Composite fiber production control system using clean flexible ingredients

Abstract

The invention discloses a composite fiber production control system using clean flexible ingredients, and relates to the technical field of industrial automatic control system devices, raw material characteristic data are collected, the proportion is dynamically adjusted, and the precision is 0.1%; the process temperature is collected at multiple points, and the temperature control precision of the PID algorithm is + / -1 DEG C; pump body parameters are adjusted to make flow velocity fluctuation smaller than or equal to 0.5 m / s; circular blowing parameters are adjusted according to different fiber finenesses; collecting whole-process data, and storing for more than or equal to 3 years; the DCS central control module is used for centrally regulating and controlling parameters; and the adaptive module is flexibly produced, and process switching is completed within 10 minutes. According to the invention, raw material ratio, temperature and flow velocity control precision are improved, spinning and post-processing technologies are optimized, whole-process quality tracing is realized, energy consumption and production loss are reduced, product performance consistency is improved, collinear multi-variety production is supported, production line flexibility and efficiency are enhanced, and the method is suitable for large-scale production of multi-specification composite fibers.

Description

Technical Field

[0001] This invention relates to the field of industrial automatic control system devices, and in particular to a composite fiber production control system using clean and flexible ingredients. Background Technology

[0002] In the composite fiber manufacturing industry, core-spun composite fibers, possessing multiple material physical properties, have become a core category of functional specialty fibers. However, their production process involves complex steps such as multi-raw material ratios, temperature / flow rate control at multiple process nodes, and flexible adaptation to various varieties. Traditional production control systems are no longer sufficient to meet the demands for high-quality and highly flexible production. Traditional systems rely heavily on manual experience for raw material ratio control. Real-time characteristics such as moisture content and particle size distribution of raw materials like recycled polyester and plastic granules are not incorporated into the dynamic adjustment system, resulting in insufficient ratio precision. This leads to fluctuations in melt properties after mixing different batches of raw materials, directly affecting the consistency of the physical properties of the composite fibers. Furthermore, temperature control at process nodes such as drying, melting, and spinning uses fixed parameters without real-time compensation based on ambient temperature and the initial state of the raw materials. Control deviations in key temperature ranges such as 160℃ for vacuum drying, 80℃ for continuous drying, and 275℃ for melting can easily cause insufficient drying of raw materials or melt degradation, increasing production losses.

[0003] In the melt delivery process, traditional systems only control the flow rate in a single dimension, without coordinating adjustments based on parameters such as melt viscosity and temperature. This leads to a deviation in the proportion of the two-component melt entering the composite spinning box, resulting in uneven component distribution in the core-sheath composite fibers and failing to fully leverage the performance advantages of multi-material composites. Furthermore, the control of annular blowing parameters in the spinning process lacks flexibility. Conventional annular blowing conditions of 800Pa pressure and ±25℃ temperature cannot meet the production needs of special varieties such as ultra-coarse denier and ultra-fine denier fibers, and cannot achieve simultaneous production of multiple varieties on the same production line, thus restricting the flexible production capacity of the production line. In addition, the operating parameters of the static mixer are not optimized in conjunction with melt characteristics, resulting in insufficient mixing uniformity between additives and the melt, affecting the dispersion effect of functional masterbatches in the fibers and reducing the functional indicators of the composite fibers.

[0004] The delayed adjustment of process parameters in post-processing stages such as drawing, crimping, and heat setting, coupled with the lack of precision in controlling the speed ratio between low-temperature humidity drawing and drying cold roller drawing, easily leads to incomplete molecular orientation of fiber monofilaments and substandard elasticity and mechanical properties. Furthermore, traditional quality traceability systems only cover finished product testing data, failing to achieve full-process data collection and correlation, including raw material ratios, process parameters, and equipment operating status. This makes it difficult to quickly pinpoint the root cause of product quality issues. The lack of a fault warning mechanism means that parameters such as temperature and flow rate cannot be self-calibrated in a timely manner when they deviate from thresholds, easily causing production interruptions, increasing production management costs, and failing to meet the large-scale production needs of 80,000 tons of functional composite specialty fibers annually. Summary of the Invention

[0005] The present invention proposes a composite fiber production control system using clean and flexible ingredients to solve the problems mentioned in the prior art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a composite fiber production control system using clean and flexible ingredients, comprising;

[0007] The raw material ratio intelligent control module is equipped with raw material component sensors and ratio algorithm models to collect data on the moisture content and particle size distribution of recycled polyester, plastic granules and chips. It dynamically adjusts the raw material mixing ratio based on product functional requirements, supports real-time adaptation of multi-component raw materials under clean and flexible processes, and records ratio parameters and associates them with production batches.

[0008] The real-time temperature monitoring and regulation module deploys multiple temperature sensors at process nodes and uses a PID adaptive algorithm to adjust the output power of the heating device and compensate for the impact of ambient temperature fluctuations on the process in real time.

[0009] The melt flow rate precision control module collects flow rate data through the speed sensors of the melt booster pump and metering pump, and adjusts the pump operating parameters in combination with the real-time value of melt viscosity to control the melt delivery flow rate fluctuation range to ≤0.5m / s. The two-component melt enters the composite spinning box according to the preset ratio.

[0010] The online optimization module for spinning process parameters integrates a ring blower sensor to monitor air pressure, air temperature, and humidity data. Based on the fiber fineness requirements, the ring blower parameters are optimized. For ultra-coarse denier / ultra-fine denier varieties, the air pressure is adjusted to 2900Pa, the air temperature is ±8℃, and the humidity is ≥90%. At the same time, the speed ratio parameters of low-temperature humidity drafting and dry cold roll drafting are optimized.

[0011] The quality traceability and data collection module associates production batches with RFID tags, collects data throughout the entire process, and stores data for no less than 3 years. It supports retrieval and traceability by batch and product model.

[0012] The DCS central control module integrates data from various sub-modules and adopts a distributed control architecture to achieve centralized control of raw material ratio, temperature, flow rate, and spinning process. It also supports one-click switching and automatic calibration of process parameters.

[0013] The flexible production adaptation module automatically adjusts the spinning components, spinneret parameters, and post-processing drawing and crimping processes based on product specifications, adapting to the production of fibers of different fineness, such as ultra-coarse denier and ultra-fine denier, with a switching response time of ≤10 minutes.

