Method for adjusting capillary wall thickness of hollow core fiber and hollow core fiber

Abstract

The application provides a capillary wall thickness adjustment method of a hollow core optical fiber and the hollow core optical fiber. It relates to the technical field of optical fibers. The method comprises the following steps: measuring the real-time vibration frequency data of multiple points on the capillary in a non-contact manner along the capillary axis by means of a laser interferometer; obtaining the vibration frequency variation of the multiple points on the capillary based on the real-time vibration frequency data of the multiple points on the capillary; generating the wall thickness variation distribution diagram corresponding to the capillary based on the vibration frequency variation of the multiple points on the capillary and a preset target mathematical model in combination with a preset spatial mapping algorithm, wherein the target mathematical model is a relationship model between the frequency variation and the wall thickness variation; and adjusting the wall thickness of the capillary based on the wall thickness variation distribution diagram corresponding to the capillary. The capillary wall thickness adjustment method of the hollow core optical fiber provided in the application can improve the detection efficiency and accuracy of the capillary wall thickness, thereby improving the long-distance production qualification rate of the anti-resonant hollow core optical fiber.

Description

Technical Field

[0001] This application relates to the field of optical fiber technology, and in particular to a method for adjusting the capillary wall thickness of a hollow optical fiber and the hollow optical fiber itself. Background Technology

[0002] In recent years, antiresonant hollow fiber has become a hot topic in international research. Its core advantage lies in confining the light field within an air core for transmission, significantly reducing the inherent material absorption, scattering losses, and nonlinear effects of traditional silica fiber. These characteristics give it broad application prospects in high-speed communication, high-power laser transmission, and precision sensing. The key to promoting the large-scale industrialization of antiresonant hollow fiber lies in the intelligent upgrading of the fiber drawing process. During the drawing process of antiresonant hollow fiber, the capillary wall thickness is one of the key structural parameters determining the transmission loss of the fiber. If the drawn wall thickness deviates from the theoretical design value, it will cause severe leakage loss of light at specific wavelengths during transmission, leading to a sharp increase in the total loss of the antiresonant hollow fiber. High-precision measurement of the capillary wall thickness is a prerequisite for achieving wall thickness control during the drawing process of antiresonant hollow fiber.

[0003] However, current traditional methods for measuring the capillary wall thickness inside antiresonant hollow optical fibers still rely on offline microscopy. This requires manually cutting the fiber during the drawing process and observing the cross-section to obtain the required internal microstructure dimensions. The drawback is that the measurement results lag significantly behind the production process, leading to a low yield rate for long-distance production of antiresonant hollow optical fibers. Summary of the Invention

[0004] This application provides a method for adjusting the capillary wall thickness of hollow optical fiber and a hollow optical fiber, which can improve the efficiency and accuracy of capillary wall thickness detection, thereby improving the yield of long-distance production of anti-resonant hollow optical fiber.

[0005] In a first aspect, this application provides a method for adjusting the capillary wall thickness of a hollow optical fiber, comprising:

[0006] Real-time vibration frequency data of multiple points on the capillary were measured non-contactly along the capillary axis using a laser interferometer.

[0007] Based on real-time vibration frequency data at multiple points on the capillary, the change in vibration frequency at multiple points on the capillary is obtained.

[0008] Based on the vibration frequency change at multiple points on the capillary and the preset target mathematical model, and combined with the preset spatial mapping algorithm, a distribution map of the wall thickness change corresponding to the capillary is generated. The target mathematical model is the relationship model between the frequency change and the wall thickness change.

[0009] The capillary wall thickness is adjusted based on the distribution map of the wall thickness variation corresponding to the capillary.

[0010] In one possible implementation, a distribution map of the capillary wall thickness variation is generated based on the vibration frequency changes at multiple points on the capillary and a preset target mathematical model, combined with a preset spatial mapping algorithm, including:

[0011] The vibration frequency changes at multiple points on the capillary are input into the preset target mathematical model to obtain the wall thickness changes at multiple points on the capillary.

[0012] Based on the spatial mapping algorithm, the wall thickness variation at multiple points on the capillary is mapped to the spatial position of each point on the capillary to obtain a distribution map of the wall thickness variation.

