An online monitoring method and system based on cabling machine

Abstract

The present invention belongs to the field of cabling machine monitoring and involves data analysis technology. It is used to solve the problem that the online monitoring method of the cabling machine in the prior art cannot combine the operation data, output data and quality inspection data of the cabling machine to optimize the setting of the traction parameters and twisting parameters of the cabling machine. Specifically, it is an online monitoring method and system based on the cabling machine, including an online monitoring platform. The online monitoring platform is communicatively connected with a real-time monitoring module, a production and quality analysis module, a parameter analysis module and a storage module; the real-time monitoring module is used to perform real-time monitoring and analysis on the operation status of the cabling machine; the production and quality analysis module is used to evaluate and analyze the output and quality of the cabling machine; the present invention can perform real-time monitoring and analysis on the operation status of the cabling machine, feedback the degree of the operation status of the cabling machine through the real-time coefficient, and timely issue an early warning when an operation abnormality occurs to avoid safety accidents caused by the operation of the cabling machine in an abnormal state.

Description

Technical Field

[0001] The invention belongs to the field of cabling machine monitoring, relates to data analysis technology, and specifically is an online monitoring method and system based on cabling machine. Background Art

[0002] A cabling machine is a wire and cable equipment used for cabling and armoring of multi-core rubber-sheathed cables, plastic power cables, cross-linked cables, telephone cables, and control cables of various cross-sections. Depending on the rotation speed, cabling machines can generally be divided into cage-type cabling machines and high-speed cage-type cabling machines. Among them, high-speed cage-type cabling machines are used for stranding of copper-core aluminum stranded wires and bare aluminum wires, and can also be used for cabling of plastic power cables, rubber-sheathed cables and other products.

[0003] The online monitoring method of the cabling machine in the prior art can usually only monitor the operating status of the cabling machine and issue an alarm when an abnormal operation occurs, but it is unable to optimize the traction parameters and twisting parameters of the cabling machine by combining the operating data, output data and quality inspection data of the cabling machine, thereby reducing the probability of failure of the cabling machine and improving its production quality.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The object of the present invention is to provide an online monitoring method and system based on a cabling machine, which is used to solve the problem that the online monitoring method of the cabling machine in the prior art cannot optimize the traction parameters and twisting parameters of the cabling machine by combining the operation data, output data and quality inspection data of the cabling machine;

[0006] The technical problem to be solved by the present invention is: how to provide an online monitoring method and system based on a cabling machine that can optimize the traction parameters and twisting parameters of the cabling machine by combining the operation data, output data and quality inspection data of the cabling machine.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] An online monitoring system based on a cabling machine includes an online monitoring platform, wherein the online monitoring platform is communicatively connected with a real-time monitoring module, a yield and quality analysis module, a parameter analysis module and a storage module;

[0009] The real-time monitoring module is used to monitor and analyze the operation status of the cabling machine in real time: generate a production cycle, mark the continuous operation process of the cabling machine in the production cycle as a monitoring process, obtain the temperature explicit data WX, pressure explicit data YX and vibration data ZD of the cabling machine in real time during the monitoring process, and perform numerical calculations to obtain the real-time coefficient SS of the cabling machine; determine whether the operation status of the cabling machine during the monitoring process meets the requirements through the real-time coefficient SS;

[0010] The yield and quality analysis module is used to evaluate and analyze the yield and quality of the cabling machine and obtain the yield performance value and quality performance value of the monitoring process, and send the yield performance value and quality performance value of the monitoring process to the parameter analysis module;

[0011] The parameter analysis module is used to analyze the operating parameters of the cabling machine and obtain a reference data set of the production cycle, and send the reference data set to the online monitoring platform. After receiving the reference data set, the online monitoring platform sends the reference data set to the mobile terminal of the manager.