[0014] Furthermore, it also includes a melt impurity removal effect evaluation module. This module collects melt impurity content data in the uniform slag removal process through an impurity concentration sensor, and combines it with the mixer conical stirring blade speed and vacuum parameters to quantify the impurity removal efficiency and feed it back to the raw material proportioning module. When the impurity removal efficiency is lower than the preset threshold, the mixer temperature parameter in the range of 275-285℃ is automatically adjusted.

[0015] Furthermore, it also includes an online fiber fineness detection module. This module is equipped with a laser fineness sensor to collect real-time data on the fineness of the fiber monofilaments after spinning and curing, with a detection accuracy of 0.1 dtex. When the fineness deviation exceeds ±0.2 dtex, it is fed back to the melt flow rate control module and the spinning process optimization module to dynamically adjust the metering pump speed and the ring blower pressure.

[0016] Furthermore, it also includes a dynamic optimization module for raw material proportions, which achieves multi-objective ingredient control by constructing a proportion optimization formula. The formula is as follows: Where M is the ratio optimization coefficient with a value of 0-1, α is the raw material density weighting coefficient with a value of 0.4-0.5, W1 is the amount of recycled polyester fed in kg, and ρ1 is the density of recycled polyester in g / cm³. 3 W2 is the amount of plastic granules fed, in kg; ρ2 is the density of plastic granules, in g / cm³. 3 β is the moisture content correction coefficient with a value of 0.3-0.4, C1 is the actual moisture content of the raw material in %, C0 is the required moisture content of the process in %, C2 is the maximum moisture content of the raw material in %, γ is the product function adaptation coefficient with a value of 0.1-0.2, and η is the fiber target function achievement degree with a value of 0-1. By dynamically adjusting the raw material ratio through this coefficient, the raw material characteristics and product function requirements can be balanced, and the flexibility and accuracy of the formulation can be improved.

[0017] Furthermore, it also includes a drying process energy efficiency optimization module. This module collects steam consumption and drying time data of the two-stage vacuum drum drying system, and optimizes the synergistic parameters of drying temperature and vacuum degree in combination with the initial moisture content of the raw material. When the moisture content of the raw material is higher than 1.5%, it automatically extends the vacuum drying time to 13-14 hours, while reducing steam consumption by 5%-8%.

[0018] Furthermore, it also includes a post-processing adaptation module. This module collects data on fiber tension, crimp degree, and moisture content for the drawing, crimping, and heat setting processes. It automatically adjusts the speed ratio parameters of low-temperature humidity drawing and the steam temperature range of 60°C for relaxation heat setting. When producing composite fibers with high elasticity requirements, it increases the crimping machine pressure and extends the heat setting time to improve the fiber elasticity recovery rate.

[0019] Furthermore, it also includes a melt flow rate and temperature coordinated control module, which achieves precise matching of process parameters by constructing a coordinated control formula, the formula being: Where V is the target melt flow rate in m / s, k is the temperature-flow rate correlation coefficient with a value of 0.02-0.03, T is the actual melt temperature in °C, T0 is the melt process reference temperature in °C, μ is the melt viscosity in Pa·s, ΔP is the melt delivery pressure difference in MPa, δ is the time correction coefficient with a value of 0.01-0.02, and t is the melt delivery time in s. By combining this formula with real-time monitored temperature, viscosity, and pressure data, the melt pump rotation is dynamically adjusted.

[0020] Furthermore, it also includes a ring air cooling zone control module, which divides the spinning ring air cooling device into multiple independent control zones. Each zone is equipped with independent air pressure, temperature and humidity sensors and regulating valves, supporting the simultaneous production of two composite fibers of different fineness on the same production line. The air pressure adjustment range for different zones is 800-2900Pa, and the temperature and humidity are independently controlled.

[0021] Furthermore, it also includes a fault warning and self-calibration module. This module analyzes the parameter deviation data collected by each sensor. When the temperature deviation exceeds ±3℃ or the flow rate fluctuation exceeds 1m / s, it automatically triggers an early warning and starts a self-calibration program to adjust the power of the heating device or the parameters of the melt pump. At the same time, it records the fault information and associates it with the quality traceability data.

[0022] Furthermore, it also includes a static mixing effect monitoring module, which collects uniformity data after the additive and melt are mixed, and optimizes the mixing unit speed and melt residence time based on the operating parameters of the spiral blade and grid dual-unit static mixer.

[0023] Compared with existing technologies, the beneficial effects of this invention are:

[0024] The composite fiber production control system of this invention, utilizing clean and flexible material proportioning, optimizes multiple dimensions such as raw material ratio, process parameter control, production flexibility adaptation, and quality traceability, significantly improving the intelligence, precision, and flexibility of composite fiber production. In the raw material proportioning stage, the system dynamically adjusts the mixing ratio by collecting real-time data on raw material moisture content, particle size distribution, and other characteristics. This overcomes the precision limitations of traditional manual proportioning, ensuring the raw material ratio adapts to the adjustment requirements of clean and flexible processes, guaranteeing the consistency of melt performance across different batches, and laying a stable raw material foundation for subsequent composite spinning.

[0025] The coordinated control of temperature and melt flow rate enables precise adjustment and real-time compensation of temperature at each process node, reducing the impact of environmental fluctuations on drying and melting processes, avoiding insufficient raw material drying or melt degradation, and improving melt purity and stability. Simultaneously, the flow rate is dynamically adjusted based on melt viscosity, pressure, and other parameters to ensure that the two-component melt enters the spinning box in a preset ratio, optimizing the core-sheath component distribution of the composite fiber and fully leveraging the performance advantages of multi-material composites. The online optimization module for spinning process parameters adjusts the ring blowing parameters for fibers of different fineness, adapting to the production of special varieties such as ultra-coarse denier and ultra-fine denier. Zoned control of the ring blowing further enables simultaneous production of multiple varieties on the same production line, significantly improving the production line's flexible production capacity and reducing product changeover time costs.

[0026] The system's quality traceability module enables full-process data collection and batch correlation, covering data such as raw material ratios, process parameters, and equipment operating status. When quality issues arise, the root cause can be quickly located, improving quality control efficiency. The fault warning and self-calibration module can promptly identify parameter deviations and automatically adjust them, reducing the risk of production interruptions and ensuring the continuity of large-scale production. The static mixing effect monitoring and post-processing adaptation module optimizes the additive dispersion effect and fiber stretching and crimping properties, respectively, improving the functionality and mechanical properties of the composite fibers.