[0013] In one possible implementation, the capillary wall thickness is adjusted based on a distribution map of the wall thickness variation corresponding to the capillary, including:

[0014] Based on the distribution map of wall thickness variation, the regions where the wall thickness increases and the regions where the wall thickness decreases on the capillary are identified.

[0015] For areas with increased wall thickness, the capillary wall thickness in those areas can be reduced by increasing the gas pressure in those areas.

[0016] For regions where the wall thickness decreases, the capillary wall thickness in those regions can be increased by reducing the gas path pressure.

[0017] In one possible implementation, it also includes:

[0018] Obtain the initial vibration frequency, initial outer diameter, initial inner diameter, and initial wall thickness corresponding to the capillary;

[0019] The ratio between the initial vibration frequency of the capillary and the change in vibration frequency is defined as the resolution.

[0020] The target mathematical model is obtained by constructing the correspondence between the resolution and the initial outer diameter, initial inner diameter, initial wall thickness, and wall thickness variation of the capillary.

[0021] In one possible implementation, it also includes:

[0022] Vibration signals of capillaries at multiple resonant frequencies were collected using multi-band vibration analysis technology, and cross-validation was performed based on a multi-band data fusion algorithm.

[0023] In one possible implementation, it also includes:

[0024] The vibration frequency changes at multiple points on the capillary are input into the wall thickness change prediction model to obtain the predicted wall thickness changes at multiple points on the capillary.

[0025] Based on the predicted wall thickness change at multiple points on the capillary and the spatial mapping algorithm, a distribution map of the predicted wall thickness change corresponding to the capillary is generated.

[0026] The gas pressure in the capillary tube is adjusted based on the predicted distribution of wall thickness variation.

[0027] In one possible implementation, before obtaining the change in vibration frequency at multiple points on the capillary based on real-time vibration frequency data at multiple points on the capillary, the method further includes:

[0028] Ambient temperature data is collected using a temperature sensor;

[0029] Ambient air pressure data is collected using a barometric pressure sensor;

[0030] Based on ambient temperature and air pressure data, a preset adaptive calibration algorithm is used to dynamically compensate the real-time vibration frequency data of multiple points on the capillary to obtain the compensated real-time vibration frequency data.

[0031] Secondly, this application provides a capillary wall thickness adjustment device for hollow optical fibers, comprising:

[0032] The detection module is used to non-contactly measure the real-time vibration frequency data of multiple points on the capillary along the capillary axis using a laser interferometer.

[0033] The processing module is used to obtain the change in vibration frequency at multiple points on the capillary based on real-time vibration frequency data at multiple points on the capillary.

[0034] The processing module is also used to generate a distribution map of the wall thickness change of the capillary based on the vibration frequency change of multiple points on the capillary and the preset target mathematical model, and combined with the preset spatial mapping algorithm. The target mathematical model is the relationship model between the frequency change and the wall thickness change.

[0035] The processing module is also used to adjust the capillary wall thickness based on the distribution map of the wall thickness variation corresponding to the capillary.

[0036] In one possible implementation, the processing module is specifically used to input the vibration frequency change at multiple points on the capillary into a preset target mathematical model to obtain the wall thickness change at multiple points on the capillary.

[0037] The processing module is also used to map the wall thickness variation at multiple points on the capillary to the spatial location of each point on the capillary based on a spatial mapping algorithm, so as to obtain a distribution map of the wall thickness variation.

[0038] In one possible implementation, the processing module is further configured to determine, based on the wall thickness variation distribution map, the regions on the capillary where the wall thickness increases and the regions where the wall thickness decreases.

[0039] The processing module is also specifically used to reduce the capillary wall thickness in areas with increased wall thickness by increasing the gas pressure in those areas.

[0040] The processing module is also used to increase the capillary wall thickness in areas where the wall thickness is reduced by decreasing the gas pressure in those areas.

[0041] In one possible implementation, the processing module is further configured to obtain the initial vibration frequency, initial outer diameter, initial inner diameter, and initial wall thickness corresponding to the capillary.

