Automatic feeding control system for processing of puffed food raw materials

Abstract

The application belongs to the technical field of food processing control, and discloses an automatic feeding control system for processing of raw materials of puffed food, which comprises a monitoring time period division module, a material distribution abnormality analysis module, a single-line conveying analysis module, a multi-line conveying analysis module, a conveying abnormality analysis module and a running parameter regulation module. When the material distribution process control is performed, the application analyzes the material distribution abnormality of each production line in each monitoring time period, and then determines whether the material distribution parameter regulation is needed, so that the raw material conveying device can be corrected according to different situations. When the conveying process control is performed, the application obtains the conveying parameter abnormality of each production line based on the interval deviation and abnormal splashing of each production line, and determines whether the conveying parameter regulation is needed in combination with the conveying parameter deviation between the production lines, so that the change of the production line state can be found and responded in time, and then the conveying parameter can be accurately and specifically adjusted.

Description

Technical Field

[0001] This invention belongs to the field of food processing control technology and relates to an automatic feeding control system for processing puffed food raw materials. Background Technology

[0002] Puffed foods are a type of food that uses a series of processing techniques to make originally dense ingredients fluffy and light. The production of puffed foods typically includes processes such as raw material preparation, conveying, processing, and baking. Among these, the conveying process for raw materials is crucial for ensuring efficient and stable production. A lack of precise control over the feeding process of puffed food raw materials can lead to inconsistencies or anomalies in the raw material conveying parameters across different production lines at different monitoring times, resulting in reduced production quality or efficiency. Therefore, automated feeding control for puffed food raw materials is of great importance.

[0003] The control of feeding raw materials in puffed food processing mainly includes the analysis and control of material distribution and conveying.

[0004] Traditional puffed food ingredient processing and feeding analysis typically focuses on analyzing the weight deviation of each packaged ingredient and then adjusting its weight accordingly. However, it neglects the correlation between the weight deviation of the packaged ingredients and the material conveying device. This results in the inability to make targeted adjustments to the packaging parameters of the material conveying device based on the existing weight deviations of the packaged ingredients. When the system accumulates errors, continuous adjustments to the weight of the packaged ingredients are required, reducing production efficiency, preventing the system from adaptively adjusting, and increasing unnecessary resource waste.

[0005] Traditional feeding processes for puffed food ingredients typically involve controlling the conveying parameters for a single production line. This approach neglects the compatibility analysis of conveying parameters across different production lines during various monitoring periods. This method of controlling conveying parameters may not guarantee consistency between production lines, potentially leading to inaccurate compounding of raw materials and resulting in abnormal product formulation, thus affecting product quality. Summary of the Invention

[0006] In view of this, in order to solve the problems mentioned in the background art, an automatic feeding control system for processing puffed food raw materials is proposed.

[0007] The objective of this invention can be achieved through the following technical solution: an automatic feeding control system for processing puffed food raw materials, comprising: a monitoring period division module, used to divide the production period of raw material processing into several monitoring periods based on equal intervals.

[0008] The material distribution anomaly analysis module is used to transport various raw materials from each raw material warehouse to the corresponding production line conveyor belt during each monitoring period using a raw material conveying device. Different production lines correspond to different raw materials. Based on pre-set material distribution parameters, the module performs intermittent material discharge operations to obtain the corresponding packaged raw materials. The module uses a weight detection device to detect the weight of each packaged raw material on each production line during each monitoring period and analyzes the material distribution anomalies on each production line during each monitoring period, thereby determining whether material distribution parameter adjustment is necessary.

[0009] The single-line conveying analysis module is used to convey raw materials for packaging based on pre-set conveying parameters. It uses high-definition cameras to collect real-time images of the state of the raw materials on the conveyor belt of each production line during each monitoring period, and then identifies conveying anomalies. The identification of conveying anomalies includes the identification of spacing deviation and abnormal splashing, and then analyzes the abnormal conveying parameters of each production line during each monitoring period.

[0010] The multi-line conveying analysis module is used to acquire the conveying parameters of each production line in real time during each monitoring period, and then analyze the deviation of the conveying parameters of each production line during each monitoring period.

[0011] The conveying anomaly analysis module is used to determine whether conveying parameter adjustment is necessary based on the abnormality and deviation of conveying parameters of each production line during each monitoring period.

[0012] The operation parameter control module is used to obtain the specific control direction when it is determined that operation parameter control is required. If the control direction is abnormal material distribution control, the module will perform material distribution parameter demand analysis; if the control direction is abnormal conveying parameter control, the module will perform conveying parameter demand analysis.

[0013] In a preferred embodiment of the present invention, the analysis of material distribution anomalies in each production line during each monitoring period is as follows: the weight of the unit packaging material corresponding to each type of raw material is obtained from the product specification information of puffed food, and recorded as the standard packaging material weight.

