing parameters of the grinding system and the processing parameters of the mixing system are determined as the processing parameters of the processing mixing system.

[0030] It should be noted that the grinding system includes multiple subsystems, and the mixing system includes multiple subsystems. The grinding processing parameters of each subsystem in the grinding system are different, and the mixing processing parameters of each subsystem in the mixing system are also different. Each subsystem will be introduced below and will not be repeated here.

[0031] Optionally, the formula data can be specified to meet the nutrition required for the predicted growth stage, and the raw material name, raw material size that can meet the large yellow croaker at this growth stage, and the proportion of each raw material are configured to determine the gap between the initial performance of each raw material and the performance required in the formula data, and determine the processing steps that each raw material needs to go through based on the gap, and determine the processing parameters of each processing step based on the characteristics of each raw material, such as mixing time, processing temperature, etc. The final processing plan is generated based on the processing steps and processing parameters, and the processing plan can be determined by the connection method and processing time of the processing mixing system.

[0032] S104, monitoring the changing state of the raw materials in the processing and mixing system in real time based on sensors.

[0033] Specifically, the sensor is integrated into the processing and mixing system and connected to the intelligent control system. The sensors include multiple types, such as temperature sensors, humidity sensors, weight sensors, etc. It should be noted that since the processing and mixing system includes a grinding system and a mixing system, the raw materials need to be ground by the grinding system first and then mixed by the mixing system after entering the processing and mixing system. The grinding system and the mixing system process the raw materials differently, so the sensors used for monitoring are also different, and the changing states of the raw materials are also different.

[0034] In specific implementation, based on the target system (grinding system or mixing system) where the raw materials are located in the processing and mixing system, corresponding sensors are selected to monitor the changing state of the raw materials in the target system in real time.

[0035] The processing plan specifies the processing state that each raw material needs to reach in each processing step. Furthermore, according to the relationship between the real-time monitored change state and the target processing state in the processing plan and the remaining processing time under the processing step, the processing parameters are adjusted so that the target processing state can be achieved within the remaining processing time.

[0036] S105, the intelligent control system optimizes the recipe data of large yellow croaker and the processing parameters of the processing mixing system in real time according to the changing state.

[0037] In a specific implementation, the intelligent control system optimizes the recipe data of large yellow croaker and the processing parameters of the processing and mixing system in real time according to the changing state, including: the intelligent control system compares the changing state with the quality standards corresponding to different raw materials in the recipe data; adjusts the recipe data and the corresponding processing parameters based on the comparison result and the changing trend of the changing state along with the recipe data; when the changing state always exceeds the quality standard after adjusting a preset number of cycles, an alarm sounds an alarm to prompt the intelligent control system to be adjusted.

[0038] Specifically, during the entire processing and mixing process, sensors are used to monitor the changing state of raw materials in the processing and mixing system in real time (since the raw materials need to be processed by the grinding system and the mixing system respectively after entering the processing and mixing system, the changing state of the raw materials is different when different systems process the raw materials, and the corresponding quality parameters are also different, including particle size, moisture content, nutrients, etc.). These changing states are transmitted to the intelligent control system through sensors for analysis and processing. When quality problems are found or the changing state deviates from the set value corresponding to the quality standard, the alarm in the intelligent control system will immediately sound an alarm to prompt the operator to make adjustments. The operator can adjust the formula data of the large yellow croaker, the processing parameters of the processing and mixing system, or the equipment status according to the prompts of the intelligent control system to ensure that the large yellow croaker feed finally produced meets the quality standards.

[0039] In a specific implementation, in a possible implementation mode, based on the changing states of raw materials in the processing and mixing system monitored by multiple sensors, the intelligent control system comprehensively analyzes the changing states monitored by the multiple sensors. When quality problems are found or the overall changing state deviates from the set value corresponding to the quality standard, the processing and mixing system corresponding to the changing state that deviates from the set value by more than the preset threshold in all the changing states is determined as the processing and mixing system to be optimized, and the processing parameters of the processing and mixing system to be optimized and the formula data of large yellow croaker are optimized based on the analysis results of the intelligent control system. The synergistic relationship of multiple changing states can be taken into consideration through overall analysis, and complex processing and mixing processes can be handled. For example, if the temperature increase has a compound effect on humidity and viscosity, the overall analysis can focus on the correlation of these states at the same time, so as to more accurately determine the root cause of the deviation from the standard and optimize the entire processing and mixing process. Since some changing states may not directly affect the product quality when they deviate from the set value alone, but if multiple changing states deviate at the same time, it may cause quality problems. Overall analysis can identify the impact of this combination of multiple states and reduce false alarms caused by a single abnormal state. In the case where multiple state changes affect each other, overall analysis can identify which states need to be adjusted synchronously to achieve the best effect. This method is particularly effective when multiple states are mutually constrained. It can avoid multiple repeated adjustments caused by individual adjustments and improve system operation efficiency.

