A real-time monitoring and management system for a puffed food production line based on big data

Abstract

The present invention discloses a real-time monitoring and management system for an extruded food production line based on big data, including a data acquisition module, a production line analysis module, a debris prediction module, and an adjustment and control module. The data acquisition module is used to collect relevant information of production equipment for the system; the production line analysis module is used to analyze the production line for transporting products; the debris prediction module is used to evaluate the probability of product breakage; the adjustment and control module is used to adjust the production line. By monitoring the transportation process of the extruded food production line in real time, analyzing the collision force generated by products on the conveyor belt, and judging the safety level of target products in the production line, the present invention monitors the probability of product breakage during transportation on the conveyor belt and adjusts the production line parameters through the adjustment and control module, greatly avoiding the problem of the decline in product reputation caused by too high product breakage rate. The present invention has the characteristics of high product quality and high monitoring accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of production line management, and particularly to a real-time monitoring and management system for a puffed food production line based on big data. Background Technique

[0002] In current industrial production, electricity consumption accounts for one of the main costs. To achieve efficient energy management, reduce operating costs, and improve production safety, factories need to build a comprehensive real-time monitoring and management system for production lines. Through the real-time monitoring and management system set in the production line, not only can detailed operation data of the production line be obtained at any time to optimize the production plan, but also production efficiency and machine efficiency can be improved, electricity costs can be reduced, and accurate data support can be provided.

[0003] In the production line for making puffed foods, there are a wide variety of food products, complex ingredients, and numerous production and manufacturing links. Especially during the peak season when there are many food orderers, due to the sales requirements of products by production companies, the operating speed of the production line is relatively fast. Even for a company like Lay's with very mature production technology, it is inevitable to have situations of food stacking and extrusion during the production operation process, which leads to the problem that some foods are broken and cannot be avoided, and it is very easy to damage the reputation of this brand. In the prior art, the production line monitoring system still lacks effective detection means for regulating and controlling the problem of broken puffed foods during the rapid production and transmission process of the production line. Therefore, it is very necessary to design a real-time monitoring and management system for a puffed food production line based on big data with high product quality and high monitoring accuracy. Summary of the Invention

[0004] The purpose of the present invention is to provide a real-time monitoring and management system for a puffed food production line based on big data to solve the problems raised in the above background technique.

[0005] To solve the above technical problems, the present invention provides the following technical solution: A real-time monitoring and management system for a puffed food production line based on big data, including a data acquisition module, a production line analysis module, a debris prediction module, and an adjustment and control module. The data acquisition module is used to collect relevant information of production equipment for the system; the production line analysis module is used to analyze the production line for transporting products; the debris prediction module is used to evaluate the probability of product breakage; the adjustment and control module is used to adjust the production line;

[0006] The production line analysis module includes a conveyor belt analysis module for analyzing the collision force of the target product on the conveyor belt of the transmission pipeline of the production equipment.

[0007] The debris prediction module includes: a compression force analysis module and a collision force analysis module. The compression force analysis module is used to estimate the probability of the target product being broken due to the compression force on the target product; the collision force analysis module is used to analyze whether the collision between the target products may cause the target product to break.

[0008] The compression force analysis module includes: a stacking analysis sub-module and a squeezing analysis sub-module. The stacking analysis sub-module estimates the probability of the target product being broken due to the stacking of multiple target products; the squeezing analysis sub-module estimates the probability of the target product being broken due to the squeezing between the target products.

[0009] According to the above technical solution, the data acquisition module includes a product data collection module and an equipment data collection module. The product data collection module is used to obtain the fragility of the target product; the equipment data collection module is used to obtain the relevant parameters of the production equipment. The equipment data collection module includes a transmission data sub-module and a pipeline data sub-module. The transmission data sub-module is used to obtain the relevant information of the conveyor belt of the production line; the pipeline data sub-module is used to obtain the parameters of the production equipment pipeline.

[0010] According to the above technical solution, the production line analysis module further includes a pause time analysis module and a camera module. The pause time analysis module is used to analyze the flow rate of the target product in the transmission process; the camera module is used to take pictures of the production equipment transmission pipeline.