[0014] The weight of each raw material in each production line during each monitoring period is extracted using a weight detection device. The difference between the weight of each raw material and the corresponding standard raw material weight is calculated to obtain the deviation of the raw material in each production line during each monitoring period. The absolute value of the deviation of the raw material in each production line during each monitoring period is then calculated as a ratio to the corresponding standard raw material weight to obtain the weight deviation degree of the raw material in each production line during each monitoring period.

[0015] The average weight deviation of each batch of raw materials in each production line during each monitoring period is used to calculate the corresponding material distribution anomaly index for each production line during each monitoring period.

[0016] In a preferred embodiment of the present invention, the determination of whether material distribution parameter adjustment is required is as follows: the material distribution anomaly index of each production line in each monitoring period is compared with the preset material distribution anomaly index threshold to obtain the determination result of whether material distribution parameter adjustment is required.

[0017] In a preferred embodiment of the present invention, the identification and analysis of the spacing deviation is as follows: extract the state images of the raw materials being packaged on each conveyor belt during each monitoring period, which are collected in real time using a high-definition camera; then use image processing software to obtain the outline of each raw material being packaged on each conveyor belt during each monitoring period; and finally obtain the minimum distance between the outlines of each adjacent raw material being packaged as the corresponding monitoring spacing.

[0018] The average monitoring distance is obtained by averaging the monitoring distances of each conveyor belt during each monitoring period. Then, the monitoring distance deviation is obtained by calculating the difference between each monitoring distance and the average monitoring distance. Finally, the deviation degree of each monitoring distance is obtained by calculating the ratio of the absolute value of the monitoring distance deviation to the average monitoring distance.

[0019] The average value of the deviation of each monitoring interval is used to calculate the corresponding interval deviation index for each conveyor belt at each monitoring time period.

[0020] In a preferred embodiment of the present invention, the specific analysis of the abnormal splashing situation identification is as follows: extract the status images of the raw materials being packaged on each conveyor belt during each monitoring period, which are collected in real time using a high-definition camera; locate the raw material packaging area and the splashing raw material area within a pre-set collection distance around the raw materials in the status images; and then use image processing software to obtain the outline of each raw material being packaged and the outline of each splashing raw material, and obtain the outline area of ​​each raw material being packaged and the outline area of ​​each splashing raw material.

[0021] The splashed material contour areas corresponding to each sub-packaged material are summed to obtain the splashed material area corresponding to each sub-packaged material. The reference area is obtained by summing the area of ​​each sub-packaged material and the corresponding splashed material area. Then, the ratio of each splashed material area to the reference area is calculated to obtain the abnormal splashed area ratio of each sub-packaged material.

[0022] The abnormal splashing area ratio of each batch of raw materials in each monitoring period of each conveyor belt is averaged to obtain the abnormal splashing index for each monitoring period of each conveyor belt.

[0023] In a preferred embodiment of the present invention, the analysis of abnormal conveying parameters of each production line in each monitoring period is specifically as follows: the spacing deviation index and abnormal splash index of each production line in each monitoring period are accumulated according to weight to obtain the conveying abnormality index of each production line in each monitoring period.

[0024] In a preferred embodiment of the present invention, the analysis of the conveying parameter deviation of each production line in each monitoring period is specifically as follows: the conveying parameters of each production line in each monitoring period are extracted in real time, and then the conveying parameters are compared. Any conveyor belt is selected as a reference conveyor belt, and the conveying parameters of the reference conveyor belt are recorded as reference conveying parameters. The difference between the conveying parameters of each conveyor belt and the reference conveying parameters is calculated to obtain the conveying parameter deviation value. Then, the ratio of each conveying parameter deviation value to the reference conveying parameters is calculated to obtain the corresponding conveying parameter deviation index.

[0025] By comparing the deviation indices of each conveying parameter, the largest conveying parameter deviation index is selected as the conveying parameter deviation index of the corresponding production line during the monitoring period.

[0026] In a preferred embodiment of the present invention, the determination of whether to adjust the conveying parameters is required is as follows: the conveying anomaly index and the conveying parameter deviation index of each production line in each monitoring period are compared with the preset conveying anomaly index threshold and the conveying parameter deviation index threshold to obtain the determination result of whether to adjust the conveying parameters is required.

[0027] In a preferred embodiment of the present invention, the material distribution parameter requirement analysis is specifically as follows: obtain the material distribution parameters of the corresponding raw material conveying device of each production line in each monitoring period, and then calculate the average value to obtain the target material distribution parameters.

[0028] The average weight of the raw materials packaged for each production line in each monitoring period is calculated by averaging the weight of the corresponding raw materials in each monitoring period. Then, the difference between the average weight of the raw materials packaged for each production line in each monitoring period and the corresponding standard weight of the raw materials is calculated to obtain the weight deviation of the raw materials packaged for each production line in each monitoring period. Finally, the ratio of this deviation to the corresponding standard weight of the raw materials is calculated to obtain the correction degree of the material distribution parameters for each production line in each monitoring period.