[0042] The processing module is also used to determine the ratio between the initial vibration frequency of the capillary and the change in vibration frequency as the resolution;

[0043] The processing module is also used to obtain the target mathematical model based on the correspondence between the construction resolution and the initial outer diameter, initial inner diameter, initial wall thickness and wall thickness change of the capillary.

[0044] In one possible implementation, the processing module is further configured to acquire the vibration signals of the capillary at multiple resonant frequencies using multi-band vibration analysis technology, and perform cross-validation based on a multi-band data fusion algorithm.

[0045] In one possible implementation, the processing module is further configured to input the vibration frequency change of multiple points on the capillary into the wall thickness change prediction model to obtain the predicted wall thickness change corresponding to multiple points on the capillary.

[0046] The processing module is also used to generate a distribution map of the predicted wall thickness change of the capillary based on the predicted wall thickness change of multiple points on the capillary and the spatial mapping algorithm.

[0047] The processing module is also used to adjust the gas path pressure of the capillary based on the predicted distribution map of wall thickness variation.

[0048] In one possible implementation, the processing module is also used to collect ambient temperature data via a temperature sensor;

[0049] The processing module is also used to collect ambient air pressure data through a barometric pressure sensor;

[0050] The processing module is also used to dynamically compensate the real-time vibration frequency data of multiple points on the capillary based on ambient temperature data and ambient air pressure data, using a preset adaptive calibration algorithm, so as to obtain the compensated real-time vibration frequency data.

[0051] Thirdly, this application provides a capillary wall thickness adjustment device for hollow optical fibers, including: a drawing unit, a capillary wall thickness measurement and control unit, a coating unit, and a fiber take-up unit. The drawing unit includes: an optical fiber preform, a high-temperature heating furnace, and a cooler. The capillary wall thickness measurement and control unit includes: a frequency detection component, a voltage control component, and a control component. The coating unit includes a coating component. The fiber take-up unit includes: a power wheel and a fiber take-up shaft.

[0052] The drawing unit is used to fuse and cool the pre-formed optical fiber to obtain the corresponding anti-resonant hollow fiber.

[0053] The coating unit is used to coat one or more layers of polymer material onto the surface of anti-resonant hollow optical fiber;

[0054] The fiber collection unit is used to provide traction force for the anti-resonant hollow fiber to control the drawing speed of the anti-resonant hollow fiber and to collect the anti-resonant hollow fiber.

[0055] The capillary wall thickness measurement and control unit is used to perform the steps of the capillary wall thickness adjustment method for hollow optical fibers as described in the first aspect and / or any possible implementation of the first aspect.

[0056] Fourthly, this application provides an anti-resonant hollow optical fiber, including a support tube and a capillary tube, wherein the inner diameter of the support tube is larger than the outer diameter of the capillary tube, the capillary tube is fixed on the inner wall of the support tube, and the thickness of the capillary tube is monitored and adjusted using the capillary wall thickness adjustment method of hollow optical fiber as described in the first aspect and / or any possible implementation of the first aspect.

[0057] Fifthly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0058] The memory stores the instructions that the computer executes;

[0059] The processor executes computer execution instructions stored in memory to implement the capillary wall thickness adjustment method for hollow optical fibers as described in the first aspect and / or any possible implementation of the first aspect.

[0060] In a sixth aspect, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement a capillary wall thickness adjustment method for hollow optical fibers as described in the first aspect and / or any possible implementation of the first aspect.

[0061] In a seventh aspect, this application provides a computer program product, including a computer program that, when executed by a processor, implements a capillary wall thickness adjustment method for hollow optical fibers as described in the first aspect and / or any possible implementation of the first aspect.