[0011] According to the above technical solution, the adjustment control module includes a production line adjustment module and a product transmission volume control module. The production line diagram adjustment module is used to adjust the transmission speed of the production line in real time; the product transmission volume control module is used to control the number of target products transmitted through the output pipeline.

[0012] According to the above technical solution, the operation method of the production line real-time monitoring and management system mainly includes the following steps:

[0013] Step S1: The data acquisition module obtains the relevant information of the food production line. The product data collection module obtains the product information produced on the same day. The limit value of no breakage when the target products collide with each other is M; the equipment data collection module obtains the conveyor belt speed V of the production equipment and the safe speed E of the conveyor belt through the transmission data sub-module, and obtains the parameters of the production equipment pipeline through the pipeline data sub-module.

[0014] Step S2: The production line analysis module stores relevant information of the production line through the data acquisition module, and the camera module captures the scene of the target product being transported during the transmission process, and obtains that the angle between the transmission process pipeline of the production equipment and the plane is X°; the pause time analysis module analyzes the number of target products input from the conveyor belt entrance during the interval time through the transportation video;

[0015] Step S3: The conveyor belt analysis module obtains the conveyor belt information of the transmission process pipeline of the production equipment, and analyzes the collision force generated by the target product in the transmission pipeline affected by the conveyor belt speed;

[0016] Step S4: The debris prediction module extracts the parameter information of the production equipment in the production line analysis module, and analyzes the possibility that the target product may be broken during the conveyor belt transportation time;

[0017] Step S5: The compression force analysis module estimates the probability of the target product being broken due to the compression force, and transmits the broken ratio information to the adjustment control module;

[0018] Step S6: The collision force analysis module estimates the probability of the target product being broken due to the collision between the target products, and transmits the broken ratio information to the adjustment control module;

[0019] Step S7: The adjustment control module receives the broken ratio information sent by the compression force analysis module and the collision force analysis module respectively, and adjusts the operation rate of the production line through the production line adjustment module; at the same time, the product transmission volume control module outputs information to the system to reduce the transportation volume of the product through the pipeline.

[0020] According to the above technical solution, in the step S2, after the pause time analysis sub-module obtains that the conveyor belt of the pipeline conveys the target product for A seconds, the system controls the conveyor belt to stop advancing for B seconds, where A > B. The target product is in the normal transmission stage within A seconds, and stacking and extrusion occur within B seconds after the baffle is erected; at the same time, it is analyzed through the camera module that the number of target products transmitted per second from the conveyor belt entrance is K, and the number of target products transmitted per second following the conveyor belt is Z 1 。

[0021] According to the above technical solution, in the step S3, the additional collision force generated by the conveyor belt where m is the mass of a single target product and g is the acceleration due to gravity.

[0022] According to the above technical solution, in step S5, if the speed V of the equipment conveyor belt is lower than the safe speed E of the conveyor belt, the pressure of the target product on the rear conveyor belt on the target product at the baffle can be ignored. Therefore, only the pressure on the target product under stacking is considered; the stacking analysis sub-module calculates the pressure on the bottommost target product under stacking. When stacking of target products occurs on the conveyor belt, the number of pieces of target products stacked per unit area at the end of the conveyor belt is where μ is the target product stacking index, δ is the unit conversion parameter. After rounding the calculation result of Z, the probability that the nth target product from top to bottom in the stacked target products is crushed due to extrusion is where n is a positive integer and n ≤ Z, λ 1 is the superposition parameter, and its value is determined according to the flexibility of the target product, 0 < λ 1 < 1. The probability η(n) of the nth target product being broken is η(n) = L(n). If the result is less than or equal to (1 - the integrity qualification rate Ω of the target product), it is determined that the production line speed is qualified; if the result is greater than (1 - the integrity qualification rate Ω of the target product), it is determined that the production line speed is unqualified, and the information is transmitted to the adjustment control module.

