Metal wire woven rat-proof optical cable forming control method and system

Abstract

The invention relates to the technical field of optical cable manufacturing, and discloses a metal wire woven rat-proof optical cable forming control method and system, and the method comprises the steps: obtaining the instruction speed of a main traction motor, the actual rotation speed of a spindle drive motor, and the measurement value of a linear speed encoder, and calculating the theoretical expected linear speed according to the data. When the deviation between the measured value and the theoretical expected linear speed exceeds a preset threshold value and is continuously negative deviation, the system can intelligently identify whether the linear speed encoder slips or not. Once slipping is confirmed, the method does not simply depend on a possibly distorted encoder measurement value, but creatively fuses the theoretical expected linear speed and the historical trend data of the linear speed encoder to obtain a more accurate and robust fusion speed value as the input of tension control. Therefore, the system can accurately adjust the metal wire tension.

Description

Technical Field

[0001] This invention relates to the field of optical cable manufacturing technology, and in particular to a method and system for controlling the forming of a metal wire braided rodent-proof optical cable. Background Technology

[0002] In actual industrial production environments, to meet growing market demand and reduce production costs, production departments typically source metal wire from multiple suppliers. These wires from different suppliers, even if seemingly identical in specifications, may exhibit subtle but persistent differences in their microscopic physical properties. For example, their surface roughness, the type and amount of residual agents used for rust prevention or lubrication, and the microcrystalline structure of the material itself may vary. These differences directly affect the coefficient of friction between the wire and mechanical components such as guide rollers and spindles during the weaving process.

[0003] Furthermore, with the increasing market demand for diversified optical cable products, production lines need to frequently switch product models. This may involve different diameter optical cable cores, as well as different strand counts and metal wire braiding schemes. Each model switch means that the mechanical configuration, operating speed, wire arrangement, and required tension range of the braiding machine all need to be adjusted. Summary of the Invention

[0004] This invention provides a method and system for controlling the forming of metal wire braided rodent-proof optical cables, aiming to solve the problem in the prior art where insufficient tension control accuracy is caused by multi-source dynamic interference such as material differences, frequent model switching and linear speed encoder slippage, which in turn affects the uniformity and long-term reliability of the optical cable braiding layer.

[0005] In a first aspect, to solve the above-mentioned technical problems, the present invention provides a method for controlling the forming of a metal wire braided rodent-proof optical cable, comprising: Acquire the commanded speed of the main traction motor, the actual speed of the spindle drive motor, and the measured value of the linear speed encoder; Calculate the theoretical expected linear speed based on the commanded speed, the actual rotational speed, and the production line parameters; The deviation between the measured value and the theoretical expected linear velocity is obtained, and it is determined whether the deviation exceeds a preset deviation threshold and is a negative deviation within a preset time period. If so, it is identified whether the linear velocity encoder is slipping. If so, the theoretically expected linear velocity is fused with the historical trend data of the linear velocity encoder to obtain a fused velocity value as the input for tension control; The tension of the metal wire is adjusted according to the input of the tension control.

[0006] Preferably, if so, identifying whether the linear speed encoder is slipping includes: when the negative deviation exists, acquiring the internal temperature and operating current of the main traction motor; Calculate the expected current after temperature compensation based on the internal temperature. Obtain the current difference between the operating current and the expected current after temperature compensation; If the current difference does not exceed the preset fluctuation threshold, then the linear speed encoder is identified as slipping.

[0007] Preferably, if so, the theoretically expected linear velocity is fused with the historical trend data of the linear velocity encoder to obtain a fused velocity value as input for tension control, including: After identifying slippage in the linear speed encoder, the production line operating parameters are obtained; Based on the production line operating parameters, dynamically adjust the weighting coefficients of the theoretical expected linear speed and the historical trend data in the fused speed value; Based on the adjusted weighting coefficients, the theoretically expected linear velocity and the historical trend data are fused to obtain the fused velocity value; The fusion speed value is used as the input for the tension control.

[0008] Preferably, the step of dynamically adjusting the weighting coefficients of the theoretical expected linear velocity and the historical trend data in the fused velocity value based on the production line operating parameters includes: Obtain the operating parameters of the production line; Obtain production line uptime; Based on the production line operating parameters and the production line running time, within a preset parameter adjustment cycle, the weighting coefficients of the theoretical expected linear velocity and the historical trend data in the fusion velocity value are periodically evaluated. The weighting coefficients are adjusted based on the evaluation results.

[0009] Preferably, the step of periodically evaluating the weighting coefficients of the theoretical expected linear velocity and the historical trend data in the fused velocity value within a preset parameter adjustment period, based on the production line operating parameters and the production line running time, includes: Continuously monitor the rate of change of the operating parameters of the production line; When the rate of change exceeds a preset instantaneous change threshold, the non-periodic weighting coefficient evaluation is triggered. Adjust the weighting coefficients of the theoretical expected linear velocity and the historical trend data in the fused velocity value based on the current production line operating parameters.

[0010] Preferably, adjusting the weighting coefficients of the theoretical expected linear velocity and the historical trend data in the fused velocity value based on the current production line operating parameters includes: Determine the type of change in the current production line operating parameters; If the change type is a drastic change type, then the weighting coefficient of the theoretical expected linear velocity is set to a preset high weighting value; The weighting coefficients of the historical trend data are set to preset low weighting values.

[0011] Preferably, determining the type of change in the current production line operating parameters includes: Obtain operating parameters from multiple production lines, including optical cable type parameters, metal wire material parameters, and equipment operating load parameters; Based on the operating parameters, set the corresponding preset threshold and rate of change threshold; When the change value of any of the operating condition parameters exceeds the preset change threshold, the operating condition parameter is marked as a potential dominant change parameter. Based on preset priority rules and mutual influence matrix, identify the currently dominant change type.

[0012] Preferably, identifying the currently dominant change type based on preset priority rules and a mutual influence matrix includes: Within a preset parameter adjustment period, the applicability of the priority rules and the mutual influence matrix is ​​periodically evaluated; If the priority rule or the mutual influence matrix conflicts with the current operating condition, the priority rule or the mutual influence matrix is ​​adjusted according to the conflict, and the currently dominant change type is identified based on the adjustment result.

[0013] Preferably, the step of periodically evaluating the applicability of the priority rule and the mutual influence matrix within a preset parameter adjustment period includes: Obtain the dominant change types under different priority rules and mutual influence relationship matrices in historical production data, and identify the corresponding accuracy and stability indicators; Gain experience and judgment under different working conditions; Based on the accuracy, the stability index, and the empirical judgment, the priority rule and the mutual influence matrix are scored using a multi-dimensional weighted score. Based on the multi-dimensional weighted scoring results, determine the applicability of the priority rules and the mutual influence matrix.

[0014] Secondly, the present invention provides a metal wire braided rodent-proof optical cable forming control system, comprising: The detection end is used to acquire the commanded speed of the main traction motor, the actual speed of the spindle drive motor, and the measured value of the linear speed encoder. The identification end is used to calculate the theoretical expected linear speed based on the commanded speed, the actual rotation speed, and the production line parameters; obtain the deviation between the measured value and the theoretical expected linear speed; determine whether the deviation exceeds a preset deviation threshold and is a negative deviation within a preset time period; if so, identify whether the linear speed encoder is slipping. The fusion end is used to fuse the theoretically expected linear velocity with the historical trend data of the linear velocity encoder if the condition is met, and obtain a fused velocity value as the input for tension control; and adjust the wire tension according to the input for tension control.