[0040] In another possible implementation, the intelligent control system receives the changing state of the raw materials in the processing and mixing system monitored by each sensor, analyzes each changing state, and when a quality problem is found or a certain changing state deviates from the set value corresponding to the quality standard, the processing and mixing system corresponding to the changing state is determined as the processing and mixing system to be optimized, and the processing parameters of the processing and mixing system to be optimized and the formula data of large yellow croaker are determined based on the analysis results of the intelligent control system. A single analysis method can respond faster to a single abnormal changing state, which is suitable for timely adjustment of certain particularly sensitive changing states (such as sudden temperature changes or sudden increases in humidity) to prevent the spread of these abnormal states. And a key parameter can be monitored and adjusted separately. For example, in the humidity control process of the formula, if the humidity is high but other parameters such as temperature are normal, the system only needs to adjust the parameters for humidity without affecting other states, which is suitable for systems with high requirements for refined control. When a specific state fluctuates, a single analysis is easier to fine-tune the processing parameters of the state, which will not cause a comprehensive adjustment of the entire system. It is suitable for optimization when the local state deviates from the quality standard, avoiding excessive interference with the overall system.

[0041] S106, performing processing and mixing according to the formula data and the processing parameters of the processing and mixing system to obtain large yellow croaker feed.

[0042] Specifically, the formula data of large yellow croaker is input into the processing and mixing system, and the processing and mixing system grinds and mixes the raw materials in sequence to obtain the processed and mixed large yellow croaker feed.

[0043] Combined with the above description, the processing and mixing system includes a grinding system and a mixing system. Among them, the grinding system includes a crusher, a screening machine and a batching scale, and the mixing system includes a mixer, a granulator, a cooler, an automatic packaging machine and a sealing machine. The crusher is connected to the screening machine, the screening machine is connected to the batching scale, the batching scale is connected to the mixer, the mixer is connected to the granulator, the granulator is connected to the cooler, the cooler is connected to the automatic packaging machine, and the automatic packaging machine is connected to the sealing machine. The crusher is used to crush the raw materials in the formula data to obtain small particles suitable for subsequent processing. The screening machine is used to screen the raw materials crushed by the crusher to remove impurities. The batching scale is used to accurately weigh the raw materials screened by the screening machine according to the ratio in the formula data. The mixer is used to evenly mix the various raw materials weighed by the batching scale according to the ratio. The granulator is used to press the feed raw materials mixed by the mixer into particles of regular shape, which is convenient for large yellow croaker to swallow. The cooler is used to quickly cool the feed particles made by the granulator to prevent high temperature from affecting the quality of large yellow croaker feed. The automatic packaging machine uses a precision metering device to automatically package the cooled feed particles, and the sealing machine is used to seal the packaged feed particles to ensure the freshness and safety of the large yellow croaker feed.

[0044] Optionally, the intelligent control system determines the grinding processing parameters of the crusher based on the dimensions in the recipe data; the crusher crushes the raw material based on the grinding processing parameters to obtain crushed raw material; the intelligent control system determines the average particle size as the screen aperture of the screening machine based on the particle size of the crushed raw material; the screening machine screens the crushed raw material based on the screen aperture, removes the raw material with a particle size exceeding the average particle size, and obtains the screened raw material.

[0045] Optionally, the intelligent control system determines the raw materials required for processing and mixing and the weight of the raw materials based on the ratio in the recipe data; the batching scale uses a precision metering device to weigh the raw materials based on the weight of the raw materials; during the weighing process, the weight and flow of the raw materials are monitored in real time based on sensors, and the weighed raw materials are adjusted based on the monitored weight and flow.

