A control system and method for a flexible material production line

Abstract

The present invention discloses a control system and method for a flexible material production line, specifically relating to the field of automated control technology, including a flexible material quality detection module, a flexible material packaging module, a distributed control node module, a flexible material feature management module, a flexible material label management module, and an ERP interaction module. The present invention generates high-precision recognition results by learning the multi-dimensional features of flexible materials, which is conducive to optimizing the production process and ensuring the stability and consistency of the production process. By collecting non-contact detection data of each flexible material and combining it with an image data processing model to detect physical properties, key quality indicators are quantified, providing a reliable basis for subsequent processes, and starting distributed control nodes to achieve efficient collaboration and data sharing among various links of the production line, thereby improving production efficiency and flexibility, providing a complete label management solution, and ensuring the traceability and reliability of the product throughout its life cycle.

Description

Technical Field

[0001] The present invention relates to the field of automation control technology, and more particularly to a control system and method for a flexible material production line. Background Art

[0002] In the field of modern industrial manufacturing, the production and processing of flexible materials have attracted much attention due to their wide range of application scenarios and complex process requirements. Flexible materials include but are not limited to textiles, films, composite materials, rubber products and various polymer materials. These materials play an important role in the automotive manufacturing, aerospace, electronic equipment, medical supplies and packaging industries with their light weight, flexibility and strong plasticity. However, the production process of flexible materials is more complex and uncertain than that of traditional rigid materials, and the automated control of their production lines faces many challenges.

[0003] CN103116348B discloses a production line control system and a control method thereof, including a PLC system and a main server. The PLC system includes multiple workstations connected to the main server. The production line control system also includes an RFID radio frequency reading and writing system. The RFID radio frequency reading and writing system includes an information reading point and an RFID tag. The information reading point is set on the production line. Multiple tooling boards are also placed on the production line. The tooling boards are erased and written with RFID tags. The information reading point reads the data information in the RFID tags on the tooling boards and transmits the data information to the main server. By combining the PLC system with the RFID radio frequency reading and writing system, the synchronous control of production equipment and product data collection are realized, and the purpose of jointly controlling the production line is achieved through information transmission.

[0004] However, in actual use, it still has some shortcomings. For example, when applied to the production of flexible materials, the existing production line control system still has certain deficiencies in real-time control capabilities and adaptability. It is difficult to make adaptive adjustments according to the dynamic changes in material properties, thus affecting the stability and consistency of production.

[0005] Traditional production line control systems mark, identify or track specific locations on flexible materials to facilitate accurate positioning and operation of subsequent processes. However, the response speed and accuracy of label positioning are insufficient, resulting in the control system being unable to respond quickly and accurately, thereby reducing overall operating efficiency. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a control system and method for a flexible material production line, which are used to solve the problems raised in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solutions: a control system for a flexible material production line, comprising:

[0008] Flexible material quality inspection module: collects non-contact inspection data of each flexible material through laser scanning, and combines it with image data processing models to detect the physical properties of each flexible material and issue early warnings for abnormal results.

[0009] The flexible material quality detection module is specifically:

[0010] Step S01: Install a laser transmitter and an industrial camera. The laser transmitter emits a laser beam at a set frequency and power. The laser beam propagates in a straight line toward the target surface. The laser beam accurately irradiates the target surface. Part of the laser beam is absorbed by the target surface, while part of the laser beam is reflected in various directions based on the characteristics of the target surface. The industrial camera is continuously in operation, capturing the laser beam reflected from the target surface in real time, converting the reflected light signal into an electrical signal or a digital signal, and recording the image information of the reflected light.

[0011] Step S02: using an image data processing model to monitor the thickness of the flexible material;

[0012] Step S03: Obtain the thickness of each piece of flexible material and compare it with the preset thickness. If the thickness of the flexible material is greater than the preset thickness, it indicates that there is a problem with the product quality of the flexible material, and an early warning is issued to notify relevant personnel to adjust the equipment operating parameters. Otherwise, it indicates that there is no abnormality in the product quality of the flexible material.

[0013] Flexible material packaging module: used to receive order instructions from the ERP system, complete the bagging and heat sealing of flexible material inner bags, determine the number of initial product labels based on the number of flexible material inner bags bagged and heat sealed, and generate product labels.