[0015] The method for controlling the forming of rodent-proof optical cables using braided metal wire disclosed in this application acquires the commanded speed of the main traction motor, the actual speed of the spindle drive motor, and the measured value of the linear speed encoder, and calculates the theoretical expected linear speed based on these data. When the deviation between the measured value and the theoretical expected linear speed exceeds a preset threshold and remains negative, the system can intelligently identify whether the linear speed encoder is slipping. Once slippage is confirmed, this application no longer relies solely on potentially distorted encoder measurements, but innovatively integrates the theoretical expected linear speed with historical trend data from the linear speed encoder to obtain a more accurate and robust fused speed value as the input for tension control. Accordingly, the system can precisely adjust the tension of the metal wire.

[0016] Through the above technical solution, this application effectively solves the technical problem in the prior art where the tension control system cannot accurately and in real-time maintain the tension of a single metal wire within the ideal range due to various dynamic interference factors such as differences in metal wire materials between different batches, frequent product model switching, and slippage of the linear speed encoder roller. In particular, this application overcomes the lag and inaccuracy of traditional control methods when facing measurement errors through intelligent identification of encoder slippage and speed fusion mechanism, avoiding over-adjustment or under-adjustment caused by misjudgment. Therefore, this application can significantly improve the uniformity, tensile strength, and rodent-proof performance of the metal wire braided layer, reduce the scrap rate, extend the service life of optical cables, effectively reduce after-sales maintenance costs for enterprises, and enhance brand reputation. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the forming control process of a metal wire braided rodent-proof optical cable provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of another metal wire braided rodent-proof optical cable forming control process provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of another metal wire braided rodent-proof optical cable forming control process provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of a metal wire braided rodent-proof optical cable forming control system provided in an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Reference Figure 1 The present invention provides a flowchart of a method for controlling the forming of a metal wire braided rodent-proof optical cable, comprising the following steps: S1, acquire the commanded speed of the main traction motor, the actual speed of the spindle drive motor, and the measured value of the linear speed encoder; S2, calculate the theoretical expected linear speed based on the commanded speed, the actual rotational speed, and the production line parameters; S3, obtain the deviation between the measured value and the theoretical expected linear velocity, determine whether the deviation exceeds a preset deviation threshold and is a negative deviation within a preset time period; if so, identify whether the linear velocity encoder is slipping. S4, if so, then the theoretically expected linear velocity and the historical trend data of the linear velocity encoder are fused together to obtain a fused velocity value as the input for tension control; S5, Adjust the wire tension according to the input of the tension control.

[0020] The metal wire braided rodent-proof optical cable forming control method proposed in this application aims to solve the problem of inaccurate tension control caused by various dynamic interferences in the prior art. The "main traction motor" is the core power unit driving the optical cable forward on the production line, and its "command speed" is the speed at which the system expects the optical cable to move. The "spindle drive motor" is responsible for driving the spindles wound with metal wire to rotate, and its "actual rotational speed" reflects the speed at which the metal wire is braided into the optical cable. The "linear speed encoder" is a sensor that "measures" the actual linear speed of the optical cable through rollers that maintain contact with the optical cable or drive shaft. These parameters are the basic data for precise tension control.

[0021] In its implementation, this method first requires acquiring the commanded speed of the main traction motor, the actual rotational speed of the spindle drive motor, and the measured value from the linear speed encoder. This data can be acquired in real time via their respective sensors or control interfaces. For example, the commanded speed of the main traction motor can be directly read from the host computer control system; the actual rotational speed of the spindle drive motor can be obtained through a rotary encoder mounted on the motor shaft; and the measured value from the linear speed encoder is calculated from the pulse signal generated when its rollers contact and rotate with the optical cable.

[0022] Next, the theoretical expected linear velocity is calculated based on the commanded speed, actual rotational speed, and production line parameters. Production line parameters may include the diameter of the optical cable, the transmission ratio of the braiding machine, and the winding radius of the spindle. The theoretical expected linear velocity can be calculated in the following ways: for example, it can be estimated based on the commanded speed of the main traction motor and the total transmission ratio of the production line, or it can be extrapolated based on the actual rotational speed of the spindle drive motor and the winding diameter of the wire. As a preferred embodiment, the commanded speed of the main traction motor can be simply used as the theoretical expected linear velocity, assuming the transmission system is ideal. As another preferred embodiment, the theoretically expected linear velocity of the wire can be calculated using geometric relationships based on the actual rotational speed of the spindle drive motor and the winding diameter of the wire, combined with parameters such as the braiding pitch.

[0023] Subsequently, the deviation between the measured value and the theoretically expected linear velocity is obtained, and it is determined whether this deviation exceeds a preset deviation threshold and is a negative deviation within a preset time period. The deviation between the measured value and the theoretically expected linear velocity can be obtained directly by subtracting the two. The preset deviation threshold is an empirical value used to determine whether the deviation is significant. The preset time period is used to ensure the persistence of the deviation and avoid misjudging instantaneous fluctuations. A negative deviation means that the speed measured by the linear velocity encoder is lower than the theoretically expected speed. For example, this can be determined by comparing the difference between the current measured value and the theoretically expected linear velocity and checking whether this difference is less than the negative preset deviation threshold, and whether this state has lasted for at least a preset time period, such as 2 seconds.

[0024] If so, the system identifies whether the linear speed encoder is slipping. When the above deviation condition is met, the system further determines whether the linear speed encoder has actually slipped. For example, other relevant parameters can be analyzed to assist in the judgment. As a preferred implementation, it can be simply assumed that as long as the deviation condition is met, there is a possibility of slippage. As another preferred implementation, additional sensors or logic can be introduced, for example, monitoring the friction between the encoder roller and the optical cable, or using image recognition technology to determine whether there are abnormal signs of slippage on the roller surface.

[0025] If encoder slippage is confirmed, the theoretically expected linear speed and the historical trend data of the encoder are fused to obtain a fused speed value, which is then used as the input for tension control. The purpose of this fusion is to use a more reliable data source to correct the speed input when encoder slippage occurs, thereby stabilizing tension control. For example, a weighted average method can be used for fusion, where the theoretically expected linear speed and historical trend data are assigned different weights. The historical trend data can be the average value or variation pattern obtained from long-term monitoring of the linear speed encoder under normal operating conditions. As a preferred implementation, the theoretically expected linear speed can be simply used as the fused speed value, completely ignoring the encoder measurement value during slippage. As another preferred implementation, the theoretically expected linear speed can be fine-tuned based on historical data to better reflect the actual situation.

[0026] Finally, the wire tension is adjusted based on the input to the tension control system. The fusion speed value serves as the input to the tension control system. Based on the deviation between this input and the target tension, the system adjusts the output of the main traction motor or spindle drive motor using a PID controller or other control algorithm, thereby changing the wire tension. For example, if the fusion speed value indicates that the current speed is too low, the system may appropriately increase the speed of the main traction motor to tighten the wire; conversely, if the speed is too high, it may decrease the speed.

[0027] Compared with existing technologies, the advantage of this application lies in its intelligent identification and adaptive correction capabilities for linear speed encoder slippage. Traditional methods often directly use encoder measurements for tension feedback control. When the encoder slips, erroneous speed signals can lead to misjudgments by the control system, resulting in tension fluctuations or even a vicious cycle. This application, by introducing slippage identification and data fusion mechanisms, can effectively filter out interference caused by slippage, providing more accurate tension control input. Therefore, even under complex operating conditions such as differences in metal wire materials between different batches, frequent product model changes, and equipment wear, it can still maintain precise and stable metal wire tension, significantly improving the production quality and reliability of optical cables and reducing scrap rates and after-sales maintenance costs.

