High-efficiency polyester fiber continuous production method based on multi-screw cooperation

Abstract

The invention relates to the technical field of high polymer material processing, and discloses an efficient polyester fiber continuous production method based on multi-screw cooperation, which comprises the following steps: S1, raw material pretreatment and conveying: carrying out multi-stage filtration on a polyester raw material, and simultaneously directly conveying supercritical fluid to a feed port of a multi-screw extruder through a closed pipeline; s2, adding a catalyst: adding an organic metal complex catalyst before the polyester raw material enters a reaction extrusion stage; s3, carrying out multi-screw synergistic reaction; s4, data acquisition and analysis; s5, performing dynamic adjustment and feedback; s6, separating and recycling; and S7, spinning and post-processing. Through cooperation of multiple screws and the supercritical fluid and the catalyst, impurities in the raw materials can be dissolved, the activation energy of the reaction can be reduced, the purity of the raw materials can be improved, the viscosity of the materials can be reduced, the flowability is improved, uniform mixing of the raw materials and the catalyst is promoted, the reaction activity is remarkably enhanced, and a foundation is laid for subsequent efficient polymerization reaction; the quality and the production efficiency of the polyester fibers are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of polymer material processing, and specifically to an efficient continuous production method of polyester fiber based on the cooperation of multiple screws. Background Art

[0002] With the rapid development of various industries, the demand for polyester fiber has shown an explosive growth. In order to meet the market demand for high-quality polyester fiber, the cooperation of multiple screws can be utilized to integrate process sections such as polycondensation reaction, melt extrusion, and fiber forming into a continuous process, significantly improving production efficiency and product quality. In the traditional polyester fiber production process, a single screw is used for batch production.

[0003] However, in the current technology, the reaction is directly carried out in a single-screw reactor. The reaction activation energy of polyester raw materials is relatively high and the material fluidity is poor, resulting in low reaction efficiency in the reactor, and further affecting the instability of product quality. Summary of the Invention

[0004] In view of the deficiencies of the prior art, the present invention provides an efficient continuous production method of polyester fiber based on the cooperation of multiple screws, which solves the problems of high reaction activation energy and poor material fluidity during the reaction of polyester raw materials.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: An efficient continuous production method of polyester fiber based on the cooperation of multiple screws, comprising the following steps:

[0006] S1. Raw material pretreatment and transportation: The polyester raw materials are subjected to multi-stage filtration, and at the same time, supercritical fluid is directly transported to the feed inlet of the multi-screw extruder through a closed pipeline;

[0007] S2. Catalyst addition: Before the polyester raw materials enter the reaction extrusion stage, an organometallic complex catalyst is added and preliminarily mixed;

[0008] S3. Multi-screw cooperative reaction: Through the cooperative action of a multi-screw reactor, the supercritical fluid and the preliminarily mixed polyester raw materials are secondarily mixed to form a polyester melt;

[0009] S4. Data acquisition and analysis: In the multi-screw reactor, multiple sensors are installed to real-time collect the operation data during the reaction process;

[0010] S5. Dynamic adjustment and feedback: Based on the collected operation data, machine learning algorithms are used to analyze the data and predict process parameters, and the rotation speed, temperature, and pressure of each screw are dynamically adjusted;

[0011] S6. Separation and recovery: The supercritical water and the catalyst are separated from the polyester melt;

[0012] S7, Spinning and Post-treatment: Continuously convey the polyester melt to the spinning device through a melt gear pump for continuous spinning to produce polyester fibers, and monitor the polyester fibers.

[0013] Preferably, the supercritical fluid in S1 includes supercritical carbon dioxide, supercritical water, or supercritical alcohol, and the injection amount of the supercritical fluid is 0.5% - 5% of the mass of the polyester raw material.

[0014] Preferably, the addition amount of the organometallic complex catalyst in S2 is 0.3% of the total amount of the polyester raw material, and the organometallic complex catalyst includes cerium oxide, phthalic acid derivatives, and titanium dioxide.

[0015] Preferably, the screws in the multi-screw reactor in S3 rotate in opposite directions.

[0016] Preferably, the sensors in S4 are arranged at the feed inlet, discharge outlet, and screw cavity of the multi-screw reactor, and the sensors include pressure sensors, temperature sensors, torque sensors, and flow sensors.

[0017] Preferably, the dynamic adjustment and feedback include the following steps:

[0018] S501. Based on the deep learning neural network model, perform training and learning from historical production data;

[0019] S502. Input the operating data into the model in real time for feature extraction and analysis, and predict the optimal rotational speed, temperature, and pressure parameters of each screw under the current working conditions;

[0020] S503. Send control instructions to the actuator of the multi-screw reactor to control the operating parameters in real time.

