Glass fiber with low dielectric constant, preparation process and clarification temperature control device

Abstract

The invention is applicable to the technical field of glass fibers, and provides a low-dielectric glass fiber, which is characterized by comprising 50.0 to 58.0 wt% of SiO2, 18.0 to 26.0 wt% of B2O3, 13.0 to 18.0 wt% of Al2O3, 0.0 to 5.0 wt% of Mg0, 2.0 to 5.0 wt% of Ca0, 0.0 to 0.5 wt% of R20, 0.0 to 1.5 wt% of TiO2 and 0.0 to 3.0 wt% of a titanium-zirconium-hafnium ternary mixed oxide. The method can effectively solve the problems that in the prior art, bubble detection lags behind, a temperature control system operates in an isolated mode, and technological parameter optimization depends on experience, instant feedback of bubble data is achieved through the real-time online bubble detection technology, and powerful support is provided for accurate adjustment of clarification technological parameters.

Description

Technical Field

[0001] This invention relates to the field of glass fiber technology, and in particular to a low dielectric constant glass fiber, its preparation process, and a clarification temperature control device. Background Technology

[0002] Glass fiber, as a key reinforcing material, has been widely used in wind turbine blades, aerospace, transportation, and defense industries. Its continuous performance improvement is a crucial foundation for supporting technological advancements in these industries. In particular, the development of extreme applications such as ultra-long offshore wind turbine blades and lightweight aerospace structures has placed higher demands on the modulus, strength, and defect control of glass fiber. The research and industrialization of ultra-high modulus glass fiber (modulus ≥ 100 GPa) has become a key area of ​​technological competition within the industry.

[0003] In the preparation of glass fibers, the clarification process is a crucial step in determining the level of internal defects in the final product, especially the bubble content. The clarification process primarily involves lowering the melt viscosity through heating, promoting the escape of bubbles. Temperature control (T2) and holding time directly affect clarification efficiency and finished product quality. Currently, the clarification temperature control methods commonly used in the industry still have the following significant limitations: Temperature control relies on static settings and lacks dynamic response capability: Existing clarification processes mostly operate based on fixed temperature curves and cannot be adjusted in real time according to the actual state of the melt (such as bubble content, viscosity, composition fluctuations, etc.). When there are batch differences in raw materials or changes in the state of the melting furnace, it is easy to cause insufficient or excessive clarification. The former will cause bubble residue, while the latter will increase energy consumption and accelerate furnace wear.

[0004] Delayed bubble detection and untimely process adjustments: Traditional bubble detection typically uses offline sampling and microscopic observation, resulting in severely delayed feedback that cannot be used for real-time control during production. This leads to a lack of immediate data support for adjusting clarification process parameters, making precise intervention difficult.

[0005] Temperature control systems operate in isolation and lack a coordination mechanism: the temperature control systems of the clarifying zone, melting zone, and drawing zone are often set independently, lacking a coordinated adjustment mechanism based on changes in material state, which affects the stability of the entire production system and the uniformity of the finished product.

[0006] The optimization of clarification process parameters relies on experience and has poor repeatability: the setting of clarification temperature and time depends heavily on the experience of process personnel and lacks quantitative model support, making it difficult to achieve rapid process reproduction and optimization between different production lines or different products.

[0007] In conclusion, the existing technology obviously has inconveniences and defects in practical use, so it is necessary to improve it. Summary of the Invention

[0008] To address the aforementioned shortcomings, the present invention aims to provide a low dielectric constant glass fiber, its preparation process, and a clarification temperature control device. This effectively solves problems in existing technologies such as delayed bubble detection, isolated operation of temperature control systems, and reliance on experience for process parameter optimization. Through real-time online bubble detection technology, instant feedback of bubble data is achieved, providing strong support for precise adjustment of clarification process parameters. A multi-zone temperature control coordination mechanism is constructed, enabling dynamic and coordinated adjustment of temperature control between the clarification zone, melting zone, and drawing zone based on changes in material state, improving the stability of the production system and the uniformity of the finished product. Simultaneously, a process parameter optimization system based on a quantitative model is established, reducing reliance on the experience of process personnel and enabling rapid replication and optimization of processes across different production lines or products.

