Cable production quality intelligent monitoring method and system

Abstract

The invention discloses an intelligent monitoring method and system for cable production quality, and relates to the technical field of cable quality monitoring, through the combination of a data acquisition and sensing module and a deviation detection and early warning module, the system can monitor original data in the cable production process in real time, and automatically detect and identify deviation. Once deviation is found, the system can send out an early warning signal in time. According to the real-time detection and early warning mechanism, the stability of the production process is greatly improved, potential problems can be quickly found and corrected, and generation of unqualified products is avoided. The automatic adjustment and control module automatically adjusts parameters of the production equipment according to the deviation early warning signal and the production state evaluation value, and excessive dependence on manual intervention in a traditional production mode is eliminated. The automatic adjustment not only improves the production efficiency, but also ensures the consistency and the qualified rate of the product quality. And parameters are dynamically adjusted in the production process, so that quality fluctuation caused by environment change and equipment fluctuation is reduced.

Description

Technical Field

[0001] This invention relates to the field of cable quality monitoring technology, specifically to an intelligent monitoring method and system for cable production quality. Background Technology

[0002] Intelligent monitoring systems for cable production quality fall under the industrial manufacturing sector, particularly within the scope of intelligent manufacturing and industrial automation. Intelligent manufacturing is a modern manufacturing method that utilizes information technology, automated equipment, and intelligent algorithms to precisely control and optimize the production process. As a crucial component of infrastructure construction such as power and communications, the cable manufacturing industry requires highly precise control and efficient quality assurance in its production processes. During cable production, multiple stages, including raw material stretching, heating, and forming, necessitate strict control of production parameters such as temperature, tension, and speed to ensure the quality and stability of the cables.

[0003] In traditional cable manufacturing methods, the control of production parameters often relies on manual inspection and fixed equipment settings, which are inherently lagging and prone to errors. During production, problems such as excessively high temperatures, uneven tension, and equipment vibration frequently occur, and traditional production monitoring systems fail to provide real-time warnings of these potential quality issues.

[0004] This phenomenon is related to insufficient reliance on real-time monitoring and adjustment in the cable production process. Traditional monitoring systems often only record and report production parameters, lacking predictive and self-adjusting capabilities. During production, minor fluctuations in equipment, changes in ambient temperature, or quality issues with raw materials frequently lead to deviations in key parameters such as tensile strength and temperature. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an intelligent monitoring method and system for cable production quality, solving the problems mentioned in the background section.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solution: an intelligent monitoring system for cable production quality, comprising a data acquisition and sensing module, a data preprocessing module, a deviation detection and early warning module, an automatic adjustment and control module, a system feedback and optimization module, and a data storage and reporting module;

[0007] The data acquisition and sensing module collects raw data from the production process through sensors and fits it into the original dataset GD;

[0008] The data preprocessing module cleans, fills in missing values, and normalizes the original dataset GD to obtain the cable dataset DW;

[0009] The deviation detection and early warning module monitors the data deviation in the cable dataset DW, obtains the deviation set PC, compares it with the set threshold, and determines whether to issue a deviation early warning signal; and combines the tensile change rate ΔFL and the production environment pressure change ΔPa to evaluate the cable production status and obtain the status evaluation value Ssta.

[0010] The automatic adjustment and control module automatically adjusts the parameters θ of the production equipment and obtains new parameters nθ based on the deviation set PC and the status evaluation value Ssta.

[0011] The system feedback and optimization module monitors the adjusted production status based on the acquired new parameter nθ, evaluates the adjustment effect, obtains the effect evaluation value Etop, and provides feedback status information.

[0012] The data storage and reporting module records the cable dataset DW, deviation warning signals, and effect evaluation values ​​Etop during the production process, generates reports, and records them.

[0013] Preferably, the data acquisition and sensing module includes a multi-source sensing unit and a data fitting and dynamic parameter calculation unit;

[0014] The multi-source sensing unit collects raw data during the production process through sensors installed in the cable production equipment, including temperature T, tension FL, rotational speed Vz, vibration frequency Fv, material thickness Dm, and environmental pressure Pa.

[0015] The temperature T is acquired by an infrared temperature sensor.

[0016] Tensile force FL represents the tension of the cable tensioning equipment, which is acquired through a tension sensor.

[0017] Rotational speed Vz represents the rotational speed of the cable traction motor, which is acquired by a Hall effect speed sensor;

[0018] Vibration frequency Fv represents the vibration state of the equipment and is acquired by a triaxial MEMS accelerometer.

[0019] Material thickness Dm represents the outer diameter thickness of the cable, which is obtained through a laser thickness gauge.

[0020] The ambient pressure (Pa) is acquired using a micro differential pressure sensor.

[0021] The data fitting and dynamic parameter calculation unit calculates and obtains dynamic change indicators from the raw data of the continuous time series, including the rate of change of tensile force ΔFL and the change of production environment pressure ΔPa.

[0022] The rate of change of tensile force ΔFL is obtained using the following formula:

[0023] ;

[0024] In the formula, FL(t) represents the tension at time t, FL(t-1) represents the tension at time t-1, and Δt represents the time interval;

[0025] The change in production environment pressure ΔPa is obtained using the following formula:

[0026] ;

[0027] In the formula, Pa(t) represents the ambient pressure at time t, and uPa represents the reference pressure value;

[0028] The obtained temperature T, tensile force FL, rotational speed Vz, vibration frequency Fv, material thickness Dm, environmental pressure Pa, tensile force change rate ΔFL, and production environment pressure change ΔPa are fitted to obtain the original dataset GD.

[0029] Preferably, the data preprocessing module includes a data cleaning and denoising unit and a data filling and normalization unit;

[0030] The data cleaning and denoising unit is responsible for cleaning the original dataset GD, including noise removal and outlier detection and filtering.

[0031] Noise removal was achieved by using median filtering to remove high-frequency noise from the original dataset GD.

[0032] Outlier detection and filtering are performed by using the interquartile range method to detect and filter outliers in the original dataset GD.

[0033] The data imputation and normalization unit is responsible for imputing missing data and normalizing the original dataset GD to obtain the cable dataset DW;

[0034] Missing data imputation is performed by processing the original dataset GD using linear interpolation to obtain the imputed dataset TW.

[0035] The dataset TW is populated using the following formula:

[0036] ;

[0037] In the formula, TWbfi(t) represents the b-th data item in the filled dataset TW at time t, GDb(t-1) represents the b-th data item in the original dataset GD at time t-1, and GDb(t+1) represents the b-th data item in the original dataset GD at time t+1.

[0038] Normalization was performed on the padding dataset TW using the Min-Max normalization method to obtain the cable dataset DW;

[0039] ;

[0040] In the formula, DWb represents the b-th data item in the cable dataset DW, TWb represents the b-th data item in the filling dataset TW, minTWb represents the valley value of the b-th data item in the filling dataset TW, and maxTWb represents the peak value of the b-th data item in the filling dataset TW.

[0041] Preferably, the deviation detection and early warning module includes a deviation detection and early warning unit and a production status assessment unit;

[0042] The deviation detection and early warning unit is responsible for real-time monitoring of data deviations in the cable dataset DW, including tensile force deviation DFL, temperature deviation DT, vibration frequency deviation DFv, and rotational speed deviation DVz.