[0021] Preferably, in S6, utilize the phase separation characteristics of supercritical water and the polyester melt at a temperature of 380 - 400 °C and a pressure of 8 - 10 MPa, and through gradient pressure reduction and temperature reduction operations, separate the supercritical water from the polyester melt. The catalyst separation is carried out by distillation to recover the catalyst with a purity of over 95%.

[0022] Preferably, the spinning and post-treatment specifically include the following steps:

[0023] S701. Continuously convey the separated polyester melt to the spinning device through a melt gear pump to make nascent fibers;

[0024] S702. Then, subject the nascent fibers to cooling, drawing, and heat setting to produce finished polyester fibers;

[0025] S703. Monitor the diameter, strength, and uniformity of the polyester fibers through quality inspection, and feed back the data to S5 to optimize the operating parameters.

[0026] The present invention provides an efficient continuous production method of polyester fiber based on the cooperation of multiple screws.

[0027] It has the following beneficial effects:

[0028] 1. By the cooperation of multiple screws with supercritical fluid and catalyst, the present invention can dissolve impurities in raw materials, reduce the activation energy of the reaction, improve the purity of raw materials, reduce the viscosity of materials, improve fluidity, promote the uniform mixing of raw materials and catalyst, significantly enhance the reaction activity, lay a foundation for subsequent efficient polymerization reaction, and improve the quality and production efficiency of polyester fiber.

[0029] 2. Through the deep learning neural network model, the present invention trains and learns from historical production data, and inputs operation data into the model for feature extraction and analysis in real time to predict the optimal rotation speed, temperature and pressure parameters of each screw, and then controls the operation parameters in real time, making the production process have stronger adaptability and flexibility, and improving the production efficiency and the stability of continuous production.

[0030] 3. By separating supercritical water and catalyst, the present invention realizes the efficient utilization of resources and cost reduction. And in the spinning and post-treatment steps, the diameter, strength and uniformity of polyester fiber are detected by quality inspection, and the data are fed back to optimize the production operation parameters, forming a quality closed-loop control to continuously improve the product quality. Description of the Drawings

[0031] Figure 1 It is a flowchart of the efficient continuous production method of polyester fiber based on the cooperation of multiple screws of the present invention. Detailed Embodiments

[0032] Next, the technical solutions of the present invention will be clearly and completely described in conjunction with the drawings of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0033] Please refer to the attached Figure 1 , the embodiment of the present invention provides an efficient continuous production method of polyester fiber based on the cooperation of multiple screws, including the following steps:

[0034] S1. Pretreatment and transportation of raw materials: The polyester raw materials are subjected to multi-stage filtration, and at the same time, the supercritical fluid is directly transported to the feed inlet of the multi-screw extruder through a closed pipeline respectively;

[0035] S2. Catalyst addition: Before the polyester raw materials enter the reaction extrusion stage, an organometallic complex catalyst is added and preliminarily mixed;

[0036] S3. Multi-screw collaborative reaction: Through the collaborative action of a multi-screw reactor, the supercritical fluid and the preliminarily mixed polyester raw materials are secondarily mixed to form a polyester melt.

[0037] S4. Data collection and analysis: In the multi-screw reactor, multiple sensors are installed to collect the operation data during the reaction process in real time.

[0038] S5. Dynamic adjustment and feedback: Based on the collected operation data, machine learning algorithms are used to analyze the data and predict the process parameters, and the rotational speeds, temperatures, and pressures of each screw are dynamically adjusted.

[0039] S6. Separation and recovery: The supercritical water and the catalyst are separated from the polyester melt.

[0040] S7. Spinning and post-treatment: The polyester melt is continuously transported to the spinning device through a melt gear pump for continuous spinning to prepare polyester fibers, and the polyester fibers are monitored.

[0041] Specifically, through S1 multi-stage filtration, foreign matters such as impurities and particles in the raw materials can be removed, ensuring the purity of the raw materials, avoiding the influence of these impurities on the product quality during the subsequent reaction and spinning processes, and the raw materials can be prevented from being contaminated by the outside through closed pipeline transportation, while ensuring the continuity and stability of the raw material transportation.

[0042] By adding an organometallic complex catalyst through S2 before the polyester raw materials enter the reaction extrusion stage and performing preliminary mixing, the polyester synthesis reaction can be accelerated. The organometallic complex catalyst has high catalytic activity, can lower the activation energy of the reaction, enable the polyester raw materials to rapidly undergo polymerization reactions at relatively low temperatures and pressures, improve the reaction rate and conversion rate. At the same time, the preliminary mixing can evenly disperse the catalyst in the raw materials, ensuring that the catalyst can fully play its role and making the reaction more uniform and sufficient.