[0029] The material distribution parameter correction degree of each production line in each monitoring period is multiplied by the corresponding target material distribution parameter to obtain the material distribution parameter correction amount of each production line in each monitoring period. Then, the material distribution parameter correction amount of each production line in each monitoring period is summed with the corresponding target material distribution parameter to obtain the material distribution parameter adjustment target amount of each production line in each monitoring period.

[0030] In a preferred embodiment of the present invention, the specific analysis of the conveying parameter requirements is as follows: extract the conveying parameters of each production line in each monitoring period obtained in real time, and record them as the actual conveying parameters;

[0031] The conveying parameter adjustment amount is calculated by multiplying the conveying anomaly index of each production line in each monitoring period with the actual conveying parameters, and then summing it with the corresponding actual conveying parameters to obtain the target conveying parameters of each production line in each monitoring period.

[0032] The target conveying parameters of each production line in each monitoring period are compared to determine whether further adjustments are needed. If so, any target conveying parameter is selected as the reference target conveying parameter, and the corresponding production line is recorded as the reference production line. The difference between the target conveying parameters of each conveyor belt and the reference target conveying parameter is calculated to obtain the reference conveying parameter demand deviation. The ratio of this deviation to the corresponding reference target conveying parameter is then calculated to obtain the conveying parameter demand correction degree of the corresponding production line. Finally, the average of the conveying parameter demand correction degrees of each production line in each monitoring period is calculated to obtain the conveying parameter demand correction degree of the reference production line.

[0033] By comparing the required correction degrees of conveying parameters obtained by using each production line as a reference production line, the target conveying parameters of the reference production line corresponding to the minimum required correction degree of conveying parameters are selected as the target adjustment amount of conveying parameters for each conveyor belt.

[0034] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) When controlling the material distribution process, the present invention analyzes the abnormal situation of material distribution in each production line during each monitoring period, and then determines whether the material distribution parameters need to be adjusted. This analysis method analyzes the weight deviation of the raw materials in each monitoring period in real time, and then enables targeted and adaptive adjustment of the material distribution parameters of the raw material conveying device. At the same time, continuous material distribution anomaly analysis can predict potential failures or performance degradation of the raw material conveying device, and can make targeted corrections and optimizations for the raw material conveying device under different conditions, thereby improving the material distribution efficiency and avoiding unnecessary waste of resources.

[0035] (2) When controlling the conveying process, this invention obtains the abnormal conveying parameters of each production line in each monitoring period based on the spacing deviation and abnormal splashing of each production line in each monitoring period. At the same time, it judges whether the conveying parameters need to be adjusted by combining the conveying parameter deviation of each production line in each monitoring period. This analysis method can detect and respond to changes in the production line status in real time, and then make precise and targeted adjustments to the conveying parameters to ensure the stability and efficiency of the production process. It also improves the consistency of the finished product and avoids energy waste caused by unnecessary speed adjustments.

[0036] (3) The present invention also provides a judgment result on whether each production line meets the production requirements in each monitoring period based on the analysis of abnormal material distribution parameters of each production line in each monitoring period. This analysis method can monitor the abnormal operation of each production line in each monitoring period in real time and provides a continuous optimization scheme. When the production line has continuous abnormal production parameters, the conveying device is repaired and troubleshooted in a timely manner, thereby improving the working efficiency and production stability of the production line. Attached Figure Description

[0037] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a schematic diagram showing the connections of the various modules in the system of the present invention.

[0039] Figure 2 This is a schematic diagram of the feeding device of the present invention.

[0040] Attached diagram labels: 1 – raw material silo, 2 – raw material conveying device, 3 – conveyor belt. Detailed Implementation

[0041] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] Please see Figure 1 As shown, the present invention provides an automatic feeding control system for processing puffed food raw materials. The system includes a monitoring period segmentation module, a material distribution anomaly analysis module, a single-line conveying analysis module, a multi-line conveying analysis module, a conveying anomaly analysis module, and an operating parameter control module. The monitoring period segmentation module is connected to the material distribution anomaly analysis module, the single-line conveying analysis module, and the multi-line conveying analysis module, respectively. The single-line conveying analysis module and the multi-line conveying analysis module are both connected to the conveying anomaly analysis module. The material distribution anomaly analysis module and the conveying anomaly analysis module are both connected to the operating parameter control module.

[0043] The monitoring period segmentation module is used to divide the raw material processing production period into several monitoring periods based on equal intervals.

[0044] For example, the interval is 15 minutes.

[0045] It should be noted that the reasons for dividing the production period into several monitoring periods for analysis are as follows: 1. Dividing the production process into multiple monitoring periods allows for real-time monitoring of raw material feeding, enabling timely detection and correction of any deviations. This helps maintain the stability of the production process and the consistency of product quality. 2. By subdividing the time periods, refined management of the production process can be achieved. Monitoring data from each period can be used to optimize the feeding speed or modify production parameters to adapt to changes in raw material characteristics and production needs.

