TMR central kitchen management control system and control method based on Internet of Things

Abstract

The invention provides a TMR central kitchen management control system and control method based on the Internet of Things, and belongs to the technical field of livestock feeding system management control, the TMR central kitchen management control system based on the Internet of Things comprises an Internet of Things sensing layer, an Internet of Things transmission layer, a central control layer, a control execution layer and a remote monitoring and management layer; the Internet of Things sensing layer is mainly used for detecting data information of a key position and uploading the obtained data information; the Internet of Things transmission layer is mainly used for providing a data transmission channel and establishing a communication protocol between the hardware front end and the data processing terminal; the central control layer is mainly used for receiving the data information transmitted by the Internet of Things sensing layer, performing analysis processing on the data information, and sending a control instruction to each execution mechanism according to an analysis result; the problems that materials are wasted and even animal growth cannot reach expectation due to material mixing errors caused by manual operation treatment in the conventional TMR technology at present can be solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of livestock feeding system management and control, and in particular relates to a TMR central kitchen management and control system and a control method based on the Internet of Things. Background Art

[0002] Dairy farming is gradually shifting towards large-scale and intensive operations, but large-scale farming also presents some challenges: First, feeding dairy cows is labor-intensive; second, cows at different stages of development require diets with varying nutritional levels, and traditional diet formulation methods struggle to meet the theoretical nutrient concentration requirements of dairy cows, especially for trace elements and vitamins, which are difficult to achieve uniformly. Third, artificially feeding concentrated feeds in centralized locations can easily lead to individual cows overeating, resulting in digestive and metabolic diseases such as rumen acidosis and displaced abomasum. Inadequate concentrate intake can also affect the performance of cows. Fourth, deficiencies in traditional feed processing can lead to picky eating in dairy cows, resulting in insufficient feed for production and waste. The emergence of TMR technology addresses these issues. TMR is the abbreviation of Total Mixed Ration. The so-called total mixed ration (TMR) is a feeding technology that fully mixes roughage, concentrate, and auxiliary materials (minerals, vitamins and other additives) to obtain a relatively balanced diet that can provide sufficient nutrition to meet the needs of dairy cows.

[0003] However, the existing TMR technology has a low degree of automation and mainly relies on manual operation. Phenomena such as incorrect types of raw materials added, inaccurate raw material weighing, and uneven mixing often occur, resulting in the finished feed not meeting the requirements and having a negative impact on dairy cow breeding.

[0004] The main problems of TMR technology at present are as follows: Due to manual error, the wrong feed ingredients were used, resulting in incorrect feed composition; Due to manual operation errors, the weight of added feed raw materials is incorrect, resulting in an imbalance in the feed ingredient ratio; Due to the randomness of manual mixing, the feed is not mixed evenly. Summary of the Invention

[0005] The present invention provides a TMR central kitchen management control system and control method based on the Internet of Things, which can solve the problem mentioned in the background art of the current conventional TMR technology that the entire process is confused due to manual operation errors, resulting in the final mixed feed failing to meet expectations.

[0006] The present invention is implemented as follows: The present invention provides a TMR central kitchen management and control system based on the Internet of Things, wherein the system includes an Internet of Things perception layer, an Internet of Things transmission layer, a central control layer, a control execution layer, and a remote monitoring and management layer; the Internet of Things perception layer is mainly used to detect data information at key locations and upload the obtained data information; the Internet of Things transmission layer is mainly used to provide a data transmission channel and establish a communication protocol between the hardware front end and the data processing terminal; the central control layer is mainly used to receive the data information transmitted by the Internet of Things perception layer, and parse and process the data information, and issue control instructions to each execution agency according to the parsing results; the control execution layer is mainly used to receive control instructions issued by the central control layer, and perform execution actions according to the execution instructions; the remote monitoring and management layer is mainly used to provide customers with a channel for remote monitoring, so that customers can monitor and control the system through mobile devices.