[0014] The flexible material packaging module is specifically:

[0015] S01: Connect with the external ERP system through the industrial communication protocol. When the ERP system is started, the communication link is automatically detected and verified to ensure that the connection is normal. The order instructions issued by the ERP system are monitored in real time. Upon receiving a new order instruction, the instruction is immediately formatted and checked for integrity to ensure that the instruction contains the order requirement information required for the order, including but not limited to the flexible material product type, flexible material quantity, flexible material labeling requirements, and flexible material heat sealing temperature threshold;

[0016] S02: Based on the receipt of a new order instruction, a new work order for the production line is triggered to complete the bagging and heat sealing of the flexible material inner bags. Sensors are set to monitor the bagging weight in real time to ensure that the bagging weight of each flexible material inner bag is within the allowable error range of the bagging weight specified in the order requirement information. Sensors are set to monitor the heat sealing temperature in real time to ensure that the heat sealing temperature of each flexible material inner bag is less than the flexible material heat sealing temperature threshold specified in the order requirement information. Industrial cameras and weight sensors are installed after the heat sealing production line to capture the completed packaging images and weight of the flexible material inner bags, perform a secondary inspection to determine whether the product packaging is qualified, reject unqualified products, and upload relevant records to the database.

[0017] S03: Count the actual number of flexible material inner bags that have been bagged and heat-sealed, determine the number of initial product labels, and enter the flexible material label management module to generate product labels.

[0018] Distributed control node module: used to achieve efficient collaboration and data sharing in all links of the production line.

[0019] Flexible material feature management module: used to learn the multi-dimensional features of flexible materials and generate high-precision recognition results. The flexible material feature management module includes a multimodal sensor fusion unit, a central processing unit and a deep learning feature recognition unit.

[0020] Flexible material label management module: manages the entire life cycle of labels, including label generation, printing, binding, activation, and expiration. Each label operation generates a transaction record and sends it to all nodes. Only when more than half of the nodes reach a consensus will the record be officially written into the ledger.

[0021] ERP interaction module: Exchanges production line data with the MES system through standardized interfaces.

[0022] Preferably, the distributed control node module is specifically:

[0023] The time-sensitive network protocol is used to ensure low latency and high reliability of data transmission between nodes. Dynamic communication path optimization is achieved between control nodes through a self-organizing network topology structure. Each control node is equipped with an edge computing module that can perform preliminary processing of local data.

[0024] Preferably, the dynamic communication path optimization is specifically as follows:

[0025] Based on the task priority between each node, the tasks are sorted from high to low according to their priority. The nodes with high priority mean that their tasks are more critical in the overall production process, and resources and task allocation need to be prioritized. When performing flexible material production tasks, tasks are first sent to nodes with high priority. When the tasks of high-priority nodes are processed or are in a waiting state, the tasks are assigned to nodes with lower priority.

[0026] Preferably, the flexible material feature management module is specifically:

[0027] Multimodal sensor fusion unit: including pressure sensors, temperature sensors, optical sensors and vibration sensors, which collects the initial state data of each sensor on the flexible material production line through distributed acquisition nodes and transmits it to the central processing unit through distributed acquisition nodes;

[0028] Central processing unit: used to receive the initial state data transmitted by the multimodal sensor fusion unit, use the Kalman filter algorithm to fuse the initial state data, generate initial production parameters, and implement production parameter adjustment strategies;

[0029] Deep learning feature recognition unit: By collecting images of the flexible material production process, the collected images are subjected to median filtering to remove noise and then enhanced by histogram equalization. The convolutional neural network (CNN) architecture and transfer learning technology are used to learn the image features of the flexible material production process. By minimizing the cross-entropy loss function, high-precision recognition results are generated to complete high-precision positioning of flexible materials.

[0030] Preferably, the flexible material label management module is specifically:

[0031] Integrate with the ERP system to obtain product information and identify whether the product needs color labels. If so, the label printer will automatically print color inner bag labels and box labels. If not, the label printer will automatically print inner bag labels and box labels, and set up a printing quality detection mechanism. If the printing is unqualified, it will automatically reprint. If the printing is qualified, the product label will be posted.