[0027] Overall, the system achieves centralized control and intelligent linkage of all stages through DCS central control, balancing production efficiency, product quality, and flexible adaptation requirements. It effectively reduces production losses and management costs, and is suitable for large-scale production of tens of thousands of tons of functional composite specialty fibers annually. Simultaneously, the system's precise control over impurity removal, drying, and oiling processes further enhances melt purity and fiber surface properties, reducing energy consumption and emissions during production. This aligns with the industry trend of cleaner production, comprehensively improving the company's overall production efficiency and market competitiveness. Attached Figure Description

[0028] Figure 1 This is a schematic block diagram of a composite fiber production control system using clean and flexible ingredients proposed in this invention.

[0029] Figure 2 A bar chart comparing the accuracy of raw material proportions for different fiber varieties;

[0030] Figure 3 Line graph showing the effect of annular airflow pressure on fiber cooling uniformity;

[0031] Figure 4 A bar chart comparing steam consumption for different drying processes;

[0032] Figure 5 A line graph showing the relationship between process changeover time and fiber type;

[0033] Figure 6 A bar chart comparing the fiber breaking strength of different drawing processes. Detailed Implementation

[0034] 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.

[0035] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0036] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified. Furthermore, the terms "installed," "connected," and "linked" should be interpreted broadly; for example, they may refer to a fixed connection, a detachable connection, or an integral connection; they may refer to a mechanical connection or an electrical connection; they may refer to a direct connection or an indirect connection through an intermediate medium; and they may refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances. The invention will now be described in further detail with reference to the accompanying drawings.

[0037] Reference Figures 1 to 6 A composite fiber production control system using clean and flexible ingredients includes the following modules;

[0038] The raw material ratio intelligent control module is equipped with raw material component sensors and a ratio algorithm model. The raw material component sensors collect data on the moisture content and particle size distribution of recycled polyester, plastic granules and chips once per second. The ratio algorithm model dynamically adjusts the raw material mixing ratio based on product functional requirements, with a ratio control accuracy of 0.1%. It supports real-time adaptation of multi-component raw materials under clean and flexible processes, synchronously records the ratio parameters and establishes a unique association identifier with the production batch.

[0039] The real-time temperature monitoring and regulation module deploys multiple temperature sensors at process nodes such as vacuum drying, continuous drying, extrusion melting, and spinning. The sensor detection accuracy is ±0.5℃, covering process temperature ranges such as 160℃ for vacuum drying, 80℃ for continuous drying, 275℃ for recycled polyester melting, 250-265℃ for plastic granule melting, and 275℃ for spinning. It uses a PID adaptive algorithm to adjust the output power of the heating device, with a temperature control accuracy of ±1℃. It also collects ambient temperature data in real time and compensates for the impact of ambient temperature fluctuations on process temperature.

[0040] The melt flow rate precision control module collects melt delivery flow rate data twice per second through the melt booster pump and metering pump speed sensor. Combined with the online detection value of melt viscosity, the pump operating parameters are adjusted to control the fluctuation range of melt delivery flow rate within 0.5m / s, ensuring that the two-component melt enters the composite spinning box in a preset ratio.

[0041] The online optimization module for spinning process parameters integrates sensors for ring blower pressure, temperature, and humidity. The sensor detection accuracies are ±10Pa, ±0.5℃, and ±1%, respectively. Based on the fiber fineness requirements, the ring blower parameters are optimized. For ultra-coarse denier and ultra-fine denier varieties, the air pressure is adjusted to 2900Pa, the air temperature is controlled at ±8℃, and the humidity is adjusted to ≥90%. At the same time, the speed ratio parameters of low-temperature humidity drafting and dry cold roll drafting are optimized, with the speed ratio adjustment range being 1.2-5.0.

[0042] Quality traceability and data collection module assigns a unique identifier to each production batch through RFID tags, and collects process parameters and test data for the entire process, including raw material ratio, temperature, flow rate, spinning process, and post-processing. The data storage period is set to more than 3 years, and it supports searching traceability data by production batch, product model, and production time.

[0043] The DCS central control module adopts a distributed control architecture, integrates real-time data collected by each sub-module, and realizes centralized control of raw material ratio, temperature, flow rate and spinning process parameters. It supports one-click switching and automatic calibration of process parameters, and the calibration cycle is set to once per production batch.

[0044] The flexible production adaptation module automatically adjusts the operating parameters of the spinning components and spinnerets, as well as the post-processing drawing and crimping process parameters, based on product specification requirements. It adapts to the production of fibers of different fineness, such as ultra-coarse denier and ultra-fine denier, and the process parameter switching response time is controlled within 10 minutes.

[0045] This invention also includes a melt impurity removal effect evaluation module. This module is equipped with an impurity concentration sensor with a detection accuracy of 0.01 mg / L to collect melt impurity content data during the uniform slag removal process. It combines the mixer conical stirring blade speed and vacuum degree parameters to quantify the impurity removal efficiency. The impurity removal efficiency calculation result is fed back to the raw material ratio intelligent control module. When the impurity removal efficiency is lower than the preset threshold, the mixer temperature is automatically adjusted to the target value in the range of 275-285℃ with an adjustment step of 1℃, so that the melt impurity content is controlled below 0.05 mg / L.

[0046] This invention also includes an online fiber fineness detection module. This module is equipped with a laser fineness sensor with a detection accuracy of 0.1 dtex, which collects the fiber single filament fineness data in real time at a frequency of once per second after spinning and curing. When the fineness deviation exceeds the range of ±0.2 dtex, the detection result is fed back to the melt flow rate precision control module and the online optimization module for spinning process parameters, which dynamically adjust the metering pump speed and the ring blower pressure. The metering pump speed adjustment step is 0.1 r / min, and the ring blower pressure adjustment step is 50 Pa, thereby realizing closed-loop control of fiber fineness.

[0047] This invention also includes a raw material ratio dynamic optimization module, which achieves multi-objective ingredient control by constructing a ratio optimization formula, the formula being: Where M is the ratio optimization coefficient with a value of 0-1, α is the raw material density weighting coefficient with a value of 0.4-0.5, W1 is the amount of recycled polyester fed in kg, and ρ1 is the density of recycled polyester in g / cm³. 3 W2 is the amount of plastic granules fed, in kg; ρ2 is the density of plastic granules, in g / cm³. 3 β is the moisture content correction coefficient with a value of 0.3-0.4, C1 is the actual moisture content of the raw material in %, C0 is the required moisture content of the process in %, C2 is the maximum moisture content of the raw material in %, γ is the product function adaptation coefficient with a value of 0.1-0.2, and η is the fiber target function achievement degree with a value of 0-1. By dynamically adjusting the raw material ratio through this coefficient, the raw material characteristics and product function requirements can be balanced, and the flexibility and accuracy of the formulation can be improved.

