A tension control system for tight-buffered optical cable production line based on digital twin

Abstract

The present invention discloses a tension control system for a tight-buffered optical cable production line based on digital twins, which is mainly composed of a physical world of a production line, a digital twin world of a production line, and data between the two. The physical equipment of the production line mainly collects state data and environmental data of the production process, and sends these data to a host computer. The digital twin world of the production line establishes a visual geometric model based on three-dimensional software, and the data of the physical world is integrated with the physical model and tension control model of the twin world to present a twin world corresponding to the physical world. Through the real-time tension data collected by the industrial computer in the physical world, simulation calculations are performed in the twin world to determine the optimal PID control parameters, and the data is stored in a database for easy viewing of historical data. The present invention realizes optimal control of tension under the premise of ensuring safe production through digital twin technology, performs visual monitoring of production equipment, offline simulation and other functions, and finally achieves the effect of virtual-real fusion.

Description

Technical Field

[0001] The present invention relates to the field of intelligent manufacturing of optical cables, and in particular to a tension control system of a tight-buffered optical cable production line based on digital twins. Background Art

[0002] Optical cables are the cornerstone of the development of the communications and Internet industries. The cable industry represented by optical cables is the second largest manufacturing industry in China after the automotive industry, with a product variety satisfaction rate and market share exceeding 90%. Tight-wrapping is to add a very thin sheath to the outer layer of the optical fiber for protection to prevent the internal optical fiber from being affected by external mechanical, thermal, chemical and moisture. In all the process flows of producing indoor optical cables, the production of tight-wrapped optical fibers is an indispensable process. There are two main problems in the production of this production line: (1) The optical fiber inside the tight-wrapped optical fiber is easy to break; (2) The optical fiber loss of optical cables produced by the same process on the same production line is also different. Through the analysis of the equipment, process flow and optical cables of the production line, the poor tension control of the tight-wrapped optical fiber pay-off device is the key cause of the above problems. Therefore, it is very meaningful and necessary to achieve optimal tension control under the premise of ensuring safe production, so that the tension is always kept within a reasonable range, thereby improving the product quality and qualified rate of optical cables. Summary of the invention

[0003] In view of the above problems, the purpose of the present invention is to provide a tight-buffered optical cable production line tension control system based on digital twin to control the tension of the production line. On the basis of not changing the hardware equipment of the actual production line control system as much as possible, the automation level of the production line is improved, the real-time optimal control of the tension is achieved, the production cost is reduced, and the quality of the product is improved.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is:

[0005] A tension control method for a tight-buffered optical cable production line based on digital twin, the method comprising the following steps:

[0006] Step 1: Based on the actual production equipment of the tension control system in the physical workshop, use 3dsmax to establish the geometric model of the twin model.

[0007] Step 2: Use the multiverse optimization algorithm to optimize the parameters of the PID controller for tension control and establish the control model of the system, specifically:

[0008] (1) Initialize a multiverse population:

[0009]

[0010] (2) Set the WEP parameter min=0.2, WEPmax=1, p=6, L=200 and related variables (n, d, l); where WEP represents the probability of the existence of wormholes in the multiverse space, TDR represents the step size of the object moving towards the current optimal universe, p represents the exploitation degree, and L is the maximum number of iterations.

[0011] (3) The evaluation function is determined based on the combination of PID parameters (overshoot, adjustment time, peak value, etc.). For the sake of simplicity of calculation, the adjustment time ts and overshoot σ are selected as the comparison basis, and the evaluation function is defined as:

[0012]

[0013] (4) Update WEP and TDR according to formula (③(④); Execute roulette mechanism according to formula (⑤;

[0014]

[0015] (5) Calculate the updated optimal universe according to formula ⑥. If it is better than the current optimal universe, replace it; otherwise, retain the current optimal universe.

[0016]

[0017] Where r1, r2, r3, and r4 are random numbers in the range [0,1].

[0018] (6) Assign the parameters of each universe to the proportional coefficient, integral coefficient and differential parameter in the PID controller to obtain the corresponding error performance index, and continuously iterate the universe. Finally, select the particle with the smallest error performance index in the universe as the optimal universe, and assign the parameters of the optimal universe to the proportional coefficient, integral coefficient and differential parameter in the PID controller.

[0019] Step 3: Generate the twin geometry model file in .fbx format and import it into Unity3d. Use Unity to build a virtual scene and integrate the mathematical model with the control model. Use the life cycle of the script to control the behavior of the model in the virtual world. Map the twin data to the virtual environment to synchronize the virtual environment with the physical environment.