[0032] Preferably, a control method for a flexible material production line comprises the following steps:

[0033] Step S01: Flexible material quality inspection: collect non-contact inspection data of each flexible material through laser scanning, and combine it with the image data processing model to detect the physical properties of each flexible material and issue an early warning for abnormal results;

[0034] The flexible material quality inspection is specifically as follows:

[0035] Step S11: Install a laser transmitter and an industrial camera. The laser transmitter emits a laser beam at a set frequency and power. The laser beam propagates in a straight line toward the target surface. The laser beam accurately irradiates the target surface. Part of the laser beam is absorbed by the target surface, while part of the laser beam is reflected in various directions according to the characteristics of the target surface. The industrial camera is continuously in operation, capturing the laser beam reflected from the target surface in real time, converting the reflected light signal into an electrical signal or a digital signal, and recording the image information of the reflected light.

[0036] Step S12: using the image data processing model to monitor the thickness of the flexible material;

[0037] Step S13: Obtaining the thickness of each piece of flexible material and comparing it with a preset thickness. If the thickness of the flexible material is greater than the preset thickness, it indicates that there is a problem with the product quality of the flexible material, and an early warning is issued to notify relevant personnel to adjust the equipment operating parameters. Otherwise, it indicates that there is no abnormality in the product quality of the flexible material;

[0038] Step S02: Flexible material packaging: used to receive order instructions from the ERP system, complete the bagging and heat sealing of the flexible material inner bags, determine the number of initial product labels based on the number of flexible material inner bags bagged and heat sealed, and generate product labels;

[0039] The flexible material packaging is specifically:

[0040] S21: Connect with the external ERP system through the industrial communication protocol. When the ERP system is started, the communication link is automatically detected and verified to ensure that the connection is normal. The order instructions issued by the ERP system are monitored in real time. Upon receiving a new order instruction, the instruction is immediately formatted and checked for integrity to ensure that the instruction contains the order requirement information required for the order, including but not limited to the flexible material product type, flexible material quantity, flexible material labeling requirements, and flexible material heat sealing temperature threshold;

[0041] S22: Based on the receipt of a new order instruction, a new work order for the production line is triggered to complete the bagging and heat sealing of the flexible material inner bags. Sensors are set to monitor the bagging weight in real time to ensure that the bagging weight of each flexible material inner bag is within the allowable error range of the bagging weight specified in the order requirement information. Sensors are set to monitor the heat sealing temperature in real time to ensure that the heat sealing temperature of each flexible material inner bag is less than the flexible material heat sealing temperature threshold specified in the order requirement information. Industrial cameras and weight sensors are installed after the heat sealing production line to capture the completed packaging images and weight of the flexible material inner bags, perform a secondary inspection to determine whether the product packaging is qualified, reject unqualified products, and upload relevant records to the database.

[0042] S23: Count the number of flexible material inner bags actually bagged and heat-sealed, determine the number of initial product labels, and enter the flexible material label management module to generate product labels;

[0043] Step S03: Distributed control nodes: used to achieve efficient collaboration and data sharing among all links of the production line;

[0044] Step S04: Flexible material feature management: used to learn the multi-dimensional features of flexible materials and generate high-precision recognition results. The flexible material feature management includes a multimodal sensor fusion sub-step, a central processing sub-step, and a deep learning feature recognition sub-step;

[0045] Step S05: Flexible material label management: Management of the entire label lifecycle, including label generation, printing, binding, activation, and expiration. Each label operation generates a transaction record and sends it to all nodes. Only when more than half of the nodes reach a consensus will the record be officially written into the ledger.

[0046] Step S06: ERP interaction: The production line data is exchanged with the MES system through a standardized interface.

[0047] The technical effects and advantages of the present invention are as follows:

[0048] 1. The present invention provides a control system and method for a flexible material production line. The system collects initial state data of each sensor on the flexible material production line through distributed acquisition nodes, fuses the initial state data using a Kalman filter algorithm, generates initial production parameters, and implements a production parameter adjustment strategy. The system further learns image features of the flexible material production process and generates high-precision recognition results by minimizing the cross-entropy loss function. This system achieves high-precision positioning of the flexible material, which is beneficial for optimizing the production process and ensuring the stability and consistency of the production process. It solves the problems of insufficient real-time control capability and slow response speed in the existing technology, and significantly improves the automation level and product quality of flexible material production. The system has broad application prospects and market value.

