An intelligent control system for laminating machines

Abstract

The present invention specifically relates to an intelligent laminating machine control system, which belongs to the technical field of industrial machinery control systems, and includes a PLC controller, an FGPA universal chip, a parameter setting module, an external operation module, a monitoring and protection module, an interactive execution module and a power configuration module; the present invention reduces the chip tape-out cycle and reduces the cost and price of the laminating machine by replacing the control chip with the FGPA universal chip; improves the safety performance and operating efficiency of the control system by setting a parallel control parameter control circuit and a power distribution circuit; and sets a model training unit in the parameter setting module to perform feature extraction and analysis on the laminating sample, so as to configure the execution strategy of the laminating machine, and reduce the operating error and cost loss through the execution strategy.

Description

Technical Field

[0001] The invention belongs to the technical field of industrial machinery control systems, and in particular relates to an intelligent laminating machine control system. Background Art

[0002] Laminating machines can be divided into two categories: instant laminating machines and pre-coating laminating machines. A laminating machine is a special equipment for paper, board materials and mounting films. After being pressurized by rubber rollers and heating rollers, they are combined to form a paper-plastic product. A coating laminating machine includes three parts: gluing, drying and hot pressing. It has a wide range of applications and stable and reliable processing performance. It is a widely used laminating equipment in China. A pre-coating laminating machine has no gluing and drying parts, is small in size, low in cost, and flexible and convenient to operate. It is suitable for laminating processing of small batches and scattered printed materials such as automated desktop office systems, and also performs well in laminating processing of large batches of printed materials.

[0003] With the advancement of science and technology, the development of laminating machines is moving towards intelligence, miniaturization, simplification, cost reduction and expansion of application. New laminating machines have been developed, such as cold laminating machines and small laminating machines. Cold laminating machines are laminating machines that operate at room temperature and are not heated. They directly stick the sticky film to the printed matter by applying pressure. This type of machine is cheap and widely used, such as in the board industry, decoration industry and hardware industry. Small laminating machines are simple and practical professional laminating machines. They can also be used as plastic sealing machines, cold laminating machines, and PVC heat sealing. Strictly speaking, this type of laminating machine is also upgraded from internal heat plastic sealing machines. Because of the use of internal hot rubber roller to press the film and the film feeding from top to bottom, the heating time of the pre-coated film is increased and the heat is evenly distributed, so the coated film is smooth and bright, and the effect is the same as the film coated by high-end laminating machines, but the price is between 1400-1500 yuan, compared with high-end laminating machines, the cost of use and maintenance is lower, it is the most cost-effective small laminating machine, suitable for business card laminating, recipe laminating, photo laminating and graphic printed material laminating, widely used in small printing factories, typing and copying shops, business card making companies and photo studios, and the roadside film laminating machines commonly seen in life are also an application of small film laminating machines.

[0004] The existing laminating machines mainly have the following problems: first, the control system uses ASIC dedicated integrated chip, which has a tape-out cycle of about three months, affecting the development and use of the laminating machine; second, the parameters of the control system are mostly independently controlled, which has higher stability but lower efficiency. Summary of the invention

[0005] In view of the above-mentioned deficiencies in the prior art, the present invention discloses an intelligent laminating machine control system which adopts an FGPA universal chip as a control chip, adopts integrated control for control system parameters, and realizes parameter adjustment through model training.

[0006] In order to achieve the above technical effects, the present invention adopts the following technical solutions:

[0007] An intelligent laminating machine control system, comprising:

[0008] The PLC controller is used to provide an installation location for the FGPA universal chip, the parameter setting module, the external operation module and the power configuration module; the PLC controller is connected to the laminating machine and the control system to realize the configuration and installation of the control system and connect it to the laminating machine;

[0009] FGPA universal chip, used to configure the lamination operation scheme through internal algorithm and connection interactive execution module; the FGPA universal chip realizes the configuration operation scheme to the interactive execution module by reading the operation and configuration algorithm performed by the parameter setting module and the external operation module;

[0010] A parameter setting module is used to configure the model parameters of the FGPA universal chip and the laminating machine; the parameter setting module sets and adjusts the operating parameters of the laminating machine by reading the operating data of the external operating module and adding raw material debugging;

[0011] An external operation module is used to provide an operation and control window for the staff or maintenance personnel; the external operation module senses the operation performed by the staff through the touch screen component, so as to control the control system according to the information transmitted by the touch screen component;

[0012] The monitoring and protection module is used to detect various characteristic values ​​of the laminating machine in the working state and determine whether there is any abnormality; the monitoring and protection module monitors the operating status of the laminating machine and collects parameters through sensor components and alarm components to determine whether there is any abnormality or failure in the laminating machine;

[0013] An interactive execution module is used to guide and control the various execution components of the laminating machine to perform laminating work; the interactive execution module reads the operation plan from the FGPA universal chip to guide and control the working components of the laminating machine to perform specific operations according to the operation plan, so as to achieve normal operation of the laminating machine;

[0014] A power configuration module, used to connect the PLC controller, FGPA universal chip, parameter setting module and external operation module to provide power configuration and circuit control. The power configuration module provides operating power to the PLC controller, FGPA universal chip, parameter setting module and external operation module by connecting a DC power supply;

[0015] Among them, the PLC controller is fixedly installed in the controller installation area of ​​the intelligent laminating machine by screws, the FGPA universal chip is arranged inside the PLC controller, the parameter setting module, the external operation module, the monitoring and protection module and the power supply configuration module are arranged on the outside of the PLC controller, the parameter setting module is electrically connected to the external operation module and the FGPA universal chip, the FGPA universal chip is electrically connected to the monitoring and protection module, the interactive execution module and the external operation module, the interactive execution module is arranged on the execution component of the laminating machine, the power supply configuration module is electrically connected to the DC power supply, and the parameter setting module, the external operation module and the monitoring and protection module are electrically connected to the power supply configuration module.

[0016] As a further description of the above scheme,

[0017] The parameter setting module realizes model training using raw materials and information communication using a communication interface through a model training unit and a communication receiving unit; the parameter setting module includes a material guiding unit, a model training unit and a communication receiving unit; the material guiding unit guides the raw materials therein into a specified position through a feed port to provide raw materials for the model training unit; the model training unit realizes training of an adjustable control model according to the configured raw materials through a preset online learning algorithm to configure the control model to the FGPA universal chip; the communication receiving unit realizes information communication between the control system and external components through a communication interface; the communication receiving unit connects the control system and the external components, and the external interface of the communication interface is set on the PLC controller.