[0028] In some embodiments of this application, when the deviation between the measured value and the theoretically expected linear speed exceeds a preset deviation threshold and is a negative deviation within a preset time period, it is identified whether the linear speed encoder is slipping. However, relying solely on speed deviation for slippage identification may not accurately distinguish between the actual speed drop caused by encoder slippage and the instantaneous speed fluctuations caused by changes in other production line conditions, potentially leading to misjudgments or missed judgments, thus affecting the accuracy of tension control.

[0029] In this regard, refer to Figure 2 This application further proposes that S3 includes: S31, when the negative deviation exists, obtain the internal temperature and operating current of the main traction motor; calculate the expected current after temperature compensation based on the internal temperature; S32, obtain the current difference between the operating current and the expected current after temperature compensation; S33, if the current difference does not exceed the preset fluctuation threshold, then the linear speed encoder is identified as slipping.

[0030] Specifically, when the negative deviation exists, the system acquires the internal temperature and operating current of the main traction motor 100. The internal temperature can be understood as the core temperature of the motor during operation, reflecting the motor's load condition and heat dissipation. The operating current is the actual current consumed by the motor, directly related to the motor's output torque and power. The internal temperature can be acquired using a temperature sensor built into the main traction motor 100, while the operating current can be obtained through a current sensor or the feedback interface of the motor driver.

[0031] Furthermore, based on the internal temperature, the expected current after temperature compensation is calculated. The expected current after temperature compensation refers to the operating current that the main traction motor 100 should have under normal, slippage-free conditions at the current internal motor temperature. Since the motor's internal resistance changes with temperature, the current under the same load will differ; therefore, temperature compensation is necessary to obtain a more accurate expected current value. This calculation can be performed using a preset motor temperature-current characteristic curve or model to ensure the accuracy of the expected current.

[0032] Subsequently, the current difference between the operating current and the temperature-compensated expected current is obtained. This current difference reflects the discrepancy between the actual operating state of the motor and the theoretically expected state. If the linear speed encoder slips, the resistance of the optical cable to the main traction motor 100 will decrease, resulting in a lighter motor load and a corresponding decrease in its operating current. Therefore, by comparing the actual operating current with the temperature-compensated expected current, this load change can be detected more sensitively.

[0033] Finally, if the current difference does not exceed a preset fluctuation threshold, slippage of the linear speed encoder is identified. The preset fluctuation threshold is an allowable range of current fluctuations used to filter out normal motor operating noise or slight load changes. When the current difference is less than this threshold, it indicates that the motor load has not increased significantly, but the linear speed has shown a negative deviation, strongly indicating slippage of the linear speed encoder 100. This threshold can be calibrated based on actual production experience and equipment characteristics to balance detection sensitivity and anti-interference capability.

[0034] This application's solution addresses the potential misjudgment problem of relying solely on linear speed deviation to determine slippage by introducing the internal temperature and operating current of the main traction motor 100 as auxiliary judgment criteria. When the linear speed encoder 100 slips, although the measured linear speed decreases, the actual load on the main traction motor 100 does not increase significantly, and may even be slightly reduced due to slippage. Therefore, by acquiring the internal temperature and operating current of the main traction motor 100 and calculating the expected current after temperature compensation, a current difference reflecting the motor's true load state can be obtained. If this current difference is within the normal fluctuation range, i.e., does not exceed the preset fluctuation threshold, it indicates that the motor load is normal or slightly reduced. However, if the linear speed shows a negative deviation, it can more accurately confirm that the slippage is caused by the linear speed encoder 100, rather than a decrease in the overall production line speed or an abnormal motor load.

[0035] Through the above technical solution, this application can more accurately identify slippage in the linear speed encoder 100. Compared to the judgment method that relies solely on speed deviation, the comprehensive judgment combining the internal temperature of the motor and the operating current effectively avoids the situation where speed fluctuations caused by other factors are misjudged as encoder slippage, thereby improving the accuracy and reliability of slippage identification. This precise identification capability helps to take corrective measures in a timely manner, ensuring the stability of wire tension control, thereby improving the forming quality and production efficiency of wire braided rodent-proof optical cables and reducing the scrap rate.

[0036] In some preferred embodiments, it is assumed that during the optical cable production process, the measured value of the linear speed encoder 100 suddenly exhibits a sustained negative deviation, exceeding a preset deviation threshold. At this time, the system further acquires the internal temperature of the main traction motor 100, for example, 60°C, and its operating current, for example, 15A. According to the preset motor characteristic curve, at an internal temperature of 60°C, the expected current of the main traction motor 100 during normal operation (i.e., the expected current after temperature compensation) should be 15.2A. The calculated current difference is 15A - 15.2A = -0.2A. If the preset fluctuation threshold is ±0.5A, then the current difference of -0.2A does not exceed this threshold. This indicates that although the linear speed decreases, the load on the main traction motor 100 has not increased or decreased significantly, thus accurately determining that the linear speed encoder 100 has slipped, rather than the actual speed decrease or abnormal load of the main traction motor 100. Based on this accurate slippage identification result, the subsequent tension control system can be adjusted in a timely manner to avoid excessive or insufficient tension adjustment due to misjudgment, ensuring the quality of optical cable forming.

[0037] In some embodiments described above in this application, a method is proposed to fuse theoretically predicted linear velocity with historical trend data from the linear velocity encoder to obtain a fused velocity value as input for tension control. However, in actual production, the operating parameters of the production line may change. If a fixed weighting coefficient is used for fusion, the fused velocity value may not accurately reflect the current actual linear velocity, thereby affecting the precise control of the wire tension.

[0038] In this regard, refer to Figure 3 S4 includes: S41, after identifying slippage of the linear speed encoder, obtain the production line operating parameters; S42, dynamically adjust the weighting coefficients of theoretical expected linear speed and historical trend data in the fused speed value based on production line operating parameters; S43, Based on the adjusted weighting coefficients, the theoretically expected linear velocity and historical trend data are integrated to obtain the integrated velocity value; S44 uses the fusion speed value as the input for tension control.

[0039] Specifically, after identifying slippage in the linear speed encoder, the system is configured to acquire production line operating parameters. These parameters can be understood as various real-time operational status data affecting the optical cable forming process, such as optical cable type parameters, wire material parameters, equipment operating load parameters, ambient temperature, and production speed. These parameters reflect the current operating status of the production line.

[0040] Furthermore, based on the acquired production line operating parameters, the system is configured to dynamically adjust the weighting coefficients of the theoretical expected linear velocity and historical trend data in the fused velocity value. This means that the contribution ratio of the theoretical expected linear velocity and historical trend data in calculating the fused velocity value is not fixed, but is adjusted in real time according to the actual operating conditions of the production line. For example, when the production line operating parameters indicate that the theoretical expected linear velocity has high reliability, its weighting coefficient can be appropriately increased; conversely, when historical trend data is more valuable for reference under the current operating conditions, the weighting coefficient of historical trend data can be increased.

[0041] Therefore, based on the adjusted weighting coefficients, the theoretical expected linear velocity and historical trend data are fused to obtain a more accurate and robust fused velocity value. Ultimately, this fused velocity value is used as input for tension control to guide subsequent wire tension adjustments.

[0042] This application's solution addresses the accuracy degradation that can occur with traditional fixed-weight fusion methods when operating conditions change by introducing production line operating parameters and dynamically adjusting the weighting coefficients of theoretically expected linear speed and historical trend data in the fused speed value based on these parameters. Specifically, when linear speed encoder slippage is detected, the system no longer blindly fuses data at a preset ratio. Instead, it intelligently assesses the relative reliability of theoretically expected linear speed and historical trend data based on the current actual operating conditions of the production line. For example, under certain operating conditions, the theoretical model may be more accurate; while under other conditions, historical experience data may be more instructive. By dynamically adjusting the weights, the system ensures that the optimal data fusion strategy is always employed under different production conditions, enabling the fused speed value to more accurately reflect the actual linear speed and providing a more reliable input for subsequent tension control.