[0043] Through the collaborative action of the multi-screw reactor in S3, the screws with different functions cooperate with each other in the reactor, enabling efficient transportation, mixing, and reaction of the materials. At the same time, the supercritical fluid and the preliminarily mixed polyester raw materials are secondarily mixed. The presence of the supercritical fluid further improves the fluidity and mass transfer performance of the materials, enabling the raw materials and the catalyst to contact and react more fully. Under the action of the multi-screws, the materials in the reactor experience multiple mixing, shearing, and extrusion, promoting the polymerization reaction and forming a uniform and high-quality polyester melt.

[0044] Install multiple sensors in the multi-screw reactor through S4 to collect the operating data during the reaction process in real time, such as material pressure, temperature, screw torque, etc. These data can reflect the real-time state of the reaction process and the characteristics of the materials, and can timely understand the progress of the reaction, the flow state of the materials, and the operating conditions of the equipment. At the same time, the collected data can provide a basis for subsequent process adjustment and optimization to ensure that the reaction process is always in the best state;

[0045] Through S5, machine learning algorithms can process a large amount of complex data, mine the laws and trends behind the data, accurately predict the optimal process parameters of each screw under the current working conditions, and by dynamically adjusting the operating parameters of each screw, the reaction process can always be maintained in the best state, making the production process more adaptable and flexible, and improving production efficiency and the stability of continuous production;

[0046] Through S6, supercritical water and catalyst are separated from the polyester melt to realize the recycling of resources. Since supercritical water plays a role in promoting the reaction and improving the material properties during the reaction process, but may affect the product quality during subsequent spinning and product use, it is necessary to separate it. At the same time, although the catalyst plays a key role in the reaction, if it remains in the polyester product, it may affect the stability and performance of the product, and the recycling of the catalyst can reduce production costs;

[0047] Through S7, the polyester melt is continuously transported to the spinning device through a melt gear pump for continuous spinning to prepare polyester fibers, and by real-time monitoring and feedback of the quality of the polyester fibers, the efficient production and quality stability of the polyester fibers can be ensured.

[0048] In S1, the supercritical fluid includes supercritical carbon dioxide, supercritical water or supercritical alcohol, and the injection amount of the supercritical fluid is 0.5% - 5% of the mass of the polyester raw material.

[0049] Specifically, relying on its unique solubility and swelling properties, the supercritical fluid can effectively dissolve the impurities in the raw materials, promote the diffusion of small molecules, improve the fluidity of the materials, and can also change the physical and chemical properties of the reaction system, accelerate the collision of reactant molecules, promote the subsequent polymerization reaction, and achieve the improvement of the raw material quality and uniformity and the promotion of production efficiency;

[0050] In S2, the addition amount of the organometallic complex catalyst is 0.3% of the total amount of the polyester raw material, and the organometallic complex catalyst includes cerium oxide, phthalic acid derivatives and titanium dioxide.

[0051] Specifically, an organometallic complex catalyst composed of cerium oxide, phthalic acid derivatives, and titanium dioxide, accounting for 0.3% of the total amount, is added to the polyester raw materials. Among them, cerium oxide, due to its special electronic structure, enhances the stability of the catalyst and its ability to resist impurities, inhibiting the occurrence of side reactions; phthalic acid derivatives, because of their similar structure to the polyester raw materials, not only regulate the characteristics of the central metal ions but also improve the solubility and dispersibility of the catalyst in the raw materials; titanium dioxide forms coordination bonds with reactant molecules using its vacant orbitals, significantly reducing the reaction activation energy. The synergistic effect of the three accelerates the polyester synthesis reaction, increases the reaction rate and conversion rate, makes the molecular weight distribution of the resulting polyester product narrower, significantly optimizes the product quality and performance, and enhances the physical properties such as the strength and toughness of the polyester fiber.

[0052] In S3, the screws in the multi-screw reactor rotate in opposite directions.

[0053] Specifically, the multi-screw reactor uses screws that rotate in opposite directions. On the one hand, the opposite rotation causes the materials between the screws to be subjected to forces in both positive and negative directions, strengthening the mixing effect of the materials and ensuring uniform secondary mixing of the supercritical fluid and the preliminarily mixed polyester raw materials, providing a more homogeneous system for subsequent reactions. On the other hand, it can effectively control the residence time distribution of the materials, avoiding local overheating or insufficient reaction of the materials, thereby efficiently forming a polyester melt with excellent performance and stable quality, improving the product quality and production efficiency.