[0046] The material distribution anomaly analysis module is used to transport various raw materials from each raw material warehouse to the corresponding production line's conveyor belt using the raw material conveying device during each monitoring period. Please refer to [link / reference needed]. Figure 2 The diagram shows a feeding device where different production lines correspond to different raw materials. Based on pre-set feeding parameters, each raw material is intermittently discharged to obtain the corresponding packaged raw material. A weight detection device is used to detect the weight of each packaged raw material in each production line during each monitoring period, and analyze the abnormal feeding situation of each production line in each monitoring period to determine whether the feeding parameters need to be adjusted.

[0047] For example, puffed foods can be potato chips, French fries, and rice cakes. Taking potato chips as an example, the corresponding raw materials are corn starch, fruit and vegetable powder, and seasoning powder.

[0048] For example, the raw material conveying device can be a screw conveyor, and the material distribution parameter can be the screw conveyor speed.

[0049] Preferably, the analysis of material distribution anomalies in each production line during each monitoring period is as follows: obtain the weight of the unit packaging material corresponding to each type of raw material from the product specification information of puffed food, and record it as the standard packaging material weight.

[0050] It should be noted that the weight of raw materials per unit package refers to the weight of the corresponding raw materials required for one bag of puffed food.

[0051] The weight of each raw material in each production line during each monitoring period is extracted using a weight detection device. The difference between the weight of each raw material and the corresponding standard raw material weight is calculated to obtain the deviation of the raw material in each production line during each monitoring period. The absolute value of the deviation of the raw material in each production line during each monitoring period is then calculated as a ratio to the corresponding standard raw material weight to obtain the weight deviation degree of the raw material in each production line during each monitoring period.

[0052] The average weight deviation of each batch of raw materials in each production line during each monitoring period is used to calculate the corresponding material distribution anomaly index for each production line during each monitoring period.

[0053] Preferably, the determination of whether material distribution parameter adjustment is needed is as follows: the material distribution anomaly index of each production line in each monitoring period is compared with the pre-set material distribution anomaly index threshold to obtain the determination result of whether material distribution parameter adjustment is needed.

[0054] For example, the material distribution anomaly index threshold is 0.05.

[0055] It should be added that if the material distribution anomaly index of a certain production line is greater than the material distribution anomaly index threshold during a certain monitoring period, it is determined that the material distribution parameters need to be adjusted. If the material distribution anomaly index of a certain production line is less than or equal to the material distribution anomaly index threshold during a certain monitoring period, it is determined that the material distribution parameters do not need to be adjusted.

[0056] It should be noted that, when controlling the material distribution process, this invention analyzes the abnormal material distribution situations of each production line during each monitoring period to determine whether material distribution parameter adjustments are necessary. This analysis method analyzes the weight deviation of the packaged raw materials in real time during each monitoring period, thereby enabling targeted and adaptive material distribution parameter adjustments. At the same time, continuous material distribution anomaly analysis can predict potential equipment failures or performance degradation, allowing for targeted corrections and optimizations of the raw material conveying device under different conditions, improving material distribution efficiency and avoiding unnecessary resource waste.

[0057] The single-line conveying analysis module is used to convey the packaging raw materials based on pre-set conveying parameters. It uses a high-definition camera to collect real-time images of the packaging raw materials on the corresponding conveyor belt of each production line during each monitoring period, and then identifies conveying anomalies. The identification of conveying anomalies includes the identification of spacing deviation and abnormal splashing, and then analyzes the abnormal conveying parameters of each production line during each monitoring period.

[0058] For example, the conveying parameter can be the conveying speed.

[0059] It's important to explain why spacing deviation and abnormal splashing were chosen as the criteria for judging abnormal conveying parameters: Taking conveying speed as an example, spacing deviation reflects the uniformity of material distribution during conveying. Large spacing deviations indicate uneven material distribution, which may affect the quality and consistency of the final product. Splashing typically means that material is thrown out during conveying, which not only wastes material but also increases cleaning costs, especially when handling expensive or sensitive raw materials. Both spacing deviation and abnormal splashing directly or indirectly affect production efficiency. The former may lead to production line stoppages or adjustments, while the latter may require additional time and resources for cleaning.

[0060] Preferably, the specific analysis of the spacing deviation identification is as follows: extract the state images of the raw materials being packaged on each conveyor belt during each monitoring period, which are collected in real time using a high-definition camera, and then use image processing software to obtain the outline of each raw material being packaged on each conveyor belt during each monitoring period, and then obtain the minimum distance between the outlines of each adjacent raw material being packaged as the corresponding monitoring spacing.

[0061] The average monitoring distance is obtained by averaging the monitoring distances of each conveyor belt during each monitoring period. Then, the monitoring distance deviation is obtained by calculating the difference between each monitoring distance and the average monitoring distance. Finally, the deviation degree of each monitoring distance is obtained by calculating the ratio of the absolute value of the monitoring distance deviation to the average monitoring distance.