[0012] Furthermore, the process of acquiring the temperature explicit data WX includes: acquiring the temperature value of the stranding head of the cabling machine and the standard temperature range, marking the average value of the maximum value and the minimum value of the standard temperature range as the temperature reference value, and marking the absolute value of the difference between the temperature value of the stranding head of the cabling machine and the temperature reference value as the temperature explicit data WX of the cabling machine; the process of acquiring the pressure explicit data YX includes: acquiring the discharge pressure value and the standard pressure range of the cabling machine, marking the average value of the maximum value and the minimum value of the standard pressure range as the pressure reference value, and marking the absolute value of the difference between the discharge pressure value and the pressure reference value as the pressure explicit data YX of the cabling machine; the vibration data ZD is the vibration amplitude of the outer shell of the stranding head of the cabling machine.

[0013] Furthermore, the specific process of determining whether the operating state of the cabling machine during the monitoring process meets the requirements includes: obtaining the real-time threshold SSmax through the storage module, and comparing the real-time coefficient SS of the cabling machine with the real-time threshold SSmax: if the real-time coefficient SS is less than the real-time threshold SSmax, it is determined that the operating state of the cabling machine meets the requirements; if the real-time coefficient SS is greater than or equal to the real-time threshold SSmax, it is determined that the operating state of the cabling machine does not meet the requirements, and the monitoring process is marked as a fault process.

[0014] Furthermore, the process of obtaining the production performance value and the quality performance value of the monitoring process includes: after the monitoring process is completed, obtaining the cable making length value of the monitoring process, marking the ratio of the cable making length value to the duration of the monitoring process as the production performance value of the monitoring process, performing quality inspection on the cables produced by the monitoring process, marking the cable length value of the part that fails the quality inspection as the quality inspection value, and marking the ratio of the quality inspection value to the cable making length value as the quality performance value.

[0015] Furthermore, the specific process of the parameter analysis module analyzing the operating parameters of the cabling machine includes: obtaining the traction speed value and the twisting tension value of the cabling machine during the monitoring process, forming a traction range by the maximum and minimum values ​​of the traction speed values ​​of all monitoring processes, dividing the traction range into several traction intervals, and calculating the recommended coefficient TJ of the traction interval; obtaining the recommended threshold value TJmin through the storage module, and comparing the recommended coefficient TJ of the traction interval with the recommended threshold value TJmin: if the recommended coefficient TJ is less than the recommended threshold value TJmin, the corresponding traction interval is marked as an invalid interval; if the recommended coefficient TJ is greater than or equal to the recommended threshold value TJmin, the corresponding traction interval is marked as a valid interval; and then the valid interval is deeply analyzed.

[0016] Furthermore, the calculation process of the recommended coefficient TJ of the traction interval includes: marking the monitoring process in which the traction speed value is within the traction interval as the matching process of the traction interval, obtaining the fault data GZ, production data CL and quality data ZL of the traction interval, the fault data GZ is the ratio of the number of fault processes to matching processes in the traction interval, the production data CL is the average value of the production performance values ​​of all matching processes in the traction interval, and the quality data ZL is the average value of the quality performance values ​​of all matching processes in the traction interval, and the recommended coefficient TJ of the traction interval is obtained by numerically calculating the fault data GZ, the production data CL and the quality data ZL.

[0017] Furthermore, the specific process of in-depth analysis of the effective interval includes: the twisting range of the effective interval is formed by the maximum and minimum values ​​of the twisting tension values ​​of all matching processes in the effective interval, the twisting range is divided into several twisting intervals, and a screening data group is formed by a valid interval and a twisting interval, and the monitoring process of the traction speed value and the twisting tension value that respectively meet the effective interval and the twisting interval in the screening data group is marked as the screening process of the screening data group, the recommended coefficient TJ of the screening data group is calculated and the calculated recommended coefficient TJ is marked as the screening coefficient of the screening data group, and the L1 screening data groups with the largest screening coefficient values ​​are marked as reference data groups.