[0043] The tensile deviation DFL is obtained using the following formula:

[0044] ;

[0045] In the formula, FLtar represents the set target tensile force value;

[0046] Temperature deviation DT is obtained using the following formula:

[0047] ;

[0048] In the formula, T(t) represents the temperature at time t, and Ttar represents the set target temperature value;

[0049] The vibration frequency deviation DFv is obtained by the following formula:

[0050] ;

[0051] In the formula, FV(t) represents the vibration frequency at time t, and Fvtar represents the target vibration frequency;

[0052] The speed deviation DVz is obtained using the following formula:

[0053] ;

[0054] In the formula, Vz(t) represents the rotational speed at time t, and Vztar represents the set target rotational speed;

[0055] The obtained tensile deviation DFL, temperature deviation DT, vibration frequency deviation DFv, and speed deviation DVz are compared with the preset tensile warning threshold Tdf, temperature warning threshold Tdt, vibration warning threshold Tfv, and speed warning threshold Tvz to determine whether the warning signal Yw is triggered.

[0056] The warning signal Yw is obtained using the following formula:

[0057] ;

[0058] In the formula, when the warning signal Yw=1, it indicates that a warning has been triggered; when the warning signal Yw=0, it indicates that there is no warning.

[0059] Preferably, the production status assessment unit fits the obtained tensile deviation DFL, temperature deviation DT, vibration frequency deviation DFv and speed deviation DVz to obtain the deviation set PC={DFL, DT, DFv, DVz}.

[0060] The obtained deviation set PC is combined with the tensile change rate ΔFL and the production environment pressure change ΔPa to evaluate the cable production status, obtain the status evaluation value Ssta, and compare it with the preset evaluation threshold Tst to determine the cable production status.

[0061] The state evaluation value Ssta is obtained using the following formula:

[0062] ;

[0063] In the formula, Let PCi represent the weight coefficient of the i-th deviation term in the deviation set PC. The weighting coefficient represents the rate of change of tensile force ΔFL. The weighting coefficient represents the change in production environment pressure ΔPa;

[0064] The production status of the cable is obtained by matching in the following way:

[0065] When the status assessment value Ssta > the assessment threshold Tst, it indicates that the cable's production status is abnormal.

[0066] When the status assessment value Ssta ≤ assessment threshold Tst, it indicates that the cable's production status is normal.

[0067] Preferably, the automatic adjustment and control module includes a deviation response and adjustment unit and a production status feedback and optimization unit;

[0068] The deviation response and adjustment unit adjusts the parameters θ of the production equipment based on the acquired deviation set PC, including tension deviation DFL, temperature deviation DT, vibration frequency deviation DFv, and speed deviation DVz. The parameters θ include tension FL, temperature T, speed Vz, and vibration frequency Fv. The new parameter nθ is acquired by adjusting tension nFL, adjusting temperature nT, adjusting speed nVz, and adjusting vibration frequency nFv.

[0069] The tension (nFL) is adjusted using the following formula:

[0070]

[0071] In the formula, R1 represents the adjustment factor for tension deviation;

[0072] The temperature nT is obtained using the following formula:

[0073]

[0074] In the formula, R2 represents the adjustment factor for temperature deviation;

[0075] The rotational speed nVz is obtained using the following formula:

[0076]

[0077] In the formula, R3 represents the adjustment factor for the speed deviation;

[0078] The vibration frequency adjustment nFv is obtained using the following formula:

[0079]

[0080] In the formula, R4 represents the adjustment factor for the vibration frequency deviation.

[0081] Preferably, the production status feedback and optimization unit adjusts the adjustment factors R1 for tension deviation, R2 for temperature deviation, R3 for speed deviation, and R4 for vibration frequency deviation based on the production status assessment value Ssta.

[0082] Among them, the adjustment factors R1 for tension deviation, R2 for temperature deviation, R3 for rotational speed deviation, and R4 for vibration frequency deviation are integrated to obtain the set of adjustment factors R={R1, R2, R3, R4}.

[0083] When the status evaluation value Ssta is greater than the evaluation threshold Tst, the production status of the cable is abnormal. The adjustment factor set R = {R1, R2, R3, R4} is adjusted to obtain a new adjustment factor set nR = {nR1, nR2, nR3, nR4}.

[0084] The formula is as follows:

[0085] ;

[0086] In the formula, nRa represents the a-th adjustment factor in the new adjustment factor set, Ra represents the a-th adjustment factor in the adjustment factor set, and γ represents the adjustment coefficient.

[0087] Preferably, the system feedback and optimization module evaluates the adjusted production status by comparing the new parameter nθ with the target parameter, and obtains the adjustment effect and the effect evaluation value Etop;

[0088] The target parameters include the target tensile force value FLtar, the target temperature value Ttar, the target vibration frequency Fvtar, and the target rotational speed Vztar;

[0089] The adjustment effects include tension adjustment effect XFL, temperature adjustment effect XT, speed adjustment effect XVz, and vibration frequency adjustment effect XFv;

[0090] The tension adjustment effect XFL is obtained using the following formula:

[0091] ;

[0092] The temperature adjustment effect XT is obtained using the following formula:

[0093] ;

[0094] The vibration frequency adjustment effect XFv is obtained through the following formula:

[0095] ;

[0096] The speed adjustment effect XVz is obtained using the following formula:

[0097] ;

[0098] The effectiveness evaluation value Etop is obtained using the following formula:

[0099] ;

[0100] In the formula, These represent the preset weight values ​​for the tension adjustment effect XFL, temperature adjustment effect XT, vibration frequency adjustment effect XFv, and speed adjustment effect XVz, respectively.

[0101] The obtained effect evaluation value Etop is compared with the preset effect threshold Teto to determine the accuracy of the adjustment effect;

[0102] The accuracy of the adjustment effect is obtained by matching in the following ways:

[0103] When the effect evaluation value Etop ≤ the effect threshold Teto, it means that the adjustment effect is accurate and ideal, and no feedback needs to be triggered.

[0104] When the effect evaluation value Etop > the effect threshold Teto, it indicates that the accuracy of the adjustment effect is not ideal, triggering feedback. The effect evaluation value Etop is used as feedback status information and fed back to the automatic adjustment and control module to correct the new adjustment factor set nR and obtain the corrected adjustment factor set XnR={XnR1, XnR2, XnR3, XnR4}.

[0105] The formula is as follows:

[0106] ;

[0107] In the formula, XnRa represents the a-th adjustment factor in the set of adjustment factors.

[0108] Preferably, the data storage and reporting module is responsible for real-time recording, storage and management of cable dataset DW, deviation warning signals and effect evaluation values ​​Etop, and generating automated reports, including production indicators, adjustment effects and deviation control status.

[0109] Production indicators represent various data during cable production, including temperature T, tensile force FL, rotational speed Vz, vibration frequency Fv, material thickness Dm, tensile force change rate ΔFL, and production environment pressure change ΔPa.

[0110] The adjustment effect represents the comparison between the actual result obtained after adjusting deviations in the production process and the expected target, including the tension adjustment effect XFL, temperature adjustment effect XT, speed adjustment effect XVz, and vibration frequency adjustment effect XFv.

[0111] The deviation control status reflects whether the tension deviation (DFL), temperature deviation (DT), vibration frequency deviation (DFv), and speed deviation (DVz) in the production process are maintained within the preset threshold range. Whenever the deviation exceeds the preset threshold, the deviation will be recorded and the problem of taking adjustment measures to correct the deviation will be described.

