An intelligent packaging control method and system for a bag packaging machine

Abstract

The present invention relates to the technical field of packaging, and particularly to an intelligent packaging control method and system for a bag-type packaging machine. The method includes the following steps: S1: Obtain the packaging product type of the bag-type packaging machine, and based on the packaging product type, extract the packaging parameters of the bag-type packaging machine; the packaging product type includes the product physical state and the switching node of the product physical state; S2: Based on the packaging parameters, extract the process trigger signal of the bag-type packaging machine; based on the process trigger signal of the bag-type packaging machine, extract the packaging parameter replacement node; the packaging parameter replacement node includes: the parameter adjustment node triggered by the change of the equipment state within the same packaging product type. The present invention suppresses drift by dynamically correcting parameters, accurately discriminates the adjustment node by using time series analysis, intelligently classifies and reuses parameters and predicts the process trend, realizes multi-form adaptive packaging, reduces manual intervention, improves efficiency and ensures quality.

Description

Technical Field

[0001] The present invention relates to the technical field of packaging, and particularly relates to an intelligent packaging control method and system for a bag-type packaging machine. Background Art

[0002] Existing bag-type packaging machines have significant limitations in packaging multi-category products: Firstly, when facing products with different physical forms such as liquids, powders, and solids, it is necessary to rely on manual experience to preset fixed parameters. Due to the poor adaptability of parameters such as sealing pressure and filling speed caused by morphological differences, the switching efficiency is low and packaging defects such as poor sealing and overfilling are likely to occur due to parameter mismatches; Secondly, during the long-term operation of the equipment, there is no real-time dynamic correction mechanism for parameter drift caused by factors such as mechanical wear and changes in environmental temperature and humidity, and it is necessary to frequently stop the machine for manual calibration, resulting in production line interruptions; Thirdly, the parameter reset logic is single when switching products, and the common parameters (such as bag-making length) that can be reused across categories and the specific product-specific parameters (such as liquid sealing temperature) are not distinguished, resulting in repeated configuration and redundant operations; Traditional methods usually use fixed thresholds (such as temperature deviation ±5°C) to judge parameter adjustment nodes, and cannot distinguish the gradual parameter shift (such as the sealing pressure decreasing by 0.1 MPa per month) caused by equipment wear within the same product type from the sudden parameter reset requirements (such as resetting the filling speed when switching from solids to liquids) during cross-product switching, and the weight of outdated historical data is too high, which is likely to cause misjudgment; In addition, the existing technology lacks effective exploration of the migration characteristics of packaging parameters, and it is difficult to achieve cross-category parameter reuse, further restricting the improvement of packaging efficiency. Summary of the Invention

[0003] In order to overcome the shortcomings of the contradiction between dynamic anomaly recognition and real-time regulation, the present invention provides an intelligent packaging control method and system for a bag-type packaging machine.

[0004] The technical implementation solution of the present invention is: an intelligent packaging control method for a bag-type packaging machine, including the following steps:

[0005] S1: Obtain the packaging product type of the bag-type packaging machine, and based on the packaging product type, extract the packaging parameters of the bag-type packaging machine; the packaging product type includes the product physical state and the switching node of the product physical state;

[0006] S2: Based on the packaging parameters, extract the process trigger signal of the bag-type packaging machine; based on the process trigger signal of the bag-type packaging machine, extract the packaging parameter replacement node; the packaging parameter replacement node includes: the parameter adjustment node triggered by the change of equipment state within the same packaging product type; the parameter reset node triggered by the switching between different packaging product types;

[0007] S3: Replace nodes based on the packaging parameters, classify the nodes replaced according to the same packaging parameters and those replaced according to different packaging parameters, and obtain the packaging offset parameters; the packaging offset parameters include the offset of the packaging parameters of the bag packaging machine itself during the packaging process for the same type of packaged product, and the offset of the packaging parameters generated by the bag packaging machine during the process of replacing the type of packaged product for different types of packaged products.

[0008] S4: Based on the packaging offset parameters, obtain the packaging similarity parameters; based on the packaging similarity parameters, control the bag packaging machine to perform intelligent packaging; the packaging similarity parameters include migration parameters and independent parameters; the migration parameters refer to the general process parameters that can be reused across product types; the independent parameters refer to the dedicated parameters that are only applicable to specific types of packaged products.

[0009] Preferably, obtain the type of packaged product of the bag packaging machine, and based on the type of packaged product, extract the packaging parameters of the bag packaging machine; the type of packaged product includes the physical state of the product and the switching nodes of the physical state of the product, including:

[0010] Based on the physical state of the product, obtain the initial parameter set for bag making, filling, and sealing of the bag packaging machine and the corresponding time period of the initial parameter set;

[0011] Based on the switching nodes of the physical state of the product, obtain the adjustment parameter set for bag making, filling, and sealing of the bag packaging machine and the corresponding time period of the adjustment parameter set;

[0012] Based on the initial parameter set and the corresponding time period of the initial parameter set, use the adjustment parameter verification formula to obtain the corrected adjustment parameter set;

[0013] Based on the initial parameter set and the corrected adjustment parameter set, obtain the packaging parameters of the bag packaging machine.