[0018] An online monitoring method based on a cabling machine comprises the following steps:

[0019] Step 1: Real-time monitoring and analysis of the operation status of the cabling machine: Generate a production cycle, mark the continuous operation process of the cabling machine in the production cycle as the monitoring process, obtain the temperature explicit data WX, pressure explicit data YX and vibration data ZD of the cabling machine in real time during the monitoring process, and perform numerical calculations to obtain the real-time coefficient SS;

[0020] Step 2: Determine whether the operation status of the cabling machine meets the requirements through the real-time coefficient SS, and mark the corresponding monitoring process as a fault process if it does not meet the requirements;

[0021] Step 3: Evaluate and analyze the output and quality of the cabling machine and obtain the output performance value and quality performance value of the monitoring process, and send the output performance value and quality performance value of the monitoring process to the parameter analysis module;

[0022] Step 4: Analyze the operating parameters of the cabling machine: obtain the traction speed value and the twisting tension value of the cabling machine during the monitoring process, generate a screening data set based on the traction speed value and the twisting tension value, calculate the screening coefficient of the screening data set, and mark the L1 screening data group with the largest screening coefficient value as the reference data group.

[0023] The present invention has the following beneficial effects:

[0024] 1. The real-time monitoring module can monitor and analyze the operation status of the cabling machine in real time. During the continuous operation of the cabling machine, multiple operation parameters are collected and comprehensively analyzed and calculated to obtain the real-time coefficient. The real-time coefficient is used to provide feedback on the operation status of the cabling machine. When an abnormal operation occurs, an early warning is given in time to avoid safety accidents caused by the abnormal operation of the cabling machine.

[0025] 2. The yield and quality analysis module can be used to evaluate and analyze the yield and quality of the cabling machine. After the monitoring process is completed, the yield parameters and quality inspection parameters of the monitoring process are obtained. After analysis, the yield performance value and quality performance value of the monitoring process are obtained, providing data support for parameter optimization analysis;

[0026] 3. The parameter analysis module can be used to analyze the operating parameters of the cabling machine, collect statistics on the operating parameters of the cabling machine corresponding to the independent monitoring process within the production cycle, and then calculate the screening coefficient of the screening data group composed of the effective interval and the twisting interval. The reference data group is screened based on the screening coefficient, and the reference data group is used to adjust the operating parameters of the cabling machine in the next production cycle to ensure the output efficiency and production quality of the cabling machine while reducing the probability of failure. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0029] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0030] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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.

[0031] Embodiment 1

[0032] like Figure 1 As shown, an online monitoring system based on a cabling machine includes an online monitoring platform, which is communicatively connected to a real-time monitoring module, a production quality analysis module, a parameter analysis module and a storage module.

[0033] The real-time monitoring module is used to monitor and analyze the operation status of the cabling machine in real time: generate a production cycle, mark the continuous operation process of the cabling machine in the production cycle as the monitoring process, and obtain the temperature explicit data WX, pressure explicit data YX and vibration data ZD of the cabling machine in real time during the monitoring process. The acquisition process of the temperature explicit data WX includes: obtaining the temperature value of the cabling machine stranding head and the standard temperature range, marking the average value of the maximum and minimum values ​​of the standard temperature range as the temperature reference value, and marking the absolute value of the difference between the temperature value of the cabling machine stranding head and the temperature reference value as the temperature explicit data WX of the cabling machine; the acquisition process of the pressure explicit data YX includes: obtaining the discharge pressure value and the standard pressure range of the cabling machine, marking the average value of the maximum and minimum values ​​of the standard pressure range as the pressure reference value, and marking the absolute value of the difference between the discharge pressure value and the pressure reference value as the pressure explicit data YX of the cabling machine; the vibration data ZD is the shell of the cabling machine stranding head. Vibration amplitude; the real-time coefficient SS of the cabling machine is obtained by the formula SS=k1*WX+k2*YX+k3*ZD, where k1, k2 and k3 are all proportional coefficients, and k1>k2>k3>1; the real-time threshold SSmax is obtained through the storage module, and the real-time coefficient SS of the cabling machine is compared with the real-time threshold SSmax: if the real-time coefficient SS is less than the real-time threshold SSmax, it is determined that the operating state of the cabling machine meets the requirements; if the real-time coefficient SS is greater than or equal to the real-time threshold SSmax, it is determined that the operating state of the cabling machine does not meet the requirements, and the monitoring process is marked as a fault process; the operating state of the cabling machine is monitored and analyzed in real time, and multiple operating parameters are collected during the continuous operation of the cabling machine, and the real-time coefficient is obtained by comprehensive analysis and calculation. The real-time coefficient is used to feedback the operating state of the cabling machine, and timely warning is given when abnormal operation occurs to avoid safety accidents caused by the operation of the cabling machine in an abnormal state.