[0048] This invention also includes a drying process energy efficiency optimization module. This module collects data on steam consumption, drying time, and initial moisture content of the raw material in the two-stage vacuum drum drying system once per minute. Based on the initial moisture content of the raw material, it optimizes the synergistic parameters of drying temperature and vacuum degree. When the initial moisture content of the raw material is higher than 1.5%, it automatically extends the vacuum drying time to 13-14 hours and reduces steam consumption by 5%-8%, so that the moisture content of the raw material after drying is controlled below 0.5%.

[0049] This invention also includes a post-processing adaptation module. This module is equipped with a filament tension sensor, a crimping tester, and a moisture content tester with detection accuracies of ±0.1N, ±1%, and ±0.2%, respectively. It collects data on filament tension, crimping, and moisture content, and automatically adjusts the speed ratio parameters of low-temperature humidity stretching and the steam temperature of relaxation heat setting. The adjustment range of the relaxation heat setting steam temperature is 60±5℃. When producing composite fibers with high elasticity requirements, the crimping machine pressure is adjusted to 0.3-0.5MPa and the heat setting time is extended to 15-20 minutes to optimize the fiber elasticity recovery rate.

[0050] This invention also includes a melt flow rate and temperature coordinated control module, which achieves precise matching of process parameters by constructing a coordinated control formula, the formula being: Where V is the target melt flow rate in m / s, k is the temperature-flow rate correlation coefficient (0.02-0.03), T is the actual melt temperature in °C, T0 is the melt process reference temperature in °C, μ is the melt viscosity in Pa·s, ΔP is the melt delivery pressure difference in MPa, δ is the time correction coefficient (0.01-0.02), and t is the melt delivery time in s. By combining this formula with real-time monitored temperature, viscosity, and pressure data, the melt pump speed is dynamically adjusted to ensure coordinated adaptation between flow rate and temperature, thereby reducing differences in melt degradation.

[0051] This invention also includes a ring air cooling zone control module, which divides the spinning ring air cooling device into at least two independent control zones. Each zone is equipped with air pressure, temperature and humidity sensors with detection accuracies of ±10Pa, ±0.5℃, and ±1%, respectively, and regulating valves with a response time of ≤2 seconds. This supports the simultaneous production of two composite fibers of different fineness on the same production line. The air pressure adjustment range for different zones is 800-2900Pa, and the temperature and humidity are independently controlled.

[0052] This invention also includes a fault warning and self-calibration module. This module analyzes the parameter deviation data collected by each sensor. When the temperature deviation exceeds ±3℃ or the flow rate fluctuation exceeds 1m / s, it automatically triggers a warning signal and starts a self-calibration program. It adjusts the power of the heating device or the parameters of the melt pump according to a preset algorithm, with adjustment steps of 5W and 0.1r / min, respectively. At the same time, it records the fault type, occurrence time, calibration process data, and associates them with the production batch data of the quality traceability module.

[0053] This invention also includes a static mixing effect monitoring module. This module is equipped with a mixing uniformity detector with a detection accuracy of ±1% to collect uniformity data after the additive and melt are mixed. Based on the operating parameters of the spiral blade and grid dual-unit static mixer, the mixing unit speed and melt residence time are optimized. The mixing unit speed is adjusted within the range of 50-150 r / min, and the melt residence time is adjusted within the range of 10-30 seconds, so that the performance index deviation of each part of the composite fiber is controlled within 2%.

[0054] The following two examples further illustrate the specific implementation of this system:

[0055] Example 1

[0056] Applications in the production of ultra-coarse denier core-spun composite fibers

[0057] This embodiment addresses the need for large-scale production of ultra-coarse denier core-spun composite fibers, with a single filament fineness ≥20dtex. It requires balancing the precision of clean and flexible raw material proportions with the stability of the spinning process. Traditional control systems suffer from problems such as large proportion fluctuations, poor adaptability of ring blowing parameters, and low product performance consistency. The composite fiber production control system using clean and flexible materials of this invention solves the above problems.

[0058] I. Preliminary Preparations and System Deployment

[0059] 1. Equipment Configuration: The system deploys a raw material ratio intelligent control module, equipped with raw material component sensors with a moisture content detection accuracy of 0.01% and a particle size distribution detection accuracy of 0.01mm, and an embedded controller with a ratio algorithm model; the real-time temperature monitoring and adjustment module deploys multi-point temperature sensors with a detection accuracy of ±0.5℃ at process nodes such as vacuum drying, continuous drying, extrusion melting, and spinning, and is equipped with a PID adaptive adjustment heating device; the melt flow rate precision control module is equipped with a melt booster pump, a metering pump speed sensor with a detection accuracy of 0.1r / min, and an online melt viscosity meter with a detection accuracy of 0. .01Pa·s; The online optimization module for spinning process parameters integrates a ring blower sensor with a wind pressure detection accuracy of ±10Pa, a wind temperature detection accuracy of ±0.5℃, and a humidity detection accuracy of ±1%, as well as a zone-controlled ring air cooling device; The quality traceability and data acquisition module deploys RFID tag reading and writing equipment, and is equipped with a distributed database with a storage capacity of ≥10TB; The DCS central control module adopts a distributed control architecture, is equipped with a multi-core processor, and supports multi-module data integration and one-click parameter switching; The flexible production adaptation module is equipped with an automatic adjustment mechanism for spinning components and spinneret parameters, with a mechanism response time of ≤10 minutes.

[0060] 2. Parameter settings: The parameters of the dynamic optimization formula for raw material ratio are set as α=0.45, β=0.35, γ=0.2; the parameters of the formula for coordinated control of melt flow rate and temperature are set as k=0.025, δ=0.015; the parameters of the ring blowing are set as air pressure 2900Pa, air temperature ±8℃, humidity ≥90%; vacuum drying temperature 160℃, processing time 12 hours, continuous drying temperature 80℃; recycled polyester melting temperature 275℃, plastic granule melting temperature 255℃; the pressure adjustment range of the coiling machine in the post-processing stage is 0.3-0.5MPa, and the relaxation heat setting temperature is 60±5℃; the fault warning threshold is set as temperature deviation ±3℃, flow rate fluctuation ±1m / s; the speed adjustment range of the mixing unit of the static mixer is 50-150r / min, and the melt residence time is 10-30 seconds.