[0062] This application provides a method for adjusting the capillary wall thickness of hollow optical fiber and the hollow optical fiber itself. By measuring real-time vibration frequency data at multiple points on the capillary, the change in vibration frequency at these points is obtained. A spatial mapping algorithm based on a mathematical model relating capillary wall thickness change and vibration frequency change is used to obtain a distribution map of the capillary wall thickness change. This distribution map allows for direct online real-time derivation of the wall thickness change, enabling online real-time adjustment of the capillary wall thickness. This reduces the reliance on fiber cutting in traditional methods, significantly shortens the detection and feedback cycle, and thus solves the lag problem of traditional offline detection, improving detection efficiency and accuracy, thereby increasing the long-distance production pass rate of anti-resonant hollow optical fiber. Attached Figure Description

[0063] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0064] Figure 1 A schematic diagram of the structure of an anti-resonant hollow fiber, as an example;

[0065] Figure 2 A schematic diagram of a cross-section of a capillary tube for example;

[0066] Figure 3 A flowchart illustrating the capillary wall thickness adjustment method for hollow optical fibers provided in this application. Figure 1 ;

[0067] Figure 4 A flowchart illustrating the capillary wall thickness adjustment method for hollow optical fibers provided in this application. Figure 2 ;

[0068] Figure 5 A flowchart illustrating the capillary wall thickness adjustment method for hollow optical fibers provided in this application. Figure 3 ;

[0069] Figure 6 A flowchart illustrating the capillary wall thickness adjustment method for hollow optical fibers provided in this application. Figure 4 ;

[0070] Figure 7 A schematic diagram of the structure of a single string as an example;

[0071] Figure 8 A flowchart illustrating the capillary wall thickness adjustment method for hollow optical fibers provided in this application. Figure 5 ;

[0072] Figure 9 A flowchart illustrating the capillary wall thickness adjustment method for hollow optical fibers provided in this application. Figure 6;

[0073] Figure 10 This is a schematic diagram illustrating the change in resolution with varying capillary wall thickness when the capillary wall thickness is 1.10 μm, serving as an example.

[0074] Figure 11 This is a schematic diagram illustrating the change in resolution with varying capillary wall thickness when the capillary wall thickness is 1.15 μm, serving as an example.

[0075] Figure 12 This is a schematic diagram illustrating the change in resolution with varying capillary wall thickness when the capillary wall thickness is 1.20 μm, serving as an example.

[0076] Figure 13 A schematic diagram of the capillary wall thickness adjustment device for hollow optical fiber provided in the embodiments of this application;

[0077] Figure 14 A schematic diagram of the capillary wall thickness adjustment device for hollow optical fiber provided in this application;

[0078] Figure 15 A schematic diagram of the structure of the electronic device provided in this application.

[0079] Figure label:

[0080] 1: Pressure control components and control components; 2: Optical fiber preform; 3: High-temperature heating furnace; 4: Cooler; 5: Frequency detection components; 6: Coating components; 7: Power wheel; 8: Fiber take-up shaft; 9: Programmable logic controller; 10: Computer.

[0081] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0082] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0083] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0084] In recent years, antiresonant hollow fiber has become a hot topic in international research. Its core advantage lies in confining the light field within an air core for transmission, significantly reducing the inherent material absorption, scattering losses, and nonlinear effects of traditional silica fiber. These characteristics give it broad application prospects in high-speed communication, high-power laser transmission, and precision sensing. The key to promoting the large-scale industrialization of antiresonant hollow fiber lies in the intelligent upgrading of the fiber drawing process. During the drawing process of antiresonant hollow fiber, the capillary wall thickness is one of the key structural parameters determining the transmission loss of the fiber. If the drawn wall thickness deviates from the theoretical design value, it will cause severe leakage loss of light at specific wavelengths during transmission, leading to a sharp increase in the total loss of the antiresonant hollow fiber. High-precision measurement of the capillary wall thickness is a prerequisite for achieving wall thickness control during the drawing process of antiresonant hollow fiber.

[0085] However, current traditional methods for measuring the capillary wall thickness inside antiresonant hollow optical fibers still rely on offline microscopy. This requires manually cutting the fiber during the drawing process and observing the cross-section to obtain the required internal microstructure dimensions. The drawback is that the measurement results lag significantly behind the production process, leading to a low yield rate for long-distance production of antiresonant hollow optical fibers.