[0007] On the basis of the above technical solution, the TMR central kitchen management and control system based on the Internet of Things of the present invention can also be improved as follows: further, the hardware part of the control execution layer mainly involves: raw material warehouse, loader, conveyor belt, weighing machine, mixer, feed quality detection equipment; there are multiple raw material warehouses, which are used to classify and store coarse materials, fine materials, auxiliary materials and additives for preparing mixed feed; additives include minerals and additives; the loader is used to transport various raw materials in the raw material warehouse to the conveyor, and then transport them to the weighing machine via the conveyor belt for weighing; the weighing machine is used to weigh various raw materials according to the designed formula to ensure the stability of the content of the prepared mixed feed; the mixer is used to cut, mix and stir various raw materials to fully mix various raw materials; the feed quality detection equipment is used to spot-check the mixed feed generated after processing by the mixer, and judge whether the various nutrients in the mixed feed match the formula.

[0008] Furthermore, the loader is located inside the raw material bin, and a preprocessor is provided between the raw material bin outlet and the conveyor belt. The preprocessor is used to simply process various raw materials to facilitate subsequent mixing and stirring; the weighing device is provided between the conveyor belt and the mixing mixer, and a flipping device for flipping the weighing device is fixedly provided under the weighing device.

[0009] Furthermore, the data information at key locations specifically includes the feeder's rising speed, conveyor belt speed, weighing value, raw material bin internal environmental data, mixer agitation torque, and feed quality testing equipment detection data; the raw material bin internal environmental data includes the internal temperature of the raw material bin, the internal humidity of the raw material bin, the internal light intensity, and the internal gas composition. The beneficial effect of adopting this further solution is that by monitoring the internal environmental data of the raw material bin, the raw materials are always kept in the optimal storage environment, preventing the external environment from affecting the internal environment, and greatly extending the storage time of the raw materials.

[0010] The present invention also provides a control method for a TMR central kitchen management control system based on the Internet of Things, wherein the method specifically includes: Step S1: Raw material reception and storage: Raw materials required for TMR processing are received and stored in the raw material warehouse, and the storage environment of different raw material warehouses is customized to ensure that the storage environment is suitable for the corresponding raw materials to be stored; Step S2, raw material quality inspection: before the process starts, the raw materials in the raw material warehouse are inspected to ensure that the raw material quality is within the specification range; Step S3, formula design, calculates and formulates scientific diet formulas based on the different physiological stages, production levels, raw material inventory and nutrient composition test results of different animals; Step S4: weighing the raw materials. After leaving the warehouse, the raw materials are transported to the weighing device via a conveyor belt. Each type of raw material is accurately weighed, and the raw materials in the weighing device are transported to the mixing mixer using a turning device below the weighing device. The order in which the raw materials enter the mixing mixer follows the principle of "long first, short later, dry first, wet later, light first, heavy later"; Step S5: Mixing the raw materials. The mixer starts rotating after receiving the first batch of raw materials and provides real-time feedback on the mixing torque. The central control layer controls the mixing time of the mixer and determines the mixing status based on the feedback torque data. If a sudden change in torque occurs, it indicates a problem with the process. At this time, the central control layer issues an alarm signal and stops the system. Step S6, discharge inspection: after the mixing and stirring is completed, the mixed feed is output by the mixer. At the same time, the feed quality inspection equipment performs a preliminary inspection on the output mixed feed and feeds back the inspection data to the central control layer; Step S7, quantitative distribution, after the mixed feed is processed in step S6, it is output to the conveyor belt and transported to each feeding trough via the conveyor belt; Step S8, leftover feed management. After the delivery in step S7 is completed, the animals are released to start eating. After eating, the leftover feed is recycled and processed. The recycled leftover feed is weighed and re-tested, and the animal's eating situation is analyzed and fed back to the central control layer to adjust the content ratio of each ingredient in the formula in step S3.