[0018] As a further description of the above scheme,

[0019] The model training unit performs feature extraction and identification on the raw materials through the feature extraction algorithm to obtain the feature parameters of the coated sample, and trains the operation model corresponding to the feature parameters through the feature parameters and the SL online learning algorithm, and outputs the operation model to the FGPA universal chip; the feature extraction algorithm realizes feature extraction of the raw materials through component analysis and feature identification, and the feature extraction algorithm realizes feature extraction through the feature extraction formula, and the expression of the feature extraction formula is:

[0020]

[0021] In the above formula (1), n ​​represents the number of extracted features, which is used to calculate the number of features to be extracted; θ represents the deviation threshold, which represents the deviation angle of the feature coordinates; i represents the cycle feature parameter, which indicates that the current cycle is the i-th cycle; ω represents the deviation weight, which represents the specific deviation value of the feature to be identified in the coordinate system; x represents the sample data, which is used to represent the input feature to be extracted; y represents the activation function parameter, which is used to represent the parameter of the desired feature;

[0022] The SL online learning algorithm realizes real-time and rapid feedback adjustment model adjustment through online feedback data and training of each sample, and performs high-density screening and high-efficiency recognition on the data passing through the model; the training process of the feedback adjustment model: first, set the learning rate and regularization parameter values ​​of the model; second, set the number of parallel learning of the model; third, continuously fill the data into the data pool; fourth, at the same time, different parallel lines will take data from the data pool for training; finally, after the data is captured, the models of different lines are merged and saved; the online learning algorithm realizes online learning and training models through the online learning formula, and the expression of the online learning formula is:

[0023] ω t＝1,i =-(z t,i -sgn(z t,i )-λ1) / (λ2+σ 1:t ) (2)

[0024] In formula (2), i is a feature parameter, which is used to indicate the input feature that needs to be trained; t is an iteration parameter, which indicates that the current process is the i-th iteration; λ1 and λ2 are feature values, which are used to increase the position weight of the parameter in the algorithm; σ 1:t Indicates the discrete degree of the gradient parameter, and is used as an intermediate quantity to calculate the discrete degree of the gradient parameter; z t 、z t,i is a custom intermediate variable, the z t 、z t,i The expression is:

[0025]

[0026] In formulas (3) and (4), σ s Indicates the discrete degree of the parameters in the algorithm, and is used as an intermediate quantity to calculate the discrete degree of the algorithm parameters; g 1:t It is the cumulative gradient of the algorithm from round 1 to round t, which is used to calculate the number of iterations of the algorithm.

[0027] As a further description of the above scheme,

[0028] The external operation module controls the laminating machine through the touch screen component and the control knob component, and connects to the external device through the external device interface to assist in controlling the laminating machine; the external operation module includes a touch screen component, a control knob component and an external device interface; the touch screen component reads the operation performed on the touch screen surface through the touch screen and the pressure sensor, so as to control the corresponding components to respond according to the operation; the control knob component controls the working state of the PLC controller through the control knob and the internal switch, so as to control the working state of the laminating machine; the external device interface reads the information transmitted by the device connected to the external device interface through the interface protocol and the data reading chip, so as to assist in parameter adjustment, fault detection and model configuration of the control system through the external device.

[0029] As a further description of the above scheme,

[0030] The monitoring and protection module monitors the working status of the laminating machine through a temperature sensor and a visual sensor, and cuts off the circuit and issues an alarm through a solenoid valve and an alarm to realize a protection control system; the monitoring and protection module includes a temperature sensor, a visual sensor, a solenoid valve and an alarm, and the temperature sensor detects the working temperature of the laminating machine through a temperature-sensitive element and outputs the temperature information to the FGPA universal chip for further processing; the visual sensor collects the working image of the laminating machine through a photosensitive element and outputs the image information to the FGPA universal chip for further processing and analysis; the solenoid valve and the alarm cut off the circuit and issue an alarm by reading the detection report and processing method output by the FGPA universal chip to realize a protection control system.

[0031] As a further description of the above scheme,

[0032] The interactive execution module realizes information exchange between the FGPA universal chip and the laminating machine execution component by connecting the FGPA universal chip and the laminating machine execution component, so as to realize the operation scheme of the FGPA universal chip adjusting the output according to the working state; the interactive execution module includes an isolation transformer unit, a temperature transmitter unit, a weight transmitter unit, a rubber roller drive unit, an electric control heating unit and an auxiliary heat dissipation unit; the isolation transformer unit realizes isolation of the current of the winding coil by controlling the isolation transformer; the temperature transmitter unit realizes measurement of the sensor signal of the temperature sensor in the monitoring and protection module by the temperature transmitter; the weight transmitter unit realizes conversion of the sensor signal of the weighing sensor by the weighing sensor to realize output of the standard industrial signal; the rubber roller drive unit realizes control of the operation, stop and speed of the rubber roller by connecting the rubber roller in the laminating machine execution component; the electric control heating unit realizes configuration of the working temperature of the laminating machine by connecting the heating roller in the laminating machine execution component; the auxiliary heat dissipation unit realizes rapid reduction of the heat of the workbench and the operating temperature of the control circuit in the control system after the laminating machine is completed by internally arranging a heat dissipation fan and dry ice.

[0033] As a further description of the above scheme,

[0034] The power configuration module configures operating power for the control system through an electric control switch and a distribution component, and protects the distribution circuit through a circuit protection unit to prevent circuit overload; the power configuration module includes an electric control switch, a distribution component and a circuit protection unit; the electric control switch adjusts the operating power of the control system by closing or cutting off the distribution circuit; the distribution component configures current outputs of different flow rates to different circuits through a distributor and respectively connecting the parameter setting module, the external operation module and the monitoring and protection module; the circuit protection unit protects the distribution circuit by connecting a protection resistor in the distribution circuit to prevent the distribution circuit from overheating and overloading.