[0062] The average value of the deviation of each monitoring interval is used to calculate the corresponding interval deviation index for each conveyor belt at each monitoring time period.

[0063] Preferably, the abnormal splashing situation identification is specifically analyzed as follows: extract the status images of the raw materials being packaged on each conveyor belt during each monitoring period, which are collected in real time using a high-definition camera; locate the raw material packaging area and the splashing raw material area within a pre-set collection distance around the raw materials in the status images; then use image processing software to obtain the outline of each raw material being packaged and the outline of each splashing raw material, and obtain the outline area of ​​each raw material being packaged and the outline area of ​​each splashing raw material.

[0064] For example, the sampling distance is 10cm.

[0065] It should be noted that the reason for setting the collection distance is that the raw materials are conveyed to the conveyor belt by the raw material conveying device. The raw materials may splash due to the excessive speed of the conveyor belt, but this behavior should be within a controllable range. Splashed raw materials beyond the collection distance should not be used as the basis for analyzing the raw material splashing situation.

[0066] The splashed material contour areas corresponding to each sub-packaged material are summed to obtain the splashed material area corresponding to each sub-packaged material. The reference area is obtained by summing the area of ​​each sub-packaged material and the corresponding splashed material area. Then, the ratio of each splashed material area to the reference area is calculated to obtain the abnormal splashed area ratio of each sub-packaged material.

[0067] The abnormal splashing area ratio of each batch of raw materials in each monitoring period of each conveyor belt is averaged to obtain the abnormal splashing index for each monitoring period of each conveyor belt.

[0068] Preferably, the analysis of abnormal conveying parameters of each production line in each monitoring period is as follows: the spacing deviation index and abnormal splash index of each production line in each monitoring period are accumulated according to weight to obtain the conveying abnormality index of each production line in each monitoring period.

[0069] For example, the weights of the spacing deviation index and the abnormal splash index are 0.6 and 0.4, respectively.

[0070] The multi-line conveying analysis module is used to acquire the conveying parameters of each production line in real time during each monitoring period, and then analyze the deviation of the conveying parameters of each production line during each monitoring period.

[0071] Preferably, the analysis of the conveying parameter deviation of each production line in each monitoring period is as follows: extract the conveying parameters of each production line in each monitoring period obtained in real time, compare the conveying parameters, select any conveyor belt as a reference conveyor belt, record the conveying parameters of the reference conveyor belt as reference conveying parameters, calculate the difference between the conveying parameters of each conveyor belt and the reference conveying parameters to obtain the conveying parameter deviation value, and then calculate the ratio between the conveying parameter deviation value and the reference conveying parameters to obtain the corresponding conveying parameter deviation index.

[0072] By comparing the deviation indices of each conveying parameter, the largest conveying parameter deviation index is selected as the conveying parameter deviation index of the corresponding production line during the monitoring period.

[0073] It should be noted that the reason for selecting the maximum conveying parameter deviation index as the conveying parameter deviation index of the corresponding production line during the monitoring period is as follows: In practice, if the maximum conveying parameter deviation index is within the allowable range, it is determined that there is no need to adjust the speed adaptation between multiple production lines; if the maximum conveying parameter deviation index exceeds the allowable range, then speed adaptation adjustment between multiple production lines should be performed.

[0074] It should be noted that in practice, it is necessary to ensure the synchronization of the conveying parameters of each production line during each monitoring period. This is because in actual production, it is necessary to ensure that all the sub-packaged raw materials arrive at the mixing area at the same time to ensure the quality of the mixed product. When there is a deviation in the conveying parameters, it may cause different sub-packaged raw materials to arrive at different times, which may lead to deviations in the weight of the mixed product or abnormalities in the proportion of each raw material.

[0075] The conveying anomaly analysis module is used to determine whether conveying parameter adjustment is necessary based on the abnormality and deviation of conveying parameters of each production line during each monitoring period.

[0076] Preferably, the determination of whether to adjust the conveying parameters is required is as follows: the conveying anomaly index and conveying parameter deviation index of each production line in each monitoring period are compared with the preset conveying anomaly index threshold and conveying parameter deviation index threshold to obtain the determination result of whether to adjust the conveying parameters is required.

[0077] For example, the transport anomaly index threshold is 0.25, and the transport parameter deviation index threshold is 0.2.

[0078] It should be added that if the conveying anomaly index of a certain production line during a certain monitoring period is greater than the conveying anomaly index threshold, it is determined that the conveying parameters need to be adjusted; if the conveying anomaly index of a certain production line during a certain monitoring period is less than or equal to the conveying anomaly index threshold, it is determined that the conveying parameters do not need to be adjusted.