[0112] A method for intelligent monitoring of cable production quality includes the following steps:

[0113] Step 1: The data acquisition and sensing module collects raw data from the production process through sensors and fits it into the original dataset GD;

[0114] Step 2: The data preprocessing module cleans, fills in missing values, and normalizes the original dataset GD to obtain the cable dataset DW;

[0115] Step 3: The deviation detection and early warning module monitors the data deviation in the cable dataset DW, obtains the deviation set PC, and compares it with the set threshold to determine whether to issue a deviation early warning signal; and combines the tensile change rate ΔFL and the production environment pressure change ΔPa to evaluate the cable production status and obtain the status evaluation value Ssta.

[0116] Step 4: The automatic adjustment and control module automatically adjusts the parameters θ of the production equipment based on the deviation set PC and the status evaluation value Ssta, and obtains the new parameters nθ.

[0117] Step 5: The system feedback and optimization module monitors the adjusted production status based on the acquired new parameter nθ, evaluates the adjustment effect, obtains the effect evaluation value Etop, and provides feedback status information.

[0118] Step Six: The data storage and reporting module records the cable dataset DW, deviation warning signals, and effect evaluation values ​​Etop during the production process, generates reports, and records them.

[0119] This invention provides an intelligent monitoring method and system for cable production quality, which has the following beneficial effects:

[0120] (1) During system operation, through the combination of data acquisition and sensing modules and deviation detection and early warning modules, the system can monitor the raw data in the cable production process in real time and automatically detect and identify deviations. Once a deviation is detected, the system can issue an early warning signal in a timely manner. This real-time detection and early warning mechanism greatly improves the stability of the production process, can quickly detect and correct potential problems, and avoid the generation of defective products. The automatic adjustment and control module automatically adjusts the parameters of the production equipment according to the deviation early warning signal and the production status assessment value, eliminating the excessive reliance on manual intervention in the traditional production mode. This automated adjustment not only improves production efficiency, but also ensures the consistency and pass rate of product quality. The dynamic adjustment of parameters during the production process reduces quality fluctuations caused by environmental changes and equipment fluctuations.

[0121] (2) Through real-time monitoring and deviation calculation by the deviation detection and early warning unit, the system can detect the tensile deviation (DFL), temperature deviation (DT), vibration frequency deviation (DFv), and rotational speed deviation (DVz) that occur during cable production. When the deviation between the actual value and the set target value of these parameters exceeds the predetermined threshold, the system will automatically issue an early warning signal. This immediate early warning mechanism can promptly detect and respond to potential problems in the production process, avoid the generation of unqualified products, and improve the stability of product quality. The production status assessment unit combines deviation data, tensile change rate (ΔFL), and production environment pressure change (ΔPa) to comprehensively assess the production status. By fitting the deviation set (PC) and combining it with other dynamic parameters, including tensile change rate (ΔFL) and production environment pressure change (ΔPa), the system can comprehensively assess the health status of the cable production process. Based on the comparison between the assessment value (Ssta) and the assessment threshold (Tst), the system can determine whether the production is abnormal and adjust the production strategy in a timely manner. Through this comprehensive assessment, the system can dynamically respond to changes in production and ensure the continuous stability of the production process.

[0122] (3) The production status feedback and optimization unit can optimize the adjustment factor in real time based on the status evaluation value Ssta during the production process. This module further improves the stability and accuracy of production by optimizing the deviation adjustment factor. When the production status is abnormal, the system automatically adjusts the set of adjustment factors through the feedback mechanism to ensure the accuracy of the adjustment measures. This closed-loop feedback and optimization mechanism can cope with various potential unstable factors in the production process and ensure the automation and adaptive adjustment of the production process. By integrating different adjustment factors, the system can comprehensively evaluate the deviation of various parameters in the production process and make timely adjustments. In this way, the system can not only respond to sudden problems in production in real time, but also ensure that every adjustment can directly improve the quality of cable products. This precise control and optimization capability improves production efficiency and effectively reduces the defect rate caused by production instability.

[0123] (4) During cable production, parameters such as tensile force (FL), temperature (T), rotational speed (Vz), and vibration frequency (Fv) are monitored in real time and compared with target parameters to quickly identify deviations and make timely adjustments. The system's feedback mechanism can promptly correct any deviations in the production process, ensuring that each stage of the production process is within controllable limits and avoiding quality problems caused by equipment fluctuations or environmental changes. The data storage and reporting module records and stores key production data, deviation warning signals, and effect evaluation values, enabling the system to automatically generate comprehensive production reports. These reports not only help management understand the production status in a timely manner but also provide data support for further optimization decisions. Detailed records of production indicators, adjustment effects, and deviation control provide decision-makers with complete production analysis and quality assurance, contributing to the continuous improvement of future production processes. Attached Figure Description

[0124] Figure 1 This is a block diagram and flowchart of an intelligent monitoring system for cable production quality according to the present invention.

[0125] Figure 2 This is a schematic diagram illustrating the steps of an intelligent monitoring method for cable production quality according to the present invention.

[0126] Figure 3 This is a schematic diagram of the system block flow for feedback regulation of the present invention;

[0127] Figure 4 This is an area diagram for the state assessment of this invention;

[0128] Figure 5 This is a bar graph showing the numerical values ​​for evaluating the effectiveness of the present invention. Detailed Implementation

[0129] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0130] Example 1

[0131] This invention provides an intelligent monitoring system for cable production quality. Please refer to [link / reference]. Figures 1 to 5 It includes a data acquisition and sensing module, a data preprocessing module, a deviation detection and early warning module, an automatic adjustment and control module, a system feedback and optimization module, and a data storage and reporting module;

[0132] The data acquisition and sensing module collects raw data from the production process through sensors and fits it into the original dataset GD;

[0133] The data preprocessing module cleans, fills in missing values, and normalizes the original dataset GD to obtain the cable dataset DW;

[0134] The deviation detection and early warning module monitors the data deviation in the cable dataset DW, obtains the deviation set PC, compares it with the set threshold, and determines whether to issue a deviation early warning signal; and combines the tensile change rate ΔFL and the production environment pressure change ΔPa to evaluate the cable production status and obtain the status evaluation value Ssta.

[0135] The automatic adjustment and control module automatically adjusts the parameters θ of the production equipment and obtains new parameters nθ based on the deviation set PC and the status evaluation value Ssta.

[0136] The system feedback and optimization module monitors the adjusted production status based on the acquired new parameter nθ, evaluates the adjustment effect, obtains the effect evaluation value Etop, and provides feedback status information.

[0137] The data storage and reporting module records the cable dataset DW, deviation warning signals, and effect evaluation values ​​Etop during the production process, generates reports, and records them.

[0138] In this embodiment, by combining the data acquisition and sensing module with the deviation detection and early warning module, the system can monitor the raw data during the cable production process in real time and automatically detect and identify deviations. Once a deviation is detected, the system can promptly issue an early warning signal. This real-time detection and early warning mechanism greatly improves the stability of the production process, enabling the rapid identification and correction of potential problems and preventing the generation of defective products. The automatic adjustment and control module automatically adjusts the parameters of the production equipment based on the deviation early warning signal and the production status assessment value, eliminating the excessive reliance on manual intervention in traditional production modes. This automated adjustment not only improves production efficiency but also ensures the consistency and pass rate of product quality. The dynamic adjustment of parameters during the production process reduces quality fluctuations caused by environmental changes and equipment fluctuations.

[0139] The system feedback and optimization module can evaluate the effects of adjustments based on the production status and provide real-time feedback. This module can further optimize the adjustment strategy based on the feedback information, ensuring continuous and stable production. This feedback mechanism helps identify potential problems during adjustments, allowing for timely corrections and ensuring the production system reaches its optimal operating state.