[0046] Optionally, the intelligent control system determines processing batches of different raw materials based on the ratios and sizes of different raw materials in the formula data; wherein the processing batches of different raw materials correspond to different mixing times and mixing speeds; based on the processing batches, corresponding raw materials are added to the mixer in sequence, and each processing batch is mixed according to the corresponding mixing time and mixing speed to obtain mixed feed raw materials for each processing batch; during the mixing process, the physical properties of the mixed feed raw materials for each processing batch are monitored in real time based on sensors, and the mixing time and mixing speed are adjusted based on the monitoring results.

[0047] For example, the formula data of large yellow croaker includes fish meal, soybean meal, sweet potato powder and lecithin. According to the formula data of large yellow croaker, the ratio and physical properties of each raw material in the current feed formula are determined. Since fish meal, soybean meal and sweet potato powder are fine particles, they are suitable for medium mixing speed. Lecithin is a functional additive and needs to be added in small doses. It is suitable for low-speed and short-time mixing to ensure uniform distribution. Further, fish meal, soybean meal and sweet potato powder are added in the first batch, and the intelligent control system sets a medium mixing speed (such as 60RPM) and a moderate mixing time (such as 5 minutes) to ensure that the three main ingredients are fully mixed. In the second batch, lecithin is added on the basis of the first batch, and low-speed mixing (such as 30 RPM) and a shorter mixing time (such as 2 minutes) are set to avoid uneven distribution of lecithin and other ingredients. During the mixing process, the sensor monitors the physical properties of the mixture such as viscosity, temperature and particle distribution in real time. If uneven particle distribution is detected in the first batch of mixing, the intelligent control system will automatically increase the mixing time or fine-tune the mixing speed (for example, from 60 RPM to 70 RPM) to improve the mixing effect. If the phospholipids are still unevenly distributed in the second batch, the intelligent control system may extend the low-speed mixing time (e.g., from 2 minutes to 3 minutes) to ensure its uniform distribution. After completing the automatic control mixing of the two batches, the intelligent control system ensures that the raw materials are fully and evenly mixed, and finally obtains feed that meets the needs of the current growth stage of large yellow croaker.

[0048] Furthermore, the sensor monitors the mixed products of each processing batch, verifies the difference between the products and the finished product requirements in the formula data, and modifies the mixing processing parameters of the subsequent processing batches based on the difference, the mixing processing parameters including mixing time and mixing speed.

[0049] Optionally, the intelligent control system determines the mixing processing parameters of the granulator based on the moisture content, particle size and shape, ratio and fluidity of different raw materials in the formula data; the mixing processing parameters include pressure, temperature and rotation speed; the granulator granulates the mixed feed raw materials based on the set pressure, temperature and rotation speed to obtain granulated feed particles; during the granulation process, the size, shape and density of the feed particles are monitored in real time based on sensors, and the mixing processing parameters are adjusted based on the monitoring results.

[0050] In specific implementation, the pressure of the granulator is determined according to the moisture content of different raw materials in the formula data and the variation trend of the granulator pressure with the moisture content.

[0051] Specifically, the moisture content of different raw materials is related to the pressure of the granulator, and the two are in a positive proportional relationship. Within a certain range, the moisture content is higher, and the pressure of the granulator is increased accordingly to promote the gelatinization and bonding of the raw materials. In the general granulation process, the moisture content of the raw materials is generally controlled between 8%-10%, and the total moisture content is controlled at 16%-17%. Correspondingly, the pressure of the granulator is generally controlled between 394-490 kPa.

[0052] Furthermore, the initial temperature of the granulator is determined according to the moisture content of different raw materials in the formula data and the changing trend of the granulator temperature with the moisture content, and the initial temperature of the granulator is adjusted based on the particle size and shape of different raw materials in the formula data and the changing trend of the granulator temperature with the particle size and shape to obtain the temperature of the granulator.

[0053] Specifically, the moisture content, particle size and shape of different raw materials are related to the temperature of the pelletizer. Pellets of different raw materials include hard particles, soft particles and expanded particles, etc., and the shape and density of each particle are different. Within a certain range, when the moisture content is high, the particle size is large and the shape is not easy to granulate, the temperature of the pelletizer needs to be increased accordingly to promote the pelletizing effect. In the general pelletizing process, the temperature of the pelletizer does not exceed 88°C, and is generally controlled between 82-88°C.