[0054] In S4, sensors are set at the feed inlet, discharge outlet, and screw cavity of the multi-screw reactor. The sensors include pressure sensors, temperature sensors, torque sensors, and flow sensors.

[0055] Specifically, pressure, temperature, torque, and flow sensors are respectively set at the feed inlet, discharge outlet, and screw cavity of the multi-screw reactor, which can comprehensively and real-time monitor the reaction state. The pressure sensor can sense the pressure at the feed, discharge, and inside the cavity to ensure stable material transportation. The temperature sensor controls the temperature of each part to ensure that the reaction proceeds in a suitable thermal environment. The torque sensor monitors the screw torque to reflect the stirring and mixing resistance of the reaction materials. Then the flow sensor measures the feed and discharge flow rates to master the material flow rate. Thus, accurate data is provided to achieve fine regulation of the reaction during subsequent analysis, ensuring stable product quality and improving production efficiency.

[0056] Dynamic adjustment and feedback include the following steps:

[0057] S501. Train and learn from historical production data based on the deep learning neural network model;

[0058] S502. Input the operation data into the model in real time for feature extraction and analysis, and predict the optimal rotation speed, temperature, and pressure parameters of each screw under the current working conditions;

[0059] S503, sending control instructions to the actuator of the multi-screw reactor to control the operating parameters in real time.

[0060] Specifically, S501 uses a deep learning neural network model to train and learn historical production data to explore potential rules and patterns in the data. The historical data covers various parameters under different raw material characteristics and production conditions, as well as corresponding product quality feedback. By learning from a large amount of data, a complex mapping relationship between production parameters and product quality and production efficiency is established, thereby having the ability to understand and predict different production conditions.

[0061] S502 inputs the real-time operation data into the trained model for feature extraction and analysis to quickly and accurately understand the actual state of the current production process. At the same time, the model extracts and analyzes data features such as pressure, temperature, and screw torque to determine which conditions in the current production conditions are similar or different from those in the historical data, and then predicts the optimal speed, temperature, and pressure parameters of each screw under the current conditions based on the learned rules to ensure the efficiency and stability of the production process.

[0062] The optimal parameters predicted by the model are converted into actual production actions through S503 to quickly adjust the screw speed, the temperature of the heating or cooling system, and the pressure of the pressure regulating device to ensure that the production process runs according to the predicted optimal parameters.

[0063] In S6, the phase separation characteristics of supercritical water and polyester melt at a temperature of 380-400°C and a pressure of 8-10MPa are utilized, and supercritical water is separated from the polyester melt through gradient pressure reduction and temperature reduction operations. The catalyst is separated by distillation, and the catalyst with a purity of more than 95% is recovered.

[0064] Specifically, by utilizing the phase separation characteristics of supercritical water and polyester melt at a temperature of 380-400°C and a pressure of 8-10MPa, and separating supercritical water through gradient pressure reduction and temperature reduction operations, it is possible to avoid adverse effects on the performance of the polyester melt due to sudden changes in temperature and pressure, and gradually reduce pressure and temperature to allow supercritical water to slowly escape from the polyester melt, thereby ensuring the stability and uniformity of the polyester melt. The recovered supercritical water can be recycled for raw material pretreatment to achieve efficient resource utilization. At the same time, by separating the catalyst through distillation, the difference in boiling points of different substances can be used to effectively separate the catalyst from the polyester melt, thereby reducing the potential impact of catalyst residues on the quality of polyester fibers and improving the production quality of polyester fibers.

[0065] Spinning and post-processing specifically include the following steps:

[0066] S701, continuously conveying the separated polyester melt to a spinning device through a melt gear pump to form nascent fibers;

[0067] S702. Subsequently, the nascent fibers are cooled, drawn, and heat-set to produce finished polyester fibers.

[0068] S703. Monitor the diameter, strength, and uniformity of the polyester fibers through quality inspection, and feedback the data to S5 to optimize the operating parameters.

[0069] Specifically, through S701, the separated polyester melt is continuously conveyed to the spinning device by a melt gear pump to form nascent fibers. The melt gear pump can precisely control the flow rate and pressure of the polyester melt, ensuring its stable and uniform entry into the spinning device. In the spinning device, under specific temperature, speed, and other conditions, the polyester melt is extruded and stretched through the micropores of the spinneret to form a continuous fibrous material, namely nascent fibers.

