Method and system for monitoring production process of pet soft food

Abstract

The invention discloses a pet soft food production process monitoring method and system, and relates to the technical field of intelligent monitoring, and the method comprises the following steps: obtaining response data, carrying out regulation and control according to a production target, obtaining new production parameters, and constructing a first mapping relation. According to the method, the production parameters are dynamically adjusted, regulation and control are performed according to actual data, it can be ensured that each batch of pet soft food can reach the consistent quality standard, the product quality problem caused by parameter fluctuation is reduced, the optimal production parameter combination is quickly found based on the mapping relation, the trial and error cost is reduced, the production period is shortened, and the production efficiency is improved. The production efficiency is improved, the production parameters are accurately controlled, excessive drying or heating is avoided, the energy consumption can be effectively reduced, the production cost is reduced, the growth conditions of microorganisms can be better controlled by monitoring and regulating the production process, and the sanitation and safety of products are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent monitoring, and in particular to a method and system for monitoring the production process of soft pet food. Background Art

[0002] In recent years, the combination of artificial intelligence algorithms and electronic nose technology has developed an intelligent mycotoxin detection method that can quickly and non-destructively detect the mycotoxin contamination level in pet soft food, significantly reducing the detection time and cost compared to traditional methods. TM 2) Installed on the production line, it measures important parameters such as protein, fat, and moisture in real time, helping production personnel to adjust production parameters in a timely manner to ensure that products meet quality requirements. By using big data analysis and artificial intelligence algorithms, it builds a mapping relationship between production parameters and product quality, optimizes the production process in a data-driven manner, and improves production efficiency and product quality.

[0003] At present, a Chinese invention patent with publication number CN112572908B discloses a wet food canning device for pet cat food production. The method can can wet cat food through the cooperation of a movable seat mechanism and a stop plate mechanism, and can intermittently push the wet food can onto the movable seat mechanism through the can pushing mechanism, thereby achieving the purpose of automatically pushing the wet food can to move, eliminating the need for manual repeated addition and placement of wet food cans, and reducing the labor of workers. However, the relevant technology does not dynamically adjust the production parameters based on historical production data and specific parameters of pet food, lacks the pertinence and continuity of production monitoring, and does not establish a mapping relationship between the relevant parameters of pet food and the production parameters, which is not conducive to quickly browsing the production parameters corresponding to the product. It lacks monitoring clarity, and does not split the monitoring process parameters and independently monitor them according to the process characteristics of the pet food, which easily leads to monitoring errors. Summary of the Invention

[0004] The technical problems solved by the present invention are: the relevant technologies do not dynamically adjust the production parameters based on historical production data and specific parameters of pet food, lack the pertinence and continuity of production monitoring, do not establish a mapping relationship between the relevant parameters of pet food and the production parameters, which is not conducive to quickly browsing the production parameters corresponding to the product, lack monitoring clarity, and do not split the monitoring process parameters and monitor them independently according to the process characteristics of pet food, which easily leads to monitoring errors.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, a method for monitoring the production process of soft pet food comprises the following steps:

[0006] Step S100, setting the first production parameter and the second production parameter, obtaining the first response data of the first production parameter and the second response data of the soft grain under the second production parameter;

[0007] Step S200, obtaining a production target, and performing a first regulation and a second regulation on the first production parameter and the second production parameter respectively according to the production target to obtain a third production parameter and a fourth production parameter respectively;

[0008] Step S300: constructing a first mapping relationship based on the relevant data of the soft pet food, the third production parameter, and the fourth production parameter.

[0009] As a preferred embodiment of the method for monitoring the production process of soft pet food described in the present invention, the first production parameter includes a first temperature, a screw speed, and a first production time. The first temperature represents the temperature for high-temperature puffing of the soft pet food. The first production time represents the preset production time for high-temperature puffing of the soft pet food. The first temperature includes a first low-speed temperature and a first high-speed temperature, which represent the temperature for high-temperature and high-speed puffing of the soft pet food and the temperature for high-temperature and low-speed puffing of the soft pet food, respectively. The corresponding first production times are the first high-speed production time and the first low-speed production time, respectively.