[0011] Furthermore, step S2 also includes raw material pretreatment. After the raw materials are taken out of the warehouse, they need to undergo a simple pretreatment process, and some large pieces of raw materials are chopped or kneaded to make the length of the large pieces of raw materials suitable for processing by the mixer, and to improve palatability and digestibility.

[0012] Furthermore, step S2 also includes a discharging process. A warehouse opening for discharging is opened on the side of the raw material warehouse near the conveyor belt. Two height sensors are installed at the warehouse opening. The two height sensors are arranged vertically and maintain data transmission with the central control layer at the same time. The height sensor is used to detect the height of the discharging. When the height of the raw material is higher than the height sensor in the high position, it means that the discharging speed is too fast. At this time, the central control layer controls the loader to reduce the discharging speed. When the height of the raw material is lower than the height sensor in the low position, it means that the discharging speed is too slow. At this time, the central control layer controls the loader to increase the discharging speed. The beneficial effect of adopting the above further scheme is: by setting the height sensor and cooperating with the control of the central control layer, balanced control of the discharging speed is achieved, ensuring that the discharging speed is constant, providing high accuracy for the subsequent raw material weighing step, and ensuring that the system can respond in time when the raw material demand reaches the designed amount of the formula to avoid excessive materials.

[0013] Furthermore, the preliminary detection process in step S6 is a random inspection, and the frequency of random inspection is once a day; step S6 specifically includes: step S61, sampling, sampling the mixed feed, sampling at different positions of the mixing agitator, and the specific positions are the bottom, surface, periphery and middle position of the mixing agitator; step S62, sensory evaluation, direct contact with the sampled material, and observation of the overall state of the mixed feed; step S63, screening test, screening the sampled mixed feed using a Pennsylvania sieve, performing physical fiber testing, and analyzing the particle distribution state; step S64, component detection, using near-infrared technology to detect the specific nutrient content of the sampled mixed feed. The beneficial effect of adopting the above further scheme is: by setting up preliminary detection, a preliminary inspection of the results of the entire process is achieved, and at the same time, the entire process can be better adjusted based on the test results.

[0014] Furthermore, during the sampling process of step S6, the component detection step of step S64 also includes: obtaining the data of each nutrient component in the sampled mixed feed after detection by near-infrared technology, calculating the absolute value of the difference between each nutrient component, and analyzing the status of the mixed feed based on the absolute value.

[0015] Compared with the existing technology, the beneficial effects of the Internet of Things-based TMR central kitchen management and control system and control method provided by the present invention are: solving the problems of low degree of full automation, large feed addition errors, and high management difficulty of the existing TMR central kitchen control system, and being able to meet the efficient, stable and safe feeding management needs of large-scale ranch farms, with significant economic and social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 Schematic diagram of the main structure of the system; Figure 2 Provide a block diagram of each level of the system; Figure 3 Provide a flowchart for the system operation; Figure 4 The flowchart of the system control method is shown in FIG. DETAILED DESCRIPTION

[0018] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0019] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are also within the scope of protection of the present invention. Example

[0020] The present invention provides a TMR central kitchen management control system and control method based on the Internet of Things, wherein the system includes an Internet of Things perception layer, an Internet of Things transmission layer, a central control layer, a control execution layer, and a remote monitoring and management layer; the Internet of Things perception layer is mainly used to detect data information at key locations and upload the obtained data information; the Internet of Things transmission layer is mainly used to provide a data transmission channel and establish a communication protocol between the hardware front end and the data processing terminal; the central control layer is mainly used to receive data information transmitted by the Internet of Things perception layer, parse and process the data information, and issue control instructions to each execution agency according to the parsing results; the control execution layer is mainly used to receive control instructions issued by the central control layer and perform execution actions according to the execution instructions; the remote monitoring and management layer is mainly used to provide customers with a remote monitoring channel, so that customers can monitor and control the system through mobile devices. Optionally, in the above technical solution, the hardware part of the control execution layer mainly involves: raw material warehouse, loader, conveyor belt, weighing machine, mixer, feed quality detection equipment; there are multiple raw material warehouses, which are used to classify and store coarse materials, fine materials, auxiliary materials and additives for preparing mixed feed; additives include minerals and additives; the loader is used to transport various raw materials in the raw material warehouse to the conveyor, and then transport them to the weighing machine via the conveyor belt for weighing; the weighing machine is used to weigh various raw materials according to the designed formula to ensure the stability of the content of the prepared mixed feed; the mixer is used to cut, mix and stir various raw materials to fully mix various raw materials; the feed quality detection equipment is used to randomly inspect the mixed feed generated after processing by the mixer, and determine whether the various nutrients in the mixed feed match the formula.