[0035] As a further description of the above scheme,

[0036] The FGPA universal chip is pre-installed with a proportional fairness algorithm for resource allocation, a feature extraction algorithm for feature identification, a model reading method for reading operation models, and a solution database; the proportional fairness algorithm is used to complete the fair allocation of execution solutions configured in the solution database according to the fair allocation formula and output the execution solutions to the interactive execution module; the feature extraction algorithm uses the feature extraction formula to identify the features of the objects to be coated in the laminating machine, and extracts the corresponding solutions in the solution database according to the type and quantity of the features; the model reading method is used to read the operation model output by the parameter setting module, and extract the specific solutions in the solution database according to the operation model; the solution database is internally configured with operation solutions classified according to the feature type and feature quantity, and the solution database implements the feature extraction algorithm through an open source interface to extract the specific operation solutions inside the solution database.

[0037] As a further description of the above scheme,

[0038] The proportional fairness algorithm realizes the configuration of the same equivalent of resources to each component of the interactive execution module by utilizing the time-frequency characteristics of the channel; the proportional fairness algorithm realizes the fair allocation of resources through a fair allocation formula, and the expression of the fair allocation formula is:

[0039]

[0040] In formula (5), K represents the equivalent of resource output after allocation, which is used to represent the parameters of the required resources, i represents the individual to be allocated in the algorithm, which is used to represent that the resources need to be allocated to i components for operation, n represents the last individual to be allocated, which is used to represent that the allocation of resources stops after being allocated to the nth individual, r represents the timely rate of resource allocation, which is used to calculate the efficiency of resource allocation and the time x of resource allocation, R represents the average rate of resource allocation, which is used to calculate the total time required for resource allocation, and x is used to represent the time used for the allocated resources, which is used to calculate the efficiency of resource allocation.

[0041]

[0042] In formula (6), x v Indicates the update time parameter, which is used to represent how long the average rate includes the condition information in the past.

[0043] In summary, the present invention has the following positive and beneficial effects:

[0044] 1. In the present invention, by replacing the chip of the control system with the FGPA universal chip, the chip tape-out cycle is reduced. Compared with the ASIC dedicated integrated chip, the FGPA universal chip has the characteristics of flexible editing, the ability to change the chip function at any time, and avoidance of one-time engineering costs and tape-out costs. It has a strong cost advantage when used in small quantities.

[0045] 2. In the present invention, by replacing the parameter control method of the control system with parallel control, the execution efficiency of the control system is improved by accelerating the parameter configuration efficiency while protecting the system stability. Compared with the single control, the parallel control has the advantages of higher execution efficiency and simplified operation;

[0046] 3. In the present invention, the model training unit is used to perform feature extraction and analysis on the coated sample, and the process parameters of the coated sample are obtained to implement the execution strategy of configuring the laminating machine. The execution strategy is used to prepare a coated printed product that is indistinguishable from the sample under the premise of automatically controlling the operation of the laminating machine, so as to reduce the loss of human participation affecting the operation and material costs;

[0047] 4. In the present invention, a PLC controller is configured to carry the control chip and provide installation positions for components to realize an integrated control system, and the integrated control system is used to reduce the overall size of the controller; and an auxiliary heat dissipation component is configured to reduce the influence of the working temperature on the laminating machine.

[0048] 5. In the present invention, by setting a temperature sensor and an alarm component, the temperature condition of the laminating machine during operation can be detected and judged, so that when the temperature fluctuates greatly, the alarm component can be used to remind the staff to make adjustments, thereby improving the safety factor and service life of the laminating machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a structural block diagram of an intelligent laminating machine control system;

[0050] Figure 2 It is a unit framework diagram of an intelligent laminating machine control system;

[0051] Figure 3 It is a structural circuit diagram of an intelligent laminating machine control system;

[0052] Figure 4 It is a three-dimensional structural schematic diagram of an intelligent laminating machine control system;

[0053] Figure 5 It is a control operation flow chart of an intelligent laminating machine control system;

[0054] In the figure, 1 PLC controller, 2 touch screen, 3 control knob, 4 feed port, 5 FGPA universal chip, 6 communication interface, 7 external device interface, 8 temperature sensor, 801 temperature sensitive element, 9 visual sensor, 901 photosensitive element, 10 alarm, 11 solenoid valve, 12 electric control switch, 13 cooling fan, 14 power distribution circuit, 15 protection resistor, 16 isolation transformer, 17 weighing sensor, 18 temperature transmitter. Specific implementation plan

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0056] like Figure 1 - Figure 5 As shown, an intelligent laminating machine control system includes:

[0057] The PLC controller 1 is used to provide an installation location for the FGPA universal chip 5, the parameter setting module, the external operation module and the power configuration module; the PLC controller 1 is configured and installed by connecting the laminating machine and the control system to the laminating machine;

[0058] FGPA universal chip 5, used to configure the laminating operation scheme through internal algorithm and connection interactive execution module; the FGPA universal chip 5 configures the operation scheme to the interactive execution module by reading the operation and configuration algorithm performed by the parameter setting module and the external operation module;

[0059] A parameter setting module is used to configure the model parameters of the FGPA universal chip and the laminating machine; the parameter setting module sets and adjusts the operating parameters of the laminating machine by reading the operating data of the external operating module and adding raw material debugging;

[0060] An external operation module is used to provide an operation and control window for the staff or maintenance personnel; the external operation module senses the operation performed by the staff through the touch screen component, so as to control the control system according to the information transmitted by the touch screen component;

[0061] The monitoring and protection module is used to detect various characteristic values ​​of the laminating machine in the working state and determine whether there is any abnormality; the monitoring and protection module monitors the operating status of the laminating machine and collects parameters through sensor components and alarm components to determine whether there is any abnormality or failure in the laminating machine;

[0062] The interactive execution module is used to guide and control the various execution components of the laminating machine to perform laminating work; the interactive execution module reads the operation scheme from the FGPA universal chip 5 to guide and control the working components of the laminating machine to perform specific operations according to the operation scheme to achieve normal operation of the laminating machine;

[0063] A power configuration module, used to connect the PLC controller 1, the FGPA universal chip 5, the parameter setting module and the external operation module to provide power configuration and circuit control. The power configuration module provides operating power to the PLC controller 1, the FGPA universal chip 5, the parameter setting module and the external operation module by connecting a DC power supply;

[0064] Among them, the PLC controller 1 is fixedly installed in the controller installation area of ​​the intelligent laminating machine by screws, the FGPA universal chip 5 is arranged inside the PLC controller 1, the parameter setting module, the external operation module, the monitoring and protection module and the power supply configuration module are arranged on the outside of the PLC controller 1, the parameter setting module is electrically connected to the external operation module and the FGPA universal chip 5, the FGPA universal chip 5 is electrically connected to the monitoring and protection module, the interactive execution module and the external operation module, the interactive execution module is arranged on the execution component of the laminating machine, the power supply configuration module is electrically connected to the DC power supply, and the parameter setting module, the external operation module and the monitoring and protection module are electrically connected to the power supply configuration module.