[0009] To achieve the above objectives, the present invention provides a low-dielectric glass fiber comprising 50.0-58.0 wt% SiO2, 18.0-26.0 wt% B2O3, 13.0-18.0 wt% Al2O3, 0.0-5.0 wt% MgO, 2.0-5.0 wt% CaO, 0.0-0.5 wt% R2O, 0.0-1.5 wt% TiO2, and 0.0%-3.0% titanium-zirconium-hafnium ternary mixed oxide.

[0010] A method for preparing low dielectric glass fiber includes: mixing the ingredients according to the formula of claim 1 evenly and putting them into a kiln, melting them at a liquid temperature of T1 and holding them at that temperature for 2-4 hours, then raising the temperature to T2 for clarification and degassing for 1-2 hours, controlling the cooling rate to T3 for drawing and forming, and obtaining the finished product after gradient cooling and surface modification treatment.

[0011] According to the preparation method of the present invention, the melting temperature T1 is 1350℃-1370℃, the clarifying temperature T2 is 1650℃, and the drawing temperature T3 is 1390-1410℃.

[0012] According to the preparation method of the present invention, the melting temperature range ΔT of the melting temperature T1 is 30-45℃.

[0013] A refining temperature system for glass fibers includes: a refining zone temperature control module for setting and adjusting the heating power of the refining zone to control its temperature, denoted as T2; an online bubble monitoring module located at the outlet or downstream of the refining zone for real-time acquisition of bubble content data Bt and bubble particle size distribution data in the glass melt; a feedback control and analysis module connected to the temperature control module and the bubble monitoring module, which incorporates a refining efficiency evaluation model and a dynamic control algorithm; and an execution unit that adjusts the refining zone temperature and refining time in real-time according to the instructions of the feedback control and analysis module.

[0014] According to the clarification temperature system of the present invention, the clarification efficiency evaluation model calculates the current clarification efficiency (η) based on the relationship between the real-time bubble content change rate (dBt / dt) and the clarification temperature (T2). The calculation formula is: η=-(dBt / dt) / k*(T2-T0); where k is a process constant and T0 is a set reference temperature (usually 1510-1520℃); when η is lower than the preset efficiency threshold η_min, the dynamic control algorithm is activated.

[0015] According to the clarification temperature system of the present invention, the dynamic control algorithm executes a graded control strategy: if the current bubble content Bt exceeds the first threshold B_max and η<η_min, then the first-level control is initiated, and the clarification temperature is increased according to the formula ΔT1=α·(Bt-B_max), where α is the temperature increase coefficient; if the bubble reduction rate does not reach the expected level within the set time T1 after the temperature is increased, then the second-level control is initiated, and the clarification time Δt is extended synchronously, and its calculation formula is: Δt=γ*Bt / η, where γ is the time compensation coefficient.

[0016] According to the clarification temperature system of the present invention, the bubble size distribution data is used for the refined selection of control strategies: when the proportion of large bubbles (diameter > 80 μm) exceeds 40%, the first-level control (significantly increasing the temperature) is preferentially adopted; when the proportion of small bubbles (diameter < 30 μm) exceeds 60%, the second-level control (significantly prolonging the clarification time) is preferentially adopted; when the bubble distribution exhibits a bimodal characteristic, a combined strategy of the first-level and second-level control is adopted.

[0017] According to the clarification temperature system of the present invention, the clarification temperature system is characterized by further including a process parameter self-learning unit, which is used to collect historical production data, establish a mapping relationship library of bubble content-clarification temperature-clarification time-finished product modulus, and optimize the initial clarification temperature T20 and the benchmark clarification time (T0) for the next production through regression analysis. The optimization objective function is: min(w1*|Bt-Bt|+w2*(t-ti)+w3*|E-100|); where w1, w2, and w3 are weighting coefficients, Bt is the target bubble content, ti is the ideal clarification time, and E is the finished product fiber modulus.

[0018] This invention provides a low dielectric constant glass fiber, its preparation process, and a clarification temperature control device.