[0054] One parameter will not be independent. Again, we control the temperature information comprehensively according to the moisture content, particle size and shape, where the temperature is proportional to the moisture content, proportional to the particle size, and inversely proportional to the granulation ease. Specifically, the difference value of each parameter in the current state is calculated according to the target moisture content and particle size corresponding to the processing link, and the proportion of each parameter is determined according to the relative size of the difference value of each parameter. The initial temperature is adjusted according to the proportion. For example, if the moisture content is quite different, but the particle size is basically close, then the parameters are adjusted to meet the moisture content requirements.

[0055] Furthermore, according to the ratio of different raw materials in the formula data and the influence of different ratios on the fluidity of the raw materials, the fluidity of different raw materials in the formula data is adjusted, and the initial rotation speed of the granulator is determined based on the adjusted fluidity and the correspondence between the fluidity and the flow rate; wherein, the fluidity of the raw material is positively correlated with the flow rate of the raw material in the granulator; the rotation speed of the granulator is positively correlated with the flow rate of the raw material; the initial rotation speed of the granulator is adjusted based on the particle size and shape of different raw materials in the formula data and the correspondence between the particle size and shape and the flow rate to obtain the rotation speed of the granulator.

[0056] Specifically, the particle size and shape, ratio and fluidity of different raw materials are related to the rotation speed of the granulator. The ratio of different raw materials will lead to changes in fluidity, density and volume. The fluidity will directly affect the flow rate of the raw material in the granulator. Raw materials with good fluidity are easy to be evenly distributed in the granulator and have a faster flow rate in the granulator. In addition, the particle size and shape of different raw materials will also affect the flow rate of the raw material in the granulator. The particles with smaller particles and more regular shapes will flow faster in the granulator. In summary, when the granulator is granulating raw materials with good fluidity, smaller particles and more regular shapes, the rotation speed of the granulator can be appropriately reduced. In specific implementation, the calculation formula for the rotation speed of the granulator is: ; Among them, the is the rotation speed of the granulator; is the flow rate of different raw materials; is the diameter of the granulator. The rotation speed is proportional to the flow rate and inversely proportional to the size of the granules.

[0057] Optionally, the particle sizes that yellow croaker can bear are different at different growth stages, and the particle sizes of different raw materials are also different, and their corresponding nutritional values ​​are also different. Therefore, it is necessary to determine the particle size that yellow croaker can bear according to the growth stage of yellow croaker, and the granulator performs granulation through preset mixing processing parameters, and continuously compares the feed particles with the particle size that yellow croaker can bear during the granulation process, and compares the nutritional value corresponding to the particle size with the nutritional requirements corresponding to the growth stage of yellow croaker, so as to ensure that the feed particles after granulation are of the particle size that yellow croaker can bear and meet the nutritional requirements corresponding to the growth stage of yellow croaker.

[0058] Optionally, the intelligent control system uses fuzzy rules to determine the processing parameters of the cooler based on the temperature, humidity, particle size and shape of the feed particles; the processing parameters include cooling time and cooling rate; the cooler cools the feed particles at the cooling time and cooling rate to obtain cooled feed particles; during the cooling process, the temperature and physical property changes of the feed particles are monitored in real time based on sensors, and the cooling time and cooling rate are adjusted based on the monitoring results.

[0059] Optionally, the intelligent control system uses fuzzy rules to determine the mixing processing parameters of the cooler based on the temperature, humidity, particle size and shape of the feed particles, including: fuzzifying the temperature and humidity of the feed particles, and mapping them to obtain fuzzy sets corresponding to the temperature and humidity; determining fuzzy rules based on the changing trends of temperature and humidity with mixing processing parameters during historical processing and mixing; reasoning according to the fuzzy rules based on the fuzzy sets corresponding to the temperature and humidity, and calculating the fuzzy values ​​of the mixing processing parameters; and converting the fuzzy values ​​into specific values ​​through a defuzzification method to determine specific mixing processing parameters.