[0023] If the speed V of the equipment conveyor belt is higher than the safe speed E of the conveyor belt, the pressure of the target product on the rear conveyor belt on the target product at the baffle should also be additionally considered. The extrusion analysis sub-module calculates the pressure of the target product on the rear conveyor belt on the target product at the baffle. When the baffle is erected, the target product on the rear conveyor belt extrudes the target product at the baffle. Through data analysis and statistics, the number of pieces of target products per unit area of the baffle is Q, and Q is a positive integer. Then the probability that the ith target product from the conveyor belt inlet to the conveyor belt end in the extruded target products is crushed due to extrusion is where i is a positive integer and i ≤ Q, λ 2 is the extrusion parameter, and its value is determined according to the flexibility of the target product, 0 < λ 2 < 0.2. The probability that the target product at the nth layer and the ith piece is broken is specifically If the result is less than or equal to (1 - the integrity qualification rate Ω of the target product), it is determined that the production line speed is qualified; if the result is greater than (1 - the integrity qualification rate Ω of the target product), it is determined that the production line speed is unqualified, and the information is transmitted to the adjustment control module.

[0024] According to the above technical solution, in step S6, the collision force analysis module calculates the probability that the target product is broken due to collision. Since the transmission speed of the target product following the conveyor belt is different from the actual speed of the flying target product, the flying target product exerts a collision force f on the target product following the conveyor belt 1, the single collision force fu received by a target product is fu = fe + f1, and the total collision force received by all target products If the total collision force F > M, it is determined that the collision force received by the target product is too large; if the total collision force F ≤ M, it is determined that the collision force received by the target product is normal.

[0025] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: Through the real-time monitoring and management system of the production line, the present invention monitors the transportation process of the production line of puffed food in real time, analyzes the collision force generated by the products on the conveyor belt through the production line analysis module, and judges the safety degree of the target products in the production line through the collision force analysis module; at the same time, the stacking analysis sub-module and the extrusion analysis sub-module monitor the probability of product breakage during the transportation of the products on the conveyor belt, and adjust the production line parameters through the adjustment control module, greatly avoiding the problem of the decline in product reputation caused by too high product breakage rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, and do not constitute a limitation to the present invention.

[0027] In the drawings:

[0028] Figure 1 is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0030] Please refer to Figure 1 , the present invention provides a technical solution: A real-time monitoring and management system for a puffed food production line based on big data, including:

[0031] A data acquisition module, a production line analysis module, a debris prediction module, and an adjustment control module. The data acquisition module is used to collect relevant information of production equipment for the system; the production line analysis module is used to analyze the production line for transporting products; the debris prediction module is used to evaluate the probability of product breakage; the adjustment control module is used to adjust the production line;

[0032] The production line analysis module includes a conveyor belt analysis module, which analyzes the collision force of the target products on the conveyor belt of the transmission pipeline of the production equipment;

[0033] The debris prediction module includes: a compression force analysis module and a collision force analysis module. The compression force analysis module is used to estimate the probability of the target product being broken due to the compression force applied. The collision force analysis module is used to analyze whether the collision between the target products may cause the target products to break.

[0034] The compression force analysis module includes: a stacking analysis sub-module and an extrusion analysis sub-module. The stacking analysis sub-module estimates the probability of the target product being broken due to the stacking of multiple target products. The extrusion analysis sub-module estimates the probability of the target product being broken due to the extrusion between the target products.

[0035] Through the production line real-time monitoring and management system of the present invention, real-time monitoring is carried out during the transportation process of the production line of the puffed food. The impact force generated by the products on the conveyor belt is analyzed by the production line analysis module, and the safety degree of the target products in the production line is judged by the collision force analysis module. At the same time, the stacking analysis sub-module and the extrusion analysis sub-module monitor the probability of the products being broken during the transportation on the conveyor belt, and adjust the production line parameters through the adjustment control module, which greatly avoids the problem of the decline of the product reputation caused by too high product breakage rate.