[0019] The low-dielectric glass fiber comprises 50.0-58.0 wt% SiO2, 18.0-26.0 wt% B2O3, 13.0-18.0 wt% Al2O3, 0.0-5.0 wt% MgO, 2.0-5.0 wt% CaO, 0.0-0.5 wt% R2O, 0.0-1.5 wt% TiO2, and 0.0%-3.0% titanium-zirconium-hafnium ternary mixed oxide. The low-dielectric glass fiber disclosed in this invention can significantly reduce signal transmission loss and improve signal transmission efficiency. Its unique composition ratio allows the glass fiber to maintain good mechanical properties while possessing an extremely low dielectric constant, effectively reducing energy loss of electromagnetic waves during transmission. Furthermore, this low-dielectric glass fiber also exhibits good heat resistance and chemical stability, enabling it to adapt to various harsh working environments and extending the product's service life. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the clarification temperature control system of the present invention; Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for explaining the invention and are not intended to limit the invention.

[0022] It should be noted that if the embodiments of the present invention involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0023] Meanwhile, the meaning of "and / or" or "and / or" appearing throughout the text is that it includes three options. Taking "A and / or B" as an example, it includes option A, option B, or an option that satisfies both A and B.

[0024] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0025] See Figure 1 This invention provides a low dielectric constant glass fiber, its preparation process, and a clarification temperature control device.

[0026] The low-dielectric glass fiber comprises 50.0-58.0 wt% SiO2, 18.0-26.0 wt% B2O3, 13.0-18.0 wt% Al2O3, 0.0-5.0 wt% MgO, 2.0-5.0 wt% CaO, 0.0-0.5 wt% R2O, 0.0-1.5 wt% TiO2, and 0.0%-3.0% titanium-zirconium-hafnium ternary mixed oxide.

[0027] The low-dielectric glass fiber disclosed in this invention can significantly reduce signal transmission loss and improve signal transmission efficiency. Its unique composition ratio allows the glass fiber to maintain good mechanical properties while possessing an extremely low dielectric constant, effectively reducing energy loss of electromagnetic waves during transmission. Furthermore, this low-dielectric glass fiber also exhibits good heat resistance and chemical stability, enabling it to adapt to various harsh working environments and extending product lifespan.

[0028] This invention also discloses a method for preparing low-dielectric glass fiber, comprising: uniformly mixing the above-mentioned ingredients and feeding them into a furnace; melting at a liquid temperature T1 and holding at that temperature for 2-4 hours; then raising the temperature to T2 for clarification and degassing for 1-2 hours; controlling the cooling rate to T3 for drawing and shaping; and obtaining the finished product after gradient cooling and surface modification treatment. The melting temperature T1 is 1350℃-1370℃, the clarification temperature T2 is 1650℃, the drawing temperature T3 is 1390-1410℃, and the melting temperature range ΔT of the melting temperature T1 is 30-45℃.

[0029] This process produces low-dielectric glass fibers with not only low dielectric constants but also significantly improved fiber uniformity and strength. By precisely controlling the temperature and time at each stage, the stability of the glass fibers during melting, refining, drawing, and cooling is ensured, resulting in high-performance low-dielectric glass fiber products. This preparation method not only improves production efficiency but also reduces production costs.

[0030] The present invention also discloses a clarification temperature system for glass fibers, comprising: The refining zone temperature control module is used to set and adjust the heating power of the refining zone to control its temperature, denoted as T2; the online bubble monitoring module is located at the outlet or downstream of the refining zone to collect real-time data on bubble content (Bt) and bubble size distribution in the glass melt; the feedback control and analysis module is connected to the temperature control module and the bubble monitoring module, and has a built-in refining efficiency evaluation model and dynamic control algorithm; the execution unit adjusts the refining zone temperature and refining time in real time according to the instructions of the feedback control and analysis module.

[0031] This refining temperature system precisely sets and adjusts the refining zone temperature through a refining zone temperature control module, ensuring that the glass melt undergoes refining treatment at the optimal temperature. An online bubble monitoring module continuously monitors the bubble situation in the glass melt, providing crucial data support for the system. The feedback control and analysis module utilizes a built-in refining efficiency evaluation model and dynamic control algorithm to analyze and process the collected data in real time, generating corresponding control commands. The execution unit then rapidly responds to these commands, dynamically adjusting the refining zone temperature and refining time to achieve efficient refining of the glass melt, thereby further improving the preparation quality and production efficiency of low-dielectric glass fibers.

[0032] In some embodiments of the invention, the clarification efficiency evaluation model calculates the current clarification efficiency (η) based on the relationship between the real-time bubble content change rate (dBt / dt) and the clarification temperature (T2), and the calculation formula is as follows: η = -(dBt / dt) / k*(T2-T0); Where k is a process constant and T0 is a set reference temperature (usually 1510-1520℃); when η is lower than the preset efficiency threshold η_min, the dynamic control algorithm is activated.