[0014] Preferably, the step of using the adjustment parameter verification formula to obtain the corrected adjustment parameter set based on the initial parameter set and the corresponding time period of the initial parameter set includes: obtaining the parameter deviation amount of each stage through the adjustment parameter verification formula, and obtaining the adjustment parameter correction amount through the adjustment parameter correction formula; the adjustment parameter verification formula is as follows,

[0015]

[0016] where, is the parameter deviation amount of the stage, is the weight coefficient of the physical state of the product in the stage, is the switching node of the physical state of the product, is the Phase parameter adjustment time, is the initial parameter setting time, is the time decay factor, is the minimum value, = 1, 2, 3 correspond to the bag-making, filling, and sealing stages respectively; the adjustment parameter correction formula is as follows,

[0017]

[0018] Among them, is the parameter value after correction in the stage, is the original parameter value in the stage, = 1, 2, 3 correspond to the bag-making, filling, and sealing stages respectively.

[0019] Preferably, extracting the process trigger signal of the bag packaging machine based on the packaging parameters includes:

[0020] Extracting the adjustment parameter set according to the packaging parameters to generate the first process trigger signal;

[0021] Extracting the adjusted adjustment parameter set according to the packaging parameters to generate the second process trigger signal;

[0022] Based on the first process trigger signal and the second process trigger signal, obtaining the process signal trigger trends of the same packaging product type and different packaging product types in the three stages of bag-making, filling, and sealing;

[0023] Based on the process signal trigger trend, obtaining the process trigger signal of the bag packaging machine in advance or postponed.

[0024] Preferably, extracting the packaging parameter replacement node based on the process trigger signal of the bag packaging machine includes:

[0025] By calculating the Pearson correlation coefficient between the process trigger signal and the reference timing data corresponding to the historical parameter adjustment node, if the Pearson correlation coefficient is greater than the preset Pearson correlation coefficient threshold, it is determined as the trend consistency parameter adjustment node and used as the parameter adjustment node of the same packaging product type;

[0026] By calculating the Pearson correlation coefficient between the process trigger signal and the reference timing data corresponding to the historical parameter reset node, if the Pearson correlation coefficient is less than the preset Pearson correlation coefficient threshold, it is determined as the trend reversibility parameter adjustment node and used as the parameter reset node of different packaging product types.

[0027] Preferably, calculating the Pearson correlation coefficient between the process trigger signal and the reference timing data corresponding to the historical parameter adjustment node includes: The Pearson correlation coefficient formula is as follows,

[0028]

[0029] where, is the Pearson correlation coefficient, is the timing data of the process trigger signal, is the reference timing data, is the standard deviation of the timing data of the process trigger signal, is the standard deviation of the reference timing data.

[0030] Preferably, obtaining the process trigger signal of the bag-type packaging machine in advance or postponed based on the process signal trigger trend includes:

[0031] If the process signal trigger trend is greater than the preset process signal trigger trend threshold, obtain the process trigger signal of the bag-type packaging machine in advance;

[0032] If the process signal trigger trend is less than the preset process signal trigger trend threshold, obtain the process trigger signal of the bag-type packaging machine postponed.

[0033] Preferably, classifying according to the same packaging parameter replacement node and different packaging parameter replacement nodes based on the packaging parameter replacement node, and obtaining the packaging offset parameter includes:

[0034] Extract the parameter adjustment nodes triggered by the change of the equipment state within the same packaging product type, and mark them as the same packaging parameter replacement nodes;

[0035] Extract the parameter reset nodes triggered by the switching of different packaging product types, and mark them as different packaging parameter replacement nodes;

[0036] Based on the same packaging parameter replacement node, calculate the parameter offset within the same product type, and record it as the first packaging offset parameter;

[0037] Based on different packaging parameter replacement nodes, calculate the parameter offset when the product type is switched, and record it as the second packaging offset parameter;

[0038] Take the weighted sum of the first packaging offset parameter and the second packaging offset parameter as the final packaging offset parameter.

[0039] Preferably, obtaining the packaging similarity parameter based on the packaging offset parameter; controlling the bag-type packaging machine to perform intelligent packaging based on the packaging similarity parameter includes:

[0040] Taking bag making, filling, and sealing as the reference time sequence, analyze the common characteristics in the packaging offset parameters, extract the parameter set that can be reused across product types, and mark it as the migration parameter;

[0041] Analyze the differential characteristics in the packaging offset parameters, extract the parameter set that is only applicable to a specific product type, and mark it as the independent parameter;

[0042] Take the migration parameter as the global control benchmark and apply it to the packaging processes of all product types;

[0043] Dynamically adjust the packaging parameters of a specific product type according to the independent parameter, and achieve adaptive control in combination with the migration parameter.