[0036] The data acquisition module includes a product data collection module and an equipment data collection module. The product data collection module is used to obtain the fragility degree of the target product, that is, under how much force it is easy to break. The equipment data collection module is used to obtain the relevant parameters of the production equipment. The equipment data collection module includes a transmission data sub-module and a pipeline data sub-module. The transmission data sub-module is used to obtain the relevant information of the conveyor belt of the production line. The pipeline data sub-module is used to obtain the parameters of the production equipment pipeline.

[0037] The production line analysis module further includes a pause time analysis module and a camera module. The pause time analysis module is used to analyze the flow rate of the target products in the transmission process. The camera module is used to take pictures of the transmission pipeline of the production equipment.

[0038] The adjustment control module includes a production line adjustment module and a product transmission volume control module. The production line diagram adjustment module is used to adjust the transmission speed of the production line in real time. The product transmission volume control module is used to control the number of target products transmitted through the output pipeline.

[0039] In a preferred embodiment, the operation method of the production line real-time monitoring and management system mainly includes the following steps:

[0040] Step S1: The data acquisition module obtains relevant information of the food production line, the information on the number of products to be produced on the same day. The product data collection module obtains the product information produced on the same day. The limit value M for the target products not to be broken when colliding with each other is obtained. The equipment data collection module obtains the conveyor belt speed V and the safe speed E of the conveyor belt of the production equipment through the transmission data sub-module, and obtains the parameters of the pipeline of the production equipment through the pipeline data sub-module.

[0041] Step S2: The production line analysis module, based on the production line-related information stored by the data acquisition module, the camera module shoots the scene of the target product transportation in the transmission process, and obtains the angle X° between the pipeline of the production equipment transmission process and the plane. The pause time analysis module analyzes the number of target products input from the conveyor belt entrance during the interval time through the transportation video.

[0042] Step S3: The conveyor belt analysis module obtains the conveyor belt information of the pipeline of the production equipment transmission process, and analyzes the collision force generated by the target products in the transmission pipeline affected by the conveyor belt speed.

[0043] Step S4: The debris prediction module extracts the parameter information of the production equipment in the production line analysis module, and analyzes the possibility of the target products being broken during the conveyor belt transportation time. The force sources causing the target products to break are divided into compressive force and collision force.

[0044] Step S5: The compressive force analysis module estimates the probability of the target products being broken due to the compressive force, and transmits the broken ratio information to the adjustment control module.

[0045] Step S6: The collision force analysis module estimates the probability of the target products being broken due to the collision between each other, and transmits the broken ratio information to the adjustment control module.

[0046] Step S7: The adjustment control module respectively receives the broken ratio information sent by the compressive force analysis module and the collision force analysis module, and adjusts the running rate of the production line through the production line adjustment module. At the same time, the product transmission volume control module outputs information to the system to reduce the transportation volume of products through the pipeline.

[0047] In step S2 of this embodiment, the pause time analysis sub-module obtains that after the conveyor belt of the pipeline conveys the target products for A seconds, the system controls the conveyor belt to stop advancing for B seconds, where A > B. The target products in the conveyor belt will not be backlogged when the conveyor belt is working. The conveyor belt transportation pipeline of the production equipment is inclined, and there is a baffle at the end of the conveyor belt. The target products are in the normal transmission stage within A seconds, and stacking and squeezing occur within B seconds after the baffle is erected. At the same time, through the analysis of the camera module, it is obtained that the number of target products transmitted per second from the conveyor belt entrance is K, and the number of target products transmitted per second following the conveyor belt is Z. 1 。

[0048] In step S3 of this embodiment, the additional collision force generated by the conveyor belt where m is the mass of a single target product, and g is the acceleration due to gravity. The range of the slope X is 0° ≤ X ≤ 30°. mgsinX is the gravitational component of a single target product on the inclined conveyor belt. is the acceleration ratio of the additional collision force. The faster the conveyor belt speed of the equipment, the greater the additional collision force; the slower the conveyor belt speed of the equipment, the smaller the additional collision force.