[0033] Once the dynamic control algorithm is activated, it generates corresponding temperature and clarification time control commands based on the current rate of change in bubble content and the difference between the clarification temperature and the set reference temperature, combined with a preset control strategy. The temperature control command adjusts the heating power of the clarification zone temperature control module to change the temperature of the clarification zone; the clarification time control command controls the residence time of the glass melt in the clarification zone. Through this dynamic control, the system can respond promptly to changes in clarification efficiency, ensuring that the glass melt is always processed in a highly efficient clarification state, effectively improving the preparation quality of low-dielectric glass fibers.

[0034] In some embodiments of the invention, the dynamic control algorithm executes a hierarchical control strategy: If the current bubble content Bt exceeds the first threshold B_max and η<η_min, then the first-level regulation is activated, and the clarification temperature is increased according to the formula ΔT1=α·(Bt-B_max), where α is the temperature increase coefficient. If the rate of bubble reduction does not reach the expected level within the set time T1 after the temperature is increased, the second-level control is activated, and the clarification time Δt is extended simultaneously. The calculation formula is as follows: Δt=γ*Bt / η, where γ is the time compensation coefficient.

[0035] After the second-level control is initiated, the system continuously monitors changes in the bubble reduction rate and clarification efficiency. If, after the second-level control, the bubble reduction rate reaches the expected level within a subsequent set time T2 and the clarification efficiency η increases to a level not lower than the preset efficiency threshold η_min, the system determines that the current control is effective and continues to operate with the existing temperature and clarification time parameters. If the expected effect is not achieved within the set time T2, the system initiates the third-level control, further increasing the values ​​of the temperature increase coefficient α and the time compensation coefficient γ, and recalculates and adjusts the clarification temperature and clarification time according to the above formula. This continuously optimizes the control parameters to ensure the high efficiency and stability of the glass melt clarification process, maximizing the quality of low-dielectric glass fiber preparation.

[0036] In some embodiments of the invention, the bubble size distribution data is used for refined selection of control strategies: When large air bubbles (diameter > 80 μm) account for more than 40%, the first-level regulation (significantly increasing the temperature) is prioritized. When the proportion of small bubbles (diameter <30μm) exceeds 60%, the second-level regulation (significantly prolonging the clarification time) is preferentially adopted. When the bubble distribution exhibits a bimodal characteristic, a combined strategy of first-level and second-level regulation is adopted.

[0037] During implementation, the system collects bubble size distribution data in real time and quickly determines the control strategy based on the aforementioned rules. If the proportion of large bubbles exceeds the standard, the system will immediately execute the first-level control, significantly increasing the temperature to promote the rapid escape of large bubbles and reduce internal defects in the melt. If the proportion of small bubbles is too high, the system switches to the second-level control, significantly extending the resolving time to provide sufficient time for the complete dissolution of small bubbles and avoid residual bubbles affecting glass quality. When the bubble distribution exhibits a bimodal characteristic, the system intelligently combines the first and second-level control strategies, increasing the temperature to accelerate the escape of large bubbles and extending the resolving time to promote the dissolution of small bubbles, thereby achieving precise control of bubble size distribution and ensuring stable and reliable preparation quality of low-dielectric glass fibers.

[0038] In some embodiments of the invention, a process parameter self-learning unit is also included, used to collect historical production data, establish a mapping relationship library of bubble content, clarification temperature, clarification time, and finished product modulus, and optimize the initial clarification temperature T20 and baseline clarification time (T0) for the next production through regression analysis. The optimization objective function is: min(w1*∣Bt-Bt∣+w2*(t-ti)+w3*∣E-100∣) Where w1, w2, and w3 are weighting coefficients, Bt is the target bubble content, ti is the ideal clarification time, and E is the finished fiber modulus.

[0039] The process parameter self-learning unit continuously updates the mapping database, enabling the system to adapt to changes in different raw material batches and production environments. Specifically, this unit periodically analyzes outliers in historical data, removes interfering factors, and recalculates weight coefficients to ensure that the optimization objective function always reflects the current optimal process conditions. When raw material composition fluctuations exceed a preset threshold, the system automatically triggers a protection mechanism, pausing parameter optimization and maintaining stable parameters from the previous cycle, while simultaneously sending a warning message to the operating terminal. The self-learning function resumes after manual confirmation. Through this dynamic adjustment mechanism, the system achieves closed-loop control of process parameters, significantly improving the stability and product consistency of the low-dielectric glass fiber preparation process.