[0049] 2. The present invention provides a control system and method for a flexible material production line. The control system collects non-contact detection data of each flexible material through laser scanning, and combines it with an image data processing model to detect the physical properties of each flexible material and issue early warnings for abnormal results, thereby accurately quantifying the key quality indicators of the flexible material and providing a reliable basis for subsequent processes. By receiving order instructions from the ERP system, the control system completes the bagging and heat sealing of the inner bags of the flexible material, determines the initial number of product labels based on the number of bagging and heat sealing of the inner bags of the flexible material, generates product labels, and starts distributed control nodes to achieve efficient collaboration and data sharing among all links of the production line, realize intelligent collaborative control of the flexible material production line, significantly improve production efficiency and flexibility, introduce a dynamic task priority algorithm, reduce task scheduling delays, enhance the real-time response capability of the system, provide a complete label management solution, and ensure the traceability and reliability of the product throughout its life cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a structural schematic diagram of a control system for a flexible material production line of the present invention.

[0051] Figure 2 This is a process of a control method for a flexible material production line of the present invention. DETAILED DESCRIPTION

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0053] See also Figure 1 As shown, the present invention provides a control system for a flexible material production line, including a flexible material quality detection module, a flexible material packaging module, a distributed control node module, a flexible material feature management module, a flexible material label management module, and an ERP interaction module.

[0054] The flexible material quality detection module is connected to the flexible material packaging module, the flexible material packaging module is connected to the distributed control node module and the flexible material label management module, the distributed control node module is connected to the flexible material feature management module, and the flexible material feature management module is connected to the ERP interaction module.

[0055] The flexible material quality detection module collects non-contact detection data of each flexible material through laser scanning, and combines it with an image data processing model to detect the physical properties of each flexible material and issue an early warning for abnormal results.

[0056] In one possible design, the flexible material quality detection module is specifically:

[0057] Step S01: Install a laser transmitter and an industrial camera. The laser transmitter emits a laser beam at a set frequency and power. The laser beam propagates in a straight line toward the target surface. The laser beam precisely irradiates the target surface. Part of the laser beam is absorbed by the target surface, while part of the laser beam is reflected in various directions based on the characteristics of the target surface. The CCD camera is continuously in operation, capturing the laser beam reflected from the target surface in real time, converting the reflected light signal into an electrical signal or digital signal, and recording the image information of the reflected light.

[0058] Step S02: Using an image data processing model to monitor the thickness of the flexible material: ,in, Expressed as the thickness of the i-th flexible material, It is represented as the focal length of the laser scanning lens for the i-th flexible material, Expressed as the laser scanning baseline length of the i-th flexible material, It is expressed as the pixel offset on the imaging plane of the i-th flexible material;

[0059] Step S03: Obtain the thickness of each piece of flexible material and compare it with the preset thickness. If the thickness of the flexible material is greater than the preset thickness, it indicates that there is a problem with the product quality of the flexible material, and an early warning is issued to notify relevant personnel to adjust the equipment operating parameters. Otherwise, it indicates that there is no abnormality in the product quality of the flexible material.

[0060] The flexible material packaging module is used to receive order instructions from the ERP system, complete the bagging and heat sealing of flexible material inner bags, determine the number of initial product labels based on the number of flexible material inner bags bagged and heat sealed, and generate product labels.

[0061] In one possible design, the flexible material packaging module is specifically:

[0062] S01: Connect with the external ERP system through the industrial communication protocol. When the ERP system is started, the communication link is automatically detected and verified to ensure that the connection is normal. The order instructions issued by the ERP system are monitored in real time. Upon receiving a new order instruction, the instruction is immediately formatted and checked for integrity to ensure that the instruction contains the order requirement information required for the order, including but not limited to the flexible material product type, flexible material quantity, flexible material labeling requirements, and flexible material heat sealing temperature threshold;

[0063] S02: Based on the receipt of a new order instruction, a new work order for the production line is triggered to complete the bagging and heat sealing of the flexible material inner bags. Sensors are set to monitor the bagging weight in real time to ensure that the bagging weight of each flexible material inner bag is within the allowable error range of the bagging weight specified in the order requirement information. Sensors are set to monitor the heat sealing temperature in real time to ensure that the heat sealing temperature of each flexible material inner bag is less than the flexible material heat sealing temperature threshold specified in the order requirement information. Industrial cameras and weight sensors are installed after the heat sealing production line to capture the completed packaging images and weight of the flexible material inner bags, perform a secondary inspection to determine whether the product packaging is qualified, reject unqualified products, and upload relevant records to the database.