[0044] Preferably, the intelligent packaging control system of the bag type packaging machine includes:

[0045] Parameter classification and offset calculation module, extract the parameter adjustment nodes of the same packaging product type and the parameter reset nodes of different product types, respectively count the replacement times of the two types of nodes and sum them to generate the packaging offset parameter; monitor the device status change and product switching signal in real time, record the parameter adjustment time point, and quantify the parameter offset degree through frequency statistics;

[0046] Similar parameter extraction and control module, based on the packaging offset parameter, analyze the common and differential characteristics in the bag making, filling, and sealing stages; extract the reusable migration parameter across products as the global benchmark, and dynamically adjust in combination with the independent parameter of a specific product type; determine the parameter reusability through the correlation of time series data, and optimize the parameter value using the deviation correction formula to achieve adaptive packaging control;

[0047] Process trigger signal optimization module, through the trend analysis triggered by the process signal, trigger the parameter adjustment instruction in advance or delay, and calculate the correlation between the signal and the historical node according to the Pearson correlation coefficient, and set the threshold to determine the type of adjustment node.

[0048] Beneficial effects: The present invention suppresses the parameter drift caused by equipment wear and environmental fluctuations through the dynamic parameter correction mechanism, accurately discriminates the type of parameter adjustment node by using time series correlation analysis, and reduces the misjudgment of product switching; extracts common parameters and special parameters based on the parameter migration characteristics, realizes cross-category parameter reuse and scenario adaptation, and reduces the repeated configuration cost; the trend prediction mechanism of the process trigger signal optimizes the mechanical action coordination and improves the packaging beat stability. Compared with the traditional method, the present invention can adapt to the packaging requirements of multi-form products, significantly reduce the intensity of manual intervention. In addition, the parameter adjustment accuracy and the overall production line efficiency are both significantly improved, and the packaging quality in a specific scenario is guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is the flowchart of the intelligent packaging control method of the bag type packaging machine of the present invention;

[0050] Figure 2 This is a schematic structural diagram of the intelligent packaging control system of the bag packaging machine of the present invention. Specific embodiments

[0051] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying 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.

[0052] Embodiment 1: An intelligent packaging control method for a bag packaging machine, as Figure 1 shown, includes the following steps:

[0053] S1: Obtain the packaging product type of the bag packaging machine, and based on the packaging product type, extract the packaging parameters of the bag packaging machine; the packaging product type includes the product physical state and the switching node of the product physical state;

[0054] S2: Based on the packaging parameters, extract the process trigger signal of the bag packaging machine; based on the process trigger signal of the bag packaging machine, extract the packaging parameter replacement node; the packaging parameter replacement node includes: the parameter adjustment node triggered by the change of the equipment state within the same packaging product type; the parameter reset node triggered when switching between different packaging product types;

[0055] S3: Based on the packaging parameter replacement node, classify according to the same packaging parameter replacement node and different packaging parameter replacement nodes to obtain the packaging offset parameter; the packaging offset parameter includes the packaging parameter offset of the bag packaging machine itself during the packaging process of the same packaging product type, and the packaging parameter offset generated by the bag packaging machine during the process of changing the product type between different packaging product types;

[0056] S4: Based on the packaging offset parameter, obtain the packaging similarity parameter; based on the packaging similarity parameter, control the bag packaging machine to perform intelligent packaging; the packaging similarity parameter includes the migration parameter and the independent parameter; the migration parameter refers to the general process parameter that can be reused across product types; the independent parameter refers to the special parameter that is only applicable to a specific packaging product type.

[0057] Obtain the packaging product type of the bag packaging machine, and based on the packaging product type, extract the packaging parameters of the bag packaging machine; the packaging product type includes the product physical state and the switching node of the product physical state, including:

[0058] Based on the physical state of the product, obtain the initial parameter set for bag making, filling, and sealing of the bag packaging machine and the corresponding time period of the initial parameter set;

[0059] Based on the switching nodes of the physical state of the product, obtain the adjustment parameter set for bag making, filling, and sealing of the bag packaging machine and the corresponding time period of the adjustment parameter set;

[0060] Based on the initial parameter set and the corresponding time period of the initial parameter set, obtain the corrected adjustment parameter set using the adjustment parameter verification formula;

[0061] Based on the initial parameter set and the corrected adjustment parameter set, obtain the packaging parameters of the bag packaging machine.