[0034] The production and quality analysis module is used to evaluate and analyze the output and quality of the cabling machine: after the monitoring process is completed, the cable making length value of the monitoring process is obtained, and the ratio of the cable making length value to the duration of the monitoring process is marked as the output performance value of the monitoring process, and the cable produced by the monitoring process is quality inspected, and the cable length value of the unqualified part of the quality inspection is marked as the quality inspection value, and the ratio of the quality inspection value to the cable making length value is marked as the quality performance value, and the output performance value and the quality performance value of the monitoring process are sent to the parameter analysis module; the output and quality of the cabling machine are evaluated and analyzed, and the output parameters and quality inspection parameters of the monitoring process are obtained after the monitoring process is completed. After analysis, the output performance value and the quality performance value of the monitoring process are obtained, providing data support for parameter optimization analysis.

[0035] The parameter analysis module is used to analyze the operating parameters of the cabling machine: obtain the traction speed value and the twisting tension value of the cabling machine during the monitoring process, the traction range is composed of the maximum and minimum traction speed values ​​of all monitoring processes, the traction range is divided into several traction intervals, and the monitoring process with the traction speed value in the traction interval is marked as the matching process of the traction interval, and the fault data GZ, production data CL and quality data ZL of the traction interval are obtained. The fault data GZ is the ratio of the number of fault processes to matching processes in the traction interval, the production data CL is the average value of the production performance values ​​of all matching processes in the traction interval, and the quality data ZL is the average value of the quality performance values ​​of all matching processes in the traction interval. The formula The recommended coefficient TJ of the traction interval is obtained, where m1, m2 and m3 are all proportional coefficients, and m1>m2>m3>1; the recommended threshold TJmin is obtained through the storage module, and the recommended coefficient TJ of the traction interval is compared with the recommended threshold TJmin: if the recommended coefficient TJ is less than the recommended threshold TJmin, the corresponding traction interval is marked as an invalid interval; if the recommended coefficient TJ is greater than or equal to the recommended threshold TJmin, the corresponding traction interval is marked as a valid interval; then the valid interval is deeply analyzed: the maximum and minimum values ​​of the twisting tension values ​​of all matching processes in the valid interval constitute the twisting range of the valid interval, the twisting range is divided into several twisting intervals, and a screening data group is composed of a valid interval and a twisting interval, and the traction speed value and the twisting tension value that respectively meet the monitoring process of the valid interval and the twisting interval in the screening data group are marked as screening data. The screening process of the data group is to calculate the recommended coefficient TJ of the screening data group and mark the calculated recommended coefficient TJ as the screening coefficient of the screening data group, mark the L1 screening data groups with the largest screening coefficient value as the reference data group, L1 is a numerical constant, and the specific value of L1 is set by the management personnel; send the reference data group to the online monitoring platform, and the online monitoring platform sends the reference data group to the mobile phone terminal of the management personnel after receiving the reference data group; analyze the operating parameters of the cabling machine, and count the operating parameters of the cabling machine corresponding to the independent monitoring process in the production cycle, and then calculate the screening coefficient of the screening data group composed of the effective interval and the twisting interval, so as to screen the reference data group based on the screening coefficient, and use the reference data group to adjust the operating parameters of the cabling machine in the next production cycle to ensure the output efficiency and production quality of the cabling machine while reducing the probability of failure.