[0079] It should be noted that, when controlling the conveying process, this invention obtains the abnormal conveying parameters of each production line in each monitoring period based on the spacing deviation and abnormal splashing of each production line in each monitoring period. At the same time, it determines whether the conveying parameters need to be adjusted by combining the conveying parameter deviations of each production line in each monitoring period. This analysis method can detect and respond to changes in the production line status in real time, and then make precise and targeted adjustments to the conveying parameters to ensure the stability and efficiency of the production process. It also improves the consistency of the finished product and avoids energy waste caused by unnecessary speed adjustments.

[0080] The operating parameter control module is used to obtain the specific control direction when it is determined that operating parameter control is required. If the control direction is abnormal material distribution control, material distribution parameter demand analysis is performed. If the control direction is abnormal conveying parameter control, conveying parameter demand analysis is performed.

[0081] Preferably, the material distribution parameter requirement analysis is as follows: obtain the material distribution parameters of the corresponding raw material conveying device of each production line in each monitoring period, and then calculate the average value to obtain the target material distribution parameters.

[0082] The average weight of the raw materials packaged for each production line in each monitoring period is calculated by averaging the weight of the corresponding raw materials in each monitoring period. Then, the difference between the average weight of the raw materials packaged for each production line in each monitoring period and the corresponding standard weight of the raw materials is calculated to obtain the weight deviation of the raw materials packaged for each production line in each monitoring period. Finally, the ratio of this deviation to the corresponding standard weight of the raw materials is calculated to obtain the correction degree of the material distribution parameters for each production line in each monitoring period.

[0083] The material distribution parameter correction degree of each production line in each monitoring period is multiplied by the corresponding target material distribution parameter to obtain the material distribution parameter correction amount of each production line in each monitoring period. Then, the material distribution parameter correction amount of each production line in each monitoring period is summed with the corresponding target material distribution parameter to obtain the material distribution parameter adjustment target amount of each production line in each monitoring period.

[0084] It should be explained that when the correction sign of the material distribution parameter of a production line is positive, the weight of the raw material being packaged on that production line is greater than the weight of the standard raw material being packaged, and the material distribution parameter of that production line needs to be reduced. When the correction sign of the material distribution parameter of a production line is negative, the weight of the raw material being packaged on that production line is less than the weight of the standard raw material being packaged, and the material distribution parameter of that production line needs to be increased.

[0085] Preferably, the conveying parameter demand analysis is as follows: extract the conveying parameters of each production line in each monitoring period obtained in real time, and record them as the actual conveying parameters.

[0086] The conveying parameter adjustment amount is calculated by multiplying the conveying anomaly index of each production line in each monitoring period with the actual conveying parameters, and then summing it with the corresponding actual conveying parameters to obtain the target conveying parameters of each production line in each monitoring period.

[0087] The target conveying parameters of each production line in each monitoring period are compared to determine whether further adjustments are needed. If so, any target conveying parameter is selected as the reference target conveying parameter, and the corresponding production line is recorded as the reference production line. Then, the difference between the target conveying parameters of each conveyor belt and the reference target conveying parameter is calculated to obtain the reference conveying parameter demand deviation. Then, the ratio of this deviation to the corresponding reference target conveying parameter is calculated to obtain the conveying parameter demand correction degree of the corresponding production line. Finally, the average of the conveying parameter demand correction degrees of each production line in each monitoring period is calculated to obtain the conveying parameter demand correction degree of the reference production line.

[0088] By comparing the required correction degrees of conveying parameters obtained by using each production line as a reference production line, the target conveying parameters of the reference production line corresponding to the minimum required correction degree of conveying parameters are selected as the target adjustment amount of conveying parameters for each conveyor belt.

[0089] It should be noted that the target conveying parameters of the reference production line corresponding to the minimum conveying parameter requirement correction degree are selected as the target adjustment amounts for each conveyor belt's conveying parameters because: choosing the minimum correction degree means the smallest adjustment range, which usually results in the lowest adjustment cost. Adjustment costs include additional energy consumption, raw material waste, equipment wear and tear, and potential production downtime caused by the adjustment. At the same time, a smaller correction degree means that changes in production parameters will not be too large, which helps maintain production stability and continuity, reducing production fluctuations and uncertainties caused by large parameter changes.

[0090] It should be added that the present invention also provides a function to determine whether each production line meets the production requirements in each monitoring period, specifically as follows: real-time acquisition of the material distribution parameters of the raw material conveying device in each monitoring period, then plotting the material distribution parameter change curve with time as the horizontal axis and material distribution parameter as the vertical axis, then evenly distributing several collection points on the change curve, and calculating the average value of the vertical axis of each collection point to obtain the monitoring material distribution parameters in that monitoring period.

[0091] Substitute the corrected material distribution parameter X and the monitored material distribution parameter X0 into the analysis formula. The abnormal index λ of the material distribution parameters of each production line in each monitoring period was obtained. 分料 , where e represents the natural constant.