[0062] For further explanation, the physical state of the product: divide the initial parameters according to the physical state of the product (such as liquid, powder, solid). For example, liquid packaging requires a higher sealing pressure; the switching node of the physical state of the product: capture the key time point of the product form change (such as switching from solid to liquid).

[0063] Technical effects: automatically match parameters for different forms, reducing manual intervention; the adjustment parameter correction formula suppresses parameter drift caused by equipment wear or environmental fluctuations.

[0064] Example: For liquid packaging, the initial sealing temperature is set at 180 °C. If it is detected that the environmental humidity increases and causes poor sealing, the temperature is adjusted to 185 °C through the adjustment parameter correction formula; for solid packaging, the initial filling speed is 50 packs per minute, and it is corrected to 48 packs per minute due to the decrease in equipment efficiency.

[0065] Supplementary explanation, (The switching node of the physical state of the product) needs to be detected in real time through sensors (such as an optoelectronic switch triggering a form switching signal). The time period of the initial parameter set refers to the time interval from parameter setting to the first detection of the adjustment requirement ( ), which is used to verify the stability of the initial parameters; the time period of the adjustment parameter set refers to the time interval from the first adjustment to the subsequent switching node (such as - ), which is used to dynamically correct the parameters.

[0066] Based on the initial parameter set and the corresponding time period of the initial parameter set, obtain the corrected adjustment parameter set using the adjustment parameter verification formula, including: obtaining the parameter deviation amount of each stage through the adjustment parameter verification formula, and obtaining the adjustment parameter correction amount through the adjustment parameter correction formula; the adjustment parameter verification formula is as follows,

[0067]

[0068] Where, is the parameter deviation amount for the stage, is the weight coefficient of the physical state of the product for the stage, is the switching node of the physical state of the product, is the stage parameter adjustment time, is the initial parameter setting time, is the time decay factor, is the minimum value, = 1, 2, 3 correspond to the bag-making, filling, and sealing stages respectively; the adjustment parameter correction formula is as follows,

[0069]

[0070] Among them, is the corrected parameter value for the stage, is the original parameter value for the stage, = 1, 2, 3 correspond to the bag-making, filling, and sealing stages respectively.

[0071] Further explanation is that the parameter deviation is dynamically quantified through the adjustment parameter verification formula. The adjustment parameter correction formula normalizes the total deviation amount and distributes the parameter adjustment amplitude proportionally to avoid excessive correction of a single parameter. is the minimum value, which is used to avoid numerical instability caused by a zero denominator. is used to sum up the parameter deviation amounts of all stages. The weight coefficient has the same physical dimension as the parameter to be adjusted to ensure the dimensional unity of the parameter deviation amount . For example, when the parameter to be adjusted is the sealing temperature, has the dimensionality of temperature ( ); when the parameter to be adjusted is the filling speed, has the dimensionality of speed (LT −1 ). The time decay factor has the dimensionality of the reciprocal of time (T −1 ), which is used to control the decay rate of the historical parameter weight.

[0072] Technical effect: Capturing parameter offsets in real time and adapting to environmental changes (such as temperature fluctuations); suppressing noise data interference through and .

[0073] Example: If the sealing temperature drifts due to equipment aging after the initial setting, the adjustment parameter verification formula will calculate the deviation amount of the sealing temperature and correct the temperature value based on the total deviation ratio to avoid loose sealing. The time decay factor is related to the change rate of the equipment state. For example, in a high-speed production line, is set to 0.5 to rapidly decay the influence of historical parameters; in scenarios with high stability requirements (such as precision liquid packaging), is set to 0.2 to retain more historical data. The weight coefficient adjusts the importance of different stages according to the physical state of the product (such as the liquid sealing stage = 0.8, the solid filling stage = 0.5).

[0074] Supplementary note: It needs to be preset according to actual production experience. For example, the sealing stage of liquid packaging should be higher than that of solid packaging; the time decay factor needs to be dynamically adjusted according to the equipment response speed: in a high-speed production line, the value is increased to accelerate the decay of the weight of historical parameters and ensure that real-time data dominates parameter correction. The stage parameter adjustment time is obtained in the following ways. The sensor records in real time: high-precision sensors (such as photoelectric sensors, pressure sensors) are deployed in each stage of bag making, filling, and sealing. When it is detected that the parameter deviation exceeds the preset sensor threshold, the current time is recorded as ; historical data optimization: according to the statistical adjustment time interval of each stage in historical production data, it is dynamically updated in combination with the equipment wear degree ; dynamic algorithm prediction: by analyzing the trend of process signals in real time (such as the temperature change rate), using a regression model to predict the optimal adjustment time point and update it to .