[0065] In the above embodiment: the parameter setting module realizes model training using raw materials and information communication using the communication interface 6 through the model training unit and the communication receiving unit; the parameter setting module includes a material guiding unit, a model training unit and a communication receiving unit; the material guiding unit realizes guiding the raw materials therein into the specified position through the feed port 4 to realize providing raw materials for the model training unit; the model training unit realizes training of an adjustable control model according to the configured raw materials through a preset online learning algorithm to realize configuring the control model to the FGPA universal chip 5; the communication receiving unit realizes information communication between the control system and the external components through the communication interface 6; the communication receiving unit connects the control system and the external components, and the external interface of the communication interface 6 is arranged on the PLC controller 1.

[0066] In a specific embodiment: the parameter setting module is used to input the parameters required for control by the control system. In this scheme, the coating sample is placed in the feed port 4 as a raw material. After the coating sample enters the PLC controller 1, the model training unit extracts features of the coating sample. The model training unit performs model training of the online learning model through the extracted features to obtain the control model, and configures the control model to the FGPA universal chip to realize process control of the material to be coated in the laminating machine; in one embodiment, the parameter setting module is connected to an external computer through a communication interface 6, and the coating parameters are freely configured to the FGPA universal chip through a parameter input program preset by the computer.

[0067] In the above embodiment: the model training unit performs feature extraction and identification on the raw material through the feature extraction algorithm to obtain the feature parameters of the coated sample, and trains the operation model corresponding to the feature parameters through the feature parameters and the SL online learning algorithm, and outputs the operation model to the FGPA universal chip 5; the feature extraction algorithm realizes feature extraction of the raw material through component analysis and feature identification, and the feature extraction algorithm realizes feature extraction through the feature extraction formula, and the expression of the feature extraction formula is:

[0068]

[0069] In the above formula (1), n ​​represents the number of extracted features, which is used to calculate the number of features to be extracted; θ represents the deviation threshold, which represents the deviation angle of the feature coordinates; i represents the cycle feature parameter, which indicates that the current cycle is the i-th cycle; ω represents the deviation weight, which represents the specific deviation value of the feature to be identified in the coordinate system; x represents the sample data, which is used to represent the input feature to be extracted; y represents the activation function parameter, which is used to represent the parameter of the desired feature;

[0070] The SL online learning algorithm realizes real-time and rapid feedback adjustment model adjustment through online feedback data and training of each sample, and performs high-density screening and high-efficiency recognition on the data passing through the model; the training process of the feedback adjustment model: first, set the learning rate and regularization parameter values ​​of the model; second, set the number of parallel learning of the model; third, continuously fill the data into the data pool; fourth, at the same time, different parallel lines will take data from the data pool for training; finally, after the data is captured, the models of different lines are merged and saved; the online learning algorithm realizes online learning and training models through the online learning formula, and the expression of the online learning formula is:

[0071] ω t＝1,i =-(z t,i -sgn(z t,i )-λ1) / (λ2+σ 1:t) (2)

[0072] In formula (2), i is a feature parameter, which is used to indicate the input feature that needs to be trained; t is an iteration parameter, which indicates that the current process is the i-th iteration; λ1 and λ2 are feature values, which are used to increase the position weight of the parameter in the algorithm; σ 1:t Indicates the discrete degree of the gradient parameter, and is used as an intermediate quantity to calculate the discrete degree of the gradient parameter; z t 、z t,i is a custom intermediate variable, the z t 、z t,i The expression is:

[0073]

[0074] In formulas (3) and (4), σ s Indicates the discrete degree of the parameters in the algorithm, and is used as an intermediate quantity to calculate the discrete degree of the algorithm parameters; g 1:t It is the cumulative gradient of the algorithm from round 1 to round t, which is used to calculate the number of iterations of the algorithm.

[0075] In a specific embodiment: the online learning algorithm runs the following code:

[0076]

[0077]

[0078]

[0079] In the above algorithm, parameter f is the iterative sample; parameter wzn is an empty container to retain the intermediate parameters; the [val alpha: Double = 0.5] [val belta: Double = 1.0] [val lambda1: Double = 1.0] [vallambda2: Double = 0] are four representative hyperparameters. t.i There is a cumulative characteristic; in the specific implementation, the data comparison table of the online learning and the traditional algorithm is shown in the table:

[0080] Table 1 Data comparison between online learning algorithm and traditional algorithm

[0081] Comparative Data Online Learning Algorithms Traditional Algorithms Input speed 12 1 Training speed 4 1 Model performance 4 1 Modifiability Modifiable parameters Unmodifiable Parallel number 4 1

[0082] In the above embodiment: the external operation module controls the laminating machine through the touch screen component and the control knob component, and the external operation module connects to the external device through the external device interface 7 to assist in controlling the laminating machine; the external operation module includes a touch screen component, a control knob component and an external device interface 7; the touch screen component reads the operation performed on the surface of the touch screen 2 through the touch screen 2 and the pressure sensor, so as to control the corresponding components to respond according to the operation; the control knob component controls the working state of the PLC controller through the control knob 3 and the internal switch, so as to control the working state of the laminating machine; the external device interface 7 reads the information transmitted by the device connected to the external device interface 7 through the interface protocol and the data reading chip, so as to assist in parameter adjustment, fault detection and model configuration of the control system through the external device.

[0083] In a specific embodiment: the external operation module realizes the recognition, reading and transmission of operation data of the surface operation to the FGPA universal chip 5 by installing a touch screen 2; the external operation module realizes manual control of the process and power distribution of the laminating machine by installing a control knob 3 with multiple gears. In this embodiment, the control knob 3 is provided with seven gears, namely, power-off gear, loading gear, unloading gear, model configuration gear, trial operation gear, working gear and maintenance gear; in this embodiment, a snap-fit ​​part is provided inside the control knob 3 to ensure that the gear of the control knob 3 is clear, so as to improve the reliability of the control of the control knob 3; the external operation module realizes the control system's permission to connect to external devices by installing an external device interface 7 electrically connected to the FGPA universal chip. In a specific implementation scheme, the control system is connected to a group of automatic maintenance devices with established technology through the external device interface 7, so as to realize the control system adding an automatic maintenance function.