[0061] II. System Operation Process

[0062] 1. Intelligent Control of Raw Material Ratio: Raw material component sensors collect data on recycled polyester and plastic granules once per second. The recycled polyester has a moisture content of 1.2% and a particle size distribution of 0.5-1.0 mm, while the plastic granules have a moisture content of 0.8% and a particle size distribution of 0.3-0.8 mm. Based on product functional requirements, the recycled polyester feed rate W1 = 300 kg, and the recycled polyester density ρ1 = 1.38 g / cm³. 3The feed amount of plastic granules is W2 = 500 kg, the density of plastic granules is ρ2 = 0.92 g / cm3, the required moisture content is C0 = 0.5%, the maximum moisture content of the raw materials is C2 = 3.0%, and the fiber target performance achievement η = 0.95. Substitute these values ​​into the proportioning optimization formula.

[0063] The calculation yields: M = 0.45 × (300 × 1.38) / (500 × 0.92) + 0.35 × (1.2 - 0.5) / (3.0 - 0.5) + 0.2 × 0.95 = 0.45 × 0.9 + 0.35 × 0.28 + 0.19 = 0.405 + 0.098 + 0.19 = 0.693. The system dynamically adjusts the raw material mixing ratio based on the M value, fine-tuning the recycled polyester feed amount to 305 kg and maintaining the plastic granule feed amount at 500 kg, achieving a ratio adjustment accuracy of 0.1%. The system simultaneously records the ratio parameters and establishes a unique RFID association with each production batch.

[0064] 2. Real-time temperature monitoring and control: Multi-point temperature sensors collect the temperature of each process node in real time. The ambient temperature of the vacuum drying drum is 25℃. After system compensation, the output power of the heating device is adjusted to 120kW to control the temperature inside the drum to be stable at 160.5℃, with a fluctuation range of ±1℃. The ambient temperature of the continuous drying device is 26℃. After compensation, the temperature inside the drying tower is controlled at 80.2℃. In the recycled polyester melting stage, the heating power of the screw extruder is adjusted to 150kW to control the melting temperature at 275℃. In the plastic granule melting stage, the heating power is adjusted to 130kW to control the melting temperature at 255℃. Both achieve a control accuracy of ±1℃.

[0065] 3. Precise control of melt flow rate: The online melt viscosity analyzer collects the melt viscosity of recycled polyester (0.8 Pa·s), the melt viscosity of plastic granules (0.75 Pa·s), the melt delivery pressure difference ΔP = 0.8 MPa, the melt delivery time t = 30 s, the melt process reference temperature T0 = 275℃, and the actual temperature T = 275℃. Substituting these values ​​into the formula for coordinated control of flow rate and temperature... The calculated value is: V = (0.025 × (275 - 275)) / (0.8 × 0.8) + 0.015 × 30 = 0 + 0.45 = 0.45 m / s. Based on this, the system adjusts the melt booster pump speed to 80 r / min and the metering pump speed to 60 r / min, controlling the melt delivery velocity to be stable at 0.45 m / s with a fluctuation range ≤ 0.5 m / s, ensuring that the two-component melt enters the composite spinning box in a 3:5 ratio.

[0066] 4. Online optimization of spinning process parameters: The ring blower sensor collects the wind pressure of 2890Pa, wind temperature of +5℃ and humidity of 92% in the ultra-coarse denier spinning area. The system determines that the parameters meet the process requirements and no adjustment is needed. At the same time, the speed ratio parameter of low temperature humidity drawing and dry cold roll drawing is optimized to 3.5 to adapt to the molecular orientation requirements of ultra-coarse denier fibers.

[0067] 5. Operation of other modules: The melt impurity removal effect evaluation module collected the melt impurity concentration of 0.03 mg / L during the uniform slag removal process, with an impurity removal efficiency of 98%, requiring no adjustment of the mixer temperature; the fiber fineness online detection module collected the fiber single filament fineness of 20.1 dtex after spinning and curing, with a deviation of ±0.1 dtex, which is within the control range; the drying process energy efficiency optimization module collected the initial moisture content of the raw material of 1.2%, maintained the vacuum drying time at 12 hours, and reduced steam consumption by 7%; the post-processing adaptation module adjusted the crimping machine pressure to 0.4 MPa and the relaxation heat setting time to 18 minutes to improve fiber elasticity; the ring blowing zone control module divided the spinning ring air cooling device into two zones, with the parameters of the ultra-coarse denier production zone being stable, while the other zone was not yet activated; the fault warning and self-calibration module monitored each parameter in real time, with no deviation exceeding the threshold; the static mixing effect monitoring module collected the additive and melt mixing uniformity of 98%, with a performance index deviation of 1.5% for each part of the composite fiber.

[0068] 6. Quality Traceability and DCS Central Control: RFID tags are bound to production batch numbers to collect data on the entire process, including raw material ratio, temperature, flow rate, and spinning process, and store it in a distributed database; the DCS central control module integrates all data, displays the status of each process node in real time, and supports one-click parameter retrieval and automatic calibration.

[0069] 7. Flexible production adaptation: After receiving the ultra-coarse denier process switching command, the system automatically adjusts the spinning components and spinneret parameters, with a switching response time of 8 minutes, which meets the design requirement of ≤10 minutes.

[0070] III. Data Characterization for Effectiveness Verification

[0071] Table 1: Comparison of Production Performance of Ultra-Coarse Denier Core-Spun Composite Fibers

[0072] Performance indicators Traditional control system The control system of this invention Raw material proportioning accuracy (%) ±0.5 ±0.1 Process temperature fluctuation (°C) ±3 ±1 Melt flow rate fluctuation (m / s) ±1.2 ±0.3 Fiber fineness deviation (dtex) ±0.8 ±0.1 Melt impurity removal efficiency (%) 85 98 Drying steam consumption reduction (%) 2 7 Process changeover response time (min) 25 8 Product performance deviation (%) 8 1.5

[0073] Table 1 clearly demonstrates the advantages of the control system of this invention in the production of ultra-coarse denier composite fibers. Traditional control systems have a raw material proportioning accuracy of only ±0.5%, large fluctuations in temperature and flow rate, resulting in fiber fineness deviations of ±0.8 dtex and product performance deviations of 8%. Furthermore, process switching requires 25 minutes, making them unsuitable for flexible production requirements. This system, through optimized proportioning formulas and coordinated temperature-flow rate control, improves proportioning accuracy to ±0.1%, controls temperature and flow rate fluctuations within ±1℃ and ±0.3 m / s respectively, reduces fineness deviation to ±0.1 dtex, and achieves a product performance deviation of only 1.5%. Simultaneously, drying steam consumption is reduced by 7%, and process switching time is shortened to 8 minutes, reducing energy consumption and improving production line flexibility, fully meeting the demands of large-scale, high-quality production of ultra-coarse denier composite fibers.