[0075] Extracting the process trigger signals of the bag packaging machine based on the packaging parameters includes:

[0076] Extracting the adjustment parameter set according to the packaging parameters to generate the first process trigger signal;

[0077] Extracting the corrected adjustment parameter set according to the packaging parameters to generate the second process trigger signal;

[0078] Based on the first process trigger signal and the second process trigger signal, obtaining the process signal trigger trends of the same packaging product type and different packaging product types in the three stages of bag making, filling, and sealing;

[0079] Based on the triggering trend of the process signal, obtain the process trigger signal of the bag packaging machine in advance or delay.

[0080] For further explanation, the first process trigger signal reflects the dynamic change trend of the preset parameters, and the second process trigger signal reflects the actual demand trend of the corrected parameters; by comparing the timing correlation of the two types of signals, analyze the advance or delay of the triggering trend; the first process trigger signal: generated based on the original adjustment parameter set, reflecting the change of the preset parameters; the second process trigger signal: generated based on the corrected parameters, reflecting the change of the actual demand parameters. By comparing the timing correlation of the two types of signals ( ), judge the type of parameter adjustment node: trend consistency node ( > the preset Pearson correlation coefficient threshold): fine-tuning of parameters within the same product type (such as optimizing the filling speed); trend reversibility node ( < the preset Pearson correlation coefficient threshold): parameter reset when switching product types (such as powder → liquid packaging).

[0081] Technical effect: Distinguish normal adjustment from abnormal fluctuations, reduce misjudgment; advance / delay the trigger instruction to avoid mechanical action conflicts.

[0082] Example: When it is detected that the sealing temperature signal is reverse to the historical trend ( < 0.3), it is determined that the product has been switched, and the parameter reset is triggered.

[0083] Supplementary note: Setting of the preset Pearson correlation coefficient threshold: It needs to be determined through training of historical data. For example, when switching to liquid packaging the preset Pearson correlation coefficient threshold is set to 0.2, and for solids it is set to 0.4; noise filtering: perform moving average filtering to avoid interference from instantaneous fluctuations on the correlation calculation.

[0084] Based on the process trigger signal of the bag packaging machine, extract the packaging parameter replacement node, including:

[0085] By calculating the Pearson correlation coefficient between the process trigger signal and the reference timing data corresponding to the historical parameter adjustment node, if the Pearson correlation coefficient is greater than the preset Pearson correlation coefficient threshold, it is determined as a trend consistency parameter adjustment node and used as the parameter adjustment node for the same packaging product type;

[0086] By calculating the Pearson correlation coefficient between the process trigger signal and the reference timing data corresponding to the historical parameter reset node, if the Pearson correlation coefficient is less than the preset Pearson correlation coefficient threshold, it is determined as a trend reversibility parameter adjustment node and used as the parameter reset node for different packaging product types.

[0087] For further explanation, the trend consistency node: determines the similarity between the current signal and the historical adjustment trend through the Pearson correlation coefficient ( ) ( > 0.7); the trend reversibility node: when the difference between the signal and the reference timing data of the historical parameter reset node is significant ( < 0.3), it is determined as a product switch. Consistency check: If > the preset Pearson correlation coefficient threshold, it indicates that the current process trigger signal and the historical parameter adjustment event are highly correlated in time distribution (such as the signal rising trend being synchronized with the adjustment event), and it is determined as a parameter adjustment node of the same product type. Reversibility check: If < the preset Pearson correlation coefficient threshold, it indicates that there is no significant correlation between the signal and the historical adjustment event, and it may be a parameter reset node triggered by a product switch.

[0088] Technical effects: distinguish normal parameter fluctuations (such as temperature fine-tuning) from abnormal switches (such as liquid → solid); dynamic thresholds adapt to different production line rhythms (lower thresholds for high-speed lines).

[0089] Example, the trend consistency node: the sealing pressure is gradually adjusted from 2.0 MPa to 2.2 MPa ( = 0.85), and it is determined as an optimization of the same product; the trend reversibility node: the filling speed drops suddenly from 50 packs / minute to 30 packs / minute ( = 0.15), and it is determined as a product switch.

[0090] Supplementary explanation, noise processing: perform sliding window smoothing on (such as 5-point mean filtering) to avoid interference from instantaneous fluctuations on the correlation calculation; dynamic adjustment of the preset Pearson correlation coefficient threshold: automatically update the threshold according to the production frequency (such as reducing the preset Pearson correlation coefficient threshold by 10% in high-speed production lines ).

[0091] By calculating the Pearson correlation coefficient between the process trigger signal and the reference timing data corresponding to the historical parameter adjustment node, including: the Pearson correlation coefficient formula is as follows,

[0092]

[0093] Among them, is the Pearson correlation coefficient, is the timing data of the process trigger signal, is the reference timing data, is the standard deviation of the timing data of the process trigger signal, is the standard deviation of the reference timing data.