[0092] The abnormal index of material distribution parameters of each production line in each monitoring period is compared with the pre-set abnormal index threshold of material distribution parameters to obtain the judgment result of whether each production line meets the production requirements in each monitoring period.

[0093] It should be added that if the abnormal index of the material distribution parameter of a certain production line is greater than the threshold of the abnormal index of the material distribution parameter, it is judged to be non-compliant with production requirements; if the abnormal index of the material distribution parameter of a certain production line is less than or equal to the threshold of the abnormal index of the material distribution parameter, it is judged to be compliant with production requirements.

[0094] It should be noted that the present invention also provides a judgment result on whether each production line meets the production requirements in each monitoring period based on the analysis of abnormal material distribution parameters of each production line in each monitoring period. This analysis method can monitor the abnormal operation of each production line in each monitoring period in real time and provides a continuous optimization scheme. When the production line has continuous abnormal production parameters, the conveying device can be repaired and troubleshooted in a timely manner, thereby improving the working efficiency and production stability of the production line.

[0095] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. An automatic feeding control system for processing puffed food raw materials, characterized in that, include: The monitoring period segmentation module is used to divide the raw material processing production period into several monitoring periods based on equal intervals. The material distribution anomaly analysis module is used to transport various raw materials from each raw material warehouse to the corresponding production line conveyor belt using the raw material conveying device during each monitoring period. Different production lines correspond to different raw materials. Based on the pre-set material distribution parameters, the module performs intermittent material discharge operations to obtain the corresponding packaged raw materials. The module uses a weight detection device to detect the weight of each packaged raw material during each monitoring period and analyzes the material distribution anomalies during each monitoring period to determine whether material distribution parameter adjustment is required. The single-line conveying analysis module is used to convey the packaging raw materials based on the pre-set conveying parameters. It uses a high-definition camera to collect real-time images of the packaging raw materials on the corresponding conveyor belt of each production line during each monitoring period, and then identifies conveying anomalies. The identification of conveying anomalies includes the identification of spacing deviation and abnormal splashing, and then analyzes the abnormal conveying parameters of each production line during each monitoring period. The multi-line conveying analysis module is used to acquire the conveying parameters of each production line in real time during each monitoring period, and then analyze the deviation of the conveying parameters of each production line during each monitoring period. The conveying anomaly analysis module is used to determine whether conveying parameter adjustment is needed based on the abnormality and deviation of conveying parameters of each production line in each monitoring period. The operation parameter control module is used to obtain the specific control direction when it is determined that operation parameter control is required. If the control direction is abnormal material distribution control, the module will perform material distribution parameter demand analysis; if the control direction is abnormal conveying parameter control, the module will perform conveying parameter demand analysis.

2. The automatic feeding control system for processing puffed food raw materials as described in claim 1, characterized in that: The specific analysis of material distribution anomalies in each production line during each monitoring period is as follows: Obtain the weight of each type of raw material in the corresponding unit of packaging from the product specification information of puffed food, and record it as the standard packaging raw material weight. The weight of each raw material in each production line during each monitoring period is extracted using a weight detection device. The weight of each raw material in each monitoring period is then calculated by comparing it with the weight of the corresponding standard raw material. The deviation of the raw material in each monitoring period is then calculated by comparing the absolute value of the deviation of the raw material in each monitoring period with the weight of the corresponding standard raw material. The average weight deviation of each batch of raw materials in each production line during each monitoring period is used to calculate the corresponding material distribution anomaly index for each production line during each monitoring period.

3. The automatic feeding control system for processing puffed food raw materials as described in claim 2, characterized in that: The specific steps for determining whether material distribution parameter adjustment is needed are as follows: The abnormal material distribution index of each production line in each monitoring period is compared with the pre-set abnormal material distribution index threshold to determine whether material distribution parameter adjustment is needed.

4. The automatic feeding control system for processing puffed food raw materials as described in claim 2, characterized in that: The specific analysis of the spacing deviation is as follows: Extract the status images of the raw materials being packaged on each conveyor belt during each monitoring period, which are collected in real time by high-definition cameras. Then, use image processing software to obtain the outline of each raw material being packaged on each conveyor belt during each monitoring period. Finally, obtain the minimum distance between the outlines of each adjacent raw material being packaged as the corresponding monitoring interval. The average monitoring distance is calculated by averaging the monitoring distances of each conveyor belt during each monitoring period. Then, the monitoring distance deviation is calculated by comparing the difference between each monitoring distance and the average monitoring distance. Finally, the deviation degree of each monitoring distance is calculated by the ratio of the absolute value of the monitoring distance deviation to the average monitoring distance. The average value of the deviation of each monitoring interval is used to calculate the corresponding interval deviation index for each conveyor belt at each monitoring time period.