[0140] Through automated control and optimization, the shortcomings of traditional production models that rely on manual judgment and adjustment are reduced. Automated systems can quickly respond to and adjust parameters during the production process, reducing the time required for manual intervention, improving production efficiency, and mitigating the risks associated with human error.

[0141] Example 2

[0142] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 and Figure 3 Specifically: the data acquisition and sensing module includes a multi-source sensing unit and a data fitting and dynamic parameter calculation unit;

[0143] The multi-source sensing unit collects raw data during the production process through sensors installed in the cable production equipment, including temperature T, tension FL, rotational speed Vz, vibration frequency Fv, material thickness Dm, and environmental pressure Pa.

[0144] The temperature T is acquired by an infrared temperature sensor.

[0145] Tensile force FL represents the tension of the cable tensioning equipment, which is acquired through a tension sensor.

[0146] Rotational speed Vz represents the rotational speed of the cable traction motor, which is acquired by a Hall effect speed sensor;

[0147] Vibration frequency Fv represents the vibration state of the equipment and is acquired by a triaxial MEMS accelerometer.

[0148] Material thickness Dm represents the outer diameter thickness of the cable, which is obtained through a laser thickness gauge.

[0149] The ambient pressure (Pa) is acquired using a micro differential pressure sensor.

[0150] The data fitting and dynamic parameter calculation unit calculates and obtains dynamic change indicators from the raw data of the continuous time series, including the rate of change of tensile force ΔFL and the change of production environment pressure ΔPa.

[0151] The rate of change of tensile force ΔFL is obtained using the following formula:

[0152] ;

[0153] In the formula, FL(t) represents the tension at time t, FL(t-1) represents the tension at time t-1, and Δt represents the time interval;

[0154] The change in production environment pressure ΔPa is obtained using the following formula:

[0155] ;

[0156] In the formula, Pa(t) represents the ambient pressure at time t, and uPa represents the reference pressure value;

[0157] The obtained temperature T, tensile force FL, rotational speed Vz, vibration frequency Fv, material thickness Dm, environmental pressure Pa, tensile force change rate ΔFL, and production environment pressure change ΔPa are fitted to obtain the original dataset GD.

[0158] The data preprocessing module includes a data cleaning and denoising unit and a data filling and normalization unit;

[0159] The data cleaning and denoising unit is responsible for cleaning the original dataset GD, including noise removal and outlier detection and filtering.

[0160] Noise removal was achieved by using median filtering to remove high-frequency noise from the original dataset GD.

[0161] Outlier detection and filtering are performed by using the interquartile range method to detect and filter outliers in the original dataset GD.

[0162] The data imputation and normalization unit is responsible for imputing missing data and normalizing the original dataset GD to obtain the cable dataset DW;

[0163] Missing data imputation is performed by processing the original dataset GD using linear interpolation to obtain the imputed dataset TW.

[0164] The dataset TW is populated using the following formula:

[0165] ;

[0166] In the formula, TWbfi(t) represents the b-th data item in the filled dataset TW at time t, GDb(t-1) represents the b-th data item in the original dataset GD at time t-1, and GDb(t+1) represents the b-th data item in the original dataset GD at time t+1.

[0167] Normalization was performed on the padding dataset TW using the Min-Max normalization method to obtain the cable dataset DW;

[0168] ;

[0169] In the formula, DWb represents the b-th data item in the cable dataset DW, TWb represents the b-th data item in the filling dataset TW, minTWb represents the valley value of the b-th data item in the filling dataset TW, and maxTWb represents the peak value of the b-th data item in the filling dataset TW.

[0170] In this embodiment, multiple sensors are used to collect key parameters in the cable production process in real time. This multi-sensor design allows the system to simultaneously monitor multiple production parameters, including temperature T, tensile force FL, rotational speed Vz, vibration frequency Fv, material thickness Dm, and environmental pressure Pa. This ensures precise monitoring of every stage of the production process, eliminating the shortcomings of relying on a single sensor in traditional production. Real-time, accurate data acquisition not only reflects the production status in real time but also promptly detects any production deviations, improving the stability of the overall production process.

[0171] The data fitting and dynamic parameter calculation unit calculates dynamic change indicators such as the rate of change in tensile force and changes in production environmental pressure, which can reflect potential deviations in the production process in real time. Through real-time monitoring of dynamic parameters, the system can not only predict possible quality problems, but also issue early warning signals to remind operators to make adjustments. This early warning mechanism can effectively reduce quality problems caused by factors such as temperature fluctuations, uneven tensile force, and changes in environmental pressure during the production process.

[0172] The data cleaning and denoising unit uses median filtering to remove noise from the raw data and interquartile range (ICR) to detect and filter outliers. This design eliminates high-frequency noise and abnormal data caused by sensor errors or environmental interference during the production process, thus ensuring data accuracy and reliability. Through data cleaning, the system ensures data quality in subsequent analysis and decision-making processes, avoiding unnecessary adjustments or misjudgments caused by data errors.

[0173] The data imputation and normalization unit uses linear interpolation to fill in missing data and then performs Min-Max normalization on the imputed data to ensure consistency and standardization. Normalized data eliminates dimensional differences between parameters, allowing for comparison and analysis of various production parameters under the same standard. This data processing method effectively improves the system's processing capacity, ensures compatibility between different data sets, and provides accurate basic data for subsequent adjustments and control.

[0174] The data storage and reporting module records all data from the production process, including cable datasets, deviation warning signals, and performance evaluation values, and automatically generates reports. This data provides management with detailed production quality assessments and supports decision-makers in developing more effective optimization strategies. Through real-time data storage and regular reporting, managers can clearly see potential problems and areas for optimization in the production process, thereby improving the accuracy of production decisions.

[0175] Example 3

[0176] This embodiment is an explanation based on Embodiment 2. Please refer to the reference figures. Figure 3 and Figure 4 Specifically: the deviation detection and early warning module includes a deviation detection and early warning unit and a production status assessment unit;

[0177] The deviation detection and early warning unit is responsible for real-time monitoring of data deviations in the cable dataset DW, including tensile force deviation DFL, temperature deviation DT, vibration frequency deviation DFv, and rotational speed deviation DVz.

[0178] The tensile deviation DFL is obtained using the following formula:

[0179] ;

[0180] In the formula, FLtar represents the set target tensile force value;

[0181] Temperature deviation DT is obtained using the following formula:

[0182] ;

[0183] In the formula, T(t) represents the temperature at time t, and Ttar represents the set target temperature value;

[0184] The vibration frequency deviation DFv is obtained by the following formula:

[0185] ;

[0186] In the formula, FV(t) represents the vibration frequency at time t, and Fvtar represents the target vibration frequency;

[0187] The speed deviation DVz is obtained using the following formula:

[0188] ;

[0189] In the formula, Vz(t) represents the rotational speed at time t, and Vztar represents the set target rotational speed;

[0190] The obtained tensile deviation DFL, temperature deviation DT, vibration frequency deviation DFv, and speed deviation DVz are compared with the preset tensile warning threshold Tdf, temperature warning threshold Tdt, vibration warning threshold Tfv, and speed warning threshold Tvz to determine whether the warning signal Yw is triggered.

[0191] The warning signal Yw is obtained using the following formula:

[0192] ;

[0193] In the formula, when the warning signal Yw=1, it indicates that a warning has been triggered; when the warning signal Yw=0, it indicates that there is no warning.

[0194] The production status assessment unit fits the obtained tension deviation DFL, temperature deviation DT, vibration frequency deviation DFv, and speed deviation DVz to obtain the deviation set PC={DFL, DT, DFv, DVz}.