[0074] Example 2: Application in the production of ultrafine denier core-spun composite fibers

[0075] This embodiment addresses the production requirements of ultrafine denier core-spun composite fibers, where the single filament fineness is ≤1dtex. This places higher demands on the accuracy of raw material proportioning, the adaptability of spinning ring blowing parameters, and post-processing drawing technology. Traditional control systems are prone to problems such as melt degradation, large fiber fineness deviation, and uneven additive dispersion. The system of this invention enables stable production of ultrafine denier fibers.

[0076] I. Preliminary Preparations and System Deployment

[0077] 1. Equipment configuration: The system configuration is the same as in Example 1. Only for the production characteristics of ultra-fine denier, the sensor sampling frequency is optimized. The sampling frequency of the raw material component sensor and the fineness online detection sensor is increased to 2 times per second to ensure high-frequency acquisition of subtle parameter changes.

[0078] 2. Parameter settings: The parameters of the dynamic optimization formula for raw material ratio are set as α = 0.4, β = 0.4, and λ = 0.1; the parameters of the coordinated control formula for melt flow rate and temperature are set as k = 0.03 and δ = 0.01; the parameters of the ring blowing are set as air pressure 2900Pa, air temperature ±8℃, and humidity ≥90%, with actual control at -3℃ and 90%; the vacuum drying temperature is 160℃, the processing time is 12 hours, and the continuous drying temperature is 80℃; the melting temperature of recycled polyester is 275℃, and the melting temperature of plastic granules is 260℃; the pressure adjustment range of the post-processing coiling machine is 0.3-0.5MPa, and the relaxation heat setting temperature is 60±5℃; the fault warning threshold and the static mixer parameters are the same as in Example 1.

[0079] II. System Operation Process

[0080] 1. Intelligent control of raw material ratio: The raw material composition sensor collects data on the moisture content of recycled polyester (1.0%) and particle size distribution (0.3-0.6 mm), and the moisture content of plastic granules (0.6%) and particle size distribution (0.1-0.4 mm). The recycled polyester feed rate is set to W1 = 200 kg, and the recycled polyester density is set to ρ1 = 1.38 g / cm³. 3 The amount of plastic granules fed is W2 = 600 kg, and the density of the plastic granules is ρ2 = 0.92 g / cm³. 3 The process requires a moisture content of C0 = 0.5%, a maximum raw material moisture content of C2 = 3.0%, and a fiber target function achievement rate of η = 0.98. Substituting these values ​​into the formulation optimization formula... The calculation yields: M = 0.4 × (200 × 1.38) / (600 × 0.92) + 0.4 × (1.0 - 0.5) / (3.0 - 0.5) + 0.1 × 0.98 = 0.4 × 0.5 + 0.4 × 0.2 + 0.098 = 0.2 + 0.08 + 0.098 = 0.378. Based on the M value, the system fine-tunes the amount of recycled polyester fed to 205 kg, while maintaining the amount of plastic granules fed at 600 kg, with a proportioning adjustment accuracy of ±0.1%, meeting the batching requirements for ultrafine denier production.

[0081] 2. Real-time temperature monitoring and adjustment: The ambient temperature of the vacuum drying drum is 24℃, and the temperature is controlled at 159.8℃ after system compensation; the ambient temperature of the continuous drying device is 23℃, and the temperature is controlled at 79.9℃ after compensation; the melting temperature of recycled polyester is stable at 275℃, and the melting temperature of plastic granules is stable at 260℃, with temperature fluctuations ≤±1℃, to avoid degradation of the melt due to temperature fluctuations.

[0082] 3. Precise control of melt flow rate: The online melt viscosity analyzer collects the melt viscosity of recycled polyester (0.7 Pa·s), the melt viscosity of plastic granules (0.65 Pa·s), the melt conveying pressure difference ΔP = 0.8 MPa, the conveying time t = 25 s, the melt process reference temperature T0 = 275℃, and the actual temperature T = 275℃. Substituting these values ​​into the formula for coordinated control of flow rate and temperature... The calculated value is: V = (0.03 × (275 - 275)) / (0.7 × 0.8) + 0.01 × 25 = 0 + 0.25 = 0.25 m / s. The system adjusts the melt booster pump speed to 70 r / min and the metering pump speed to 50 r / min, controlling the melt flow rate to stabilize at 0.25 m / s with a fluctuation range of ±0.2 m / s, ensuring that the two-component melt enters the composite spinning box uniformly.

[0083] 4. Online optimization of spinning process parameters: The ring blower sensor collects the air pressure of 2900Pa, air temperature of -3℃ and humidity of 90% in the ultra-fine denier spinning area. The system determines that the parameters are suitable for the cooling requirements of ultra-fine denier. At the same time, the speed ratio parameter of low temperature humidity drawing and dry cold roller drawing is adjusted to 4.0 to ensure that the monofilament molecules are fully oriented.

[0084] 5. Other module operation: The melt impurity removal effect evaluation module collected the melt impurity concentration at 0.04 mg / L, with an impurity removal efficiency of 97%; the fiber fineness online detection module collected the fiber single filament fineness after spinning and curing at 0.95 dtex, with a deviation of ±0.15 dtex, meeting the requirements for ultra-fine denier production; the drying process energy efficiency optimization module collected the initial moisture content of the raw material at 1.0%, maintained the vacuum drying time at 12 hours, and reduced steam consumption by 6%; the post-processing process adaptation module adjusted the crimping machine pressure to 0.35 MPa and the relaxation heat setting time to 16 minutes, improving the elasticity and mechanical properties of ultra-fine denier fibers; the ring blowing zone control module enabled two independent zones, one zone producing ultra-fine denier fibers and the other zone temporarily producing conventional fibers, realizing multi-variety production on the same line; the fault warning and self-calibration module detected a brief deviation of 2℃ in the melt temperature, automatically started the self-calibration program, adjusted the heating device power, and restored the temperature to the set value within 5 seconds; the static mixing effect monitoring module collected the additive and melt mixing uniformity at 97%, and the performance index deviation of various parts of the composite fiber at 1.8%.

[0085] 6. Quality Traceability and DCS Central Control: RFID tags are bound to production batches, collecting and storing data throughout the entire process. The DCS central control module displays the parameters of the ultra-fine denier production area and the regular production area in real time, supporting independent control.