5. The automatic feeding control system for processing puffed food raw materials as described in claim 4, characterized in that: The specific analysis of the abnormal splashing situation is as follows: Extract the status images of the raw materials being packaged on each conveyor belt during each monitoring period, which are collected in real time by high-definition cameras. Locate the raw material packaging area and the splashed raw material area within a pre-set collection distance around the raw materials in the status images. Then, use image processing software to obtain the outline of each raw material being packaged and the outline of each splashed raw material, and obtain the outline area of ​​each raw material being packaged and the outline area of ​​each splashed raw material. The splashed material contour area corresponding to each sub-packaged material is accumulated to obtain the splashed material area corresponding to each sub-packaged material. The reference area is obtained by summing the area of ​​each sub-packaged material and the corresponding splashed material area. Then, the ratio of each splashed material area to the reference area is calculated to obtain the abnormal splashed area ratio of each sub-packaged material. The abnormal splashing area ratio of each batch of raw materials in each monitoring period of each conveyor belt is averaged to obtain the abnormal splashing index for each monitoring period of each conveyor belt.

6. The automatic feeding control system for processing puffed food raw materials as described in claim 5, characterized in that: The specific analysis of abnormal conveying parameters of each production line during each monitoring period is as follows: The conveying anomaly index of each production line in each monitoring period is calculated by weighting and summing the spacing deviation index and abnormal splash index of each monitoring period.

7. The automatic feeding control system for processing puffed food raw materials as described in claim 6, characterized in that: The specific analysis of the conveying parameter deviations of each production line during each monitoring period is as follows: Extract the real-time acquisition of the conveying parameters of each production line in each monitoring period, then compare the conveying parameters, select any conveyor belt as the reference conveyor belt, and then record the conveying parameters of the reference conveyor belt as the reference conveying parameters. Calculate the difference between the conveying parameters of each conveyor belt and the reference conveying parameters to obtain the conveying parameter deviation value, and then calculate the ratio of the conveying parameter deviation value to the reference conveying parameters to obtain the corresponding conveying parameter deviation index. By comparing the deviation indices of each conveying parameter, the largest conveying parameter deviation index is selected as the conveying parameter deviation index of the corresponding production line during the monitoring period.

8. The automatic feeding control system for processing puffed food raw materials as described in claim 7, characterized in that: The specific steps for determining whether to adjust the delivery parameters are required are as follows: The conveying anomaly index and conveying parameter deviation index of each production line in each monitoring period are compared with the preset conveying anomaly index threshold and conveying parameter deviation index threshold to determine whether conveying parameter adjustment is required.

9. The automatic feeding control system for processing puffed food raw materials as described in claim 6, characterized in that: The specific analysis of the material distribution parameter requirements is as follows: The material distribution parameters of the corresponding raw material conveying devices of each production line in each monitoring period are obtained, and then the average value is calculated to obtain the target material distribution parameters. The average weight of the raw materials packaged by each production line in each monitoring period is calculated by averaging the weight of the raw materials packaged by each production line in each monitoring period. Then, the difference between the average weight of the raw materials packaged by each production line in each monitoring period and the corresponding standard weight of the raw materials packaged by each production line is calculated to obtain the weight deviation of the raw materials packaged by each production line in each monitoring period. Finally, the ratio of the deviation to the corresponding standard weight of the raw materials packaged by each production line is calculated to obtain the correction degree of the material distribution parameters of each production line in each monitoring period. The material distribution parameter correction degree of each production line in each monitoring period is multiplied by the corresponding target material distribution parameter to obtain the material distribution parameter correction amount of each production line in each monitoring period. Then, the material distribution parameter correction amount of each production line in each monitoring period is summed with the corresponding target material distribution parameter to obtain the material distribution parameter adjustment target amount of each production line in each monitoring period.

10. The automatic feeding control system for processing puffed food raw materials as described in claim 9, characterized in that: The specific analysis of the transport parameter requirements is as follows: Extract the real-time transport parameters of each production line for each monitoring period and record them as the actual transport parameters; The conveying parameter adjustment amount is calculated by multiplying the conveying anomaly index of each production line in each monitoring period with the actual conveying parameters, and then summing it with the corresponding actual conveying parameters to obtain the target conveying parameters of each production line in each monitoring period. The target conveying parameters of each production line in each monitoring period are compared to determine whether further adjustments are needed. If so, any target conveying parameter is selected as the reference target conveying parameter, and the corresponding production line is recorded as the reference production line. The difference between the target conveying parameters of each conveyor belt and the reference target conveying parameter is calculated to obtain the reference conveying parameter demand deviation. The ratio of this deviation to the corresponding reference target conveying parameter is then calculated to obtain the conveying parameter demand correction degree of the corresponding production line. Finally, the average of the conveying parameter demand correction degrees of each production line in each monitoring period is calculated to obtain the conveying parameter demand correction degree of the reference production line. By comparing the required correction degrees of conveying parameters obtained by using each production line as a reference production line, the target conveying parameters of the reference production line corresponding to the minimum required correction degree of conveying parameters are selected as the target adjustment amount of conveying parameters for each conveyor belt.

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