[0021] Optionally, in the above technical solution, the loader is located inside the raw material bin, and a preprocessor is provided between the raw material bin outlet and the conveyor belt. The preprocessor is used to simply process various types of raw materials to facilitate subsequent mixing and stirring; the weighing device is provided between the conveyor belt and the mixing mixer, and a flipping device for flipping the weighing device is fixedly provided under the weighing device.

[0022] Optionally, in the above technical solution, the data information at the key positions specifically includes the rising speed of the loader, the moving speed of the conveyor belt, the weighing value of the weighing scale, the internal environmental data of the raw material warehouse, the stirring torque of the mixing agitator and the detection data of the feed quality detection equipment; wherein the internal environmental data of the raw material warehouse includes the internal temperature of the raw material warehouse, the internal humidity of the raw material warehouse, the internal light intensity and the internal gas composition.

[0023] Optionally, in the above technical solution, the IoT perception layer includes various sensors, including but not limited to weight sensors, temperature sensors, humidity sensors, speed sensors, and altitude sensors. These sensors are all wirelessly connected to the central control system and can transmit collected data to the central control system in real time. By collecting data from various sensors, the central control layer can monitor the operating status of the entire system in real time, ensuring the normal operation of the entire process. Furthermore, if any problem occurs anywhere in the system, the central control layer will be able to detect it immediately and issue an alarm.

[0024] Optionally, in the above technical solution, the Internet of Things transmission layer establishes a wireless communication network and adopts LoRa wireless communication technology to stably and efficiently transmit the data collected by the perception layer and the information interaction between various devices, ensuring the accuracy and integrity of the data during the transmission process, so that the central control system can obtain information from each part in a timely manner.

[0025] Optionally, in the above technical solution, the central control layer includes a high-performance PLC system, which serves as the control core of the entire TMR central kitchen management and control system. The PLC system is installed with special control management software for analyzing, processing and storing various types of collected data, and generating corresponding control instructions based on preset feed formulas, processing technology and production plans, etc., to achieve automated control of various equipment in the TMR central kitchen.

[0026] Optionally, in the above technical solution, the control execution layer includes various types of automated actuators, which are all connected to the central control system and receive control instructions issued by the central control system to realize automated loading, conveying, weighing, dividing, stirring, testing and other operations of feed raw materials.

[0027] In particular, the conveyor belt drive device can automatically adjust the conveying speed according to the type of feed and conveying requirements, ensuring the stability and accuracy of the feed during the conveying process.

[0028] Optionally, in the above technical solution, the remote monitoring and management layer is based on a cloud service platform built on the Internet of Things technology, which is connected to the central control system through the Internet. Users can log in to the remote monitoring and management platform anytime and anywhere through mobile phones, tablets, computers and other terminal devices to view the operating status of the TMR central kitchen, the inventory of feed raw materials, feed processing progress and other information in real time, and can remotely set system parameters, start / stop control, fault alarm processing and other operations, which facilitates users to conduct remote management and monitoring and improves management efficiency and flexibility.

[0029] Optionally, in the above technical solution, the specific speed control of the conveyor belt is as follows: Let W be the current weight of the scale, i.e. the measured value; Wset is the set weight calculated according to the designed formula, i.e. the target value; V max is the maximum conveyor belt speed, i.e. the initial conveyor belt speed; W threshold is the deceleration trigger threshold, where W threshold =0.9×W set ; The specific control rules are as follows: If W<W threshold :Conveyor belt is V max speed of operation.