[0084] In the above embodiment: the monitoring and protection module monitors the working state of the laminating machine through the temperature sensor 8 and the visual sensor 9, and the monitoring and protection module cuts off the circuit and issues an alarm through the solenoid valve 11 and the alarm 10 to realize a protection control system; the monitoring and protection module includes a temperature sensor 8, a visual sensor 9, a solenoid valve 11 and an alarm 10, and the temperature sensor 8 detects the working temperature of the laminating machine through the temperature-sensitive element 801 and outputs the temperature information to the FGPA universal chip 5 for further processing; the visual sensor 9 collects the working image of the laminating machine through the photosensitive element 901 and outputs the image information to the FGPA universal chip 5 for further processing and analysis; the solenoid valve 11 and the alarm 10 cut off the circuit and issue an alarm by reading the detection report and processing method output by the FGPA universal chip to realize a protection control system.

[0085] In a specific embodiment: the temperature sensor 8 detects the temperature of the working area of ​​the laminating machine through the temperature sensitive element 801, and the temperature sensor 8 transmits the temperature information to the FGPA universal chip through the temperature transmitter 18 to judge the working temperature, so as to protect the working area from overheating; the visual sensor 9 detects the image of the working area of ​​the laminating machine through the photosensitive element 901 and transmits the image information to the FGPA universal chip to judge the working state, so as to prevent the workbench from being damaged in the working area and affecting the laminating process; when the temperature information output by the temperature sensor 8 or the image information output by the visual sensor 9 When the information is judged to be faulty, the FGPA universal chip 5 configures the processing plan to the monitoring and protection module, the monitoring and protection module reads the processing plan through the plan reading method, controls the solenoid valve 11 to cut off the power distribution circuit 14 and controls the alarm 10 to sound an alarm, so as to cut off the operating power of the interactive execution module, force the laminating machine to stop working and remind the staff to pay attention to the abnormal state; after the working parameters in the working area are restored to normal, the FGPA universal chip 5 controls the configuration of the stop processing plan, and after the monitoring and protection module fails to read the processing plan, the monitoring and protection module controls the solenoid valve 11 to close and the alarm 10 to stop output, and continues the laminating work.

[0086] In the above embodiment: the interactive execution module realizes information exchange between the FGPA universal chip 5 and the execution component of the laminating machine by connecting the FGPA universal chip 5 and the execution component of the laminating machine, so as to realize the operation scheme that the FGPA universal chip 5 adjusts the output according to the working state; the interactive execution module includes an isolation transformer unit, a temperature transmitter unit, a weight transmitter unit, a rubber roller drive unit, an electric control heating unit and an auxiliary heat dissipation unit; the isolation transformer unit realizes isolation of the current of the winding coil by controlling the isolation transformer 16; the temperature transmitter unit realizes measurement of the temperature transmitter 18 by measuring the temperature of the winding coil; the temperature transmitter unit realizes measurement of the temperature of the winding coil by controlling the isolation transformer 16 ... The sensor signal of the temperature sensor 8 in the monitoring protection module; the weight transmitter unit converts the sensor signal of the weighing sensor through the weighing sensor 17 to output a standard industrial signal; the rubber roller driving unit controls the operation, stop and speed of the rubber roller by connecting to the rubber roller in the laminating machine executive component; the electric control heating unit configures the working temperature of the laminating machine by connecting to the heating roller in the laminating machine executive component; the auxiliary heat dissipation unit quickly reduces the heat of the workbench and the operating temperature of the control circuit in the control system after the laminating machine is completed by arranging a heat dissipation fan 13 and dry ice inside.

[0087] In a specific embodiment: the isolation transformer unit is connected to the isolation transformer 16 to isolate the operating current of the two sets of winding coils, so as to configure, adjust and protect the interactive execution module and the operating circuit connected to the interactive execution module; the temperature transmitter unit is connected to the temperature transmitter 18 and the temperature sensor 8 to detect the temperature of the working area of ​​the laminating machine, so as to prevent the abnormal situation of drastic temperature changes and excessively high or low temperatures in the working area of ​​the laminating machine, so as to improve the safety and stability of the laminating machine; the weight transmitter unit is connected to the weighing sensor 17 to detect the weight of the material to be coated in the working area of ​​the laminating machine, so as to prevent the working area of ​​the laminating machine from exceeding the load-bearing weight. Phenomenon, so as to improve the stability, reliability and service life of the laminating machine; the rubber roller driving unit is connected to the rubber roller to configure various parameters of the rubber roller rotation, so as to control the rubber roller in the laminating machine execution component through the control system, so as to integrate various parameters of the laminating machine operation into the control system, and improve the working efficiency of the laminating machine and the control effect of the control system through the integrated circuit; the electric control heating unit is connected to the heating roller to control the heating temperature of the heating roller, so as to control the heating roller in the laminating machine execution component through the control system; the auxiliary heat dissipation component is connected to the heat dissipation fan 13 to realize natural heat dissipation of the working area of ​​the auxiliary laminating machine, so as to improve the working efficiency and service life of the laminating machine.

[0088] In the above embodiment: the power configuration module configures the operating power for the control system through the electric control switch 12 and the distribution component, and the power configuration module protects the distribution circuit 14 through the circuit protection unit to prevent the circuit from overloading; the power configuration module includes the electric control switch 12, the distribution component and the circuit protection unit; the electric control switch 12 adjusts the operating power of the control system by closing or cutting off the distribution circuit; the distribution component configures the current output of different flow rates to different circuits through the distributor and the parameter setting module, the external operation module and the monitoring and protection module respectively; the circuit protection unit protects the distribution circuit 14 in the distribution circuit 14 by connecting the protection resistor 15 to prevent the distribution circuit 14 from overheating and overloading.