[0020] Step 4: When there is inconsistency between the actual production process and the simulation process, the three parameters of the PID controller are re-optimized, and instructions are sent to the industrial computer in the physical world through the twin platform to regulate the physical equipment, thereby achieving synchronization and two-way optimization between the model and the physical equipment.

[0021] The beneficial effects of the present invention are embodied in:

[0022] The present invention utilizes digital twin technology and combines the multiverse optimization algorithm with the PID controller to effectively solve the problem of poor tension control due to the continuous change of system inertia during the winding process. By establishing a digital twin model, not only can the real-time control of tension in the actual production process be achieved, the PID parameters can be adaptively changed online as the system working conditions change, and the tension control system has real-time adjustment and high control accuracy. In addition, through the established geometric model, three-dimensional visual real-time monitoring can be achieved, and virtual simulation functions can also be realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is the framework diagram of the digital twin tension control system of the present invention

[0024] Figure 2 This is the physical world hardware diagram of the tension control system of the present invention

[0025] Figure 3 Modeling flow chart of the equipment model of the system of the present invention

[0026] Figure 4 This is a flow chart for building a twin platform in the digital twin system of the present invention;

[0027] Figure 5 This is a flow chart of the multiverse optimization algorithm in the present invention; Specific implementation methods

[0028] The invention is further explained below with reference to the accompanying drawings.

[0029] Combination Figure 1 As shown, the digital twin platform includes: the physical world, the twin platform, and the data transmission platform.

[0030] Step 1: Combine Figure 2 As shown in the figure, the physical world includes industrial computers, PLC modules, frequency converters, tension sensors, motors, and DP bus networks; the tension control system includes a system master station and a system slave station of the control system; the system master station is a PLC module of S7-300 with a DP communication port, which communicates with the industrial computer through the DP bus network, transmits control commands and given speeds to each frequency converter, and receives and processes status information from the frequency converter; the system slave station is a frequency converter equipped with a DP communication card, which is responsible for executing the instructions of the master station, and the tension signal collected by the tension sensor is transmitted to the PLC through the DP bus network of the frequency converter, and the PID controller inside the PLC calculates and processes the output signal to the frequency converter to control the speed of the motor, thereby controlling the pay-off speed of the reel and realizing the constant tension pay-off of the tight-packed optical fiber;

[0031] The industrial computer is the control center of the physical world, which obtains real-time data of the equipment, issues real-time control instructions, and interconnects data with the twin platform.

[0032] Step 2: The data transmission platform uses a switch as a unified communication hub to manage and control data transmission between the physical operation platform and the twin operation platform, and provides big data management services to store and analyze operation data to form industrial big data.

[0033] Step 3: The twin platform uses Unity3D to build a virtual workshop scene. The specific process is as follows Figure 3 As shown. By building equipment models in proportion to the equipment in actual production, the workshop equipment model is built using 3dsmax to build a model with proportions and details that correspond to the actual equipment. By extracting and generating textures from the real objects, 3D texture drawing is performed in Photoshop, and then a material ball is created in 3dsmax, the corresponding UV map and texture image are attached, and finally imported into Unity3D in .MAT file format. Finally, the light and shadow effects are adjusted to make the model in the digital workshop more realistic.

[0034] like Figure 4 As shown in the figure, data-driven is implemented on the Unity platform. The industrial computer collects real-time data of the workshop to obtain the status data of the twin workshop in the twin platform, and then assigns these data to the corresponding components in the model through C# scripts to ensure the synchronization of the status of the physical world and the twin workshop.

[0035] Analyze the collected data. When the PID control parameters of the tension control system in actual production cannot effectively control the actual tension, such as Figure 5 In the control method shown, the optimal control parameters under the current state are found through the multiverse optimization algorithm.

[0036] The specific steps of optimization are:

[0037] (1) Initialize a multiverse population:

[0038]

[0039] (2) Set the WEP parameter min =0.2 ， WEPmax=1,p=6,L=200 and related variables (n,d,l); where WEP represents the probability of the existence of wormholes in the multiverse space, TDR represents the step size of the object moving towards the current optimal universe, p represents the exploitation degree, and L is the maximum number of iterations.

[0040] (3) The evaluation function is determined based on the combination of PID parameters (overshoot, adjustment time, peak value, etc.). For the sake of simplicity of calculation, the adjustment time ts and overshoot σ are selected as the comparison basis, and the evaluation function is defined as:

[0041]

[0042] (4) Update WEP and TDR according to formulas ②③; Execute the roulette mechanism according to formula (④;

[0043]

[0044] (5) The updated optimal universe is calculated according to formula ⑤. If it is better than the current optimal universe, it is replaced; otherwise, the current optimal universe is retained.