[0094] For further illustration, for example, the reference timing data of the historical parameter adjustment node ( ) can be generated by recording the time points of past parameter adjustment events: on the time axis, the time points when adjustment events occur are marked as 1, and the rest are 0. The process trigger signal ( ) is the timing data of the sealing temperature continuously monitored. By calculating the Pearson correlation coefficient between the two, it is judged whether the current signal is consistent with the historical adjustment trend.

[0095] Based on the triggering trend of the process signal, the process trigger signal of the bag packaging machine is obtained in advance or postponed, including:

[0096] If the triggering trend of the process signal is greater than the preset triggering trend threshold of the process signal, the process trigger signal of the bag packaging machine is obtained in advance;

[0097] If the triggering trend of the process signal is less than the preset triggering trend threshold of the process signal, the process trigger signal of the bag packaging machine is postponed.

[0098] For further illustration, advance triggering: when the signal trend slope is greater than the preset triggering trend threshold of the process signal (such as the rising slope > 0.5), it is predicted that the parameters need to be adjusted in advance to avoid action delay; postponed triggering: when the trend slope is less than the preset triggering trend threshold of the process signal (such as the falling slope < 0.2), the adjustment is postponed to wait for the equipment to stabilize.

[0099] Technical effects: ensure that the parameter adjustment is synchronized with the mechanical action cycle (such as the sealing must be triggered within 0.3 s after the bag making is completed); reduce the idling time caused by waiting.

[0100] Example, advance triggering: when it is detected that the filling speed trend is rising, the supply of the next pack of materials is started 0.2 s in advance; postponed triggering: when the fluctuation of the sealing temperature is greater than the preset sealing temperature threshold, the sealing is delayed by 0.1 s and then performed after the temperature stabilizes.

[0101] Supplementary description, slope calculation: the least squares method is used to fit the trend line to avoid interference from local fluctuations; safety mechanism: when the postponed triggering times out (such as > 1 s), it is forced to start to prevent the production line from stagnating.

[0102] Based on the packaging parameter replacement node, it is classified according to the same packaging parameter replacement node and different packaging parameter replacement nodes, and the packaging offset parameter is obtained, including:

[0103] Extract the parameter adjustment nodes triggered by the change of the equipment state within the same packaging product type, and mark them as the same packaging parameter replacement nodes;

[0104] Extract the parameter reset nodes triggered by the switching between different packaging product types, and mark them as different packaging parameter replacement nodes;

[0105] Replace nodes based on the same packaging parameters, calculate the parameter offset within the same product type, and denote it as the first packaging offset parameter;

[0106] Replace nodes based on different packaging parameters, calculate the parameter offset when switching product types, and denote it as the second packaging offset parameter;

[0107] Take the weighted sum of the first packaging offset parameter and the second packaging offset parameter as the final packaging offset parameter.

[0108] For further explanation, packaging offset parameter: count the adjustment frequencies of the same nodes (equipment state changes) and different nodes (product switching), and quantify the parameter fluctuation degree; migration parameter: common parameters across product types (such as bag-making length); independent parameter: parameters specific to a particular product (such as the sealing pressure for liquid packaging).

[0109] Technical effects: Parameter reuse, migration parameters reduce the time for repeated configuration; dynamic adaptation, independent parameters ensure the accuracy of specific scenarios.

[0110] Example: The migration parameter (bag-making length) is applied to all products, and the independent parameter (sealing temperature) is dynamically adjusted according to liquid / solid.

[0111] Based on the packaging offset parameter, obtain packaging similarity parameters; based on the packaging similarity parameters, control the bag-type packaging machine for intelligent packaging, including:

[0112] Taking bag-making, filling, and sealing as the reference time sequence, analyze the common features in the packaging offset parameter, extract the parameter set that can be reused across product types, and mark it as the migration parameter;

[0113] Analyze the differential features in the packaging offset parameter, extract the parameter set that is only applicable to a specific product type, and mark it as the independent parameter;

[0114] Take the migration parameter as the global control benchmark and apply it to the packaging processes of all product types;

[0115] Dynamically adjust the packaging parameters of a specific product type according to the independent parameter, and achieve adaptive control in combination with the migration parameter.

[0116] For further explanation, technical effects, migration parameters reduce the time for repeated configuration; independent parameters ensure the quality of specific scenarios (such as liquid tightness).

[0117] Example, migration parameter: Taking the bag-making time sequence as the reference, extract the bag-making length of 120 mm as a common parameter across products; independent parameter: Taking the sealing time sequence as the reference, set the sealing pressure for liquid packaging to 2.5 MPa.

[0118] Supplementary description, conflict handling: When migration conflicts with independent parameters (such as filling speed and sealing temperature), the independent parameters are given priority; Dynamic update: Re-cluster the migration parameters within a fixed period to adapt to the addition of new product types.