[0086] 7. Flexible production adaptation: After receiving the ultra-fine denier process switching command, the system automatically adjusts the spinning components and spinneret parameters, with a switching response time of 9 minutes, meeting the design requirement of ≤10 minutes.

[0087] III. Data Characterization for Effectiveness Verification

[0088] Table 2: Comparison of Production Performance of Ultrafine Denier Core-Spun Composite Fibers

[0089] Performance indicators Traditional control system The control system of this invention Raw material proportioning accuracy (%) ±0.6 ±0.1 Process temperature fluctuation (°C) ±4 ±1 Melt flow rate fluctuation (m / s) ±1.5 ±0.2 Fiber fineness deviation (dtex) ±0.5 ±0.15 Melt impurity removal efficiency (%) 82 97 Drying steam consumption reduction (%) 1 6 Process changeover response time (min) 30 9 Product performance deviation (%) 10 1.8

[0090] Table 2 data highlights the adaptability and precision of the control system of this invention in the production of ultrafine denier composite fibers. Traditional control systems suffer from low proportioning accuracy and large fluctuations in temperature and flow rate, resulting in a fineness deviation of ±0.5 dtex and a product performance deviation of 10%, and are unable to achieve multi-variety production on the same line. This system, through precise proportioning optimization and temperature-flow rate coordinated control, achieves a proportioning accuracy of ±0.1%, with temperature and flow rate fluctuations controlled within ±1℃ and ±0.2 m / s respectively. Fineness deviation is reduced to ±0.15 dtex, and product performance deviation is only 1.8%. Simultaneously, drying steam consumption is reduced by 6%, process changeover time is shortened to 9 minutes, and zoned control of the ring blowing system enables multi-variety production on the same line. This reduces production costs and improves production line flexibility, solving the core problems of melt degradation and performance instability in ultrafine denier production of traditional systems, thus meeting the high-quality production requirements of ultrafine denier composite fibers.

[0091] Reference Figure 2 This figure illustrates the advantage of the control system of this invention in terms of proportioning accuracy in the production of multi-variety composite fibers. Traditional control systems are affected by factors such as raw material characteristics and manual adjustments, resulting in proportioning accuracy fluctuations of ±0.4% to ±0.6% for different fiber varieties. In ultra-fine denier production, due to the even smaller particle size of the raw materials, the proportioning accuracy can be as low as ±0.6%, leading to unstable melt performance. This invention uses high-frequency data acquisition from raw material component sensors and dynamically adjusts the feed rate using a proportioning optimization formula, stabilizing the proportioning accuracy of all varieties within ±0.1%, eliminating proportioning fluctuations caused by variety differences. This advantage ensures the consistency of melt composition for different functional composite fibers, laying a stable raw material foundation for subsequent spinning and post-processing stages, and significantly improving the quality stability of multi-variety fiber production.

[0092] Reference Figure 3 This figure highlights the core value of the optimized annular blowing parameters in this invention. Traditional annular blowing technology has poor adaptability; an air pressure of 800 Pa can only meet the needs of conventional denier production. When the air pressure is increased to 2900 Pa, the cooling uniformity drops to 80% due to airflow turbulence, making it unsuitable for ultra-coarse / ultra-fine denier production. This invention, through zoned control of air pressure, temperature, and humidity, achieves a cooling uniformity of 96% at 2900 Pa, precisely matching the cooling requirements of ultra-coarse / ultra-fine denier. Even when the air pressure is increased to 3500 Pa, the uniformity remains at 92%. The zoned control technology allows for independent adjustment of parameters for different spinning zones, solving the problem of uneven cooling caused by the "one-size-fits-all" approach of traditional annular blowing. This ensures the consistency of the morphology of special fiber varieties after curing, improving product surface quality and physical properties.

[0093] Reference Figure 4 This figure illustrates the significant energy efficiency optimization effect of the drying process of this invention. Traditional control systems rely solely on fixed temperature parameters, failing to dynamically adjust based on the initial moisture content of the raw materials. In this system, the steam consumption for two-stage vacuum drum drying reaches 110 kg / ton of fiber, resulting in severe energy waste. This invention, through its energy efficiency optimization module, collects data such as raw material moisture content and drying time, dynamically adjusting the vacuum level and heating power. This reduces steam consumption in two-stage vacuum drum drying to 95 kg / ton of fiber, and further reduces it to as low as 82 kg / ton of fiber in energy-saving drying. This reduction in steam consumption not only lowers production costs but also aligns with clean production requirements. Furthermore, the moisture content of the dried raw materials is more stable, avoiding melt degradation caused by insufficient drying, thus balancing energy efficiency and production quality.

[0094] Reference Figure 5This figure illustrates the core advantages of the flexible production adaptation module of this invention. Traditional control systems require manual adjustment of parameters in multiple stages, including spinning components, ring blowers, and drafting, when switching processes. For ultra-fine denier production, the parameter requirements are even more stringent, resulting in switchover times as long as 30 minutes, severely restricting production line flexibility. This invention integrates parameters from each stage through a DCS central control module. The flexible production adaptation module automatically adjusts the parameters of the spinning components, spinnerets, and post-processing. Switchover times for different varieties are stabilized at 7-9 minutes, while the switchover time between ultra-coarse and regular denier is only 8 minutes. This significant reduction in switchover time enhances the production line's adaptability to various product types, enabling rapid response to market demands for multiple varieties and small batches, reducing capacity losses from production changes, and improving production efficiency.

[0095] Reference Figure 6 This invention demonstrates the improvement in fiber mechanical properties resulting from optimized drafting processes. Traditional control systems, such as low-temperature humidity + cold roller drafting and multi-speed ratio drafting, suffer from insufficient precision in temperature and speed ratio control, resulting in a breaking strength of only 3.5-3.7 cN / dtex, which fails to fully achieve monofilament molecular orientation. This invention, through a post-processing adaptation module, precisely controls the temperature, humidity, and cold roller speed ratio during low-temperature humidity drafting. Under this composite drafting process, the fiber breaking strength reaches 4.3 cN / dtex, a 16.2% improvement over traditional processes. This improvement stems from the system's real-time monitoring and dynamic adjustment of filament tension and temperature during drafting, avoiding the problem of nanomolecules separating from the matrix, preserving the performance of functional particles, and enhancing molecular orientation, thus significantly improving the mechanical properties and stability of the composite fiber.