[0089] In a specific embodiment: the power configuration module is implemented as a control system to configure operating power and protect the distribution circuit 12. In this solution, the power configuration connected to the power configuration module is a DC power supply of 48V or above. The model of the electric control switch 12 is a 4V210-06 electromagnetic switch. The 4V210-06 electromagnetic switch has the advantages of small size, long service life, attached manual operation device and easy installation; the protection resistor 15 adopts a selective circuit breaker. Compared with the manual circuit breaker, the selective circuit breaker has more selectivity, stronger current limiting and breaking capacity, multiple protection methods and intelligence. In addition to the protection function, the selective circuit breaker has power measurement, fault recording, and communication interface to realize the function of centralized monitoring and management of distribution devices and systems.

[0090] In the above embodiment: the FGPA universal chip 5 is pre-installed with a proportional fairness algorithm for resource allocation, a feature extraction algorithm for feature identification, a model reading method for reading the operation model and a solution database; the proportional fairness algorithm is used to complete the fair allocation of the execution solutions configured in the solution database according to the fair allocation formula and output the execution solutions to the interactive execution module; the feature extraction algorithm uses the feature extraction formula to identify the features of the objects to be coated in the laminating machine, and extracts the corresponding solutions in the solution database according to the type and quantity of the features; the model reading method is used to read the operation model output by the parameter setting module, and extract the specific solutions in the solution database according to the operation model; the solution database is internally configured with operation solutions classified according to the feature type and feature quantity, and the solution database implements the feature extraction algorithm through an open source interface to extract the specific operation solutions inside the solution database.

[0091] In a specific embodiment: the FGPA universal chip 5 implements fair distribution of the schemes configured in the scheme database through a proportional disclosure algorithm, so as to implement fair distribution of operation schemes to each component of the interactive execution module; the FGPA universal chip 5 implements feature extraction of the image information of the visual sensor 9 through a feature extraction algorithm, so as to determine whether suspected fault information appears in the image information; the FGPA universal chip 5 implements feature extraction and judgment of the material to be coated through a feature extraction algorithm, so as to extract the type characteristics of the material to be coated, and configures the material to be coated with the operation scheme corresponding to the type of the characteristic by extracting the type characteristics of the material to be coated and the scheme database; the FGPA universal chip 5 implements reading the control model from the parameter setting module through a model reading method, so as to implement control operations according to the control model; a large number of operation schemes classified by type and feature are installed inside the scheme database.

[0092] In the above embodiment: the proportional fairness algorithm realizes the configuration of the same equivalent of resources to each component of the interactive execution module by utilizing the time-frequency characteristics of the channel; the proportional fairness algorithm realizes the fair allocation of resources through the fair allocation formula, and the expression of the fair allocation formula is:

[0093]

[0094] In formula (5), K represents the equivalent of resource output after allocation, which is used to represent the parameters of the required resources, i represents the individual to be allocated in the algorithm, which is used to represent that the resources need to be allocated to i components for operation, n represents the last individual to be allocated, which is used to represent that the allocation of resources stops after being allocated to the nth individual, r represents the timely rate of resource allocation, which is used to calculate the efficiency of resource allocation and the time x of resource allocation, R represents the average rate of resource allocation, which is used to calculate the total time required for resource allocation, and x is used to represent the time used for the allocated resources, which is used to calculate the efficiency of resource allocation.

[0095]

[0096] In formula (6), x v Indicates the update time parameter, which is used to represent how long the average rate includes the condition information in the past.

[0097] In a specific embodiment: the proportional public algorithm is to achieve a compromise between throughput and fairness. In one embodiment, according to the proportional fairness algorithm, in a multi-user cell, a user cannot always be scheduled to communicate. This is because if the user is always communicating, it will lead to

[0098] The average rate R of resource allocation keeps increasing. According to the fair allocation formula of the proportional fairness algorithm, the priority of users who have been communicating will continue to decrease as the average rate R increases, until the users who have been communicating at a certain moment will not be able to obtain the resource scheduling of the algorithm. Users closer to the base station will have a relatively large resource allocation and timely rate r due to better channel conditions. It can be seen from the fair allocation formula that the resource equivalent obtained by the user in the initial trial time is large; users farther away from the base station have poor channel conditions, and the resource equivalent obtained in the initial time is small and will not be scheduled for a long time. Since the user is not scheduled for a long time, the average transmission rate R of the user will gradually decrease. At this time, according to the fair allocation formula, it can be seen that the resources K obtained by users far away from the base station will increase again. When K increases to a certain extent, the user repeats the allocation process of the user who has been communicating; the proportional fairness algorithm combines the respective advantages of the maximum carrier-to-interference ratio algorithm and the polling scheduling algorithm, and achieves a compromise between fairness between users and system throughput; in specific implementation, the data comparison table of the proportional public algorithm and the traditional algorithm is shown in the table:

[0099] Table 2 Data comparison between the proportional disclosure algorithm and the traditional algorithm

[0100]

[0101] A specific implementation plan of an intelligent laminating machine control system is as follows: configure a power line and a DC power supply to the power configuration module, the power configuration module configures the operating power to each component of the control system through the power distribution circuit 14, press the corresponding position of the touch screen 2 or turn the control knob 3 to the feeding gear, the door of the feed port 4 is opened, put the laminating sample into the feed port 4, press the corresponding position of the touch screen 2 or turn the control knob 3 to the model configuration gear, the door of the feed port 4 is closed, the model training unit in the parameter setting module extracts features of the laminating sample to obtain a control model, the model training unit outputs the control model to the FGPA universal chip 5, and the touch screen 2 displays the model configuration. After the completion of the configuration, press the touch screen 2 The corresponding position or the control knob 3 is turned to the material return position, the door of the feed port 4 is opened, the film sample is taken out and the door of the feed port 4 is closed, the corresponding position of the touch screen 2 is pressed or the control knob 3 is turned to the test run position, the FGPA universal chip 5 controls the isolation transformer 16 and the temperature transmitter 18 in the interactive execution module, and the basic environment of the film coating work is detected through the temperature sensor 8 and the weighing sensor 17, the FGPA universal chip 5 processes the output result and outputs the detection result to the touch screen 2, after determining that there is no problem with the detection result displayed on the touch screen 2, place the material to be coated in the working area of ​​the laminating machine, press the corresponding position of the touch screen 2 or turn the control knob 3 to the running position, the power distribution circuit 1 4 is configured with operating power for the interactive execution module, the FGPA universal chip 5 is configured with the interactive execution module of the operation scheme, the interactive execution module reads the operation scheme through the scheme reading method, and controls the corresponding components to work, after reading the operation scheme, the interactive execution module controls the auxiliary heat dissipation unit to perform auxiliary heat dissipation and monitors the working state in real time through the temperature sensor 8 and the weighing sensor 17, when the temperature or weight of the working area exceeds the appropriate working range, the FGPA universal chip outputs the processing scheme to the monitoring and protection module, the monitoring and protection module reads the processing scheme through the scheme reading method and controls the solenoid valve 11 to cut off the power distribution circuit 14, so as to cut off the operating power of the interactive execution module and force the laminating machine to stop. working state, and at the same time, the monitoring and protection module controls the alarm 10 to sound an alarm to remind the staff to pay attention to the abnormal state; the interactive execution module continuously monitors the temperature and weight of the working area, and after the working parameters of the working area are restored to normal, the interactive execution module outputs a signal to continue working to the FGPA universal chip 5, and the FGPA universal chip reads the signal and controls the output of the stop processing solution. After failing to read the processing solution, the monitoring and protection module controls the solenoid valve 11 to close and the alarm 10 to stop output, and continues the laminating work; after the laminating process is completed, the connection between the power configuration module and the DC power supply is cut off, and the control knob is turned to the power-off position to control the laminating machine to enter the stop working state.