[0060] For example, the fuzzy sets corresponding to humidity include "low humidity" (LH), "medium humidity" (MH) and "high humidity" (HH), and the fuzzy sets corresponding to temperature include "low temperature" (LT), "moderate temperature" (MT) and "high temperature" (HT). Each fuzzy set corresponds to a fuzzy membership function, which is used to describe the degree to which the input variable belongs to the set. Similarly, the mixed processing parameters include cooling time and cooling speed. The cooling time and cooling speed are fuzzified. The fuzzy sets corresponding to the cooling time include "short time" (ST), "medium time" (MT) and "long time" (LT). The fuzzy sets corresponding to the mixing time include "low speed" (LS), "medium speed" (MS) and "high speed" (HS).

[0061] Furthermore, fuzzy rules are determined according to the changing trends of temperature and humidity along with mixing processing parameters in the historical processing and mixing process. The designed fuzzy rules are as follows: If the humidity is LH and the temperature is MT, the cooling time is ST and the cooling rate is MS (because the raw materials at low humidity and moderate temperature are easier to mix evenly, so too long cooling time and too high cooling rate are not required). If the humidity is MH and the temperature is HT, the cooling time is MT and the cooling rate is HS (because the raw materials at medium humidity and high temperature may require a higher cooling rate to ensure uniform mixing, but the cooling time does not need to be too long). If the humidity is HH and the temperature is LT, the cooling time is LT and the cooling rate is LS (because the raw materials at high humidity and low temperature may be more difficult to mix evenly, so longer cooling time and lower cooling rate are required).

[0062] When the humidity of the raw material is at a medium level and the temperature is at a low level, according to the fuzzy rules, it is calculated that the cooling time should be medium and the cooling speed should be fast. Then, these fuzzy values ​​are converted into specific control parameters (such as cooling time T=300 seconds, cooling speed V=60 rpm) through the defuzzification method and output to the cooler for real-time control.

[0063] It should be noted that after obtaining the temperature and physical property changes of the feed particles based on real-time monitoring by sensors, the intelligent control system also uses fuzzy rules to fuzzy the temperature and physical property changes of the feed particles, and determines the fuzzy rules based on the changing trends of the temperature and physical property changes of the feed particles during the historical processing and mixing process along with the mixing processing parameters, and determines the optimized mixing processing parameters based on the fuzzy processing results and fuzzy rules.

[0064] The method provided in this embodiment, in the first aspect, by being equipped with an intelligent control system, the intelligent control system can determine the formula data of the large yellow croaker and the processing parameters of the processing and mixing system according to the determined growth stage of the large yellow croaker, and perform processing and mixing based on the formula data and the processing parameters. In this way, it is ensured that the large yellow croaker feed obtained by processing and mixing is nutritionally balanced, and the needs of large yellow croaker at different growth stages can be met. Compared with the traditional large yellow croaker feed processing and mixing method, which processes large yellow croaker feed based on fixed formula data, this application will not cause feed waste, and ensure the growth and health of large yellow croaker. In the second aspect, by integrating multiple sensors in the processing and mixing system, multiple sensors monitor the changing state of raw materials in the processing and mixing system in real time, and the intelligent control system optimizes the formula data of large yellow croaker and the processing parameters of the processing and mixing system by analyzing and predicting the changing state monitored by the sensors. In this way, the formula data and processing parameters can be adjusted in real time and more accurately, so that the large yellow croaker feed obtained by processing and mixing can better meet the needs of large yellow croaker at different growth stages, reduce feed waste, improve production efficiency, and reduce costs. In the third aspect, this embodiment provides a large yellow croaker feed processing and mixing method that integrates multiple functions such as crushing, screening, batching, mixing, granulation, cooling, packaging, and sealing. The determination of the processing parameters (grinding processing parameters or mixing processing parameters) of each processing process depends on the formula data of the large yellow croaker, and each processing process is monitored and adjusted by sensors in real time. This integrated design not only improves the efficiency of large yellow croaker feed processing, but also makes the large yellow croaker feed obtained by processing and mixing better meet the needs of large yellow croaker at different growth stages, and reduces the floor space and labor cost of the large yellow croaker feed processing and mixing device. In the fourth aspect, by adding natural pigments such as astaxanthin and functional ingredients such as phospholipids to large yellow croaker feed, the body color of large yellow croaker can be improved, the fishy smell can be reduced, and the muscle fat content can be controlled. The addition of these ingredients makes large yellow croaker feed more in line with the growth needs and market requirements of large yellow croaker. In the fifth aspect, by using precision metering devices in batching scales and automatic packaging machines, the accuracy and stability of the raw materials used to process and manufacture large yellow croaker feed can be ensured, the quality of large yellow croaker feed can be improved, and the production cost can be reduced.