[0010] The second production parameters include a second temperature, wind speed, humidity, and a second production time, wherein the second temperature represents the drying temperature of the soft pet food, and the second production time represents the drying time of the soft pet food;

[0011] The first response data is represented by the fluffiness of the soft grain at the end of the first production time;

[0012] The second response data is represented by the moisture content of the soft grain at the end of the second production time period.

[0013] As a preferred embodiment of the method for monitoring the production process of soft pet food according to the present invention, step S100 further includes the following sub-steps:

[0014] Step S101, accessing a production database, and accessing any historical production data from the production data, wherein the historical production data includes a historical first temperature, a historical screw speed, a historical first production duration, a historical second temperature, a historical wind speed, a historical humidity, and a historical production duration;

[0015] Step S102 : Calculate the average value of each historical production data respectively, and set the average value of each historical production data as the first production parameter and the second production parameter.

[0016] As a preferred embodiment of the method for monitoring the production process of soft pet food of the present invention, the production target is expressed as a target fluffiness and a target moisture content;

[0017] performing a first adjustment on the first low-speed temperature or the first high-speed temperature or the screw speed or the first production time according to the target bulkiness to obtain a third production parameter;

[0018] A second adjustment is performed on the second temperature or wind speed or humidity or the second production time according to the target moisture content to obtain a fourth production parameter.

[0019] As a preferred embodiment of the method for monitoring the production process of soft pet food according to the present invention, the first control method includes:

[0020] The high-temperature and high-speed fluffing stage and the high-temperature and low-speed fluffing stage were each assigned a weight value of 0.5. In the high-temperature and high-speed fluffing stage, the first multivariate regression analysis was performed with the soft grain fluffiness as the dependent variable and the first high-speed temperature, screw speed, and first high-speed production time as independent variables to obtain the first coefficient of each independent variable.

[0021] In the high-temperature and low-speed fluffing stage, the second multiple regression analysis was conducted with the soft grain fluffiness as the dependent variable and the first low-speed temperature, screw speed and first low-speed production time as the independent variables to obtain the second coefficient of each independent variable;

[0022] Take half the value of the first coefficient and set it as the new first coefficient, take half the value of the second coefficient and set it as the new second coefficient, construct a fluffiness control model based on the new first coefficient and the new second coefficient, and perform a first control on the first parameter based on the fluffiness control model.

[0023] As a preferred embodiment of the method for monitoring the production process of soft pet food according to the present invention, the calculation expression of the fluffiness model is:

[0024]

[0025] Among them, y1 is the soft grain fluffiness in the high-temperature and high-speed fluffiness stage, y2 is the soft grain fluffiness in the high-temperature and low-speed fluffiness stage, c1~c3 are the coefficients of the first high-speed temperature, screw speed, and first high-speed production time in the high-temperature and high-speed fluffiness stage, c4~c5 are the first low-speed temperature, screw speed, and first low-speed production time in the high-temperature and low-speed fluffiness stage, x1~x3 are the independent variables corresponding to the high-temperature and high-speed fluffiness stage, and x4~x6 are the independent variables corresponding to the high-temperature and low-speed fluffiness stage.

[0026] As a preferred embodiment of the method for monitoring the production process of soft pet food described in the present invention, the target fluffiness is input into the fluffiness model to obtain the value of each corresponding independent variable, and the value of each independent variable is compared with the current first production parameter and the current second production parameter. When the value of each independent variable is not exactly the same as the current first production parameter and the current second production parameter, the different parameters are continuously increased or decreased until the value of each independent variable is exactly the same as the current first production parameter and the current second production parameter, the first regulation is stopped, and the regulated first production parameter is set as the third production parameter.