[0102] It should be noted that the above embodiments illustrate the present invention rather than limit it, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be construed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising a number of different elements and by means of a suitably programmed computer. In a unit claim enumerating a number of means, several of these means may be embodied by the same hardware item. The use of the words first, second and third, etc., does not indicate any order. These words may be interpreted as names.

[0103] Specific examples are used herein to illustrate the principles and implementation methods of the present application, and the description of the above embodiments is only used to help understand the method and core ideas of the present application. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present application, several improvements and modifications can be made to the present application, and these improvements and modifications also fall within the scope of protection of the claims of the present application.

Claims

1. An intelligent laminating machine control system, characterized in that: include: A PLC controller (1) is used to provide an installation location for the FGPA universal chip (5), the parameter setting module, the external operation module and the power configuration module; the PLC controller (1) is configured and installed by connecting the laminating machine and the control system to the laminating machine; The FGPA universal chip (5) is used to configure a laminating operation plan through an internal algorithm and a connection interactive execution module; the FGPA universal chip (5) configures the operation plan to the interactive execution module by reading the operations performed by the parameter setting module and the external operation module and the configuration algorithm; A parameter setting module is used to configure the model parameters of the FGPA universal chip and the laminating machine; the parameter setting module sets and adjusts the operating parameters of the laminating machine by reading the operating data of the external operating module and adding raw material debugging; An external operation module is used to provide an operation and control window for the staff or maintenance personnel; the external operation module senses the operation performed by the staff through the touch screen component, so as to control the control system according to the information transmitted by the touch screen component; The monitoring and protection module is used to detect various characteristic values ​​of the laminating machine in working state and determine whether there is any abnormality; The monitoring and protection module monitors the operating status of the laminating machine and collects parameters through sensor components and alarm components to determine whether the laminating machine is abnormal or faulty; An interactive execution module is used to guide and control the various execution components of the laminating machine to perform laminating operations; the interactive execution module reads the operation plan from the FGPA universal chip (5) to guide and control the working components of the laminating machine to perform specific operations according to the operation plan, so as to achieve normal operation of the laminating machine; A power configuration module, used to connect the PLC controller (1), the FGPA universal chip (5), the parameter setting module and the external operation module to provide power configuration and circuit control, wherein the power configuration module is connected to a DC power supply to provide operating power to the PLC controller (1), the FGPA universal chip (5), the parameter setting module and the external operation module; The PLC controller (1) is fixedly mounted on the controller mounting area of ​​the intelligent laminating machine by means of screws, the FGPA universal chip (5) is arranged inside the PLC controller (1), the parameter setting module, the external operation module, the monitoring and protection module and the power configuration module are arranged outside the PLC controller (1), the parameter setting module is electrically connected to the external operation module and the FGPA universal chip (5), the FGPA universal chip (5) is electrically connected to the monitoring and protection module, the interactive execution module and the external operation module, the interactive execution module is arranged on the execution component of the laminating machine, the power configuration module is electrically connected to the DC power supply, and the parameter setting module, the external operation module and the monitoring and protection module are electrically connected to the power configuration module; The parameter setting module uses the raw materials for model training and uses the communication interface (6) for information communication through the model training unit and the communication receiving unit; the parameter setting module includes a material guiding unit, a model training unit and a communication receiving unit; the material guiding unit guides the raw materials therein into a designated position through the feed port (4) to provide the raw materials for the model training unit; the model training unit trains an adjustable control model according to the configured raw materials through a preset online learning algorithm to configure the control model to the FGPA universal chip (5); the communication receiving unit uses the communication interface (6) to communicate information between the control system and the external components; the communication receiving unit connects the control system and the external components, and the external interface of the communication interface (6) is arranged on the PLC controller (1); The model training unit performs feature extraction and identification on the raw material through a feature extraction algorithm to obtain feature parameters of the coated sample, and trains an operation model corresponding to the feature parameters through the feature parameters and the SL online learning algorithm, and outputs the operation model to the FGPA universal chip (5); the feature extraction algorithm realizes feature extraction and identification of the raw material through component analysis and feature identification, and the feature extraction algorithm realizes feature extraction and identification through a feature extraction formula, and the expression of the feature extraction formula is: （1） In the above formula (1), n ​​represents the number of extracted features, which is used to calculate the number of features to be extracted; θ represents the deviation threshold, which represents the deviation angle of the feature coordinates; i represents the cycle feature parameter, which indicates that the current cycle is the i-th cycle; ω represents the deviation weight, which represents the specific deviation value of the feature to be identified in the coordinate system; x represents the sample data, which is used to represent the input feature to be extracted; y represents the activation function parameter, which is used to represent the parameter of the feature to be found; The SL online learning algorithm realizes real-time and rapid feedback adjustment model adjustment through online feedback data and training of each sample, and performs high-density screening and high-efficiency recognition on the data passing through the model; the training process of the feedback adjustment model: first, set the learning rate and regularization parameter values ​​of the model; second, set the number of parallel learning of the model; third, continuously fill the data into the data pool; fourth, at the same time, different parallel lines will take data from the data pool for training; finally, after the data is captured, the models of different lines are merged and saved; the online learning algorithm realizes online learning and training models through the online learning formula, and the expression of the online learning formula is: oh t=1,i =- (2) In formula (2), i is a feature parameter, which is used to indicate the input feature that needs to be trained; t is an iteration parameter, which indicates that the current process is the i-th iteration; is the eigenvalue, which is used to increase the position weight of the parameter in the algorithm; Indicates the discrete degree of the gradient parameter, and is used as an intermediate quantity to calculate the discrete degree of the gradient parameter; For custom intermediate variables, The expression is: （3） （4） In formulas (3) and (4), Indicates the discrete degree of the parameters in the algorithm and is used as an intermediate quantity to calculate the discrete degree of the algorithm parameters; It is the cumulative gradient of the algorithm from round 1 to round t, which is used to calculate the number of iterations of the algorithm.