[0040] Of course, the present invention may have other various embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and modifications according to the present invention, but these corresponding changes and modifications should all fall within the protection scope of the appended claims.

Claims

1. A low-dielectric glass fiber, characterized in that, include, 50.0-58.0 wt% SiO2, 18.0-26.0 wt% B2O3, 13.0-18.0 wt% Al2O3, 0.0-5.0wt% MgO, 2.0-5.0 wt% CaO, 0.0-0.5wt% R20, 0.0-1.5wt% TiO2, And 0.0%-3.0% of titanium-zirconium-hafnium ternary mixed oxides.

2. A method for preparing low-dielectric glass fiber, characterized in that, include: After the ingredients according to claim 1 are mixed evenly, they are put into the kiln, melted at liquid temperature T1 and kept at that temperature for 2-4 hours, then heated to T2 for clarification and degassing for 1-2 hours, and the cooling rate is controlled to T3 for wire drawing and forming. After gradient cooling and surface modification treatment, the finished product is obtained.

3. The preparation method according to claim 2, characterized in that, The melting temperature T1 is 1350℃-1370℃, the clarifying temperature T2 is 1650℃, and the drawing temperature T3 is 1390-1410℃.

4. The preparation method according to claim 2, characterized in that, The melting temperature range ΔT of the melting temperature T1 is 30-45℃.

5. A clarification temperature system for glass fibers, characterized in that, include: The clarification zone temperature control module is used to set and adjust the heating power of the clarification zone to control its temperature, denoted as T2; The bubble online monitoring module is set at the outlet or downstream of the clarification zone to collect real-time data on bubble content (Bt) and bubble particle size distribution in the glass melt. The feedback control and analysis module is connected to the temperature control module and the bubble monitoring module, and has a built-in clarification efficiency evaluation model and dynamic control algorithm. The execution unit adjusts the temperature and clarification time of the clarification zone in real time according to the instructions of the feedback control and analysis module.

6. The clarification temperature system according to claim 5, characterized in that, The clarification efficiency evaluation model calculates the current clarification efficiency (η) based on the relationship between the real-time bubble content change rate dBt / dt and the clarification temperature (T2). The calculation formula is as follows: η = -(dBt / dt) / k*(T2-T0); Where k is a process constant and T0 is a set reference temperature (usually 1510-1520℃); when η is lower than the preset efficiency threshold η_min, the dynamic control algorithm is activated.

7. The clarification temperature system according to claim 5, characterized in that, The dynamic control algorithm executes a hierarchical control strategy: If the current bubble content Bt exceeds the first threshold B_max and η<η_min, then the first-level regulation is activated, and the clarification temperature is increased according to the formula ΔT1=α·(Bt-B_max), where α is the temperature increase coefficient. If the rate of bubble reduction does not reach the expected level within the set time T1 after the temperature is increased, the second-level control is activated, and the clarification time Δt is extended simultaneously. The calculation formula is as follows: Δt=γ*Bt / η, where γ is the time compensation coefficient.

8. The clarification temperature system according to claim 7, characterized in that, The bubble size distribution data is used for refined selection of control strategies: When the proportion of large bubbles with a diameter >80μm exceeds 40%, the first-level control is used first. When the proportion of small bubbles with a diameter of <30μm exceeds 60%, the second-level control is preferentially adopted; When the bubble distribution exhibits a bimodal characteristic, a combined strategy of first-level and second-level regulation is adopted.

9. The clarification temperature system according to claim 5, characterized in that, It also includes a process parameter self-learning unit, used to collect historical production data, establish a mapping relationship library of bubble content, clarification temperature, clarification time, and finished product modulus, and optimize the initial clarification temperature T20 and baseline clarification time (T0) for the next production through regression analysis. The optimization objective function is: min(w1*∣Bt-Bt∣+w2*(t-ti)+w3*∣E-100∣); Where w1, w2, and w3 are weighting coefficients, Bt is the target bubble content, ti is the ideal clarification time, and E is the finished fiber modulus.

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