[0064] S03: Count the actual number of flexible material inner bags that have been bagged and heat-sealed, determine the number of initial product labels, and enter the flexible material label management module to generate product labels.

[0065] In this embodiment, it should be specifically explained that the allowable error range is given by the formula: ,in, Expressed as the allowable error range, It is expressed as the average bag weight, and k is the preset proportional coefficient.

[0066] The distributed control node module is used to achieve efficient collaboration and data sharing among various links of the production line.

[0067] In one possible design, the distributed control node module is specifically:

[0068] The time-sensitive network protocol is used to ensure low latency and high reliability of data transmission between nodes. Dynamic communication path optimization is achieved between control nodes through a self-organizing network topology structure. Each control node is equipped with an edge computing module that can perform preliminary processing of local data.

[0069] In this embodiment, it should be specifically explained that the implementation method of the dynamic communication path optimization is:

[0070] ,in, Expressed as the task priority of the x-th node, Expressed as the task importance weight of the x-th node, It represents the estimated completion time of the task of the xth node, Expressed as the task resource consumption of the xth node, Expressed as the total amount of available resources at the x-th node, Expressed as adjustment coefficient;

[0071] Obtain the task priority between each node and sort them from high to low according to the task priority. The node with high priority means that its task is more critical in the overall production process, and resources and task allocation need to be prioritized. When performing flexible material production tasks, tasks are sent to nodes with high priority first. When the tasks of high-priority nodes are processed or in a waiting state, the tasks are assigned to nodes with lower priority.

[0072] For example, in the coating process of flexible materials, the control nodes distributed near the coating machine head will collect key parameters such as coating thickness and uniformity in real time, and quickly transmit the data to the central processing unit through the time-sensitive network protocol. When the production line needs to add new processes or equipment, only the corresponding control nodes need to be added to achieve seamless integration.

[0073] The flexible material feature management module is used to learn the multi-dimensional features of flexible materials and generate high-precision recognition results. The flexible material feature management module includes a multimodal sensor fusion unit, a central processing unit and a deep learning feature recognition unit.

[0074] In one possible design, the flexible material feature management module is specifically:

[0075] Multimodal sensor fusion unit: including pressure sensors, temperature sensors, optical sensors and vibration sensors, which collects the initial state data of each sensor on the flexible material production line through distributed acquisition nodes and transmits it to the central processing unit through distributed acquisition nodes;

[0076] Central processing unit: used to receive the initial state data transmitted by the multimodal sensor fusion unit, use the Kalman filter algorithm to fuse the initial state data, generate initial production parameters, and implement production parameter adjustment strategies.

[0077] Deep learning feature recognition unit: By collecting images of the flexible material production process, the collected images are subjected to median filtering to remove noise and then enhanced by histogram equalization. The convolutional neural network (CNN) architecture and transfer learning technology are used to learn the image features of the flexible material production process. By minimizing the cross-entropy loss function, high-precision recognition results are generated to complete high-precision positioning of flexible materials.

[0078] In this embodiment, it should be specifically explained that the calculation formula of the Kalman filter algorithm is:

[0079]

[0080] in, Represents the estimated state at the current moment, It is represented as the state prediction value at the previous moment, Represents the sensor measurement value at the current moment, Represented as an observation matrix;

[0081] In practical applications, during the hot pressing process of flexible materials, when the temperature sensor detects an abnormal increase in local temperature, the Kalman filter algorithm generates the optimal adjustment strategy to dynamically reduce the heating power of the corresponding area to ensure the consistency of material properties. It can effectively filter out noise interference in complex production environments, thereby improving data reliability and accuracy.

[0082] In this embodiment, it should be specifically explained that the training formula of the cross entropy loss function is:

[0083]

[0084] in, Expressed as the loss function value, is represented as the model prediction value, Represents the true label, and m represents the total number of samples;

[0085] Specifically, the loss function value reflects the degree of difference between the model prediction value and the true label. The smaller the loss value, the more accurate the model prediction.