[0070] Through S702, the nascent fibers are cooled, drawn, and heat-set. Cooling causes the fibers to solidify rapidly and stabilizes their morphology. Drawing, through mechanical stretching, aligns the molecular chains inside the fibers along the fiber axis, improving the strength and crystallinity of the fibers. Heat-setting, under certain temperature and tension conditions, eliminates the internal stress inside the fibers, further stabilizing the structure and properties of the fibers, enabling the fibers to obtain good dimensional stability, elasticity, and gloss, thereby improving the practicality and durability of the fibers and broadening the application range of polyester fibers.

[0071] Through S703, monitor the diameter, strength, and uniformity of the polyester fibers, and feedback the data to S5 to optimize the operating parameters. Quality inspection can promptly grasp the product quality status, timely detect problems occurring during the production process, and feedback the inspection data to the dynamic adjustment and feedback link, enabling the system to adjust the operating parameters of the multi-screw reactor according to the changes in product quality, realizing the closed-loop control and continuous optimization of the production process.

[0072] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An efficient continuous production method of polyester fiber based on multi-screw cooperation, characterized in that It includes the following steps: S1. Pretreatment and transportation of raw materials: The polyester raw materials are subjected to multi-stage filtration, and at the same time, the supercritical fluid is directly transported to the feed inlet of the multi-screw extruder through a closed pipeline; S2. Catalyst addition: Before the polyester raw materials enter the reaction extrusion stage, an organometallic complex catalyst is added and preliminarily mixed; S3. Cooperative reaction of multi-screws: Through the cooperative action of the multi-screw reactor, the supercritical fluid is added, and the supercritical fluid is secondarily mixed with the preliminarily mixed polyester raw materials to form a polyester melt; S4. Data collection and analysis: In the multi-screw reactor, multiple sensors are installed to collect the operating data during the reaction process in real time; S5. Dynamic adjustment and feedback: Based on the collected operating data, machine learning algorithms are used to analyze the data and predict the process parameters, and the rotational speeds, temperatures, and pressures of each screw are dynamically adjusted; S6. Separation and recovery: The supercritical water and the catalyst are separated from the polyester melt; S7. Spinning and post-treatment: The polyester melt is continuously transported to the spinning device through a melt gear pump for continuous spinning to prepare polyester fibers, and the polyester fibers are monitored.

2. The continuous production method of high-efficiency polyester fiber based on multi-screw cooperation according to claim 1, characterized in that In S1, the supercritical fluid includes supercritical carbon dioxide, supercritical water, or supercritical alcohol, and the injection amount of the supercritical fluid is 0.5% - 5% of the mass of the polyester raw materials.

3. The continuous production method of high-efficiency polyester fiber based on multi-screw cooperation according to claim 1, characterized in that, In S2, the addition amount of the organometallic complex catalyst is 0.3% of the total amount of the polyester raw materials, and the organometallic complex catalyst includes cerium oxide, phthalic acid derivatives, and titanium dioxide.

4. The continuous production method of high-efficiency polyester fiber based on multi-screw cooperation according to claim 1, characterized in that, In S3, the screws in the multi-screw reactor rotate in opposite directions.

5. The continuous production method of high-efficiency polyester fiber based on multi-screw cooperation according to claim 1, characterized in that In S4, the sensors are arranged at the feed inlet, discharge outlet, and screw cavity of the multi-screw reactor, and the sensors include pressure sensors, temperature sensors, torque sensors, and flow sensors.

6. The continuous production method of high-efficiency polyester fiber based on multi-screw coordination according to claim 1, characterized in that, The dynamic adjustment and feedback include the following steps: S501. Based on the deep learning neural network model, training and learning are carried out from historical production data; S502. The operating data is input into the model in real time for feature extraction and analysis, and the optimal rotational speeds, temperatures, and pressure parameters of each screw under the current working conditions are predicted; S503. A control instruction is sent to the actuator of the multi-screw reactor to control the operating parameters in real time.

7. The continuous production method of high-efficiency polyester fiber based on multi-screw cooperation according to claim 1, characterized in that, In S6, the phase separation characteristics of supercritical water and the polyester melt at a temperature of 380 - 400 °C and a pressure of 8 - 10 MPa are utilized, and through gradient pressure reduction and temperature reduction operations, the supercritical water is separated from the polyester melt, and the catalyst is separated by distillation to recover a catalyst with a purity of over 95%.

8. The continuous production method of high-efficiency polyester fiber based on multi-screw coordination according to claim 1, wherein, The spinning and post-treatment specifically include the following steps: S701. The separated polyester melt is continuously transported to the spinning device through a melt gear pump to make nascent fibers; S702. Then the nascent fibers are cooled, drawn, and heat-set to prepare finished polyester fibers; S703. The diameter, strength, and uniformity of the polyester fibers are monitored through quality inspection, and the data is fed back to S5 to optimize the operating parameters.

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