[0043] Through the above technical solution, this application can significantly improve the accuracy and robustness of linear speed measurement during the forming process of metal wire braided rodent-proof optical cables. Especially when the operating parameters of the production line change, such as when materials are changed, production speed is adjusted, or equipment load is changed, this solution can adaptively adjust the data fusion strategy to avoid tension control deviations caused by fixed-weight fusion, thereby effectively reducing product defects and improving production efficiency and product quality.

[0044] In some preferred embodiments, a specific example is given below. Suppose that during the production of a braided rodent-proof optical cable, the linear speed encoder detects slippage. At this time, the system acquires the current production line operating parameters, for example, detecting a switch from cable type A to type B, and a change in wire material from copper to aluminum. Due to the change in material and type, historical trend data may differ significantly from the current operating conditions, while the theoretical expected linear speed calculated based on the current production line parameters may be more reliable. In this case, the system dynamically adjusts the weighting coefficients based on these operating parameters; for example, increasing the weighting coefficient of the theoretical expected linear speed to 0.7, while decreasing the weighting coefficient of the historical trend data to 0.3. Subsequently, the system fuses the theoretical expected linear speed and the historical trend data with a weighting ratio of 0.7 and 0.3 to obtain a fused speed value that better reflects the current actual operating conditions. This fused speed value is then input into the tension controller to precisely adjust the wire tension, thereby ensuring that the forming quality of the optical cable is effectively guaranteed even when production conditions change significantly.

[0045] In some embodiments described above, this application proposes dynamically adjusting the weighting coefficients of theoretically expected linear speed and historical trend data in the fusion speed value based on production line operating parameters. However, in its implementation, adjusting the weighting coefficients solely based on instantaneous or short-term production line operating parameters may not adequately address performance drift, equipment aging, or slow changes in environmental factors that occur during long-term production line operation. This results in inaccurate adjustment of the weighting coefficients or failure to reflect the true state of the production line in a timely manner. If these problems are not addressed, the accuracy of the fusion speed value may decrease with prolonged operation, thereby affecting the stability of wire tension control and molding quality.

[0046] In this regard, this application further proposes the following steps for dynamically adjusting the weighting coefficients of theoretically expected linear speed and historical trend data in the fused speed value based on production line operating parameters: Obtain the operating parameters of the production line; Obtain production line uptime; Based on the production line operating parameters and the production line running time, within a preset parameter adjustment cycle, the weighting coefficients of the theoretical expected linear velocity and the historical trend data in the fusion velocity value are periodically evaluated. The weighting coefficients are adjusted based on the evaluation results.

[0047] Specifically, acquiring production line uptime refers to the system continuously recording and updating the cumulative uptime since the production line started or since the last reset. This uptime can be measured in hours, shifts, or production batches, etc., and its purpose is to provide a time-dimensional reference for the evaluation of weighting coefficients, in order to capture changes in the long-term operating status of the production line.

[0048] Based on production line operating parameters and operating time, the system periodically evaluates the weighting coefficients of theoretically expected linear velocity and historical trend data in the fused velocity value within a preset parameter adjustment cycle. This means the system doesn't only adjust weights when operating parameters change significantly, but proactively triggers an evaluation process at preset time intervals (e.g., hourly, per shift, or daily). During this evaluation, the system comprehensively considers current production line operating parameters and accumulated operating time to analyze the effectiveness, accuracy, and adaptability of the currently used weighting coefficients. For example, it can use historical data, machine learning models, or expert rules to determine whether the current weighting coefficients still best reflect the relative reliability of theoretically expected linear velocity and historical trend data under current operating conditions and operating time. The goal is to ensure that the weighting coefficients remain optimal as production line operating time increases and operating conditions change slightly.

[0049] In practical applications, adjusting the weighting coefficients based on the evaluation results involves adjusting or redistributing the weighting coefficients of the theoretical expected linear velocity and historical trend data according to the analysis results obtained from periodic evaluations. For example, if the evaluation results show that the reference value of historical trend data has decreased under the current operating time, its weighting coefficient can be appropriately reduced while the weighting coefficient of the theoretical expected linear velocity is increased, and vice versa. The purpose is to ensure that the fused velocity value can more accurately reflect the actual linear velocity of the production line, thereby providing a more reliable input for tension control.

[0050] This application's solution overcomes the limitations of relying solely on instantaneous operating parameters for weight adjustments by incorporating production line runtime and conducting periodic evaluations. Specifically, production line runtime, as a cumulative indicator, reflects changes that are difficult to capture by instantaneous operating parameters, such as equipment wear, minor variations in material properties, or the long-term impact of environmental factors. By combining production line operating parameters with runtime within a preset parameter adjustment cycle, the system can gain a more comprehensive and in-depth understanding of the production line's current state and evolution trends. The periodic evaluation mechanism ensures that even without drastic changes in operating parameters, the system can proactively check and correct weight coefficients, preventing weight mismatches caused by long-term operation. Consequently, the weight coefficients of theoretically expected linear speed and historical trend data in the fused speed value can more dynamically and accurately adapt to the actual operating conditions of the production line, thereby improving the accuracy and stability of the fused speed value.

[0051] Through the above technical solution, this application effectively solves the problem of lagging or inaccurate adjustment of weighting coefficients in traditional methods. By introducing production line running time as an evaluation basis and combining it with a periodic evaluation mechanism, the adjustment of weighting coefficients can not only respond to instantaneous changes in operating parameters, but also adapt to the cumulative and gradual changes during long-term production line operation. This significantly improves the accuracy and robustness of the fusion speed value, provides a more reliable and stable input for wire tension control, and ultimately helps to improve the quality and efficiency of optical cable forming, and reduce the scrap rate caused by improper tension control.

[0052] In some preferred embodiments, a specific example is given below. Assume a metal wire braided rodent-proof optical cable production line has been running continuously for 8 hours. Initially, because the equipment is in optimal condition, the weighting factor for the theoretically expected linear speed may be set to 0.7, and the weighting factor for historical trend data may be set to 0.3. However, as the running time increases, the equipment may experience slight wear, or environmental factors such as temperature and humidity may change slowly. These changes may cause slight drifts in the linear speed encoder measurements, or a decrease in the fit between the theoretically expected linear speed calculation model and the actual situation.

[0053] In some embodiments described above in this application, a method is proposed to periodically evaluate the weighting coefficients of theoretically expected linear speed and historical trend data in the fusion speed value within a preset parameter adjustment cycle, based on production line operating parameters and production line running time. However, in its implementation, relying solely on periodic evaluation may lead to a lag in the adjustment of the weighting coefficients, failing to respond promptly to instantaneous or drastic changes in production line operating conditions, thereby affecting the accuracy of the fusion speed value and consequently impacting the precision and stability of wire tension control.

[0054] In response, this application further proposes a method for optimizing the aforementioned weighting coefficient evaluation and adjustment mechanism. This method involves periodically evaluating the weighting coefficients of theoretically expected linear velocity and historical trend data in the fusion velocity value within a preset parameter adjustment period, based on production line operating parameters and production line running time. This includes: Continuously monitor the rate of change of the operating parameters of the production line; When the rate of change exceeds a preset instantaneous change threshold, the non-periodic weighting coefficient evaluation is triggered. Adjust the weighting coefficients of the theoretical expected linear velocity and the historical trend data in the fused velocity value based on the current production line operating parameters.