[0027] As a preferred embodiment of the method for monitoring the production process of soft pet food according to the present invention, the second control method includes:

[0028] Performing a second regulation based on the target moisture content to obtain a fourth production parameter, obtaining a current moisture content, comparing the current moisture content with the target moisture content, and performing a second regulation when the target moisture content is less than the current moisture content. After the second regulation is completed, setting the regulated second production parameter as the production parameter;

[0029] When the target moisture content is greater than or equal to the current moisture content, not only the second regulation is performed, but also the second production parameter is updated to the fourth production parameter;

[0030] The first value is set as the second temperature single change amount, the second value is set as the wind speed single change amount, the third value is set as the humidity single change amount, and the fourth value is set as the second production time single change amount;

[0031] When a second regulation is required, each second production parameter and the corresponding single change amount are continuously added or subtracted, and the corresponding soft grain moisture content is continuously obtained. When the soft grain moisture content is less than or equal to the target moisture content, the regulation of the second production parameter is stopped, and the calculated second production parameter is updated to the fourth production parameter.

[0032] As a preferred embodiment of the method for monitoring the production process of soft pet food of the present invention, the relevant data of the soft pet food includes the ingredients of the soft pet food and the proportion of each ingredient;

[0033] A first mapping relationship is constructed based on the relevant data of the pet soft food, the third production parameter and the fourth production parameter. By inputting the relevant data of the new pet soft food into the first mapping relationship, the new third production parameter and the new fourth production parameter corresponding to the relevant data of the new pet soft food are matched.

[0034] In the second aspect, a pet soft food production process monitoring system includes a simulation module, a control module and a construction module;

[0035] The simulation module sets a first production parameter and a second production parameter, and obtains first response data of the first production parameter and second response data of the soft grain under the second production parameter;

[0036] The control module obtains a production target, and performs a first control and a second control on the first production parameter and the second production parameter according to the production target, to obtain a third production parameter and a fourth production parameter respectively;

[0037] The construction module constructs a first mapping relationship according to relevant data of the soft pet food, the third production parameter and the fourth production parameter.

[0038] The beneficial effects of the present invention are as follows: by dynamically adjusting production parameters and regulating according to actual data, it is possible to ensure that each batch of soft pet food meets consistent quality standards, reduce product quality problems caused by parameter fluctuations, quickly find the optimal production parameter combination based on the mapping relationship, reduce trial and error costs, shorten the production cycle, improve production efficiency, accurately control production parameters, avoid excessive drying or heating, effectively reduce energy consumption, reduce production costs, and better control microbial growth conditions by monitoring and regulating the production process to ensure product hygiene and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A schematic diagram of the basic flow of a method for monitoring the production process of soft pet food provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0041] Example, see Figure 1 , as one embodiment of the present invention, provides a method for monitoring the production process of soft pet food, comprising the following steps:

[0042] Step S100, setting the first production parameter and the second production parameter, obtaining the first response data of the first production parameter and the second response data of the soft grain under the second production parameter;

[0043] Step S200, obtaining a production target, and performing a first regulation and a second regulation on the first production parameter and the second production parameter respectively according to the production target to obtain a third production parameter and a fourth production parameter respectively;

[0044] Step S300: constructing a first mapping relationship based on the relevant data of the soft pet food, the third production parameter, and the fourth production parameter.

[0045] The present invention dynamically adjusts production parameters and regulates them according to actual data, thereby ensuring that each batch of soft pet food meets consistent quality standards, reducing product quality problems caused by parameter fluctuations, and quickly finding the optimal production parameter combination based on the mapping relationship, reducing trial and error costs, shortening the production cycle, improving production efficiency, and accurately controlling production parameters to avoid excessive drying or heating. It can effectively reduce energy consumption and production costs, and by monitoring and regulating the production process, it can better control microbial growth conditions and ensure the hygiene and safety of the product.