[0195] The obtained deviation set PC is combined with the tensile change rate ΔFL and the production environment pressure change ΔPa to evaluate the cable production status, obtain the status evaluation value Ssta, and compare it with the preset evaluation threshold Tst to determine the cable production status.

[0196] The state evaluation value Ssta is obtained using the following formula, as shown in Table 1:

[0197] ;

[0198] In the formula, Let PCi represent the weight coefficient of the i-th deviation term in the deviation set PC. The weighting coefficient represents the rate of change of tensile force ΔFL. The weighting coefficient represents the change in production environment pressure ΔPa;

[0199] The production status of the cable is obtained by matching in the following way:

[0200] When the status assessment value Ssta > the assessment threshold Tst, it indicates that the cable's production status is abnormal.

[0201] When the status assessment value Ssta ≤ assessment threshold Tst, it indicates that the cable's production status is normal.

[0202] Specific examples:

[0203] The evaluation threshold Tst is set to 0.04;

[0204] Table 1 Data Status Judgment Table:

[0205] Data group DFL DT DFv DVz ΔFL ΔPa Ssta Production status 1 0.05 0.03 0.02 0.01 0.03 0.01 0.030 normal 2 0.07 0.04 0.03 0.02 0.05 0.02 0.0435 abnormal 3 0.03 0.02 0.01 0.03 0.02 0.03 0.026 normal 4 0.06 0.05 0.04 0.01 0.04 0.02 0.0475 abnormal 5 0.04 0.03 0.02 0.02 0.03 0.02 0.0335 normal

[0206] In this embodiment, through real-time monitoring and deviation calculation by the deviation detection and early warning unit, the system can detect tensile deviation (DFL), temperature deviation (DT), vibration frequency deviation (DFv), and rotational speed deviation (DVz) occurring during cable production in real time. When the deviation between the actual values ​​of these parameters and the set target values ​​exceeds a predetermined threshold, the system automatically issues an early warning signal. This immediate early warning mechanism can promptly detect and address potential problems during production, preventing the generation of defective products and improving product quality stability. The production status assessment unit combines deviation data, tensile change rate (ΔFL), and production environment pressure change (ΔPa) to comprehensively assess the production status. By fitting the deviation set (PC) and combining other dynamic parameters, including tensile change rate (ΔFL) and production environment pressure change (ΔPa), the system can comprehensively assess the health status of the cable production process. Based on the comparison between the assessment value (Ssta) and the assessment threshold (Tst), the system can determine whether production is abnormal and adjust the production strategy in a timely manner. Through this comprehensive assessment, the system can dynamically respond to changes in production, ensuring the continuous stability of the production process.

[0207] This system reduces the need for manual intervention and improves the intelligence level of the production process by automating deviation monitoring and real-time production status assessment. By comparing real-time data of multiple production parameters with preset target values, the system can automatically identify potential problems in production and take proactive measures to adjust them. This not only improves production efficiency but also enhances production stability and quality control capabilities. Through the combination of deviation detection and early warning with production status assessment, the system can detect unstable factors in advance during production and make timely adjustments. For example, the system can automatically adjust production equipment settings when there is uneven tension or excessive temperature to avoid defective products caused by production deviations. Identifying and resolving problems in advance helps reduce downtime in production, improves the overall efficiency of the production line, and reduces production costs.

[0208] By integrating deviation monitoring, production status assessment, and automatic adjustment control, the system provides more precise assurance in quality control. Each deviation parameter and production status can be monitored and adjusted in real time, ensuring that every stage of cable production meets predetermined quality standards. This refined quality control effectively improves the consistency and pass rate of cable products and reduces quality fluctuations during production. Through the comprehensive recording of deviation data and production status assessment data, the system provides management with detailed production process data support. Management can analyze problems in production based on this data and optimize production strategies. Automatically generated reports help management quickly understand the production status, evaluate the effectiveness of adjustment measures, and provide a reliable basis for subsequent production decisions.

[0209] Example 4

[0210] This embodiment is an explanation based on Embodiment 3. Please refer to it. Figure 1 Specifically: the automatic adjustment and control module includes a deviation response and adjustment unit and a production status feedback and optimization unit;

[0211] The deviation response and adjustment unit adjusts the parameters θ of the production equipment based on the acquired deviation set PC, including tension deviation DFL, temperature deviation DT, vibration frequency deviation DFv, and speed deviation DVz. The parameters θ include tension FL, temperature T, speed Vz, and vibration frequency Fv. The new parameter nθ is acquired by adjusting tension nFL, adjusting temperature nT, adjusting speed nVz, and adjusting vibration frequency nFv.

[0212] The tension (nFL) is adjusted using the following formula:

[0213]

[0214] In the formula, R1 represents the adjustment factor for tension deviation;

[0215] The temperature nT is obtained using the following formula:

[0216]

[0217] In the formula, R2 represents the adjustment factor for temperature deviation;

[0218] The rotational speed nVz is obtained using the following formula:

[0219]

[0220] In the formula, R3 represents the adjustment factor for the speed deviation;

[0221] The vibration frequency adjustment nFv is obtained using the following formula:

[0222]

[0223] In the formula, R4 represents the adjustment factor for the vibration frequency deviation.

[0224] The production status feedback and optimization unit adjusts the adjustment factors R1 for tension deviation, R2 for temperature deviation, R3 for speed deviation, and R4 for vibration frequency deviation based on the production status assessment value Ssta.

[0225] Among them, the adjustment factors R1 for tension deviation, R2 for temperature deviation, R3 for rotational speed deviation, and R4 for vibration frequency deviation are integrated to obtain the set of adjustment factors R={R1, R2, R3, R4}.

[0226] When the status evaluation value Ssta is greater than the evaluation threshold Tst, the production status of the cable is abnormal. The adjustment factor set R = {R1, R2, R3, R4} is adjusted to obtain a new adjustment factor set nR = {nR1, nR2, nR3, nR4}.

[0227] The formula is as follows:

[0228] ;

[0229] In the formula, nRa represents the a-th adjustment factor in the new adjustment factor set, Ra represents the a-th adjustment factor in the adjustment factor set, and γ represents the adjustment coefficient.

[0230] In this embodiment, by acquiring various deviation data in real time, including tensile force deviation (DFL), temperature deviation (DT), vibration frequency deviation (DFv), and rotational speed deviation (DVz), and combining them with adjustment factors, the system intelligently adjusts the key parameters of the production equipment. Through these dynamic adjustments, the system can ensure that all key parameters during the production process remain within the set range, thereby guaranteeing the stability and consistency of cable production quality. This dynamic adjustment mechanism is more intelligent and precise than traditional fixed setting methods, and can automatically correct any deviations caused by equipment fluctuations or environmental changes during the production process.

[0231] The production status feedback and optimization unit can optimize adjustment factors in real time based on the status assessment value Ssta during the production process. This module further improves production stability and accuracy by optimizing the deviation adjustment factors. When production status is abnormal, the system automatically adjusts the set of adjustment factors through a feedback mechanism to ensure the accuracy of the adjustment measures. This closed-loop feedback and optimization mechanism can cope with various potential unstable factors in the production process, ensuring the automation and adaptive adjustment of the production process. By integrating different adjustment factors, the system can comprehensively evaluate the deviations of various parameters in the production process and make timely adjustments. In this way, the system can not only respond to sudden problems in production in real time, but also ensure that every adjustment directly improves the quality of cable products. This precise control and optimization capability improves production efficiency and effectively reduces the defect rate caused by production instability.