[0055] Specifically, "continuously monitoring the rate of change of the production line operating parameters" refers to the system collecting and analyzing the values ​​of production line operating parameters in real time, such as optical cable type parameters, metal wire material parameters, and equipment operating load parameters, and calculating the magnitude or rate of change of these parameters per unit time. This monitoring can be continuous or high-frequency sampling monitoring to ensure that dynamic changes in parameters can be captured in a timely manner.

[0056] The "preset instantaneous change threshold" is a critical value set based on experience, historical data, or process requirements. It is used to determine whether changes in production line operating parameters have reached a level requiring immediate response. When the monitored rate of change exceeds this threshold, it indicates that significant and unexpected fluctuations or changes have occurred in the production line operating conditions. In practical applications, "triggering aperiodic weighting coefficient evaluation" means that once the rate of change is detected to exceed the preset instantaneous change threshold, the system will immediately initiate the weighting coefficient evaluation process without waiting for the next preset parameter adjustment cycle. This aperiodic evaluation mechanism aims to improve the system's response speed to sudden changes in operating conditions.

[0057] Furthermore, "adjusting the weighting coefficients of the theoretical expected linear velocity and the historical trend data in the fused velocity value based on the current production line operating parameters" means that after triggering a non-periodic evaluation, the system will recalculate or find weighting coefficients applicable to the current operating conditions based on the current production line operating parameters. For example, when the operating parameters indicate that the production line is in an unstable state, the weight of the theoretical expected linear velocity may be increased to provide a more stable benchmark; conversely, when the operating conditions are stable, the weight of the historical trend data may be increased to utilize its long-term accumulated experience.

[0058] This application's solution introduces continuous monitoring of the rate of change of production line operating parameters and sets instantaneous change thresholds, enabling the system to proactively identify and respond to sudden or drastic changes in production line conditions. When the rate of change of operating parameters exceeds the preset threshold, the system no longer passively waits for periodic evaluation but immediately triggers a non-periodic weighting coefficient evaluation. Therefore, the adjustment of the weighting coefficients can more promptly reflect the current actual production status, avoiding tension control deviations caused by the lag in periodic evaluations. It is precisely because of this instantaneous response mechanism that the fused speed value can more accurately reflect the actual line speed, thus providing a more reliable input for wire tension control.

[0059] Through the above technical solution, this application can significantly improve the adaptability and robustness of the metal wire braided rodent-proof optical cable forming control system to changes in production line conditions. Especially when instantaneous changes occur during production, such as fluctuations in raw material characteristics, sudden changes in equipment load, or adjustments to process parameters, the system can quickly adjust the weighting coefficients of theoretically expected linear speed and historical trend data in the fused speed value, ensuring that the accuracy of the fused speed value is not affected. As a result, the precision and stability of metal wire tension control are greatly improved, effectively avoiding problems such as tension runaway and product quality degradation caused by sudden changes in operating conditions, thereby ensuring the continuity of the optical cable forming process and the consistency of product quality.

[0060] As a specific implementation method, a concrete example is given below. Suppose that during the optical cable production process, due to a supplier change, the elastic modulus and diameter of the new batch of metal wire materials exhibit slight but significant differences. Under a traditional periodic evaluation mechanism, the system may need to wait for the next preset parameter adjustment cycle to identify and adjust the weighting coefficients. During this period, due to inaccurate input (fusion speed value) for metal wire tension control, uneven tightness in the optical cable braiding may occur, or even wire breakage. However, in the solution of this application, the system continuously monitors the production line operating parameters, including the rate of change of metal wire material parameters. When a new batch of metal wire is put into use, its material parameter change rate will rapidly exceed the preset instantaneous change threshold. At this time, the system will immediately trigger a non-periodic weighting coefficient evaluation. Based on the currently detected metal wire material parameters, the system will dynamically adjust the weighting coefficients of theoretically expected linear velocity and historical trend data in the fusion speed value. For example, the weight of theoretically expected linear velocity may be temporarily increased to quickly adapt to new material properties, or the weight contribution of historical trend data may be adjusted according to the new material parameters. Through this instant response and adjustment, the fusion speed value can quickly adapt to new working conditions, thereby ensuring the accuracy and stability of wire tension control, avoiding production problems caused by material changes, and guaranteeing the quality of optical cable products.

[0061] In some embodiments described above, when the rate of change of production line operating parameters exceeds a preset instantaneous change threshold, a non-periodic weighting coefficient evaluation is triggered, and the weighting coefficients of the theoretically expected linear velocity and historical trend data in the fusion speed value are adjusted according to the current production line operating parameters. However, in actual production, changes in production line operating parameters may have different natures and degrees of impact. If a uniform weighting adjustment is made solely based on the current operating parameters, it may not be sufficient to cope with various complex and changing operating conditions, especially when facing drastic changes. This could lead to insufficient accuracy and response speed of the fusion speed value, thereby affecting the stability of wire tension control and molding quality.

[0062] In response, this application further proposes a method for adjusting the weighting coefficients of theoretically expected linear velocity and historical trend data in the fused velocity value based on current production line operating parameters, specifically including: Determine the type of change in the current production line operating parameters; If the change type is a drastic change type, then the weighting coefficient of the theoretical expected linear velocity is set to a preset high weighting value; The weighting coefficients of the historical trend data are set to preset low weighting values.

[0063] Specifically, determining the type of change in current production line operating parameters involves a comprehensive analysis of various operating parameters affecting the optical cable forming process to identify the nature and potential impact of these changes. These operating parameters may include, but are not limited to, optical cable type parameters, wire material parameters, and equipment operating load parameters. Through real-time monitoring and analysis of these parameters, changes of different degrees and types can be distinguished, such as slight fluctuations, gradual changes, or drastic changes. Dramatic changes typically refer to rapid and significant parameter fluctuations that have a substantial impact on the stability of the production process, such as sudden acceleration of the production line, major batch changes in materials, or a sharp increase in equipment load.

[0064] When the change in production line operating parameters is identified as a drastic change, this application sets the weight coefficient of the theoretical expected linear velocity to a preset high weight value and the weight coefficient of historical trend data to a preset low weight value. The theoretical expected linear velocity is calculated based on the commanded speed of the main traction motor, the actual speed of the spindle drive motor, and production line parameters. It can reflect the current theoretical operating state and control commands of the production line in real time. Under drastic operating conditions, the production line state may deviate rapidly from historical norms. In this case, the linear velocity calculated based on the current theory more accurately reflects the immediate operating conditions, so it is given a high weight value to ensure that the fused velocity value can quickly respond to the current actual production needs. Conversely, although historical trend data has reference value under stable operating conditions, it may have lag or be inconsistent with the current operating conditions during drastic changes. Therefore, its weight is reduced to avoid negatively impacting the accuracy of the fused velocity value. The preset high and low weight values ​​can be set according to actual production experience and system debugging results to achieve the best control effect.

[0065] This application's solution effectively addresses the problem of insufficient accuracy and response speed of the fused speed value, which can occur under complex and variable operating conditions, especially when facing sudden and significant changes in operating conditions, by introducing a judgment on the type of change in production line operating parameters and adopting a differentiated weight adjustment strategy for drastic changes. This is because the system can intelligently identify and prioritize the theoretically expected linear velocity, which better reflects the real-time operating conditions, while reducing the interference of historical trend data during drastic changes. This allows the fused speed value to more quickly and accurately approximate the actual linear velocity, providing a more reliable input for subsequent wire tension control.