[0036] Embodiment 2

[0037] like Figure 2 As shown, an online monitoring method based on a cabling machine includes the following steps:

[0038] Step 1: Real-time monitoring and analysis of the operation status of the cabling machine: Generate a production cycle, mark the continuous operation process of the cabling machine in the production cycle as the monitoring process, obtain the temperature explicit data WX, pressure explicit data YX and vibration data ZD of the cabling machine in real time during the monitoring process, and perform numerical calculations to obtain the real-time coefficient SS;

[0039] Step 2: Determine whether the operation status of the cabling machine meets the requirements through the real-time coefficient SS, and mark the corresponding monitoring process as a fault process if it does not meet the requirements;

[0040] Step 3: Evaluate and analyze the output and quality of the cabling machine and obtain the output performance value and quality performance value of the monitoring process, and send the output performance value and quality performance value of the monitoring process to the parameter analysis module;

[0041] Step 4: Analyze the operating parameters of the cabling machine: obtain the traction speed value and the twisting tension value of the cabling machine during the monitoring process, generate a screening data set based on the traction speed value and the twisting tension value, calculate the screening coefficient of the screening data set, and mark the L1 screening data group with the largest screening coefficient value as the reference data group.

[0042] An online monitoring method and system based on a cabling machine, when working, generates a production cycle, marks the continuous operation process of the cabling machine in the production cycle as a monitoring process, obtains the temperature explicit data WX, pressure explicit data YX and vibration data ZD of the cabling machine in real time during the monitoring process, and performs numerical calculation to obtain the real-time coefficient SS; determines whether the operation state of the cabling machine meets the requirements through the real-time coefficient SS, and marks the corresponding monitoring process as a fault process when the requirements are not met; evaluates and analyzes the output and quality of the cabling machine and obtains the output performance value and quality performance value of the monitoring process, and sends the output performance value and quality performance value of the monitoring process to a parameter analysis module; obtains the traction speed value and the twisting tension value of the cabling machine during the monitoring process, generates a screening data set according to the traction speed value and the twisting tension value, calculates the screening coefficient of the screening data set, and marks L1 screening data groups with the largest screening coefficient values ​​as reference data groups.

[0043] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0044] The above formulas are obtained by collecting a large amount of data and performing software simulation to select a formula close to the actual value. The coefficients in the formula are set by technicians in this field according to actual conditions; for example: Formula ; A technician in this field collects multiple groups of sample data and sets corresponding recommended coefficients for each group of sample data; Substitute the set recommended coefficients and the collected sample data into the formula, any three formulas constitute a three-variable linear equation system, screen the calculated coefficients and take the average, and obtain the values ​​of m1, m2 and m3 as 3.47, 2.25 and 2.03 respectively;

[0045] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the corresponding recommended coefficient initially set by technical personnel in this field for each set of sample data; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the recommended coefficient is proportional to the value of the production data.