[0049] In step S5 of this embodiment, if the conveyor belt speed V of the equipment is lower than the conveyor belt safety speed E, the pressure of the target product on the rear conveyor belt on the target product at the baffle can be ignored. Therefore, only the pressure on the target product under stacking is considered; the stacking analysis sub-module calculates the pressure on the lowermost target product under stacking. When stacking of target products occurs on the conveyor belt, the number of pieces of target products stacked per unit area at the end of the conveyor belt is where μ is the target product stacking index and δ is the unit conversion parameter. is the amount of target products flying out per second per unit area of the conveyor belt. is the total amount of target products flying out within B seconds of stopping at the end of the conveyor belt per unit area.

[0050] From a macroscopic perspective, the flying target products approximately fall evenly on the target products conveyed out following the conveyor belt and move forward in a decreasing manner step by step under the vibration of the conveyor belt. The power function can represent the trend of the number of target products decreasing with the running steps of the conveyor belt. Therefore, is used to represent the number of pieces of target products stacked flying out after the conveyor belt stops at the end for B seconds per unit area. Round the calculation result of Z. Then, the probability that the nth layer of target products from top to bottom among the stacked target products is crushed due to extrusion where n is a positive integer and n ≤ Z, and λ 1 is the superposition parameter, and its value is determined according to the flexibility of the target product. 0 < λ 1 < 1. The probability η(n) of the nth layer of target products being broken is η(n) = L(n). If the result is less than or equal to (1 - the integrity pass rate Ω of the target product), it is determined that the production line speed is qualified; if the result is greater than (1 - the integrity pass rate Ω of the target product), it is determined that the production line speed is unqualified, and the information is transmitted to the adjustment control module; when n = 1, the topmost target product on the conveyor belt is not squeezed, and the probability of being broken is 0; when n = 2, the second layer of target products on the conveyor belt is squeezed with the least force. At this time When n = Z, the lowermost target product on the conveyor belt is squeezed with the greatest force, and the probability of being broken is also the greatest. At this time, L(Z) = λ 1 ;

[0051] If the speed V of the equipment conveyor belt is higher than the safe speed E of the conveyor belt, the pressure of the target product on the rear conveyor belt on the target product at the baffle should also be considered additionally. The extrusion analysis sub-module calculates the pressure of the target product on the rear conveyor belt on the target product at the baffle. When the baffle is erected, the target product on the rear conveyor belt squeezes the target product at the baffle. Through data analysis and statistics, the number of pieces of the target product per unit area of the baffle is Q, and Q is a positive integer. Then, among the squeezed target products, the probability that the i-th target product from the conveyor belt inlet to the conveyor belt end is broken due to extrusion where i is a positive integer and i ≤ Q, λ 2 is the extrusion parameter, and the value is determined according to the flexibility of the target product. 0 < λ 2 < 0.2. The value of P(i) is also affected by the speed of the conveyor belt. The higher the speed V of the conveyor belt, the greater the probability of breakage. Use to represent the influence index of the conveyor belt speed on P(i); when i = 1, the target product at the conveyor belt inlet is not squeezed, and the probability of breakage is 0; when i = 2, the target product on the second layer at the conveyor belt inlet is squeezed with the least force, and at this time When i = Q, the target product on the bottom layer of the conveyor belt is squeezed with the greatest force, and the probability of breakage is also the greatest. At this time The probability that the target product on the n-th layer and the i-th piece is broken is not simply the linear superposition of the breakage probabilities. Specifically If the result is less than or equal to (1 - the integrity qualification rate Ω of the target product), it is determined that the production line speed is qualified; if the result is greater than (1 - the integrity qualification rate Ω of the target product), it is determined that the production line speed is unqualified, and the information is transmitted to the adjustment control module.

[0052] It takes a certain amount of time to package the target product under the conveyor belt device, so it is necessary to have a certain pause interval when the conveyor belt conveys the target product; but on the other hand, the target product is prone to stacking and extrusion when the production equipment conveyor belt stops transmitting. The longer the stacking and extrusion time, the greater the possibility of breakage of the target product, and the possibility of breakage of the target product when it is running on the conveyor belt is small. The target product in the conveyor belt should enter the packaging device as soon as possible under the condition of ensuring the normal progress of the packaging procedure, so as to effectively reduce the debris of the target product.