[0066] Through the above technical solution, this application can significantly improve the adaptability and robustness of the metal wire braided rodent-proof optical cable forming control system in the face of drastic changes in operating conditions. By intelligently judging the type of change and dynamically adjusting the weighting coefficients, the system can ensure that when drastic changes occur on the production line, the input signal of tension control can quickly and accurately reflect the current actual operating conditions, thereby effectively avoiding problems such as metal wire breakage, uneven braiding, or decreased optical cable forming quality caused by lagging or inaccurate tension control. This not only improves production efficiency and product qualification rate, but also reduces equipment failure rate and maintenance costs, providing a more stable and reliable guarantee for optical cable production.

[0067] In some preferred embodiments, a specific example is given below. Suppose that during the production of braided rodent-proof optical cables, the production line suddenly switches from a low-speed to a high-speed operating mode, or the cable type changes from a thin-diameter cable to a thick-diameter cable. This is identified by the system as a drastic change. At this time, the control system immediately determines that the change in the current production line operating parameters is a drastic change. For example, the system may detect a significant increase in the commanded speed of the main traction motor within a short period, or a significant change in the cable type parameters. Based on this determination, the system sets the weighting coefficient of the theoretically expected linear speed to a preset high weighting value, such as 0.8, while setting the weighting coefficient of historical trend data to a preset low weighting value, such as 0.2. Therefore, in the calculation of the fused speed value, the theoretically expected linear speed will dominate, enabling the fused speed value to quickly track drastic changes in the production line speed. This ensures that the wire tension control can be adjusted in a timely and accurate manner, avoiding tension imbalance caused by sudden speed changes and guaranteeing the stability of the optical cable forming quality.

[0068] In some embodiments of this application, in order to effectively adjust the weighting coefficients of theoretically expected linear velocity and historical trend data in the fused velocity value when production line operating parameters change drastically, it is necessary to accurately determine the type of change in the current production line operating parameters. However, production line operating parameters are complex and diverse, and may influence each other. Simply determining their type of change may lead to misjudgment, thereby affecting the accuracy of tension control. Therefore, this application further proposes a method for determining the type of change in the current production line operating parameters, which specifically includes: Obtain operating parameters from multiple production lines, including optical cable type parameters, metal wire material parameters, and equipment operating load parameters; Based on the operating parameters, set the corresponding preset threshold and rate of change threshold; When the change value of any of the operating condition parameters exceeds the preset change threshold, the any operating condition parameter is marked as a potential dominant change parameter. Based on preset priority rules and mutual influence matrix, identify the currently dominant change type.

[0069] Specifically, during the production process, it is necessary to continuously acquire operating parameters from multiple production lines. These parameters can cover multiple dimensions affecting the optical cable forming process. For example, optical cable model parameters can indicate the specifications and structure of the optical cable currently being produced; wire material parameters can reflect the material, diameter, strength, and other characteristics of the wire used; and equipment operating load parameters can reflect the real-time operating status of key equipment such as the main traction motor and spindle drive motor, such as power consumption and speed fluctuations. Accurate acquisition of these parameters is the basis for subsequent judgments.

[0070] Based on the acquired operating parameters, corresponding preset thresholds and rate of change thresholds can be set for each parameter. The preset thresholds are used to determine whether the absolute value of the parameter is within the normal range, while the rate of change thresholds are used to determine whether the magnitude of the parameter's change within a unit of time is abnormal. These thresholds can be set based on historical production data, expert experience, or process requirements, and can be dynamically adjusted according to actual production conditions.

[0071] In practical applications, when the deviation between the real-time monitored value of any operating condition parameter and its historical benchmark value or set target value—that is, its change value—exceeds a preset change threshold, that operating condition parameter is marked as a potentially dominant change parameter. This means that the parameter may be undergoing significant changes and could have a significant impact on the entire production process. For example, changes in optical cable model parameters or significant fluctuations in metal wire material parameters may both result in this flag.

[0072] Furthermore, to identify the true dominant change type from multiple potential dominant change parameters, pre-defined priority rules and inter-parameter interaction matrices can be used. Priority rules can rank changes in different operating parameters based on experience or importance; for example, changes in some parameters may be considered more decisive than others. Inter-parameter interaction matrices describe the degree and direction of interaction between different operating parameters; for example, a change in one parameter may lead to a chain reaction in another. By comprehensively applying these rules and matrices, the main change type currently facing the production line can be more accurately determined, such as whether the change is due to material replacement, equipment failure, or process adjustment.

[0073] This application's solution systematically acquires and analyzes multiple key production line operating parameters, and combines them with preset thresholds, priority rules, and a mutual influence matrix to accurately identify the types of changes in production line operating parameters. Traditional methods may rely solely on a single parameter or simple threshold, easily overlooking the complex relationships between parameters and leading to misjudgments of the causes of changes. This solution incorporates multiple dimensions, such as optical cable model parameters, metal wire material parameters, and equipment operating load parameters, and introduces a comparison between the changed values ​​and preset thresholds, enabling the initial screening of potential dominant change factors. More importantly, by introducing priority rules and a mutual influence matrix, this solution can deeply analyze the intrinsic connections and influence weights among these potential factors, thereby accurately identifying the current dominant change type in a complex and ever-changing production environment. This refined identification mechanism provides a solid foundation for subsequent targeted adjustments to weight coefficients based on the change type, avoiding the negative impacts of blind adjustments.

[0074] The above technical solution overcomes the potential bias and inaccuracy of traditional methods in determining the types of changes in production line operating parameters. This solution significantly improves the accuracy and robustness of identifying the types of changes in production line operating parameters by acquiring and analyzing multi-dimensional parameters, combining dynamic threshold settings, and utilizing priority rules and mutual influence matrices. This ensures that when production line conditions change, the nature and cause of the change can be determined promptly and accurately, providing a reliable basis for adjusting the weighting coefficients of theoretically expected linear speed and historical trend data in the fused speed value. This precise judgment helps avoid tension control instability or efficiency decline due to misjudgment, thereby improving the overall stability and product quality of the metal wire braided rodent-proof optical cable forming process.

[0075] In some embodiments described above, preset priority rules and interrelationship matrices are used to identify the dominant change type. However, in actual production, production line operating parameters may continuously change; for example, factors such as optical cable type parameters, wire material parameters, or equipment operating load parameters may all change. In this dynamic environment, static preset priority rules and interrelationship matrices may not be fully adaptable to all operating conditions, affecting the accuracy and adaptability of identifying the dominant change type, and consequently impacting the precision of wire tension control.

[0076] In response, this application further proposes the method for identifying the currently dominant change type based on preset priority rules and a mutual influence matrix, including: Within a preset parameter adjustment period, the applicability of the priority rules and the mutual influence matrix is ​​periodically evaluated; If the priority rule or the mutual influence matrix conflicts with the current operating condition, the priority rule or the mutual influence matrix is ​​adjusted according to the conflict, and the currently dominant change type is identified based on the adjustment result.

[0077] Specifically, "periodically evaluating the applicability of the priority rules and the interaction matrix" means that at preset time intervals, the system checks the currently used priority rules and interaction matrix to determine whether they can still accurately reflect the actual operating conditions of the production line and the interaction relationships between parameters. Here, "applicability" can be understood as whether these rules and matrices can effectively and accurately guide the identification of the dominant change type under the current operating conditions.

[0078] "If the priority rule or the interaction matrix conflicts with the current operating condition" means that when the evaluation results show that the current priority rule or interaction matrix differs significantly from the actual behavior or expected results of the production line in actual application, for example, the dominant change parameter identified according to the rule does not match the main influencing factors actually observed, or it leads to unreasonable tension adjustment results.