[0065] Corresponding to the aforementioned embodiment of a large yellow croaker feed processing and mixing method, the present application also provides an embodiment of a large yellow croaker feed processing and mixing device.

[0066] Figure 2 This is a schematic diagram of the structure of the large yellow croaker feed processing and mixing device provided in Example 2 of this application. Figure 2 The device provided in this embodiment includes an intelligent control system and a processing mixing system connected to each other; wherein, The intelligent control system is used to determine the formula data of the large yellow croaker based on the growth stage of the large yellow croaker; the formula data includes the ratio of different raw materials and the size of different raw materials, and different growth stages correspond to different nutritional requirements; The intelligent control system is further used to determine the processing parameters of the processing and mixing system based on the formula data; wherein the processing and mixing system at least includes a grinding system and a mixing system, the order of raw materials entering the grinding system is determined according to the ratio in the formula data, and the grinding processing parameters of the grinding system are determined according to the size in the formula data; the mixing processing parameters of the mixing system are determined according to the ratio; The processing and mixing system is used to process and mix based on the formula data and the processing parameters to obtain large yellow croaker feed; The intelligent control system is also used to monitor the changing state of the raw materials in the processing and mixing system in real time based on sensors, and optimize the formula data and the processing parameters in real time based on the changing state.

[0067] The device of this embodiment can be used to perform Figure 1 The steps, specific implementation principles and implementation processes of the method embodiment shown are similar and will not be repeated here.

[0068] The implementation process of the functions and effects of each unit in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

[0069] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application scheme. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0070] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A large yellow croaker feed processing and mixing method, characterized in that: The method comprises: Determine the growth stage of large yellow croaker; Determine the formula data of large yellow croaker based on the growth stage; the formula data includes the ratio of different raw materials and the size of different raw materials, and different growth stages correspond to different nutritional requirements; The intelligent control system determines the processing parameters of the processing and mixing system based on the formula data; wherein the processing and mixing system at least includes a grinding system and a mixing system, the order of raw materials entering the grinding system is determined according to the ratio in the formula data, and the grinding processing parameters of the grinding system are determined according to the size in the formula data; the mixing processing parameters of the mixing system are determined according to the ratio; Real-time monitoring of the changing state of the raw materials in the processing and mixing system based on sensors; The intelligent control system optimizes the recipe data of large yellow croaker and the processing parameters of the processing and mixing system in real time according to the changing state; Processing and mixing are carried out according to the formula data and the processing parameters of the processing and mixing system to obtain large yellow croaker feed.

2. The method according to claim 1, characterized in that The grinding system at least includes a batching scale; The intelligent control system determines the raw materials required for processing and mixing and the weight of the raw materials based on the ratio in the formula data; The batching scale uses a precision measuring device to weigh the raw materials based on the weight of the raw materials; During the weighing process, the weight and flow rate of the raw materials are monitored in real time based on sensors, and the weighed raw materials are adjusted based on the monitored weight and flow rate.

3. The method according to claim 1, characterized in that: The mixing system comprises at least a mixer; The intelligent control system determines the processing batches of different raw materials based on the ratios and sizes of different raw materials in the formula data; wherein the processing batches of different raw materials correspond to different mixing times and mixing speeds; Adding corresponding raw materials to the mixer in sequence based on the processing batches, mixing each processing batch according to the corresponding mixing time and mixing speed, to obtain mixed feed raw materials for each processing batch; During the mixing process, the physical property changes of the mixed feed raw materials in each processing batch are monitored in real time based on sensors, and the mixing time and mixing speed are adjusted based on the monitoring results.