[0053] In step S6 of this embodiment, the collision force analysis module calculates the probability that the target product is broken due to collision. Since the transmission speed of the target product following the conveyor belt is different from the actual speed of the flying target product, the flying target product exerts a collision force f on the target product following the conveyor belt 1 , then the single collision force fu received by a target product is fu = fe + f1, f uThe collision force received by the u-th target product from another target product, and the total collision force received by all target products If the total collision force F > M, it is determined that the collision force received by the target product is too large; if the total collision force F ≤ M, it is determined that the collision force received by the target product is normal.

[0054] It should be noted that in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device.

[0055] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A real-time monitoring and management system for a puffed food production line based on big data, characterized in that: It includes a data acquisition module, a production line analysis module, a debris prediction module and an adjustment control module. The data acquisition module is used to systematically collect relevant information of production equipment; the production line analysis module is used to analyze the production line of the transmission product; the debris prediction module is used to evaluate the probability of product breakage; and the adjustment control module is used to adjust the production line; The production line analysis module includes a conveyor belt analysis module, which analyzes the collision force of the target product on the conveyor belt of the production equipment transmission pipeline; The debris prediction module includes: a compression force analysis module and a collision force analysis module. The compression force analysis module is used to estimate the probability of the target product being crushed due to the compression force; the collision force analysis module is used to analyze whether collision between target products may cause the target product to be crushed; The compression force analysis module includes: a stacking analysis submodule and an extrusion analysis submodule. The stacking analysis submodule estimates the probability of a target product being broken due to stacking of multiple target products; the extrusion analysis submodule estimates the probability of a target product being broken due to mutual extrusion between target products.

2. According to claim 1, a real-time monitoring and management system for a puffed food production line based on big data, characterized in that: The data acquisition module includes a product data collection module and an equipment data collection module. The product data collection module is used to obtain the vulnerability of the target product; the equipment data collection module is used to obtain relevant parameters of the production equipment. The equipment data collection module includes a transmission data submodule and a pipeline data submodule. The transmission data submodule is used to obtain relevant information of the conveyor belt of the production line; the pipeline data submodule is used to obtain parameters of the pipeline of the production equipment.

3. The real-time monitoring and management system for a puffed food production line based on big data according to claim 2 is characterized by: The production line analysis module also includes a pause time analysis module and a camera module. The pause time analysis module is used to analyze the flow of the target product in the transmission process; the camera module is used to photograph the transmission pipeline of the production equipment.

4. The real-time monitoring and management system for a puffed food production line based on big data according to claim 3 is characterized by: The regulation control module includes a production line regulation module and a product transmission volume control module. The production line diagram adjustment module is used to adjust the transmission speed of the production line in real time; the product transmission volume control module is used to control the number of target products transmitted by the output pipeline.

5. The real-time monitoring and management system for a puffed food production line based on big data according to claim 4 is characterized by: The operation method of the production line real-time monitoring and management system mainly includes the following steps: Step S1: The data acquisition module obtains the relevant information of the food production line, the product data collection module obtains the product information produced on the day, and the limit value of the target products not being broken when they collide with each other is M; the equipment data collection module obtains the conveyor belt speed of the production equipment as V and the safe speed of the conveyor belt as E through the transmission data submodule, and obtains the parameters of the pipeline of the production equipment through the pipeline data submodule; Step S2: The production line analysis module uses the production line related information stored in the data acquisition module, and the camera module captures the scene of the target product transportation in the transmission process, and obtains the angle between the production equipment transmission process pipeline and the plane as X°; the pause time analysis module analyzes the number of target products input from the conveyor belt entrance within the interval time through the transportation picture; Step S3: The conveyor belt analysis module obtains the conveyor belt information of the transmission process pipeline of the production equipment, and analyzes the collision force of the target product in the transmission pipeline affected by the conveyor belt speed; Step S4: The debris prediction module extracts parameter information of the production equipment in the production line analysis module and analyzes the possibility of the target product being broken during the conveyor belt transportation time; Step S5: the compression force analysis module estimates the compression force of the target product, leading to an estimated probability of breakage of the target product, and transmits the breakage ratio information to the adjustment control module; Step S6: The collision force analysis module estimates the probability of target products being broken due to collision between each other, and transmits the breakage ratio information to the adjustment control module; Step S7: the adjustment control module receives the problem information and adjusts the operation rate of the production line through the production line adjustment module; at the same time, the product transmission volume control module outputs information to the system to reduce the transportation volume of the product through the pipeline.