[0079] "Adjusting the priority rules or the mutual influence matrix based on the conflict" means that once a conflict is identified, the system will modify or update the priority rules or mutual influence matrix according to the specific manifestation and degree of the conflict. For example, the priority order of certain parameters can be adjusted, the influence weights between parameters or between parameters and tension can be modified, or new association rules can be introduced. The purpose is to make these rules and matrices better adaptable to the current production conditions and improve the accuracy of identifying the dominant change type.

[0080] This application's solution effectively addresses the problem of insufficient adaptability of preset rules under dynamic operating conditions by introducing a periodic evaluation and dynamic adjustment mechanism for priority rules and mutual influence matrix. Specifically, within a preset parameter adjustment cycle, the system continuously monitors changes in production line operating parameters and evaluates the applicability of the priority rules and mutual influence matrix used to identify dominant change types. When the evaluation finds a conflict between these rules or matrices and the current actual operating conditions—for example, when the dominant change type identified according to existing rules does not match the actual production line performance—the system can promptly identify this mismatch. Therefore, the system will adjust the priority rules or mutual influence matrix accordingly based on the identified conflict, ensuring that they always accurately reflect the actual operating characteristics of the current production line. It is precisely this adaptive adjustment capability that makes the identification process of dominant change types more accurate and robust, thus providing a more reliable input for subsequent wire tension control.

[0081] Through the above technical solution, this application enables dynamic optimization of the priority rules and mutual influence matrix used to identify dominant change types. Compared to using fixed preset rules, this solution allows the system to maintain high adaptability and accuracy even when faced with continuous changes in production line operating parameters such as optical cable model parameters, wire material parameters, or equipment operating load parameters. Therefore, the identification of dominant change types will be more accurate, avoiding misjudgments caused by lagging or inapplicable rules, thus ensuring the precision and stability of wire tension control, and ultimately significantly improving the forming quality and production efficiency of braided rodent-proof optical cables.

[0082] As a specific implementation method, a concrete example is given below. Suppose that on a certain optical cable production line, a set of priority rules and mutual influence matrix were initially set based on experience, in which "optical cable model parameters" were given a higher priority. In the early stages of production, this set of rules worked well. However, as the production line operated for a long time, some equipment components experienced slight wear, causing the impact of "equipment operating load parameters" on the stability of the linear speed to become more significant, even exceeding the impact of "optical cable model parameters".

[0083] In this scenario, the system periodically evaluates the applicability of the priority rules and the mutual influence matrix within a preset parameter adjustment cycle. The evaluation results may show that when the "equipment operating load parameters" undergo specific changes, the system still identifies the "optical cable model parameters" as the dominant changing parameter according to the original priority rules. However, the actually observed tension fluctuations are more correlated with the changes in the "equipment operating load parameters." At this point, the system recognizes a conflict between the priority rules and the current operating condition.

[0084] Based on the aforementioned conflict, the system will trigger an adjustment mechanism. For example, the system can reassess the impact weight of each operating condition parameter on tension control based on historical data analysis or machine learning models, and adjust the priority rules, increasing the priority of the "equipment operating load parameter," or modifying the correlation strength between the "equipment operating load parameter" and other parameters in the mutual influence matrix. Through this dynamic adjustment, the system can more accurately identify the current dominant change type, such as identifying the "equipment operating load parameter" as the main cause of tension fluctuations. Therefore, subsequent tension control strategies can be adjusted accordingly, effectively maintaining the stability of the wire tension and ensuring the quality of optical cable forming.

[0085] In some of the embodiments described above in this application, the applicability of the priority rules and the mutual influence matrix is ​​periodically evaluated within a preset parameter adjustment period. However, in the implementation process, how to conduct an effective and comprehensive evaluation to ensure that the adopted rules and matrix can accurately reflect the current production conditions is a problem that needs further refinement.

[0086] In response, this application further proposes the following: periodically evaluating the applicability of the priority rule and the mutual influence matrix within a preset parameter adjustment period, including: Obtain the dominant change types under different priority rules and mutual influence relationship matrices in historical production data, and identify the corresponding accuracy and stability indicators; Gain experience and judgment under different working conditions; Based on the accuracy, the stability index, and the empirical judgment, the priority rule and the mutual influence matrix are scored using a multi-dimensional weighted score. Based on the multi-dimensional weighted scoring results, determine the applicability of the priority rules and the mutual influence matrix.

[0087] Specifically, acquiring the dominant change types under different combinations of priority rules and interrelationship matrices in historical production data, and identifying the corresponding accuracy and stability indicators, means that the system traces and analyzes past production records. This historical production data includes various combinations of priority rules and interrelationship matrices used by the system under different production conditions, as well as the dominant change types identified under these combinations. By comparing these identification results with actual production line changes, the accuracy of each combination can be calculated, i.e., the degree to which the identification results match the actual situation. Simultaneously, stability indicators can be evaluated, such as the consistency or volatility of identification results under similar conditions, to measure its reliability at different points in time or in different batches of production. The aim is to objectively evaluate the historical performance of different rule and matrix combinations through quantitative analysis.

[0088] The acquisition of experiential judgments under different operating conditions can be understood as collecting and integrating the professional knowledge and practical experience from senior engineers, production experts, or operators. These experiential judgments are typically based on their long-term observation of the production process, in-depth understanding of equipment characteristics, and intuitive perception of abnormal situations. For example, an expert might determine, based on the characteristics of a certain fiber optic cable model or metal wire material, whether a particular priority rule or interrelationship matrix might perform better or pose a potential risk under specific load parameters. The aim is to introduce qualitative expert wisdom into the evaluation process, compensating for the potential limitations of pure data analysis.

[0089] In practical applications, the priority rules and the mutual influence matrix are weighted and scored in multiple dimensions based on the accuracy, stability indicators, and empirical judgments. Specifically, this involves comprehensively considering the quantitative indicators (accuracy, stability) and qualitative judgments (empirical judgments) obtained above, and assigning a comprehensive score to each combination of priority rules and mutual influence matrices. When performing weighted scoring, different weight coefficients can be set for different dimensions according to actual needs and evaluation priorities. For example, in scenarios with extremely high product quality requirements, the weight of accuracy may be set to a higher value; while in scenarios where stable production processes are prioritized, the weight of stability indicators may be higher. The weight of empirical judgments can be adjusted according to their reliability and importance. The aim is to provide a comprehensive, objective, and flexible evaluation framework.

[0090] Therefore, judging the applicability of the priority rules and the mutual influence matrix based on the multi-dimensional weighted scoring results involves comparing the calculated comprehensive score with a preset applicability threshold. If the comprehensive score of a combination of a priority rule and the mutual influence matrix is ​​higher than the preset threshold, it is considered to have good applicability under the current or similar working conditions; conversely, if the score is lower than the threshold, it may indicate a decrease in applicability, requiring optimization or adjustment. The purpose is to provide the system with a clear decision-making basis to determine whether the existing priority rules and mutual influence matrix need to be updated.

[0091] This application's solution obtains the dominant change types under different combinations of priority rules and mutual influence matrices in historical production data, and identifies the corresponding accuracy and stability indicators, thus objectively quantifying the performance of these rules and matrices in practical applications. Simultaneously, by acquiring empirical judgments under different operating conditions, it introduces expert knowledge and practical wisdom, compensating for the potential limitations of pure data analysis. Multi-dimensional weighted scoring based on accuracy, stability indicators, and empirical judgments makes the evaluation of priority rules and mutual influence matrices more comprehensive and scientific. Therefore, it can more accurately determine whether the currently adopted priority rules and mutual influence matrices are still applicable to the current production conditions, thereby providing a reliable basis for subsequent adjustments.