2. The intelligent laminating machine control system according to claim 1, characterized in that: The external operation module controls the laminating machine through a touch screen component and a control knob component, and the external operation module connects to an external device through an external device interface (7) to assist in controlling the laminating machine. The external operation module comprises a touch screen component, a control knob component and an external device interface (7). The touch screen component reads the operation performed on the surface of the touch screen (2) through a touch screen (2) and a pressure sensor, so as to control the corresponding components to respond according to the operation. The control knob component controls the working state of the PLC controller through a control knob (3) and an internal switch, so as to control the working state of the laminating machine. The external device interface (7) reads information transmitted by a device connected to the external device interface (7) through an interface protocol and a data reading chip, so as to assist in parameter adjustment, fault detection and model configuration of the control system through an external device.

3. The intelligent laminating machine control system according to claim 1, characterized in that: The monitoring and protection module monitors the working state of the laminating machine through a temperature sensor (8) and a visual sensor (9), and cuts off the circuit and issues an alarm through a solenoid valve (11) and an alarm (10) to realize a protection control system; the monitoring and protection module comprises a temperature sensor (8), a visual sensor (9), a solenoid valve (11) and an alarm (10); the temperature sensor (8) detects the working temperature of the laminating machine through a temperature-sensitive element (801) and outputs the temperature information to the FGPA universal chip (5) for further processing; the visual sensor (9) collects the working image of the laminating machine through a photosensitive element (901) and outputs the image information to the FGPA universal chip (5) for further processing and analysis; the solenoid valve (11) and the alarm (10) cut off the circuit and issue an alarm by reading the detection report and processing method output by the FGPA universal chip to realize a protection control system.

4. The intelligent laminating machine control system according to claim 1, characterized in that: The interactive execution module connects the FGPA universal chip (5) and the execution component of the laminating machine to realize information exchange between the FGPA universal chip (5) and the execution component of the laminating machine, so as to realize the operation scheme of the FGPA universal chip (5) adjusting the output according to the working state; the interactive execution module comprises an isolation transformer unit, a temperature transmitter unit, a weight transmitter unit, a rubber roller drive unit, an electric control heating unit and an auxiliary heat dissipation unit; the isolation transformer unit realizes isolation of the current of the winding coil by controlling the isolation transformer (16); the temperature transmitter unit realizes measurement of the monitoring temperature by a temperature transmitter (18). The sensor signal of the temperature sensor (8) in the protection module; the weight transmitter unit converts the sensor signal of the weighing sensor through the weighing sensor (17) to output a standard industrial signal; the rubber roller drive unit controls the operation, stop and speed of the rubber roller by connecting to the rubber roller in the laminating machine execution component; the electric control heating unit configures the working temperature of the laminating machine by connecting to the heating roller in the laminating machine execution component; the auxiliary heat dissipation unit quickly reduces the heat of the workbench and reduces the operating temperature of the control circuit in the control system after the laminating machine is completed by arranging a heat dissipation fan (13) and dry ice inside.

5. The intelligent laminating machine control system according to claim 1, characterized in that: The power configuration module configures operating power for the control system through an electric control switch (12) and a power distribution component, and the power configuration module protects the power distribution circuit (14) through a circuit protection unit to prevent circuit overload; the power configuration module comprises an electric control switch (12), a power distribution component and a circuit protection unit; the electric control switch (12) adjusts the operating power of the control system by closing or disconnecting the power distribution circuit; the power distribution component configures current outputs of different flows to different circuits through a power distributor and respectively connecting the parameter setting module, the external operation module and the monitoring protection module; the circuit protection unit protects the power distribution circuit (14) in the power distribution circuit (14) by connecting a protection resistor (15) to prevent the power distribution circuit (14) from overheating or overloading.

6. The intelligent laminating machine control system according to claim 1, characterized in that: The FGPA universal chip (5) is pre-installed with a proportional fairness algorithm for resource allocation, a feature extraction algorithm for feature recognition, a model reading method for reading an operation model, and a solution database; the proportional fairness algorithm is used to complete fair allocation of execution solutions configured in the solution database according to a fair allocation formula and output the execution solutions to the interactive execution module; the feature extraction algorithm recognizes the features of the object to be coated in the laminating machine through the feature extraction formula, and extracts the corresponding solutions in the solution database according to the type and quantity of the features; the model reading method is used to read the operation model output by the parameter setting module, and extracts the specific solutions in the solution database according to the operation model; the solution database is configured with operation solutions classified according to the feature type and feature quantity, and the solution database realizes that the feature extraction algorithm can extract the specific operation solutions in the solution database through an open source interface.

7. The intelligent laminating machine control system according to claim 6, characterized in that: The proportional fairness algorithm realizes the configuration of the same equivalent of resources to each component of the interactive execution module by utilizing the time-frequency characteristics of the channel; the proportional fairness algorithm realizes the fair allocation of resources through a fair allocation formula, and the expression of the fair allocation formula is: （5） In formula (5), K represents the equivalent of resource output after allocation, which is used to represent the parameters of the required resources, i represents the individual to be allocated in the algorithm, which is used to represent that the resources need to be allocated to i components for operation, n represents the last individual to be allocated, which is used to represent that the allocation of resources stops after being allocated to the nth individual, r represents the timely rate of resource allocation, which is used to calculate the efficiency of resource allocation and the time x of resource allocation, R represents the average rate of resource allocation, which is used to calculate the total time required for resource allocation, and x is used to represent the time used for the allocated resources, which is used to calculate the efficiency of resource allocation. （6） In formula (6), Indicates the update time parameter, which is used to indicate how long the average rate includes the condition information in the past.

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