[0096] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A composite fiber production control system using clean and flexible ingredients, characterized in that, Includes the following modules: The raw material ratio intelligent control module is equipped with raw material component sensors and ratio algorithm models to collect data on the moisture content and particle size distribution of recycled polyester, plastic granules and chips. It dynamically adjusts the raw material mixing ratio based on product functional requirements, supports real-time adaptation of multi-component raw materials under clean and flexible processes, and records ratio parameters and associates them with production batches. The real-time temperature monitoring and regulation module deploys multiple temperature sensors at process nodes and uses a PID adaptive algorithm to adjust the output power of the heating device and compensate for the impact of ambient temperature fluctuations on the process in real time. The melt flow rate precision control module collects flow rate data through the speed sensors of the melt booster pump and metering pump, and adjusts the pump operating parameters in combination with the real-time value of melt viscosity to control the melt delivery flow rate fluctuation range to ≤0.5m / s. The two-component melt enters the composite spinning box according to the preset ratio. The online optimization module for spinning process parameters integrates a ring blower sensor to monitor air pressure, air temperature, and humidity data. Based on the fiber fineness requirements, the ring blower parameters are optimized. For ultra-coarse denier / ultra-fine denier varieties, the air pressure is adjusted to 2900Pa, the air temperature is ±8℃, and the humidity is ≥90%. At the same time, the speed ratio parameters of low-temperature humidity drafting and dry cold roll drafting are optimized. The quality traceability and data collection module associates production batches with RFID tags, collects data throughout the entire process, and stores data for no less than 3 years. It supports retrieval and traceability by batch and product model. The DCS central control module integrates data from various sub-modules and adopts a distributed control architecture to achieve centralized control of raw material ratio, temperature, flow rate, and spinning process. It also supports one-click switching and automatic calibration of process parameters. The flexible production adaptation module automatically adjusts the spinning components, spinneret parameters, and post-processing drawing and crimping processes based on product specifications, adapting to the production of fibers of different finenesses such as ultra-coarse denier and ultra-fine denier, with a switching response time of ≤10 minutes.

2. The composite fiber production control system using clean and flexible ingredients according to claim 1, characterized in that, It also includes a melt impurity removal effect evaluation module. This module collects melt impurity content data in the uniform slag removal process through an impurity concentration sensor. Combined with the mixer's conical stirring blade speed and vacuum parameters, it quantifies the impurity removal efficiency and feeds it back to the raw material proportioning module. When the impurity removal efficiency is lower than the preset threshold, it automatically adjusts the mixer temperature parameters in the range of 275-285℃.

3. A composite fiber production control system using clean and flexible ingredients according to claim 1, characterized in that, It also includes an online fiber fineness detection module, which is equipped with a laser fineness sensor to collect real-time data on the fineness of the fiber monofilaments after spinning and curing. The detection accuracy is 0.1 dtex. When the fineness deviation exceeds ±0.2 dtex, it is fed back to the melt flow rate control module and the spinning process optimization module to dynamically adjust the metering pump speed and the air pressure of the ring blower.

4. A composite fiber production control system using clean and flexible ingredients according to claim 1, characterized in that, It also includes a raw material ratio dynamic optimization module, which achieves multi-objective ingredient control by constructing a ratio optimization formula. The formula is as follows: ,in The optimal ratio coefficient is set to a value between 0 and 1. The raw material density weighting coefficient is set to 0.4-0.

5. The unit for the amount of recycled polyester fed is kg. The density of recycled polyester is expressed in g / cm³, and the amount of plastic pellets fed is expressed in kg. The unit for plastic particle density is g / cm³. The moisture content correction factor is set to a value of 0.3-0.

4. The actual moisture content of the raw materials is expressed in percentage. The unit for moisture content required by the process is %. The unit for the maximum moisture content of the raw material is %. The product functionality compatibility coefficient should be set between 0.1 and 0.

2. The fiber target function achievement is set to a value of 0-1. The raw material ratio is dynamically adjusted through this coefficient to balance the raw material characteristics and product functional requirements, thereby improving the flexibility and accuracy of the formulation.

5. A composite fiber production control system using clean and flexible ingredients according to claim 1, characterized in that, It also includes a drying process energy efficiency optimization module, which collects steam consumption and drying time data of the two-stage vacuum drum drying system, and optimizes the synergistic parameters of drying temperature and vacuum degree in combination with the initial moisture content of the raw materials.

6. A composite fiber production control system using clean and flexible ingredients according to claim 1, characterized in that, It also includes a post-processing adaptation module. This module collects data on fiber tension, crimp degree, and moisture content for drawing, crimping, and heat setting processes. It automatically adjusts the speed ratio parameters of low-temperature humidity drawing and the steam temperature range of 60°C for relaxation heat setting. When producing composite fibers with high elasticity requirements, it increases the crimping machine pressure and extends the heat setting time to improve the fiber elasticity recovery rate.

7. A composite fiber production control system using clean and flexible ingredients according to claim 1, characterized in that, It also includes a melt flow rate and temperature coordinated control module, which achieves precise matching of process parameters by constructing a coordinated control formula, the formula being: ,in The target flow rate of the melt. The temperature-flow-rate correlation coefficient is set to a value of 0.02-0.

03. This is the actual temperature of the melt. This is the reference temperature for the melt process. This refers to the melt viscosity. To provide pressure differential for the melt, The time correction factor ranges from 0.01 to 0.

02. The melt delivery time is calculated using this formula, combined with real-time monitoring of temperature, viscosity, and pressure data, to dynamically adjust the melt pump speed.

8. A composite fiber production control system using clean and flexible ingredients according to claim 1, characterized in that, It also includes a ring air cooling zone control module, which divides the spinning ring air cooling device into multiple independent control zones. Each zone is equipped with independent air pressure, temperature and humidity sensors and regulating valves, supporting the simultaneous production of two composite fibers of different fineness on the same production line. The air pressure adjustment range for different zones is 800-2900Pa, and the temperature and humidity are independently controlled.

9. A composite fiber production control system using clean and flexible ingredients according to claim 1, characterized in that, It also includes a fault warning and self-calibration module. This module analyzes the parameter deviation data collected by each sensor. When the temperature deviation exceeds ±3℃ or the flow rate fluctuation exceeds 1m / s, it automatically triggers an early warning and starts a self-calibration program to adjust the power of the heating device or the parameters of the melt pump. At the same time, it records the fault information and associates it with the quality traceability data.

10. A composite fiber production control system using clean and flexible ingredients according to claim 1, characterized in that, It also includes a static mixing effect monitoring module, which collects uniformity data after the additive and melt are mixed, and optimizes the mixing unit speed and melt residence time based on the operating parameters of the spiral blade and grid dual-unit static mixer.

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