[0092] The above technical solution enables a refined, multi-dimensional evaluation of the applicability of priority rules and interrelationship matrices. Compared to relying solely on a single indicator or empirical judgment, this solution combines the objectivity of historical data analysis with the professionalism of expert judgment, resulting in more comprehensive, accurate, and reliable evaluation results. This helps to promptly identify and correct inapplicable rules and matrices, ensuring that the system can more accurately and quickly identify the dominant change type when production line conditions change. This provides more precise input for subsequent tension control, effectively improving the stability and product quality of the metal wire braided rodent-proof optical cable forming process.

[0093] Reference Figure 4 The present invention provides a structural diagram of a metal wire braided rodent-proof optical cable forming control system, comprising: The detection end is used to acquire the commanded speed of the main traction motor, the actual speed of the spindle drive motor, and the measured value of the linear speed encoder. The identification end is used to calculate the theoretical expected linear speed based on the commanded speed, the actual rotation speed, and the production line parameters; obtain the deviation between the measured value and the theoretical expected linear speed; determine whether the deviation exceeds a preset deviation threshold and is a negative deviation within a preset time period; if so, identify whether the linear speed encoder is slipping. The fusion end is used to fuse the theoretically expected linear velocity with the historical trend data of the linear velocity encoder if the condition is met, and obtain a fused velocity value as the input for tension control; and adjust the wire tension according to the input for tension control.

[0094] It should be noted that the metal wire braided rodent-proof optical cable forming control system provided in this embodiment of the invention is used to execute all the process steps of the metal wire braided rodent-proof optical cable forming control method in the above embodiment. The working principle and beneficial effects of the two are one-to-one, so they will not be described again.

[0095] This invention also provides a terminal device. The terminal device includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the above-described embodiments of the metal wire braided rodent-proof optical cable forming control method, for example... Figure 1 The step S11 shown. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the above system embodiments.

[0096] It should be noted that the system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the system embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0097] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method of forming control of a metal wire braided rodent resistant optical cable, characterized by, The method comprises: obtaining an instruction speed of a main traction motor, an actual rotating speed of a spindle driving motor and a measured value of a linear speed encoder; calculating a theoretical expected linear speed according to the instruction speed, the actual rotating speed and production line parameters; obtaining a deviation of the measured value from the theoretical expected linear speed, judging whether the deviation exceeds a preset deviation threshold and is a negative deviation in a preset time period, and if so, identifying whether the linear speed encoder slips; if so, fusing the theoretical expected linear speed and historical trend data of the linear speed encoder to obtain a fused speed value as an input of tension control; adjusting a wire tension according to the input of the tension control.

2. The metal wire braiding ratproof optical cable forming control method according to claim 1, characterized in that, The if so, identifying whether the linear speed encoder slips comprises: when the negative deviation exists, obtaining an internal temperature and an operating current of the main traction motor; calculating a temperature-compensated expected current according to the internal temperature; obtaining a current difference between the operating current and the temperature-compensated expected current; if the current difference does not exceed a preset fluctuation threshold, identifying that the linear speed encoder slips.

3. The method of claim 1, wherein the metal wire braided rodent-proof optical cable forming control method is characterized by, The if so, fusing the theoretical expected linear speed and historical trend data of the linear speed encoder to obtain a fused speed value as an input of tension control comprises: after identifying that the linear speed encoder slips, obtaining production line working condition parameters; dynamically adjusting weight coefficients of the theoretical expected linear speed and the historical trend data in the fused speed value according to the production line working condition parameters; fusing the theoretical expected linear speed and the historical trend data according to the adjusted weight coefficients to obtain the fused speed value; taking the fused speed value as the input of the tension control.

4. The metal wire braiding ratproof optical cable forming control method according to claim 3, characterized in that, The dynamically adjusting weight coefficients of the theoretical expected linear speed and the historical trend data in the fused speed value according to the production line working condition parameters comprises: obtaining the production line working condition parameters; obtaining a production line operating time; periodically evaluating the weight coefficients of the theoretical expected linear speed and the historical trend data in the fused speed value in a preset parameter adjustment period according to the production line working condition parameters and the production line operating time; adjusting the weight coefficients according to an evaluation result.

5. A method of forming a rodent-resistant optical cable according to claim 4, wherein The periodically evaluating the weight coefficients of the theoretical expected linear speed and the historical trend data in the fused speed value in a preset parameter adjustment period according to the production line working condition parameters and the production line operating time comprises: continuously monitoring a change rate of the production line working condition parameters; when the change rate exceeds a preset instantaneous change threshold, triggering aperiodic weight coefficient evaluation; adjusting the weight coefficients of the theoretical expected linear speed and the historical trend data in the fused speed value according to current production line working condition parameters.

6. A method of forming a rodent-resistant optical cable according to claim 5, wherein The adjusting the weight coefficients of the theoretical expected linear speed and the historical trend data in the fused speed value according to current production line working condition parameters comprises: judging a change type of current production line working condition parameters; if the change type belongs to a drastic change type, setting a weight coefficient of the theoretical expected linear speed to a preset high weight value; The weight coefficient of the historical trend data is set as a preset low weight value.

7. A method of forming a rodent-resistant optical cable according to claim 6, wherein The judgment of the change type of the current production line working condition parameter includes: Obtaining working condition parameters of multiple production lines, the working condition parameters including optical cable model parameters, wire material parameters, and equipment running load parameters; According to the working condition parameters, corresponding preset threshold values and change rate threshold values are set; When the change value of any working condition parameter exceeds the preset change threshold value, any working condition parameter is marked as a potential dominant change parameter; According to the preset priority rule and the mutual influence relationship matrix, the current dominant change type is identified.

8. The method of claim 7, wherein the metal wire braided rodent-proof optical cable forming control method is characterized by, According to the preset priority rule and the mutual influence relationship matrix, the current dominant change type is identified, including: Periodically evaluating the applicability of the priority rule and the mutual influence relationship matrix within a preset parameter adjustment period; If the priority rule or the mutual influence relationship matrix conflicts with the current working condition, the priority rule or the mutual influence relationship matrix is adjusted according to the conflict, and the current dominant change type is identified according to the adjustment result.

9. The method of claim 8, wherein the metal wire braided rodent-proof optical cable forming control method is characterized by, Periodically evaluating the applicability of the priority rule and the mutual influence relationship matrix within a preset parameter adjustment period includes: Obtaining the dominant change type under different priority rule and mutual influence relationship matrix combinations in historical production data, and identifying corresponding accuracy and stability indicators; Obtaining experience judgments of different working conditions; According to the accuracy, the stability indicators, and the experience judgments, the priority rule and the mutual influence relationship matrix are multi-dimensionally weighted and scored; According to the multi-dimensionally weighted scoring results, the applicability of the priority rule and the mutual influence relationship matrix is judged.

10. A metal wire braided rodent resistant optical cable forming control system, characterized by, The system includes: A detection end is configured to obtain an instruction speed of a main traction motor, an actual rotating speed of a spindle driving motor, and a measurement value of a linear speed encoder; An identification end is configured to calculate a theoretical expected linear speed according to the instruction speed, the actual rotating speed, and production line parameters, obtain a deviation between the measurement value and the theoretical expected linear speed, judge whether the deviation exceeds a preset deviation threshold value and is a negative deviation in a preset time period, and identify whether the linear speed encoder is slipping if the deviation exceeds the preset deviation threshold value and is the negative deviation; A fusion end is configured to fuse the theoretical expected linear speed and historical trend data of the linear speed encoder and obtain a fusion speed value as an input of tension control if the linear speed encoder is slipping; According to the input of the tension control, the wire tension is adjusted.

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