[0045]

[0046] Where r1, r2, r3, and r4 are random numbers in the range [0,1].

[0047] (6) Assign the parameters of each universe to the proportional coefficient, integral coefficient and differential coefficient in the PID controller to obtain the corresponding error performance index, and continuously iterate the universe. Finally, select the particle with the smallest error performance index in the universe as the optimal universe, and assign the parameters of the optimal universe to the proportional coefficient, integral coefficient and differential parameter in the PID controller.

[0048] The decisions made by the twin platform are transmitted to the industrial computer in the physical world via TCP / IP, and are promptly fed back to the physical workshop. The lower computer receives instructions to adjust the PID control parameters and regulate the physical equipment, thus achieving synchronization and two-way optimization between the model and the physical equipment.

[0049] Before actual production, simulation can be performed through the digital twin platform to obtain the optimal control parameters in the simulation environment, which can greatly save material loss before the production of new products. By logging into the digital twin platform, the real-time status of the equipment during production operation can be viewed in real time. The platform can also analyze and process the collected data, continuously optimize the real-time control parameters, and feed back to the real-time production process to achieve optimal control.

[0050] When a failure occurs during operation, the user can input the historical time nodes through the data stored in the data transmission platform to reproduce the status when the failure occurred, so that the user can analyze the failure more clearly and intuitively.

Claims

1. A tension control system for a tight-buffered optical cable production line based on digital twin, characterized in that: The system comprises the following steps: (1) The digital twin platform includes: the physical world, the twin platform, and the data transmission platform; (2) Step 1: The physical world includes industrial computers, PLC modules, frequency converters, tension sensors, motors, and DP bus networks; the tension control system includes a system master station and a system slave station; the system master station is a S7-300 PLC module with a DP communication port, which communicates with the industrial computer through the DP bus network, transmits control commands and given speeds to each frequency converter, and receives and processes status information from the frequency converter; the system slave station is a frequency converter equipped with a DP communication card, which is responsible for executing the instructions of the master station. The tension signal collected by the tension sensor is transmitted to the PLC through the DP bus network of the frequency converter, and the PID controller inside the PLC calculates and processes the signal and outputs it to the frequency converter to control the speed of the motor, thereby controlling the pay-off speed of the cable drum and achieving constant tension pay-off of the tight-buffered optical fiber; (3) The industrial computer is the control center of the physical world, which obtains real-time data of the equipment, issues real-time control instructions, and interconnects data with the digital twin platform; (4) Step 2: The data transmission platform uses a switch as a unified communication hub to manage and control data transmission between the physical operation platform and the twin operation platform, and provides big data management services to store and analyze operation data to form industrial big data; (5) Step 3: The twin platform uses Unity3D to build a virtual workshop scene; by building a proportional equipment model of the equipment in actual production, the workshop equipment model is built using 3dsmax to build a model with proportions and details that correspond to the actual equipment; by extracting and generating textures from the real objects, 3D texture drawing is performed in Photoshop, and then a material ball is created in 3dsmax, and the corresponding UV map and texture image are attached, and finally imported into Unity3D in .MAT file format, and finally the light and shadow effects are adjusted to make the model in the digital workshop more realistic; (6) Implement data-driven on the Unity platform, collect real-time data of the workshop through the industrial computer, obtain the status data of the twin workshop in the twin platform, and then assign these data to the corresponding components in the model through C# scripts to ensure the synchronization of the status of the physical world and the twin workshop; (7) Analyze the collected data. When the PID control parameters of the tension control system in actual production cannot effectively control the actual tension, find the optimal control parameters under the current state through the multiverse optimization algorithm; (8) Assign the parameters of each universe to the proportional coefficient, integral coefficient and differential coefficient in the PID controller to obtain the corresponding error performance index, and continuously iterate the universe. Finally, select the particle with the smallest error performance index in the universe as the optimal universe, and assign the parameters of the optimal universe to the proportional coefficient, integral coefficient and differential parameter in the PID controller; (9) The decisions made by the twin platform are transmitted to the industrial computer in the physical world through TCP / IP, and are fed back to the physical workshop in a timely manner. The lower computer receives instructions to adjust the PID control parameters and regulate the physical equipment, thus achieving synchronization and two-way optimization between the model and the physical equipment. (10) By logging into the digital twin platform, the real-time status of the equipment during production operation can be viewed in real time. The platform can also analyze and process the collected data, continuously optimize the real-time control parameters, and feed back to the real-time production process to achieve optimal control; (11) When a failure occurs during operation, the data stored in the data transmission platform allows the user to input historical time nodes to reproduce the status when the failure occurred, allowing the user to analyze the failure more clearly and intuitively.

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