[0046] The first production parameters include a first temperature, a screw speed, and a first production time. The first temperature represents the temperature for high-temperature puffing of the soft pet food. The first production time represents the preset production time for high-temperature puffing of the soft pet food. The first temperature includes a first low-speed temperature and a first high-speed temperature, which represent the temperature for high-temperature and high-speed puffing of the soft pet food and the temperature for high-temperature and low-speed puffing of the soft pet food, respectively. The corresponding first production times are the first high-speed production time and the first low-speed production time, respectively.

[0047] The second production parameters include a second temperature, wind speed, humidity, and a second production time. The second temperature represents the drying temperature of the soft pet food, and the second production time represents the drying time of the soft pet food.

[0048] The first response data is expressed as the soft grain fluffiness at the end of the first production period;

[0049] The second response data is represented by the moisture content of the soft grain at the end of the second production period.

[0050] In specific implementation, by setting the parameters of high-temperature puffing (including high-temperature high-speed and high-temperature low-speed puffing) and drying respectively, and adjusting according to actual response data (such as the fluffiness and moisture content of soft food), it is possible to ensure that the pet soft food achieves ideal physical properties during the production process. The optimized production parameters can make the texture, fluffiness and moisture content of the soft food reach the best, thereby improving the palatability of the product while reducing the loss of nutrients. By constructing a mapping relationship, production personnel can quickly adjust production parameters according to the target to avoid production failure or defective products caused by improper parameter settings, thereby improving production efficiency. Accurate parameter control can reduce production delays caused by parameter fluctuations and ensure the continuity and stability of the production process. By precisely controlling the drying temperature and time, the moisture content of the soft food is ensured to be within a safe range, thereby reducing the breeding of microorganisms and extending the shelf life of the product. It can be flexibly adjusted according to different raw material characteristics and product requirements, and has strong adaptability.

[0051] Step S100 also includes the following sub-steps:

[0052] Step S101, retrieve the production database and retrieve any historical production data from the production data, the historical production data including the historical first temperature, the historical screw speed, the historical first production time, the historical second temperature, the historical wind speed, the historical humidity and the historical production time;

[0053] Step S102 : Calculate the average value of each historical production data respectively, and set the average value of each historical production data as the first production parameter and the second production parameter.

[0054] Production targets are expressed as target bulk and target moisture content;

[0055] performing a first adjustment on the first low-speed temperature or the first high-speed temperature or the screw speed or the first production time according to the target bulkiness to obtain a third production parameter;

[0056] A second adjustment is performed on the second temperature or wind speed or humidity or the second production time according to the target moisture content to obtain a fourth production parameter.

[0057] In specific implementation, the production process can be started quickly and the downtime caused by parameter adjustment can be reduced, the utilization rate of production equipment can be improved, and a simple and easy-to-understand parameter setting method is provided for new employees to help them quickly master production operations. Parameter settings based on historical data are used as part of the operating standards to ensure consistency among different operators.

[0058] The first control method includes:

[0059] The high-temperature and high-speed fluffing stage and the high-temperature and low-speed fluffing stage were each assigned a weight value of 0.5. In the high-temperature and high-speed fluffing stage, the first multivariate regression analysis was performed with the soft grain fluffiness as the dependent variable and the first high-speed temperature, screw speed, and first high-speed production time as independent variables to obtain the first coefficient of each independent variable.

[0060] In the high-temperature and low-speed fluffing stage, the second multiple regression analysis was conducted with the soft grain fluffiness as the dependent variable and the first low-speed temperature, screw speed and first low-speed production time as the independent variables to obtain the second coefficient of each independent variable;

[0061] Take half the value of the first coefficient and set it as the new first coefficient, take half the value of the second coefficient and set it as the new second coefficient, construct a fluffiness control model based on the new first coefficient and the new second coefficient, and perform a first control on the first parameter based on the fluffiness control model.