[0030] If W threshold ≤W≤W set : Speed ​​from V max Decreases linearly to 0.

[0031] Specific speed calculation formula:

[0032] Among them, W set -W threshold =0.1×W set , that is, the weight interval is 10% of the set value range; V is the conveyor belt speed at the current weight, and V decreases linearly with the increase of W; When W=W threshold When V = V max ;W=W set When V=0.

[0033] The control method specifically includes: Step S1: Raw material reception and storage: Raw materials required for TMR processing are received and stored in the raw material warehouse, and the storage environment of different raw material warehouses is customized to ensure that the storage environment is suitable for the corresponding raw materials to be stored; Step S2, raw material quality inspection: before the process starts, the raw materials in the raw material warehouse are inspected to ensure that the raw material quality is within the specification range; Step S3, formula design, calculates and formulates scientific diet formulas based on the different physiological stages, production levels, raw material inventory and nutrient composition test results of different animals; Step S4: weighing the raw materials. After leaving the warehouse, the raw materials are transported to the weighing device via a conveyor belt. Each type of raw material is accurately weighed, and the raw materials in the weighing device are transported to the mixing mixer using a turning device below the weighing device. The order in which the raw materials enter the mixing mixer follows the principle of "long first, short later, dry first, wet later, light first, heavy later"; Step S5: Mixing the raw materials. The mixer starts rotating after receiving the first batch of raw materials and provides real-time feedback on the mixing torque. The central control layer controls the mixing time of the mixer and determines the mixing status based on the feedback torque data. If a sudden change in torque occurs, it indicates a problem with the process. At this time, the central control layer issues an alarm signal and stops the system. Step S6, discharge inspection: after the mixing and stirring is completed, the mixed feed is output by the mixer. At the same time, the feed quality inspection equipment performs a preliminary inspection on the output mixed feed and feeds back the inspection data to the central control layer; Step S7, quantitative distribution, after the mixed feed is processed in step S6, it is output to the conveyor belt and transported to each feeding trough via the conveyor belt; Step S8, leftover feed management. After the delivery in step S7 is completed, the animals are released to start eating. After eating, the leftover feed is recycled and processed. The recycled leftover feed is weighed and re-tested, and the animal's eating situation is analyzed and fed back to the central control layer to adjust the content ratio of each ingredient in the formula in step S3.

[0034] Optionally, in the above technical solution, step S2 also includes raw material pretreatment. After the raw materials are out of the warehouse, they need to undergo a simple pretreatment process, and some large pieces of raw materials are chopped or kneaded to make the length of the large pieces of raw materials suitable for processing by the mixing agitator, and to improve palatability and digestibility.

[0035] Optionally, in the above technical solution, step S2 also includes a discharging process, and a warehouse opening for discharging is opened on the side of the raw material warehouse near the conveyor belt. Two height sensors are installed at the warehouse opening, and the two height sensors are arranged vertically, and maintain data transmission with the central control layer at the same time; the height sensor is used to detect the height of the discharging, when the raw material height is higher than the height sensor in the high position, it means that the discharging speed is too fast, and the central control layer controls the loader to reduce the discharging speed; when the raw material height is lower than the height sensor in the low position, it means that the discharging speed is too slow, and the central control layer controls the loader to increase the discharging speed.

[0036] Optionally, in the above technical solution, the preliminary detection process in step S6 is a random inspection, and the frequency of random inspection is once a day; step S6 specifically includes: Step S61, sampling, sampling the mixed feed at different positions of the mixer, specifically the bottom, surface, periphery and middle of the mixer; Step S62, sensory evaluation, direct contact with the sampled material to observe the overall state of the mixed feed; Step S63, screening test, screening the sampled mixed feed using a Pennsylvania sieve, performing physical fiber testing, and analyzing the particle distribution state; Step S64, component detection, uses near infrared technology to detect the specific nutritional content of the sampled mixed feed.