[0232] This invention significantly reduces the need for manual intervention through an integrated automatic adjustment and control system. By intelligently adjusting production parameters, managers can focus more on optimizing the production process and making decisions, without worrying about minor fluctuations or human error. This highly automated production control mode not only improves production efficiency but also reduces operational complexity and ensures high stability in the production process.

[0233] The system supports continuous intelligent management during production by optimizing and adjusting the set of adjustment factors in real time. When abnormalities occur in production, the system automatically adjusts the factor set and, combined with real-time feedback data, ensures that the production equipment is adjusted in the correct direction. Through this continuous optimization management approach, the cable production line can adaptively adjust to a dynamically changing environment, reducing the risk of production interruptions and maintaining a highly efficient and stable production status.

[0234] Example 5

[0235] This embodiment is an explanation based on Embodiment 4. Please refer to it. Figure 3 and Figure 5Specifically: The system feedback and optimization module evaluates the adjusted production status by comparing the new parameter nθ with the target parameter, and obtains the adjustment effect and the effect evaluation value Etop;

[0236] The target parameters include the target tensile force value FLtar, the target temperature value Ttar, the target vibration frequency Fvtar, and the target rotational speed Vztar;

[0237] The adjustment effects include tension adjustment effect XFL, temperature adjustment effect XT, speed adjustment effect XVz, and vibration frequency adjustment effect XFv;

[0238] The tension adjustment effect XFL is obtained using the following formula:

[0239] ;

[0240] The temperature adjustment effect XT is obtained using the following formula:

[0241] ;

[0242] The vibration frequency adjustment effect XFv is obtained through the following formula:

[0243] ;

[0244] The speed adjustment effect XVz is obtained using the following formula:

[0245] ;

[0246] The effectiveness evaluation value Etop is obtained using the following formula, as shown in Table 2:

[0247] ;

[0248] In the formula, These represent the preset weight values ​​for the tension adjustment effect XFL, temperature adjustment effect XT, vibration frequency adjustment effect XFv, and speed adjustment effect XVz, respectively.

[0249] Specific examples:

[0250] Table 2: Evaluation Values ​​of Cable Production Adjustment Effects

[0251] Data group XFL XT XFv XVz Etop 1 0.04 0.03 0.02 0.01 0.03 2 0.06 0.05 0.04 0.02 0.046 3 0.03 0.02 0.01 0.03 0.019 4 0.05 0.04 0.03 0.01 0.0335 5 0.04 0.03 0.02 0.02 0.029

[0252] The obtained effect evaluation value Etop is compared with the preset effect threshold Teto to determine the accuracy of the adjustment effect;

[0253] The accuracy of the adjustment effect is obtained by matching in the following ways:

[0254] When the effect evaluation value Etop ≤ the effect threshold Teto, it means that the adjustment effect is accurate and ideal, and no feedback needs to be triggered.

[0255] When the effect evaluation value Etop > the effect threshold Teto, it indicates that the accuracy of the adjustment effect is not ideal, triggering feedback. The effect evaluation value Etop is used as feedback status information and fed back to the automatic adjustment and control module to correct the new adjustment factor set nR and obtain the corrected adjustment factor set XnR={XnR1, XnR2, XnR3, XnR4}.

[0256] The formula is as follows:

[0257] ;

[0258] In the formula, XnRa represents the a-th adjustment factor in the set of adjustment factors.

[0259] The data storage and reporting module is responsible for recording, storing and managing the cable dataset DW, deviation warning signals and effect evaluation values ​​Etop in real time, and generating automated reports, including production indicators, adjustment effects and deviation control status.

[0260] Production indicators represent various data during cable production, including temperature T, tensile force FL, rotational speed Vz, vibration frequency Fv, material thickness Dm, tensile force change rate ΔFL, and production environment pressure change ΔPa.

[0261] The adjustment effect represents the comparison between the actual result obtained after adjusting deviations in the production process and the expected target, including the tension adjustment effect XFL, temperature adjustment effect XT, speed adjustment effect XVz, and vibration frequency adjustment effect XFv.

[0262] The deviation control status reflects whether the tension deviation (DFL), temperature deviation (DT), vibration frequency deviation (DFv), and speed deviation (DVz) in the production process are maintained within the preset threshold range. Whenever the deviation exceeds the preset threshold, the deviation will be recorded and the problem of taking adjustment measures to correct the deviation will be described.

[0263] In this embodiment, through the implementation of the system feedback and optimization module, the system can not only monitor the adjusted production parameters in real time, but also evaluate the adjustment effect by comparing them with the target parameters. This precise adjustment effect evaluation mechanism can clearly determine the effect of each adjustment step, thereby ensuring that every adjustment in the production process achieves the expected goal and avoiding quality fluctuations or defective products caused by inaccurate adjustments. When the adjustment effect does not meet expectations, i.e., the effect evaluation value exceeds the set threshold Teto, the system will automatically trigger the feedback mechanism to correct the adjustment factor. This mechanism can self-optimize the adjustment process, ensuring that the production status is always maintained at the optimal level. Through real-time feedback and self-correction, the system can dynamically adapt to changes in the production process and continuously optimize production efficiency and product quality.

[0264] The system reduces the need for manual intervention by automating adjustment evaluation and feedback correction. Tasks that previously required manual judgment and adjustment are now monitored and automatically adjusted in real time by the intelligent system, significantly improving the automation level of the production process. This not only increases production efficiency but also reduces human error, enhancing production stability and consistency.

[0265] During cable production, parameters such as tensile force (FL), temperature (T), rotational speed (Vz), and vibration frequency (Fv) are monitored in real time and compared with target parameters. This allows for rapid detection and timely adjustments to identify deviations. The system's feedback mechanism promptly corrects any deviations in the production process, ensuring that every step remains within controllable limits and preventing quality issues caused by equipment fluctuations or environmental changes. The data storage and reporting module records and stores key production data, deviation warning signals, and performance evaluation values, automatically generating comprehensive production reports. These reports not only help management understand the production status but also provide data support for further optimization decisions. Detailed records of production indicators, adjustment effects, and deviation control provide decision-makers with complete production analysis and quality assurance, contributing to continuous improvement of future production processes.

[0266] Through intelligent production adjustments and deviation control, the system ensures the stability of every stage of cable production, thereby improving product consistency and quality. The adjustment effect evaluation and feedback correction mechanism helps to promptly identify potential risks associated with non-conforming products and avoids large-scale quality problems through immediate corrective measures. This refined quality control reduces fluctuations in the production process and guarantees a high pass rate for cable products.

[0267] Example 6

[0268] A method for intelligent monitoring of cable production quality, please refer to... Figure 2 Specifically, it includes the following steps:

[0269] Step 1: The data acquisition and sensing module collects raw data from the production process through sensors and fits it into the original dataset GD;

[0270] Step 2: The data preprocessing module cleans, fills in missing values, and normalizes the original dataset GD to obtain the cable dataset DW;

[0271] Step 3: The deviation detection and early warning module monitors the data deviation in the cable dataset DW, obtains the deviation set PC, and compares it with the set threshold to determine whether to issue a deviation early warning signal; and combines the tensile change rate ΔFL and the production environment pressure change ΔPa to evaluate the cable production status and obtain the status evaluation value Ssta.

[0272] Step 4: The automatic adjustment and control module automatically adjusts the parameters θ of the production equipment based on the deviation set PC and the status evaluation value Ssta, and obtains the new parameters nθ.