[0086] Figure 1 A schematic diagram of the structure of an anti-resonant hollow fiber is shown below. Figure 1 As shown, antiresonant hollow-core fiber is a combination of a support tube and a capillary tube. Antiresonant hollow-core fiber is a novel photonic device. Its core structure significantly reduces the material absorption, scattering loss, and nonlinear effects of traditional silica fiber by confining the light field within an air core, making it valuable for applications in high-speed optical communication, high-power laser transmission, and precision sensing (such as distributed temperature / strain sensing). During the manufacturing process of antiresonant hollow-core fiber, the capillary wall thickness is one of the key structural parameters determining its transmission performance. If the capillary wall thickness deviates from the design value, leakage loss at specific wavelengths will occur, significantly increasing the total loss of the fiber and even leading to product failure. Performance requirements can be met by drawing the preform into a long fiber under high temperature conditions and precisely controlling the capillary wall thickness. Figure 2 A schematic diagram of a cross-section of a capillary tube is shown below. Figure 2 As shown, the outer diameter of the capillary can be defined as D, the inner diameter as d, and the thickness as t. The thickness of the capillary is half the difference between the outer and inner diameters. Currently, in related technologies, the detection of capillary wall thickness mainly relies on offline microscopy, which requires cutting the optical fiber during the drawing process to obtain cross-sectional images. This results in delayed detection results and low detection efficiency, leading to a low yield rate in long-distance production of anti-resonant hollow optical fibers.

[0087] This application provides a method for adjusting the capillary wall thickness of hollow optical fiber and the hollow optical fiber itself. First, a laser interferometer is used to non-contactly measure real-time vibration frequency data at multiple points along the capillary axis, obtaining the frequency variation at these points. Then, a pre-set target mathematical model and a pre-set spatial mapping algorithm are used to obtain a distribution map of the capillary wall thickness variation. Finally, the capillary wall thickness is adjusted based on this distribution map. This application uses a mathematical model relating capillary wall thickness variation to vibration frequency variation, directly deriving the wall thickness variation online in real time. This reduces the reliance on fiber cutting in traditional methods, significantly shortens the detection and feedback cycle, and thus solves the lag problem of traditional offline detection, improving detection efficiency and consequently increasing the long-distance production yield of anti-resonant hollow optical fiber.

[0088] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0089] Figure 3 A flowchart illustrating the capillary wall thickness adjustment method for hollow optical fibers provided in this application. Figure 1 ,like Figure 3 As shown, the operation flow of the capillary wall thickness adjustment method for hollow optical fibers is as follows:

[0090] S301. Using a laser interferometer, measure the real-time vibration frequency data of multiple points on the capillary in a non-contact manner along the capillary axis.

[0091] Combined with scenario examples, Figure 1A capillary tube refers to a hollow glass tube used to form the hollow structure during the manufacturing process of anti-resonant hollow optical fiber. Its wall thickness is a key structural parameter determining the transmission performance of the optical fiber. The vibration frequency of the capillary tube can be detected in real time using a preset frequency detection device to obtain the change in vibration frequency. A laser interferometer is a non-contact device that measures vibration frequency using the principle of laser interference. For example, it calculates the vibration frequency by irradiating the capillary tube with a laser beam and receiving the reflected signal. Non-contact measurement refers to a measurement method that does not require physical contact with the object being measured. For example, a laser interferometer acquires data through optical signals, avoiding physical disturbance to the capillary tube. The laser interferometer irradiates the surface of the capillary tube with a laser beam, receives the reflected signal, and analyzes the vibration frequency. It does not require cutting the capillary tube or contacting its surface, ensuring the continuity and non-destructive nature of the measurement process. For example, by randomly determining multiple target points on the capillary tube, during the fiber drawing process, the laser interferometer monitors the real-time vibration state of multiple target points along the capillary tube axis in real time, obtaining real-time vibration frequency data for multiple points on the capillary tube. Non-contact measurement eliminates the destructive handling of optical fibers inherent in traditional microscopy techniques, avoiding material waste and production interruptions. Simultaneously, the high-precision measurement capabilities of the laser interferometer improve the accuracy of frequency detection, providing a reliable data foundation for subsequent calculations of wall thickness variations.

[0092] S302. Based on the real-time vibration frequency data of multiple points on the capillary, obtain the change in vibration frequency of multiple points on the capillary.