6. The real-time monitoring and management system for a puffed food production line based on big data according to claim 5 is characterized by: In step S2, the pause time analysis submodule obtains that after the conveyor belt of the pipeline transmits the target product for A seconds, the system controls the conveyor belt to stop advancing for B seconds, wherein A>B, the target product is in the normal transmission stage within A seconds, and stacking and squeezing occur within B seconds after the baffle is erected; at the same time, the camera module analyzes and obtains that the target product quantity transmitted from the conveyor belt entrance per second is K, and the target product quantity following the conveyor belt per second is Z1.

7. The real-time monitoring and management system for a puffed food production line based on big data according to claim 6 is characterized by: In step S3, the additional collision force generated by the conveyor belt Where m is the mass of a single target product and g is the acceleration of gravity.

8. The real-time monitoring and management system for a puffed food production line based on big data according to claim 7 is characterized by: In step S5, if the conveyor belt speed V of the equipment is lower than the conveyor belt safety speed E, the pressure of the target product on the rear conveyor belt on the target product at the baffle can be ignored, so only the pressure on the target product under the accumulation is considered; The stacking analysis submodule calculates the pressure on the bottom layer of the target product when it is stacked. When the target products are stacked on the conveyor belt, the number of target products stacked per unit area at the end of the conveyor belt is Where μ is the target product stacking index, δ is the unit conversion parameter, and the calculated result of Z is rounded to an integer. Then, the probability of the nth layer of target products being squeezed and broken from top to bottom in the stacked target products is Where n is a positive integer and n≤Z, λ1 is a superposition parameter, the value of which is determined by the flexibility of the target product, 0<λ1<1, the probability of the target product in the nth layer being broken η(n)=L(n), if the result is less than or equal to (1-target product integrity qualified rate Ω), the production line speed is determined to be qualified; If the result is greater than (1-target product integrity qualified rate Ω), the production line speed is determined to be unqualified and the information is transmitted to the regulation control module; If the conveyor belt speed V of the equipment is higher than the conveyor belt safety speed E, the pressure of the target product of the rear conveyor belt on the target product at the baffle should also be considered. The extrusion analysis submodule calculates the pressure of the target product of the rear conveyor belt on the target product at the baffle. When the baffle is erected, the target product of the rear conveyor belt squeezes the target product at the baffle. Through data analysis, the number of target products per unit area of ​​the baffle is Q, and Q is a positive integer. Then, among the squeezed target products, the probability of the i-th target product being squeezed and broken from the conveyor belt entrance to the conveyor belt end is Where i is a positive integer and i≤Q, λ2 is an extrusion parameter whose value is determined by the flexibility of the target product, 0<λ2<0.2, and the probability of the target product in the nth layer and the i-th piece breaking is If the result is less than or equal to (1-target product integrity qualified rate Ω), the production line speed is determined to be qualified; If the result is greater than (1-target product integrity qualification rate Ω), the production line speed is determined to be unqualified and the information is transmitted to the regulation control module.

9. The real-time monitoring and management system for a puffed food production line based on big data according to claim 8, characterized in that: In step S6, the collision force analysis module calculates the probability of the target product being broken by the collision. Since the transmission speed of the target product following the conveyor belt is different from the actual speed of the target product flying out, the flying target product will exert a collision force of f1 on the target product following the conveyor belt. Then, the single collision force fu received by a target product is fu=fe+f1, and the total collision force received by all target products is If the total collision force F>M, it is determined that the collision force received by the target product is too large; if the total collision force F≤M, it is determined that the collision force received by the target product is normal.

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