[0273] Step 5: The system feedback and optimization module monitors the adjusted production status based on the acquired new parameter nθ, evaluates the adjustment effect, obtains the effect evaluation value Etop, and provides feedback status information.

[0274] Step Six: The data storage and reporting module records the cable dataset DW, deviation warning signals, and effect evaluation values ​​Etop during the production process, generates reports, and records them.

[0275] In this embodiment, the data preprocessing module cleans, imputes missing values, and normalizes the original dataset to ensure data integrity and consistency. This automated data cleaning and processing workflow effectively removes noise, fills in missing data, and standardizes the data, making comparisons between various parameters more scientific and accurate. These steps reduce the need for manual intervention, ensuring the accuracy and efficiency of subsequent analysis and decision-making.

[0276] The deviation detection and early warning module can monitor various parameter deviations in cable production in real time, compare them with set thresholds, and issue early warning signals promptly. This real-time deviation monitoring and early warning mechanism ensures that problems in the production process can be detected and addressed at the earliest possible moment, thereby avoiding large-scale defective products or production stoppages caused by uncorrected deviations. The automatic adjustment and control module can automatically adjust the parameters of the production equipment based on deviation early warning signals and production status assessment results. This function combines automation and intelligence, enabling real-time adjustments to key production parameters such as tension, temperature, rotational speed, and vibration frequency to ensure that the production process remains in optimal condition. The system's automatic adjustment capability reduces human intervention and ensures the timeliness and accuracy of adjustment measures.

[0277] The data storage and reporting module can record cable production data, deviation warning signals, and adjustment effect evaluation values ​​in real time, and generate automated reports. These reports provide management with a comprehensive and detailed analysis of production status and data support for future decision-making and optimization. The system can regularly generate different types of reports, such as daily, weekly, and monthly reports, according to production cycles or needs, ensuring the transparency and traceability of the production process.

[0278] Because the system can monitor and automatically adjust key production parameters in real time, the quality of cable products is effectively controlled. Timely adjustment of deviations, continuous optimization of production status, and the feedback mechanism ensure that each batch of products maintains consistent quality standards, avoiding quality problems caused by fluctuations or instability in the production process and enhancing the product's market competitiveness.

[0279] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A smart monitoring system for cable production quality, characterized in that: It includes a data acquisition and sensing module, a data preprocessing module, a deviation detection and early warning module, an automatic adjustment and control module, a system feedback and optimization module, and a data storage and reporting module; The data acquisition and sensing module collects raw data from the production process through sensors and fits it into the original dataset GD; The data preprocessing module cleans, fills in missing values, and normalizes the original dataset GD to obtain the cable dataset DW; The deviation detection and early warning module monitors the data deviation in the cable dataset DW, obtains the deviation set PC, compares it with the set threshold, and determines whether to issue a deviation early warning signal; and combines the tensile change rate ΔFL and the production environment pressure change ΔPa to evaluate the cable production status and obtain the status evaluation value Ssta. The automatic adjustment and control module automatically adjusts the parameters θ of the production equipment and obtains new parameters nθ based on the deviation set PC and the status evaluation value Ssta. The system feedback and optimization module monitors the adjusted production status based on the acquired new parameter nθ, evaluates the adjustment effect, obtains the effect evaluation value Etop, and provides feedback status information. The data storage and reporting module records the cable dataset DW, deviation warning signals, and effect evaluation values ​​Etop during the production process, generates reports, and records them.

2. The intelligent monitoring system for cable production quality according to claim 1, characterized in that: The data acquisition and sensing module includes a multi-source sensing unit and a data fitting and dynamic parameter calculation unit; The multi-source sensing unit collects raw data during the production process through sensors installed in the cable production equipment, including temperature T, tension FL, rotational speed Vz, vibration frequency Fv, material thickness Dm, and environmental pressure Pa. The temperature T is acquired by an infrared temperature sensor. Tensile force FL represents the tension of the cable tensioning equipment, which is acquired through a tension sensor. Rotational speed Vz represents the rotational speed of the cable traction motor, which is acquired by a Hall effect speed sensor; Vibration frequency Fv represents the vibration state of the equipment, which is acquired by a triaxial MEMS accelerometer. Material thickness Dm represents the outer diameter thickness of the cable, which is obtained by a laser thickness gauge. The ambient pressure (Pa) is acquired using a micro differential pressure sensor. The data fitting and dynamic parameter calculation unit calculates and obtains dynamic change indicators from the raw data of the continuous time series, including the rate of change of tensile force ΔFL and the change of production environment pressure ΔPa. The rate of change of tensile force ΔFL is obtained using the following formula: ； In the formula, FL(t) represents the tension at time t, FL(t-1) represents the tension at time t-1, and Δt represents the time interval; The change in production environment pressure ΔPa is obtained using the following formula: ； In the formula, Pa(t) represents the ambient pressure at time t, and uPa represents the reference pressure value; The obtained temperature T, tensile force FL, rotational speed Vz, vibration frequency Fv, material thickness Dm, environmental pressure Pa, tensile force change rate ΔFL, and production environment pressure change ΔPa are fitted to obtain the original dataset GD.

3. The intelligent monitoring system for cable production quality according to claim 2, characterized in that: The data preprocessing module includes a data cleaning and denoising unit and a data filling and normalization unit; The data cleaning and denoising unit is responsible for cleaning the original dataset GD, including noise removal and outlier detection and filtering. Noise removal was achieved by using median filtering to remove high-frequency noise from the original dataset GD. Outlier detection and filtering are performed by using the interquartile range method to detect and filter outliers in the original dataset GD. The data imputation and normalization unit is responsible for imputing missing data and normalizing the original dataset GD to obtain the cable dataset DW; Missing data imputation is performed by processing the original dataset GD using linear interpolation to obtain the imputed dataset TW. The dataset TW is populated using the following formula: ； In the formula, TWbfi(t) represents the b-th data item in the filled dataset TW at time t, GDb(t-1) represents the b-th data item in the original dataset GD at time t-1, and GDb(t+1) represents the b-th data item in the original dataset GD at time t+1. Normalization was performed on the padding dataset TW using the Min-Max normalization method to obtain the cable dataset DW; ； In the formula, DWb represents the b-th data item in the cable dataset DW, TWb represents the b-th data item in the filling dataset TW, minTWb represents the valley value of the b-th data item in the filling dataset TW, and maxTWb represents the peak value of the b-th data item in the filling dataset TW.

4. The intelligent monitoring system for cable production quality according to claim 3, characterized in that: The deviation detection and early warning module includes a deviation detection and early warning unit and a production status assessment unit; The deviation detection and early warning unit is responsible for real-time monitoring of data deviations in the cable dataset DW, including tensile force deviation DFL, temperature deviation DT, vibration frequency deviation DFv, and rotational speed deviation DVz. The tensile deviation DFL is obtained using the following formula: ； In the formula, FLtar represents the set target tensile force value; Temperature deviation DT is obtained using the following formula: ； In the formula, T(t) represents the temperature at time t, and Ttar represents the set target temperature value; The vibration frequency deviation DFv is obtained by the following formula: ； In the formula, FV(t) represents the vibration frequency at time t, and Fvtar represents the target vibration frequency; The speed deviation DVz is obtained using the following formula: ； In the formula, Vz(t) represents the rotational speed at time t, and Vztar represents the set target rotational speed; The obtained tensile deviation DFL, temperature deviation DT, vibration frequency deviation DFv, and speed deviation DVz are compared with the preset tensile warning threshold Tdf, temperature warning threshold Tdt, vibration warning threshold Tfv, and speed warning threshold Tvz to determine whether the warning signal Yw is triggered. The warning signal Yw is obtained using the following formula: ； In the formula, when the warning signal Yw=1, it indicates that a warning has been triggered; when the warning signal Yw=0, it indicates that there is no warning.