[0093] Based on the scenario example and the real-time vibration frequency data of multiple points obtained above, for each target point, the vibration frequency of the target point at the current moment is compared with the vibration frequency at the previous moment to obtain the vibration frequency change corresponding to the target point. In this way, the vibration frequency change corresponding to each target point is obtained, which is to say, the vibration frequency change of multiple points on the capillary is obtained.

[0094] S303. Based on the vibration frequency change at multiple points on the capillary and the preset target mathematical model, and combined with the preset spatial mapping algorithm, generate the distribution map of the wall thickness change corresponding to the capillary. The target mathematical model is the relationship model between the frequency change and the wall thickness change.

[0095] In the context of the scenario, the target mathematical model refers to the mapping relationship between frequency change and wall thickness change established based on string vibration theory. This mapping relationship can be used to derive the wall thickness change. Here, the anti-resonant hollow fiber can be considered as the string. The spatial mapping algorithm is an algorithm that associates the frequency data at each point with the wall thickness change at the corresponding location. The wall thickness change distribution map reflects the wall thickness change at each point on the capillary.

[0096] Optional, Figure 4 A flowchart illustrating the capillary wall thickness adjustment method for hollow optical fibers provided in this application. Figure 2 ,like Figure 4 As shown in S303, based on the vibration frequency changes at multiple points on the capillary and a preset target mathematical model, and combined with a preset spatial mapping algorithm, a distribution map of the capillary wall thickness change is generated, including:

[0097] S401. Input the vibration frequency change at multiple points on the capillary into the preset target mathematical model to obtain the wall thickness change at multiple points on the capillary.

[0098] Based on the scenario example, and the mapping relationship between frequency change and wall thickness change in the target mathematical model, the vibration frequency change at each point on the capillary is mapped to obtain the wall thickness change corresponding to the vibration frequency change at each point on the capillary, thereby obtaining the wall thickness change at each point on the capillary.

[0099] S402. Based on the spatial mapping algorithm, the wall thickness variation at multiple points on the capillary is mapped to the spatial position of each point on the capillary to obtain a distribution map of the wall thickness variation.

[0100] Based on a scenario example, the spatial coordinates of each point on the capillary can be determined by creating a direct spatial coordinate system, thus obtaining the corresponding spatial geometric model of the capillary. Using a spatial mapping algorithm, the wall thickness variation at each point is mapped to the corresponding position on the spatial geometric model of the capillary, resulting in a distribution map of the wall thickness variation.

[0101] S304. Adjust the capillary wall thickness based on the distribution map of the wall thickness variation corresponding to the capillary.

[0102] In the capillary drawing process, the thickness variation at different locations on the capillary may differ. Therefore, a wall thickness variation distribution diagram can reflect the thickness variation at various locations on the capillary. The capillary wall thickness variation can be divided into three cases: capillary wall thickness increase, capillary wall thickness decrease, and capillary wall thickness remaining constant. When the capillary wall thickness increases, the corresponding increase in capillary wall thickness is reduced. For example, if the capillary wall thickness increases by 0.01 μm, the capillary wall thickness is controlled to decrease by 0.01 μm. Similarly, when the capillary wall thickness decreases, the corresponding increase in capillary wall thickness is increased. For example, if the capillary wall thickness decreases by 0.01 μm, the capillary wall thickness is controlled to increase by 0.01 μm. When the capillary wall thickness remains constant, no adjustment is needed.

[0103] Based on the capillary wall thickness adjustment method for hollow optical fibers provided in this example, the change in vibration frequency at multiple points on the capillary can be obtained by measuring real-time vibration frequency data at multiple points on the capillary. Then, using a pre-defined spatial mapping algorithm based on the mathematical model between the change in capillary wall thickness and the change in vibration frequency, a distribution map of the capillary wall thickness change is obtained. This distribution map allows for direct online real-time derivation of the wall thickness change, thus enabling online real-time adjustment of the capillary wall thickness. This reduces the reliance on fiber cutting in traditional methods, significantly shortens the detection and feedback cycle, and solves the lag problem of traditional offline detection, improving detection efficiency and accuracy, thereby increasing the long-distance production pass rate of anti-resonant hollow optical fibers.