[0062] The calculation expression of the bulkiness model is:

[0063]

[0064] Among them, y1 is the soft grain fluffiness in the high-temperature and high-speed fluffiness stage, y2 is the soft grain fluffiness in the high-temperature and low-speed fluffiness stage, c1~c3 are the coefficients of the first high-speed temperature, screw speed, and first high-speed production time in the high-temperature and high-speed fluffiness stage, c4~c5 are the first low-speed temperature, screw speed, and first low-speed production time in the high-temperature and low-speed fluffiness stage, x1~x3 are the independent variables corresponding to the high-temperature and high-speed fluffiness stage, and x4~x6 are the independent variables corresponding to the high-temperature and low-speed fluffiness stage.

[0065] In practice, fluffiness is a key physical property of soft pet food, influencing its palatability and digestibility. Precisely controlling fluffiness ensures better palatability and nutritional value. By constructing a fluffiness control model, we can quickly identify optimal production parameters to achieve the desired fluffiness, reducing commissioning time during production. Precise parameter control ensures continuity and stability in the production process, minimizing interruptions caused by parameter fluctuations. By ensuring stable and consistent product quality, we can enhance brand image and strengthen consumer trust in our products.

[0066] Input the target bulkiness into the bulkiness model to obtain the values of the corresponding independent variables, compare the values of the independent variables with the current first production parameter and the current second production parameter, and when the values of the independent variables are not exactly the same as the current first production parameter and the current second production parameter, continuously increase or decrease the different parameters until the values of the independent variables are exactly the same as the current first production parameter and the current second production parameter, stop the first regulation, and set the regulated first production parameter as the third production parameter.

[0067] In specific implementation, a stable production process improves the utilization rate of production equipment, reduces equipment maintenance costs, obtains real-time response data during the production process, and dynamically adjusts production parameters based on this data, ensuring that each batch of products meets quality standards. As the pet food market's demand for personalized and functional products increases, this control method can help companies quickly adjust production processes to meet the needs of different customers.

[0068] The second control method includes:

[0069] Performing a second regulation based on the target moisture content to obtain a fourth production parameter, obtaining a current moisture content, comparing the current moisture content with the target moisture content, and performing a second regulation when the target moisture content is less than the current moisture content. After the second regulation is completed, setting the regulated second production parameter as the production parameter;

[0070] When the target moisture content is greater than or equal to the current moisture content, not only the second regulation is performed, but also the second production parameter is updated to the fourth production parameter;

[0071] The first value is set as the second temperature single change amount, the second value is set as the wind speed single change amount, the third value is set as the humidity single change amount, and the fourth value is set as the second production time single change amount;

[0072] When a second regulation is required, each second production parameter and the corresponding single change amount are continuously added or subtracted, and the corresponding soft grain moisture content is continuously obtained. When the soft grain moisture content is less than or equal to the target moisture content, the regulation of the second production parameter is stopped, and the calculated second production parameter is updated to the fourth production parameter.

[0073] In specific implementation, product quality problems caused by too high or too low moisture content are avoided, the defective rate is reduced, and production efficiency is improved. By precisely controlling the drying process, energy waste and raw material waste caused by improper parameter settings are reduced. By setting the single change amount of temperature, wind speed, humidity and drying time, parameters can be adjusted more finely to avoid production instability caused by excessive adjustment. Through continuous accumulation or subtraction calculations and real-time monitoring of moisture content, the continuity and accuracy of parameter adjustment are ensured.

[0074] The relevant data of pet soft food include the ingredients and proportion of each ingredient;

[0075] A first mapping relationship is constructed based on the relevant data of the pet soft food, the third production parameter and the fourth production parameter. By inputting the relevant data of the new pet soft food into the first mapping relationship, the new third production parameter and the new fourth production parameter corresponding to the new relevant data of the pet soft food are matched.