4. The method according to claim 1, characterized in that: The mixing system comprises at least a granulator; The intelligent control system determines the mixing processing parameters of the granulator based on the moisture content, particle size and shape, ratio and fluidity of different raw materials in the formula data; the mixing processing parameters include pressure, temperature and rotation speed; The granulator granulates the mixed feed raw materials based on the set pressure, temperature and rotation speed to obtain granulated feed particles; During the pelleting process, the size, shape and density of the feed particles are monitored in real time based on sensors, and the mixing process parameters are adjusted based on the monitoring results.

5. The method according to claim 4, characterized in that The mixing system comprises at least a cooler; The intelligent control system uses fuzzy rules to determine the mixing process parameters of the cooler based on the temperature, humidity, particle size and shape of the feed particles; the mixing process parameters include cooling time and cooling speed; The cooler cools the feed particles at the cooling time and cooling speed to obtain cooled feed particles; During the cooling process, the temperature and physical property changes of the feed particles are monitored in real time based on sensors, and the cooling time and cooling speed are adjusted based on the monitoring results.

6. The method according to claim 5, characterized in that The intelligent control system uses fuzzy rules to determine the mixing process parameters of the cooler based on the temperature, humidity, and particle size and shape of the feed particles, including: Performing fuzzy processing on the temperature and humidity of the feed particles, and mapping to obtain fuzzy sets corresponding to the temperature and humidity; Determine fuzzy rules based on the changing trends of temperature and humidity along with mixing process parameters in the historical processing and mixing process; Based on the fuzzy sets corresponding to the temperature and humidity, reasoning is performed according to the fuzzy rules to calculate the fuzzy values ​​of the mixed processing parameters; The fuzzy value is converted into a specific value through a defuzzification method to determine the specific mixing processing parameters.

7. The method according to claim 2, characterized in that The grinding system at least includes a crusher and a screening machine; wherein the crusher is connected to the screening machine; The intelligent control system determines the grinding processing parameters of the crusher based on the dimensions in the recipe data; The crusher crushes the raw material based on the grinding processing parameters to obtain crushed raw material; The intelligent control system determines the average particle size as the mesh aperture of the screening machine based on the particle size of the crushed raw material; The screening machine screens the crushed raw material based on the sieve aperture, removes the raw material with a particle size exceeding the average particle size, and obtains the screened raw material.

8. The method according to claim 1, characterized in that The intelligent control system optimizes the recipe data of large yellow croaker and the processing parameters of the processing and mixing system in real time according to the changing state, including: The intelligent control system compares the change state with the quality standards corresponding to different raw materials in the formula data; Adjust the recipe data and corresponding processing parameters based on the comparison result and the change state along with the change trend of the recipe data; When the change state always exceeds the quality standard after adjusting the preset number of cycles, the alarm will sound an alarm to prompt the intelligent control system to be adjusted.

9. The method according to claim 1, characterized in that: The method of determining the formula data of large yellow croaker based on the growth stage comprises: Determining the nutritional requirements of the large yellow croaker based on the growth stage of the large yellow croaker; the nutritional requirements include nutrients of different components; Determining raw materials for providing nutrients based on the nutrients; Based on the maximum bearing size of the growth stage and the relationship between the nutritional performance of the raw materials and the size of the raw materials, the ratio and size of different raw materials corresponding to the nutritional requirements are determined to generate recipe data.

10. A large yellow croaker feed processing and mixing device, characterized in that: The device comprises an intelligent control system and a processing mixing system which are interconnected; wherein, The intelligent control system is used to determine the formula data of the large yellow croaker based on the growth stage of the large yellow croaker; the formula data includes the ratio of different raw materials and the size of different raw materials, and different growth stages correspond to different nutritional requirements; The intelligent control system is further used to determine the processing parameters of the processing and mixing system based on the formula data; wherein the processing and mixing system at least includes a grinding system and a mixing system, the order of raw materials entering the grinding system is determined according to the ratio in the formula data, and the grinding processing parameters of the grinding system are determined according to the size in the formula data; the mixing processing parameters of the mixing system are determined according to the ratio; The processing and mixing system is used to process and mix based on the formula data and the processing parameters to obtain large yellow croaker feed; The intelligent control system is also used to monitor the changing state of the raw materials in the processing and mixing system in real time based on sensors, and optimize the formula data and the processing parameters in real time based on the changing state.

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