[0104] Optional, Figure 5 A flowchart illustrating the capillary wall thickness adjustment method for hollow optical fibers provided in this application. Figure 3 ,like Figure 5 As shown, S304 includes:

[0105] S501. Based on the wall thickness variation distribution map, determine the regions where the wall thickness increases and the regions where the wall thickness decreases on the capillary.

[0106] Based on a scenario example, the capillary can be divided into multiple segments according to a preset length. For each segment, the average value of the wall thickness change at each point on that segment is determined. If the average value of the wall thickness change for that segment is greater than a first preset value, then that segment is determined to be a region where the wall thickness increases; conversely, if the average value of the wall thickness change for that segment is less than a second preset value, then that segment is determined to be a region where the wall thickness decreases. The first preset value is greater than or equal to zero, and the second preset value is less than or equal to zero. The specific values ​​of the first and second preset values ​​can be determined according to the actual situation.

[0107] S502. For areas with increased wall thickness, the capillary wall thickness in those areas can be reduced by increasing the gas pressure in those areas.

[0108] In the capillary drawing process, the air pressure in the capillary is inversely proportional to the capillary wall thickness. Therefore, for areas where the wall thickness increases, the air pressure in the capillary can be increased to reduce the capillary wall thickness in that area. The required increase in air pressure can be determined by setting an inverse ratio between the air pressure and the capillary wall thickness, and by calculating the actual amount of wall thickness reduction needed.

[0109] S503. For regions where the wall thickness is reduced, the capillary wall thickness in that region is increased by reducing the gas pressure in that region.

[0110] Based on the scenario example, for areas where the wall thickness decreases, the capillary gas pressure can be reduced to increase the capillary wall thickness in that area. Similarly, by setting an inverse ratio between the capillary gas pressure and the capillary wall thickness, the actual amount of increase in capillary wall thickness can be determined to identify the required reduction in gas pressure.

[0111] Based on the method provided in this example, the air pressure of each section is adjusted in a targeted manner to adjust the capillary wall thickness of each section, thereby improving the precision of capillary thickness adjustment, which in turn improves the accuracy of capillary thickness adjustment and enhances the overall uniformity of capillary thickness.

[0112] Optional, Figure 6 A flowchart illustrating the capillary wall thickness adjustment method for hollow optical fibers provided in this application. Figure 4 ,like Figure 6 As shown, it also includes:

[0113] S601. Obtain the initial vibration frequency, initial outer diameter, initial inner diameter, and initial wall thickness corresponding to the capillary.

[0114] In a scenario example, before drawing the capillary into a wire, the frequency of the capillary is measured using the aforementioned frequency detection device or laser interferometer to obtain its initial vibration frequency. The initial outer diameter, initial inner diameter, and initial wall thickness of the capillary are its initial parameters, which can be obtained through measurement. The initial vibration frequency of the capillary can be defined as f0, the initial outer diameter as D0, the initial inner diameter as d0, and the initial wall thickness as t0.

[0115] S602. The ratio between the initial vibration frequency of the capillary and the change in vibration frequency is determined as the resolution.

[0116] This invention relates to a technique for measuring capillary wall thickness by measuring the frequency of string vibration. The string is a single capillary or a combination of a capillary and a support tube, i.e., an anti-resonant hollow optical fiber.

[0117] Figure 7 A schematic diagram of the structure of a single string as an example, such as Figure 7 As shown, the string is confined between two points L apart. For a string with internal tension F, volume density ρ, and cross-sectional area s, the frequency of vibration of the string is:

[0118]

[0119] Changes in capillary wall thickness cause changes in capillary cross-sectional area, thus altering the capillary vibration frequency. This frequency change can be defined as Δf, and the ratio of Δf to the initial vibration frequency f0 can be defined as the resolution. Furthermore, the initial capillary cross-sectional area can be defined as S0. Since changes in capillary wall thickness cause changes in the capillary cross-sectional area, the real-time cross-sectional area can be defined as S. Therefore, the corresponding resolution formula is:

[0120]

[0121] S603. Based on the correspondence between the construction resolution and the initial outer diameter, initial inner diameter, initial wall thickness and wall thickness change of the capillary, the target mathematical model is obtained.