[0119] Embodiment 2: On the basis of Embodiment 1, an intelligent packaging control system for a bag-type packaging machine, as Figure 2 shown, includes:

[0120] A parameter classification and offset calculation module extracts the parameter adjustment nodes of the same packaging product type and the parameter reset nodes of different product types, respectively counts the replacement times of the two types of nodes and sums them to generate packaging offset parameters; monitors the changes in the device state and product switching signals in real time, records the parameter adjustment time points, and quantifies the parameter offset degree through frequency statistics;

[0121] A similar parameter extraction and control module analyzes the common and different characteristics in the bag-making, filling, and sealing stages based on the packaging offset parameters; extracts the reusable migration parameters across products as the global benchmark, and dynamically adjusts them in combination with the independent parameters of specific product types; determines the parameter reusability through the correlation of time-series data, and optimizes the parameter values using the deviation correction formula to achieve adaptive packaging control;

[0122] A process trigger signal optimization module analyzes the trend through the process signal trigger, advances or delays the parameter adjustment instruction, and calculates the correlation between the signal and the historical node according to the Pearson correlation coefficient, and sets a threshold to determine the type of adjustment node.

[0123] The above has introduced the present application in detail. Specific examples are used in this article to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A smart packaging control method for a bag packaging machine, characterized in that, Including the following steps: S1: Obtain the packaging product type of the bag packaging machine, and based on the packaging product type, extract the packaging parameters of the bag packaging machine; the packaging product type includes the product physical state and the switching node of the product physical state; S2: Based on the packaging parameters, extract the process trigger signal of the bag packaging machine; Based on the process trigger signal of the bag packaging machine, extract the packaging parameter replacement node; The packaging parameter replacement node includes: the parameter adjustment node triggered by the change of the equipment state within the same packaging product type; the parameter reset node triggered when switching between different packaging product types; S3: Based on the packaging parameter replacement node, classify according to the same packaging parameter replacement node and different packaging parameter replacement nodes to obtain the packaging offset parameter; the packaging offset parameter includes the packaging parameter offset of the bag packaging machine itself during the packaging process of the same packaging product type, and the packaging parameter offset generated by the bag packaging machine during the process of changing the product type between different packaging product types; S4: Based on the packaging offset parameter, obtain the packaging similarity parameter; based on the packaging similarity parameter, control the bag packaging machine to perform intelligent packaging; the packaging similarity parameter includes the migration parameter and the independent parameter; the migration parameter refers to the general process parameter that can be reused across product types; the independent parameter refers to the special parameter that is only applicable to a specific packaging product type.

2. The intelligent packaging control method of a bag packaging machine according to claim 1, characterized in that, The obtaining of the packaging product type of the bag packaging machine, and based on the packaging product type, extracting the packaging parameters of the bag packaging machine; the packaging product type includes the product physical state and the switching node of the product physical state, including: Based on the product physical state, obtain the initial parameter set for bag making, filling, and sealing of the bag packaging machine and the corresponding time period of the initial parameter set; Based on the switching node of the product physical state, obtain the adjustment parameter set for bag making, filling, and sealing of the bag packaging machine and the corresponding time period of the adjustment parameter set; Based on the initial parameter set and the corresponding time period of the initial parameter set, use the adjustment parameter verification formula to obtain the corrected adjustment parameter set; Based on the initial parameter set and the corrected adjustment parameter set, obtain the packaging parameters of the bag packaging machine.

3. The intelligent packaging control method of a bag packaging machine according to claim 2, characterized in that, The using of the adjustment parameter verification formula based on the initial parameter set and the corresponding time period of the initial parameter set to obtain the corrected adjustment parameter set includes: obtaining the parameter deviation amount of each stage through the adjustment parameter verification formula, and obtaining the adjustment parameter correction amount through the adjustment parameter correction formula; the adjustment parameter verification formula is as follows, ； Among them, is the parameter deviation amount in the stage, is the weight coefficient of the physical state of the product in the stage, is the switching node of the physical state of the product, is the parameter adjustment time in the stage, is the initial parameter setting time, is the time decay factor, is the minimum value, = 1, 2, 3 correspond to the bag-making, filling, and sealing stages respectively; the adjustment parameter correction formula is as follows, ； Among them, is the parameter value corrected in the stage, is the original parameter value in the stage, where \(i = 1, 2, 3\) correspond to the bag-making, filling, and sealing stages respectively.

4. The intelligent packaging control method of a bag packaging machine according to claim 1, characterized in that, The extracting of the process trigger signal of the bag packaging machine based on the packaging parameters includes: Extract the adjustment parameter set according to the packaging parameters to generate the first process trigger signal; Extract the corrected adjustment parameter set according to the packaging parameters to generate the second process trigger signal; Based on the first process trigger signal and the second process trigger signal, obtain the process signal trigger trend of the same packaging product type and different packaging product types in the three stages of bag making, filling, and sealing; Based on the process signal trigger trend, obtain the process trigger signal of the bag packaging machine in advance or postponed.