5. The intelligent monitoring system for cable production quality according to claim 4, characterized in that: The production status assessment unit fits the obtained tension deviation DFL, temperature deviation DT, vibration frequency deviation DFv, and speed deviation DVz to obtain the deviation set PC={DFL, DT, DFv, DVz}. The obtained deviation set PC is combined with the tensile change rate ΔFL and the production environment pressure change ΔPa to evaluate the cable production status, obtain the status evaluation value Ssta, and compare it with the preset evaluation threshold Tst to determine the cable production status. The state evaluation value Ssta is obtained using the following formula: ； Where, Let PCi represent the weight coefficient of the i-th deviation term in the deviation set PC. The weighting coefficient represents the rate of change of tensile force ΔFL. The weighting coefficient represents the change in production environment pressure ΔPa; The production status of the cable is obtained by matching in the following way: When the status assessment value Ssta > the assessment threshold Tst, it indicates that the cable's production status is abnormal. When the status assessment value Ssta ≤ assessment threshold Tst, it indicates that the cable's production status is normal.

6. The intelligent monitoring system for cable production quality according to claim 5, characterized in that: The automatic adjustment and control module includes a deviation response and adjustment unit and a production status feedback and optimization unit; The deviation response and adjustment unit adjusts the parameters θ of the production equipment based on the acquired deviation set PC, including tension deviation DFL, temperature deviation DT, vibration frequency deviation DFv, and speed deviation DVz. The parameters θ include tension FL, temperature T, speed Vz, and vibration frequency Fv. The unit also acquires new parameters nθ, including adjusting tension nFL, adjusting temperature nT, adjusting speed nVz, and adjusting vibration frequency nFv. The tension (nFL) is adjusted using the following formula: ; In the formula, R1 represents the adjustment factor for tension deviation; The temperature nT is obtained using the following formula: ; In the formula, R2 represents the adjustment factor for temperature deviation; The rotational speed nVz is obtained using the following formula: ; In the formula, R3 represents the adjustment factor for the speed deviation; The vibration frequency adjustment nFv is obtained using the following formula: ； In the formula, R4 represents the adjustment factor for the vibration frequency deviation.

7. The intelligent monitoring system for cable production quality according to claim 6, characterized in that: The production status feedback and optimization unit adjusts the adjustment factors R1 for tension deviation, R2 for temperature deviation, R3 for speed deviation, and R4 for vibration frequency deviation based on the production status assessment value Ssta. Among them, the adjustment factors R1 for tension deviation, R2 for temperature deviation, R3 for rotational speed deviation, and R4 for vibration frequency deviation are integrated to obtain the set of adjustment factors R={R1, R2, R3, R4}. When the status evaluation value Ssta is greater than the evaluation threshold Tst, the production status of the cable is abnormal. The adjustment factor set R = {R1, R2, R3, R4} is adjusted to obtain a new adjustment factor set nR = {nR1, nR2, nR3, nR4}. The formula is as follows: ； In the formula, nRa represents the a-th adjustment factor in the new adjustment factor set, Ra represents the a-th adjustment factor in the adjustment factor set, and γ represents the adjustment coefficient.

8. The intelligent monitoring system for cable production quality according to claim 1, characterized in that: The system feedback and optimization module evaluates the adjusted production status by comparing the new parameter nθ with the target parameter, and obtains the adjustment effect and the effect evaluation value Etop; The target parameters include the target tensile force value FLtar, the target temperature value Ttar, the target vibration frequency Fvtar, and the target rotational speed Vztar; The adjustment effects include tension adjustment effect XFL, temperature adjustment effect XT, speed adjustment effect XVz, and vibration frequency adjustment effect XFv; The tension adjustment effect XFL is obtained using the following formula: ； The temperature adjustment effect XT is obtained using the following formula: ； The vibration frequency adjustment effect XFv is obtained using the following formula: ； The speed adjustment effect XVz is obtained using the following formula: ； The effectiveness evaluation value Etop is obtained using the following formula: ； Where, These represent the preset weight values ​​for the tension adjustment effect XFL, temperature adjustment effect XT, vibration frequency adjustment effect XFv, and speed adjustment effect XVz, respectively. The obtained effect evaluation value Etop is compared with the preset effect threshold Teto to determine the accuracy of the adjustment effect; The accuracy of the adjustment effect is obtained by matching in the following ways: When the effect evaluation value Etop ≤ the effect threshold Teto, it means that the adjustment effect is accurate and ideal, and no feedback needs to be triggered. When the effect evaluation value Etop > the effect threshold Teto, it indicates that the accuracy of the adjustment effect is not ideal, triggering feedback. The effect evaluation value Etop is used as feedback status information and fed back to the automatic adjustment and control module to correct the new adjustment factor set nR and obtain the corrected adjustment factor set XnR={XnR1, XnR2, XnR3, XnR4}. The formula is as follows: ； In the formula, XnRa represents the a-th adjustment factor in the set of adjustment factors.

9. The intelligent monitoring system for cable production quality according to claim 8, characterized in that: The data storage and reporting module is responsible for recording, storing and managing the cable dataset DW, deviation warning signals and effect evaluation values ​​Etop in real time, and generating automated reports, including production indicators, adjustment effects and deviation control status. Production indicators represent various data during cable production, including temperature T, tensile force FL, rotational speed Vz, vibration frequency Fv, material thickness Dm, tensile force change rate ΔFL, and production environment pressure change ΔPa. The adjustment effect represents the comparison between the actual result obtained after adjusting deviations in the production process and the expected target, including the tension adjustment effect XFL, temperature adjustment effect XT, speed adjustment effect XVz, and vibration frequency adjustment effect XFv. The deviation control status reflects whether the tension deviation (DFL), temperature deviation (DT), vibration frequency deviation (DFv), and speed deviation (DVz) in the production process are maintained within the preset threshold range. Whenever the deviation exceeds the preset threshold, the deviation will be recorded and the problem of taking adjustment measures to correct the deviation will be described.

10. A method for intelligent monitoring of cable production quality, applied to the intelligent monitoring system for cable production quality as described in any one of claims 1 to 9, characterized in that: Includes the following steps: Step 1: The data acquisition and sensing module collects raw data from the production process through sensors and fits it into the original dataset GD; Step 2: The data preprocessing module cleans, fills in missing values, and normalizes the original dataset GD to obtain the cable dataset DW; Step 3: The deviation detection and early warning module monitors the data deviation in the cable dataset DW, obtains the deviation set PC, and compares it with the set threshold to determine whether to issue a deviation early warning signal; and combines the tensile change rate ΔFL and the production environment pressure change ΔPa to evaluate the cable production status and obtain the status evaluation value Ssta. Step 4: The automatic adjustment and control module automatically adjusts the parameters θ of the production equipment based on the deviation set PC and the status evaluation value Ssta, and obtains the new parameters nθ. Step 5: The system feedback and optimization module monitors the adjusted production status based on the acquired new parameter nθ, evaluates the adjustment effect, obtains the effect evaluation value Etop, and provides feedback status information. Step Six: The data storage and reporting module records the cable dataset DW, deviation warning signals, and effect evaluation values ​​Etop during the production process, generates reports, and records them.

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