[0037] Optionally, in the above technical solution, during the sampling process of step S6, the component detection step of step S64 also includes: obtaining the data of each nutrient component in the sampled mixed feed after detection by near-infrared technology, calculating the absolute value of the difference between each nutrient component, and analyzing the status of the mixed feed based on the absolute value.

[0038] Optionally, in the above technical solution, the specific method of inspecting the mixing quality by random inspection is as follows: Taking protein as an example, the percentage of protein content in multiple samples is: x1, x2...xn; where n≥2; First calculate its mean: , which is used to express the central tendency of the sample component content; Next, calculate the standard deviation: , which is used to express the degree of dispersion of the sample content around the mean value. The smaller the SD, the higher the degree of mixing. Calculate the relative standard deviation: ; The smaller the RSD, the smaller the relative variation and the more uniform the mixing.

[0039] The above is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A TMR central kitchen management and control system based on the Internet of Things, characterized in that: The system includes the Internet of Things perception layer, the Internet of Things transmission layer, the central control layer, the control execution layer and the remote monitoring and management layer; the Internet of Things perception layer is mainly used to detect data information at key locations and upload the obtained data information; the Internet of Things transmission layer is mainly used to provide data transmission channels and establish communication protocols between the hardware front end and the data processing terminal; the central control layer is mainly used to receive data information transmitted by the Internet of Things perception layer, and parse and process the data information, and issue control instructions to each execution agency based on the analysis results; the control execution layer is mainly used to receive control instructions issued by the central control layer, and perform execution actions according to the execution instructions; the remote monitoring and management layer is mainly used to provide customers with remote monitoring channels, so that customers can monitor and control the system through mobile devices.

2. A TMR central kitchen management and control system based on the Internet of Things according to claim 1, characterized in that: The hardware part of the control execution layer mainly involves: raw material warehouse, loader, conveyor belt, weighing machine, mixer, feed quality detection equipment; there are multiple raw material warehouses, which are used to classify and store coarse materials, fine materials, auxiliary materials and additives for preparing mixed feed; additives include minerals and additives; the loader is used to transport various raw materials in the raw material warehouse to the conveyor, and then transport them to the weighing machine via the conveyor belt for weighing; the weighing machine is used to weigh various raw materials according to the designed formula to ensure the stability of the content of the prepared mixed feed; the mixer is used to cut, mix and stir various raw materials to ensure that all raw materials are fully mixed; the feed quality detection equipment is used to randomly inspect the mixed feed generated after processing by the mixer, and determine whether the nutrients in the mixed feed match the formula.

3. A TMR central kitchen management and control system based on the Internet of Things according to claim 2, characterized in that: The loader is located inside the raw material bin, and a preprocessor is provided between the raw material bin outlet and the conveyor belt. The preprocessor is used to simply process various raw materials to facilitate subsequent mixing and stirring; the weighing device is provided between the conveyor belt and the mixing mixer, and a flipping device for flipping the weighing device is fixedly provided under the weighing device.

4. A control method for a TMR central kitchen management control system based on the Internet of Things according to claim 2, characterized in that: in, The data information at key locations specifically includes the rising speed of the loader, the moving speed of the conveyor belt, the weighing value of the scale, the internal environmental data of the raw material warehouse, the stirring torque of the mixer, and the detection data of the feed quality detection equipment; among them, the internal environmental data of the raw material warehouse includes the internal temperature of the raw material warehouse, the internal humidity of the raw material warehouse, the internal light intensity, and the internal gas composition.