[0076] In specific implementation, by constructing a mapping relationship, the most suitable production parameters (the third production parameter and the fourth production parameter) are quickly matched according to the different ingredients and proportions of pet soft food. This helps to ensure that each batch of products can meet the expected quality standards. The ingredients and proportions of pet soft food directly affect its nutritional value and palatability. Through precise control of production parameters, the physical properties of the product such as texture, fluffiness, and moisture content are ensured to remain consistent, thereby improving the stability of product quality. Pet soft food usually contains meat, grains, soy products, lipids, vitamins, minerals and other ingredients. By precisely controlling the production parameters, these nutrients can be better retained, reducing nutrient loss caused by high temperature or long processing time. The optimal production parameters are quickly found through the mapping relationship, reducing production delays caused by parameter adjustments and improving production efficiency.

[0077] The present invention dynamically adjusts production parameters and regulates them according to actual data, thereby ensuring that each batch of soft pet food meets consistent quality standards, reducing product quality problems caused by parameter fluctuations, and quickly finding the optimal production parameter combination based on the mapping relationship, reducing trial and error costs, shortening the production cycle, improving production efficiency, and accurately controlling production parameters to avoid excessive drying or heating. It can effectively reduce energy consumption and production costs, and by monitoring and regulating the production process, it can better control microbial growth conditions and ensure the hygiene and safety of the product.

[0078] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a fully hardware embodiment, a fully software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage medium may be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0079] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that modifications or equivalent replacements of the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A method for monitoring the production process of pet soft food, characterized in that: The following steps are involved: Step S100, setting the first production parameter and the second production parameter, obtaining the first response data of the first production parameter and the second response data of the soft grain under the second production parameter; Step S200, obtaining a production target, and performing a first regulation and a second regulation on the first production parameter and the second production parameter respectively according to the production target to obtain a third production parameter and a fourth production parameter respectively; Step S300: constructing a first mapping relationship based on the relevant data of the soft pet food, the third production parameter, and the fourth production parameter.

2. The method for monitoring the production process of soft pet food according to claim 1, wherein: The first production parameters include a first temperature, a screw speed, and a first production time. The first temperature represents the temperature for high-temperature puffing of the soft pet food. The first production time represents the preset production time for high-temperature puffing of the soft pet food. The first temperature includes a first low-speed temperature and a first high-speed temperature, which represent the temperature for high-temperature and high-speed puffing of the soft pet food and the temperature for high-temperature and low-speed puffing of the soft pet food, respectively. The corresponding first production times are the first high-speed production time and the first low-speed production time, respectively. The second production parameters include a second temperature, wind speed, humidity, and a second production time, wherein the second temperature represents the drying temperature of the soft pet food, and the second production time represents the drying time of the soft pet food; The first response data is represented by the fluffiness of the soft grain at the end of the first production time; The second response data is represented by the moisture content of the soft grain at the end of the second production time period.

3. The method for monitoring the production process of soft pet food according to claim 1, wherein: The step S100 further includes the following sub-steps: Step S101, accessing a production database, and accessing any historical production data from the production data, wherein the historical production data includes a historical first temperature, a historical screw speed, a historical first production duration, a historical second temperature, a historical wind speed, a historical humidity, and a historical production duration; Step S102 : Calculate the average value of each historical production data respectively, and set the average value of each historical production data as the first production parameter and the second production parameter.

4. The method for monitoring the production process of soft pet food according to claim 1, wherein: The production target is expressed as target bulk and target moisture content; performing a first adjustment on the first low-speed temperature or the first high-speed temperature or the screw speed or the first production time according to the target bulkiness to obtain a third production parameter; A second adjustment is performed on the second temperature or wind speed or humidity or the second production time according to the target moisture content to obtain a fourth production parameter.

5. The method for monitoring the production process of soft pet food according to claim 4, wherein: The first control method includes: The high-temperature and high-speed fluffing stage and the high-temperature and low-speed fluffing stage were each assigned a weight value of 0.