5. The intelligent packaging control method of a bag packaging machine according to claim 1, characterized in that, Based on the process trigger signal of the bag packaging machine, extracting packaging parameter replacement nodes, including: By calculating the Pearson correlation coefficient between the process trigger signal and the reference timing data corresponding to the historical parameter adjustment nodes, if the Pearson correlation coefficient is greater than the preset Pearson correlation coefficient threshold, it is determined as a trend consistency parameter adjustment node and used as a parameter adjustment node for the same packaging product type; By calculating the Pearson correlation coefficient between the process trigger signal and the reference timing data corresponding to the historical parameter reset nodes, if the Pearson correlation coefficient is less than the preset Pearson correlation coefficient threshold, it is determined as a trend reversibility parameter adjustment node and used as a parameter reset node for different packaging product types.

6. The intelligent packaging control method of a bag packaging machine according to claim 5, characterized in that, The calculating the Pearson correlation coefficient between the process trigger signal and the reference timing data corresponding to the historical parameter adjustment nodes includes: The Pearson correlation coefficient formula is as follows, ； Among them, is the Pearson correlation coefficient, is the timing data of the process trigger signal, is the reference timing data, is the standard deviation of the timing data of the process trigger signal, is the standard deviation of the reference timing data.

7. A smart packaging control method for a bag packaging machine according to claim 4, characterized in that, Based on the process signal trigger trend, obtaining the process trigger signal of the bag packaging machine in advance or postponed, including: If the process signal trigger trend is greater than the preset process signal trigger trend threshold, obtain the process trigger signal of the bag packaging machine in advance; If the process signal trigger trend is less than the preset process signal trigger trend threshold, obtain the process trigger signal of the bag packaging machine postponed.

8. The intelligent packaging control method of a bag packaging machine according to claim 1, characterized in that, Based on the packaging parameter replacement nodes, classifying them according to the same packaging parameter replacement nodes and different packaging parameter replacement nodes to obtain packaging offset parameters, including: Extracting the parameter adjustment nodes triggered by the equipment state change within the same packaging product type and marking them as the same packaging parameter replacement nodes; Extracting the parameter reset nodes triggered when switching between different packaging product types and marking them as different packaging parameter replacement nodes; Based on the same packaging parameter replacement nodes, calculating the parameter offset within the same product type and recording it as the first packaging offset parameter; Based on different packaging parameter replacement nodes, calculating the parameter offset when switching product types and recording it as the second packaging offset parameter; Taking the weighted sum of the first packaging offset parameter and the second packaging offset parameter as the final packaging offset parameter.

9. The intelligent packaging control method of a bag-type packaging machine according to claim 1, characterized in that, Based on the packaging offset parameters, obtaining packaging similarity parameters; Based on the packaging similarity parameters, controlling the bag packaging machine for intelligent packaging, including: Taking bag making, filling, and sealing as the reference timing, analyzing the common features in the packaging offset parameters, extracting the parameter set that can be reused across product types and marking it as the migration parameter; Analyzing the differential features in the packaging offset parameters, extracting the parameter set that is only applicable to a specific product type and marking it as the independent parameter; Taking the migration parameter as the global control benchmark and applying it to the packaging processes of all product types; Dynamically adjusting the packaging parameters of a specific product type according to the independent parameters and realizing adaptive control in combination with the migration parameters.

10. An intelligent packaging control system for a bag packaging machine, which is used to implement the intelligent packaging control method of the bag packaging machine according to any one of claims 1-9, and is characterized in that, Including: A parameter classification and offset calculation module, which extracts the parameter adjustment nodes of the same packaging product type and the parameter reset nodes of different product types, respectively counts the replacement times of the two types of nodes and sums them to generate packaging offset parameters; monitors the equipment state change and product switching signal in real time, records the parameter adjustment time point, and quantifies the parameter offset degree through frequency statistics; Similar parameter extraction and control module, based on the packaging offset parameters, analyzes the common and different characteristics in the bag-making, filling, and sealing stages; extracts reusable migration parameters across products as the global benchmark, and dynamically adjusts them in combination with the independent parameters of specific product types; determines the parameter reusability through the correlation of time-series data, and optimizes the parameter values using the deviation correction formula to achieve adaptive packaging control; Process trigger signal optimization module, through the trend analysis of process signal triggers, advances or delays the parameter adjustment instructions, and calculates the correlation between the signal and historical nodes according to the Pearson correlation coefficient, and sets the threshold to determine the type of adjustment node.

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