[0086] The flexible material label management module manages the entire life cycle of the label, including label generation, printing, binding, activation, and expiration. Each label operation generates a transaction record and sends it to all nodes. Only when more than half of the nodes reach a consensus will the record be officially written into the ledger.

[0087] In one possible design, the flexible material label management module is specifically:

[0088] Integrate with the ERP system to obtain product information and identify whether the product needs color labels. If so, the label printer will automatically print color inner bag labels and box labels. If not, the label printer will automatically print inner bag labels and box labels, and set up a printing quality detection mechanism. If the printing is unqualified, it will automatically reprint. If the printing is qualified, the product label will be posted.

[0089] The ERP interaction module exchanges production line data with the MES system through a standardized interface.

[0090] See also Figure 2 As shown, the present invention provides a control method for a flexible material production line, comprising the following steps:

[0091] Step S01: Flexible material quality inspection: collect non-contact inspection data of each flexible material through laser scanning, and combine it with the image data processing model to detect the physical properties of each flexible material and issue an early warning for abnormal results;

[0092] Step S02: Flexible material packaging: used to receive order instructions from the ERP system, complete the bagging and heat sealing of the flexible material inner bags, determine the number of initial product labels based on the number of flexible material inner bags bagged and heat sealed, and generate product labels;

[0093] Step S03: Distributed control nodes: used to achieve efficient collaboration and data sharing among all links of the production line;

[0094] Step S04: Flexible material feature management: used to learn the multi-dimensional features of flexible materials and generate high-precision recognition results. The flexible material feature management includes a multimodal sensor fusion sub-step, a central processing sub-step, and a deep learning feature recognition sub-step;

[0095] Step S05: Flexible material label management: Management of the entire label lifecycle, including label generation, printing, binding, activation, and expiration. Each label operation generates a transaction record and sends it to all nodes. Only when more than half of the nodes reach a consensus will the record be officially written into the ledger.

[0096] Step S06: ERP interaction: The production line data is exchanged with the MES system through a standardized interface.

[0097] In this embodiment, it should be specifically explained that the present invention collects the initial state data of each sensor on the flexible material production line through distributed acquisition nodes, uses the Kalman filter algorithm to fuse the initial state data, generates initial production parameters, and implements a production parameter adjustment strategy. Furthermore, by learning the image features of the flexible material production process and minimizing the cross-entropy loss function, a high-precision recognition result is generated, and high-precision positioning of the flexible material is completed, which is conducive to optimizing the production process and ensuring the stability and consistency of the production process. It solves the problems of insufficient real-time control capability and slow response speed in the prior art, and significantly improves the automation level and product quality of flexible material production. It has broad application prospects and market value.

[0098] The present invention collects non-contact detection data of each flexible material through laser scanning, and combines it with an image data processing model to detect the physical properties of each flexible material and issue early warnings for abnormal results, thereby being able to accurately quantify the key quality indicators of the flexible material, providing a reliable basis for subsequent processes, and completing the bagging and heat sealing of the flexible material inner bags by receiving order instructions from the ERP system. The initial number of product labels is determined based on the number of bagging and heat sealing of the flexible material inner bags, and product labels are generated, and distributed control nodes are started to achieve efficient collaboration and data sharing in all links of the production line, thereby realizing intelligent collaborative control of the flexible material production line, significantly improving production efficiency and flexibility, introducing a dynamic task priority algorithm, reducing task scheduling delays, enhancing the real-time response capability of the system, providing a complete label management solution, and ensuring the traceability and reliability of the product throughout its life cycle.