5. In the high-temperature and high-speed fluffing stage, the first multivariate regression analysis was performed with the soft grain fluffiness as the dependent variable and the first high-speed temperature, screw speed, and first high-speed production time as independent variables to obtain the first coefficient of each independent variable. In the high-temperature and low-speed fluffing stage, the second multiple regression analysis was conducted with the soft grain fluffiness as the dependent variable and the first low-speed temperature, screw speed and first low-speed production time as the independent variables to obtain the second coefficient of each independent variable; Take half the value of the first coefficient and set it as the new first coefficient, take half the value of the second coefficient and set it as the new second coefficient, construct a fluffiness control model based on the new first coefficient and the new second coefficient, and perform a first control on the first parameter based on the fluffiness control model.

6. The method for monitoring the production process of soft pet food according to claim 5, wherein: The calculation expression of the bulkiness model is: Among them, y1 is the soft grain fluffiness in the high-temperature and high-speed fluffiness stage, y2 is the soft grain fluffiness in the high-temperature and low-speed fluffiness stage, c1~c3 are the coefficients of the first high-speed temperature, screw speed, and first high-speed production time in the high-temperature and high-speed fluffiness stage, c4~c5 are the first low-speed temperature, screw speed, and first low-speed production time in the high-temperature and low-speed fluffiness stage, x1~x3 are the independent variables corresponding to the high-temperature and high-speed fluffiness stage, and x4~x6 are the independent variables corresponding to the high-temperature and low-speed fluffiness stage.

7. The method for monitoring the production process of soft pet food according to claim 6, wherein: Input the target bulkiness into the bulkiness model to obtain the values of the corresponding independent variables, compare the values of the independent variables with the current first production parameter and the current second production parameter, and when the values of the independent variables are not exactly the same as the current first production parameter and the current second production parameter, continuously increase or decrease the different parameters until the values of the independent variables are exactly the same as the current first production parameter and the current second production parameter, stop the first regulation, and set the regulated first production parameter as the third production parameter.

8. The method for monitoring the production process of soft pet food according to claim 4, wherein: The second control method includes: Performing a second regulation based on the target moisture content to obtain a fourth production parameter, obtaining a current moisture content, comparing the current moisture content with the target moisture content, and performing a second regulation when the target moisture content is less than the current moisture content. After the second regulation is completed, setting the regulated second production parameter as the production parameter; When the target moisture content is greater than or equal to the current moisture content, not only the second regulation is performed, but also the second production parameter is updated to the fourth production parameter; The first value is set as the second temperature single change amount, the second value is set as the wind speed single change amount, the third value is set as the humidity single change amount, and the fourth value is set as the second production time single change amount; When a second regulation is required, each second production parameter and the corresponding single change amount are continuously added or subtracted, and the corresponding soft grain moisture content is continuously obtained. When the soft grain moisture content is less than or equal to the target moisture content, the regulation of the second production parameter is stopped, and the calculated second production parameter is updated to the fourth production parameter.

9. The method for monitoring the production process of soft pet food according to claim 1, wherein: The relevant data of pet soft food include the ingredients and proportion of each ingredient; A first mapping relationship is constructed based on the relevant data of the pet soft food, the third production parameter and the fourth production parameter. By inputting the relevant data of the new pet soft food into the first mapping relationship, the new third production parameter and the new fourth production parameter corresponding to the relevant data of the new pet soft food are matched.

10. A pet soft food production process monitoring system, the system being used to implement the pet soft food production process monitoring method according to claim 1, characterized in that: Includes simulation module, control module and construction module; The simulation module sets a first production parameter and a second production parameter, and obtains first response data of the first production parameter and second response data of the soft grain under the second production parameter; The control module obtains a production target, and performs a first control and a second control on the first production parameter and the second production parameter according to the production target, to obtain a third production parameter and a fourth production parameter respectively; The construction module constructs a first mapping relationship according to relevant data of the soft pet food, the third production parameter and the fourth production parameter.

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