5. A control method for a TMR central kitchen management control system based on the Internet of Things, characterized in that: The method is applicable to a TMR central kitchen management and control system based on the Internet of Things according to any one of claims 1 to 4, wherein the method specifically comprises: Step S1: Raw material reception and storage: Raw materials required for TMR processing are received and stored in the raw material warehouse, and the storage environment of different raw material warehouses is customized to ensure that the storage environment is suitable for the corresponding raw materials to be stored; Step S2, raw material quality inspection: before the process starts, the raw materials in the raw material warehouse are inspected to ensure that the raw material quality is within the specification range; Step S3, formula design, calculates and formulates scientific diet formulas based on the different physiological stages, production levels, raw material inventory and nutrient composition test results of different animals; Step S4: weighing the raw materials. After leaving the warehouse, the raw materials are transported to the weighing device via a conveyor belt. Each type of raw material is accurately weighed, and the raw materials in the weighing device are transported to the mixing mixer using a turning device below the weighing device. The order in which the raw materials enter the mixing mixer follows the principle of "long first, short last, dry first, wet last, light first, heavy last"; Step S5: Mixing the raw materials. The mixer starts rotating after receiving the first batch of raw materials and provides real-time feedback on the mixing torque. The central control layer controls the mixing time of the mixer and determines the mixing status based on the feedback torque data. If a sudden change in torque occurs, it indicates a problem with the process. At this time, the central control layer issues an alarm signal and stops the system. Step S6, discharge inspection: after the mixing and stirring is completed, the mixed feed is output by the mixer. At the same time, the feed quality inspection equipment performs a preliminary inspection on the output mixed feed and feeds back the inspection data to the central control layer; Step S7, quantitative distribution, after the mixed feed is processed in step S6, it is output to the conveyor belt and transported to each feeding trough via the conveyor belt; Step S8, leftover feed management. After the delivery in step S7 is completed, the animals are released to start eating. After eating, the leftover feed is recycled and processed. The recycled leftover feed is weighed and re-tested, and the animal's eating situation is analyzed and fed back to the central control layer to adjust the content ratio of each ingredient in the formula in step S3.

6. A control method for a TMR central kitchen management control system based on the Internet of Things according to claim 5, characterized in that: Step S2 also includes raw material pretreatment. After the raw materials are taken out of the warehouse, they need to undergo a simple pretreatment process. Some large pieces of raw materials are chopped or kneaded to make the length of the large pieces of raw materials suitable for the processing of the mixer and to improve palatability and digestibility.

7. A control method for a TMR central kitchen management control system based on the Internet of Things according to claim 6, characterized in that: Step S2 also includes a discharging process. A warehouse opening for discharging is opened on the side of the raw material warehouse near the conveyor belt. Two height sensors are installed at the warehouse opening. The two height sensors are arranged vertically and maintain data transmission with the central control layer at the same time; the height sensor is used to detect the height of the discharging. When the height of the raw material is higher than the height sensor in the high position, it means that the discharging speed is too fast. At this time, the central control layer controls the loader to reduce the discharging speed; when the height of the raw material is lower than the height sensor in the low position, it means that the discharging speed is too slow. At this time, the central control layer controls the loader to increase the discharging speed.

8. A control method for a TMR central kitchen management control system based on the Internet of Things according to claim 5, characterized in that: The preliminary inspection process in step S6 is a random inspection, and the inspection frequency is once a day; step S6 specifically includes: Step S61, sampling, sampling the mixed feed at different positions of the mixer, specifically the bottom, surface, periphery and middle of the mixer; Step S62, sensory evaluation, direct contact with the sampled material to observe the overall state of the mixed feed; Step S63, screening test, screening the sampled mixed feed using a Pennsylvania sieve, performing physical fiber testing, and analyzing the particle distribution state; Step S64, component detection, uses near infrared technology to detect the specific nutritional content of the sampled mixed feed.

9. A control method for a TMR central kitchen management control system based on the Internet of Things according to claim 8, characterized in that: During the sampling process of step S6, the component detection step of step S64 also includes: obtaining the nutritional component data of the sampled mixed feed after detection by near-infrared technology, calculating the absolute value of the difference between the nutritional components, and analyzing the status of the mixed feed based on the absolute value.

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