[0099] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A control system for a flexible material production line, characterized in that: include: Flexible material quality inspection module: This module collects non-contact inspection data of each flexible material through laser scanning, and combines it with an image data processing model to detect the physical properties of each flexible material and issue early warnings for abnormal results. The flexible material quality detection module is specifically: Step S01: Install a laser transmitter and an industrial camera. The laser transmitter emits a laser beam at a set frequency and power. The laser beam propagates in a straight line toward the target surface. The laser beam accurately irradiates the target surface. Part of the laser beam is absorbed by the target surface, while part of the laser beam is reflected in various directions based on the characteristics of the target surface. The industrial camera is continuously in operation, capturing the laser beam reflected from the target surface in real time, converting the reflected light signal into an electrical signal or a digital signal, and recording the image information of the reflected light. Step S02: using an image data processing model to monitor the thickness of the flexible material; Step S03: Obtaining the thickness of each piece of flexible material and comparing it with a preset thickness. If the thickness of the flexible material is greater than the preset thickness, it indicates that there is a problem with the product quality of the flexible material, and an early warning is issued to notify relevant personnel to adjust the equipment operating parameters. Otherwise, it indicates that there is no abnormality in the product quality of the flexible material; Flexible material packaging module: used to receive order instructions from the ERP system, complete the bagging and heat sealing of flexible material inner bags, determine the number of initial product labels based on the number of flexible material inner bags bagged and heat-sealed, and generate product labels; The flexible material packaging module is specifically: S01: Connect with the external ERP system through the industrial communication protocol. When the ERP system is started, the communication link is automatically detected and verified to ensure that the connection is normal. The order instructions issued by the ERP system are monitored in real time. Upon receiving a new order instruction, the instruction is immediately formatted and checked for integrity to ensure that the instruction contains the order requirement information required for the order, including but not limited to the flexible material product type, flexible material quantity, flexible material labeling requirements, and flexible material heat sealing temperature threshold; S02: Based on the receipt of a new order instruction, a new work order for the production line is triggered to complete the bagging and heat sealing of the flexible material inner bags. Sensors are set to monitor the bagging weight in real time to ensure that the bagging weight of each flexible material inner bag is within the allowable error range of the bagging weight specified in the order requirement information. Sensors are set to monitor the heat sealing temperature in real time to ensure that the heat sealing temperature of each flexible material inner bag is less than the flexible material heat sealing temperature threshold specified in the order requirement information. Industrial cameras and weight sensors are installed after the heat sealing production line to capture the completed packaging images and weight of the flexible material inner bags, perform a secondary inspection to determine whether the product packaging is qualified, reject unqualified products, and upload relevant records to the database. S03: Count the number of flexible material inner bags actually bagged and heat-sealed, determine the number of initial product labels, and enter the flexible material label management module to generate product labels; Distributed control node module: used to achieve efficient collaboration and data sharing among all links of the production line; Flexible material feature management module: used to learn the multi-dimensional features of flexible materials and generate high-precision recognition results. The flexible material feature management module includes a multimodal sensor fusion unit, a central processing unit, and a deep learning feature recognition unit; Flexible material label management module: manages the entire label lifecycle, including label generation, printing, binding, activation, and expiration. Each label operation generates a transaction record and sends it to all nodes. Only when more than half of the nodes reach a consensus will the record be officially written into the ledger. ERP interaction module: Exchanges production line data with the MES system through standardized interfaces.

2. A control system for a flexible material production line according to claim 1, characterized in that: The distributed control node module is specifically: The time-sensitive network protocol is used to ensure low latency and high reliability of data transmission between nodes. Dynamic communication path optimization is achieved between control nodes through a self-organizing network topology structure. Each control node is equipped with an edge computing module that can perform preliminary processing of local data.

3. A control system for a flexible material production line according to claim 2, characterized in that: The dynamic communication path optimization is specifically as follows: Based on the task priority between each node, the tasks are sorted from high to low according to their priority. The nodes with high priority mean that their tasks are more critical in the overall production process, and resources and task allocation need to be prioritized. When performing flexible material production tasks, tasks are first sent to nodes with high priority. When the tasks of high-priority nodes are processed or are in a waiting state, the tasks are assigned to nodes with lower priority.

4. The control system for a flexible material production line according to claim 1, characterized in that: The flexible material feature management module is specifically: Multimodal sensor fusion unit: including pressure sensors, temperature sensors, optical sensors and vibration sensors, which collects the initial state data of each sensor on the flexible material production line through distributed acquisition nodes and transmits it to the central processing unit through distributed acquisition nodes; Central processing unit: used to receive the initial state data transmitted by the multimodal sensor fusion unit, use the Kalman filter algorithm to fuse the initial state data, generate initial production parameters, and implement production parameter adjustment strategies; Deep learning feature recognition unit: By collecting images of the flexible material production process, the collected images are subjected to median filtering to remove noise and then enhanced by histogram equalization. The convolutional neural network (CNN) architecture and transfer learning technology are used to learn the image features of the flexible material production process. By minimizing the cross-entropy loss function, high-precision recognition results are generated to complete high-precision positioning of flexible materials.