[0046] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0047] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An online monitoring system based on a cabling machine, characterized in that: It includes an online monitoring platform, which is communicatively connected with a real-time monitoring module, a production quality analysis module, a parameter analysis module and a storage module; The real-time monitoring module is used to monitor and analyze the operation status of the cabling machine in real time: generate a production cycle, mark the continuous operation process of the cabling machine in the production cycle as a monitoring process, obtain the temperature explicit data WX, pressure explicit data YX and vibration data ZD of the cabling machine in real time during the monitoring process, and perform numerical calculations to obtain the real-time coefficient SS of the cabling machine; determine whether the operation status of the cabling machine during the monitoring process meets the requirements through the real-time coefficient SS; The yield and quality analysis module is used to evaluate and analyze the yield and quality of the cabling machine and obtain the yield performance value and quality performance value of the monitoring process, and send the yield performance value and quality performance value of the monitoring process to the parameter analysis module; The parameter analysis module is used to analyze the operating parameters of the cabling machine and obtain a reference data set of the production cycle, and send the reference data set to the online monitoring platform. After receiving the reference data set, the online monitoring platform sends the reference data set to the mobile phone terminal of the manager; The process of obtaining the temperature explicit data WX includes: obtaining the temperature value of the stranding head of the cabling machine and the standard temperature range, marking the average value of the maximum value and the minimum value of the standard temperature range as the temperature reference value, and marking the absolute value of the difference between the temperature value of the stranding head of the cabling machine and the temperature reference value as the temperature explicit data WX of the cabling machine; the process of obtaining the pressure explicit data YX includes: obtaining the discharge pressure value and the standard pressure range of the cabling machine, marking the average value of the maximum value and the minimum value of the standard pressure range as the pressure reference value, and marking the absolute value of the difference between the discharge pressure value and the pressure reference value as the pressure explicit data YX of the cabling machine; the vibration data ZD is the vibration amplitude of the outer shell of the stranding head of the cabling machine; The specific process of determining whether the operating state of the cabling machine during the monitoring process meets the requirements includes: obtaining the real-time threshold SSmax through the storage module, and comparing the real-time coefficient SS of the cabling machine with the real-time threshold SSmax: if the real-time coefficient SS is less than the real-time threshold SSmax, it is determined that the operating state of the cabling machine meets the requirements; if the real-time coefficient SS is greater than or equal to the real-time threshold SSmax, it is determined that the operating state of the cabling machine does not meet the requirements, and the monitoring process is marked as a fault process; The process of obtaining the output performance value and the quality performance value of the monitoring process includes: after the monitoring process is finished, obtaining the cable making length value of the monitoring process, marking the ratio of the cable making length value to the duration of the monitoring process as the output performance value of the monitoring process, performing quality inspection on the cables produced by the monitoring process, marking the cable length value of the part that fails the quality inspection as the quality inspection value, and marking the ratio of the quality inspection value to the cable making length value as the quality performance value; The specific process of the parameter analysis module analyzing the operating parameters of the cabling machine includes: obtaining the traction speed value and the twisting tension value of the cabling machine during the monitoring process, forming a traction range by the maximum and minimum traction speed values ​​of all monitoring processes, dividing the traction range into several traction intervals, and calculating the recommended coefficient TJ of the traction interval; obtaining the recommended threshold value TJmin through the storage module, and comparing the recommended coefficient TJ of the traction interval with the recommended threshold value TJmin: if the recommended coefficient TJ is less than the recommended threshold value TJmin, the corresponding traction interval is marked as an invalid interval; if the recommended coefficient TJ is greater than or equal to the recommended threshold value TJmin, the corresponding traction interval is marked as a valid interval; and then the valid interval is deeply analyzed; The calculation process of the recommended coefficient TJ of the traction interval includes: marking the monitoring process whose traction speed value is within the traction interval as the matching process of the traction interval, obtaining the fault data GZ, the production data CL and the quality data ZL of the traction interval, the fault data GZ is the ratio of the number of fault processes to the matching processes in the traction interval, the production data CL is the average value of the production performance values ​​of all matching processes in the traction interval, and the quality data ZL is the average value of the quality performance values ​​of all matching processes in the traction interval, and obtaining the recommended coefficient TJ of the traction interval by numerically calculating the fault data GZ, the production data CL and the quality data ZL; The calculation formula of the recommended coefficient TJ of the traction interval is: , where m1, m2 and m3 are all proportional coefficients, and m1>m2>m3>1.

2. The online monitoring system based on the cabling machine according to claim 1 is characterized in that: The specific process of in-depth analysis of the effective interval includes: the maximum and minimum values ​​of the twisting tension values ​​of all matching processes in the effective interval constitute the twisting range of the effective interval, the twisting range is divided into several twisting intervals, and a screening data group is composed of a valid interval and a twisting interval, and the monitoring process of the traction speed value and the twisting tension value that respectively meet the effective interval and the twisting interval in the screening data group is marked as the screening process of the screening data group, the recommended coefficient TJ of the screening data group is calculated and the calculated recommended coefficient TJ is marked as the screening coefficient of the screening data group, and the L1 screening data groups with the largest screening coefficient values ​​are marked as reference data groups.

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