5. The control system for a flexible material production line according to claim 1, characterized in that: The flexible material label management module is specifically: Integrate with the ERP system to obtain product information and identify whether the product needs color labels. If so, the label printer will automatically print color inner bag labels and box labels. If not, the label printer will automatically print inner bag labels and box labels, and set up a printing quality detection mechanism. If the printing is unqualified, it will automatically reprint. If the printing is qualified, the product label will be posted.

6. A control method for a flexible material production line, using a control system for a flexible material production line according to any one of claims 1 to 4, characterized in that: The following steps are involved: Step S01: Flexible material quality inspection: collect non-contact inspection data of each flexible material through laser scanning, and combine it with the image data processing model to detect the physical properties of each flexible material and issue an early warning for abnormal results; The flexible material quality inspection is specifically as follows: Step S11: Install a laser transmitter and an industrial camera. The laser transmitter emits a laser beam at a set frequency and power. The laser beam propagates in a straight line toward the target surface. The laser beam accurately irradiates the target surface. Part of the laser beam is absorbed by the target surface, while part of the laser beam is reflected in various directions according to the characteristics of the target surface. The industrial camera is continuously in operation, capturing the laser beam reflected from the target surface in real time, converting the reflected light signal into an electrical signal or a digital signal, and recording the image information of the reflected light. Step S12: using the image data processing model to monitor the thickness of the flexible material; Step S13: Obtaining the thickness of each piece of flexible material and comparing it with a preset thickness. If the thickness of the flexible material is greater than the preset thickness, it indicates that there is a problem with the product quality of the flexible material, and an early warning is issued to notify relevant personnel to adjust the equipment operating parameters. Otherwise, it indicates that there is no abnormality in the product quality of the flexible material; Step S02: Flexible material packaging: used to receive order instructions from the ERP system, complete the bagging and heat sealing of the flexible material inner bags, determine the number of initial product labels based on the number of flexible material inner bags bagged and heat sealed, and generate product labels; The flexible material packaging is specifically: S21: Connect with the external ERP system through the industrial communication protocol. When the ERP system is started, the communication link is automatically detected and verified to ensure that the connection is normal. The order instructions issued by the ERP system are monitored in real time. Upon receiving a new order instruction, the instruction is immediately formatted and checked for integrity to ensure that the instruction contains the order requirement information required for the order, including but not limited to the flexible material product type, flexible material quantity, flexible material labeling requirements, and flexible material heat sealing temperature threshold; S22: Based on the receipt of a new order instruction, a new work order for the production line is triggered to complete the bagging and heat sealing of the flexible material inner bags. Sensors are set to monitor the bagging weight in real time to ensure that the bagging weight of each flexible material inner bag is within the allowable error range of the bagging weight specified in the order requirement information. Sensors are set to monitor the heat sealing temperature in real time to ensure that the heat sealing temperature of each flexible material inner bag is less than the flexible material heat sealing temperature threshold specified in the order requirement information. Industrial cameras and weight sensors are installed after the heat sealing production line to capture the completed packaging images and weight of the flexible material inner bags, perform a secondary inspection to determine whether the product packaging is qualified, reject unqualified products, and upload relevant records to the database. S23: Count the number of flexible material inner bags actually bagged and heat-sealed, determine the number of initial product labels, and enter the flexible material label management module to generate product labels; Step S03: Distributed control nodes: used to achieve efficient collaboration and data sharing among all links of the production line; Step S04: Flexible material feature management: used to learn the multi-dimensional features of flexible materials and generate high-precision recognition results. The flexible material feature management includes a multimodal sensor fusion sub-step, a central processing sub-step, and a deep learning feature recognition sub-step; Step S05: Flexible material label management: Management of the entire label lifecycle, including label generation, printing, binding, activation, and expiration. Each label operation generates a transaction record and sends it to all nodes. Only when more than half of the nodes reach a consensus will the record be officially written into the ledger. Step S06: ERP interaction: The production line data is exchanged with the MES system through a standardized interface.

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