[0122] Based on the scenario example and the initial outer diameter, initial inner diameter, and initial wall thickness of the capillary obtained above, the target mathematical model is constructed as follows:

[0123]

[0124] Where Δt is the change in capillary wall thickness, and f0 is the initial vibration frequency. Since the initial outer diameter D0, initial inner diameter d0, initial wall thickness t0, and initial vibration frequency f0 are constants, this objective mathematical model can be used to represent the correspondence between the change in vibration frequency and the change in capillary wall thickness.

[0125] Based on the method provided in this example, the change in capillary wall thickness can be directly derived online in real time using the frequency change through a target mathematical model between the change in capillary wall thickness and the change in vibration frequency, thereby improving the efficiency and accuracy of determining the change in capillary wall thickness.

[0126] Optional, also includes:

[0127] Vibration signals of capillaries at multiple resonant frequencies were collected using multi-band vibration analysis technology, and cross-validation was performed based on a multi-band data fusion algorithm.

[0128] In this example, multi-band vibration analysis technology refers to the technique of simultaneously monitoring the vibration signals of a capillary at multiple resonant frequencies. For example, simultaneously acquiring the fundamental frequency and higher harmonic frequencies. Data fusion algorithms are algorithms that comprehensively analyze multi-band data. For example, eliminating errors in a single frequency band through weighted averaging or outlier removal algorithms. By simultaneously acquiring vibration signals at multiple resonant frequencies and cross-validating the results using data fusion algorithms, for example, when a frequency band is abnormal due to environmental noise, normal data from other frequency bands can be used as a reference for that frequency band, ensuring the reliability of the wall thickness change calculation. This example eliminates potential errors in single-frequency measurements through cross-validation of multi-band data. For example, abnormal frequency band data caused by environmental noise or local structural deformation can be corrected using data from other frequency bands, significantly improving the accuracy of frequency detection.

[0129] Optional, Figure 8 A flowchart illustrating the capillary wall thickness adjustment method for hollow optical fibers provided in this application. Figure 5 ,like Figure 8 As shown, it also includes:

[0130] S801. Input the vibration frequency changes at multiple points on the capillary into the wall thickness change prediction model to obtain the predicted wall thickness changes at multiple points on the capillary.

[0131] Using a scenario example, a wall thickness change prediction model is constructed based on machine learning algorithms and historical frequency data, air pressure parameters, and wall thickness change records during the filament drawing process. This model can predict future wall thickness change trends. Therefore, by inputting the vibration frequency changes at multiple points on the capillary into the wall thickness change prediction model, the model can output real-time trends of future wall thickness changes at these multiple points on the capillary.

[0132] S802. Based on the predicted wall thickness change at multiple points on the capillary and the spatial mapping algorithm, generate a distribution map of the predicted wall thickness change corresponding to the capillary.

[0133] Similarly, by creating a direct spatial coordinate system, the spatial coordinates of each point on the capillary can be determined, thus obtaining the corresponding spatial geometric model of the capillary. Using a spatial mapping algorithm, the future wall thickness variation trend of each point is mapped to the corresponding position in the spatial geometric model of the capillary, resulting in a predicted wall thickness variation distribution map.

[0134] S803. Adjust the gas path pressure of the capillary tube based on the predicted wall thickness variation distribution map.

[0135] By using a scenario example, a predictive model can identify potential capillary wall thickness change trends in advance, allowing for proactive adjustment of the capillary gas path pressure before the actual change occurs. For instance, if the model predicts an increase in capillary wall thickness, the gas path pressure can be increased in advance to suppress the increase; conversely, if the model predicts a decrease in capillary wall thickness, the gas path pressure can be decreased in advance to suppress the decrease. Based on the method provided in this example, by predicting capillary wall thickness change trends in advance and proactively adjusting the gas path pressure before the actual wall thickness change occurs, the control response time is significantly shortened.

[0136] Optional, Figure 9 A flowchart illustrating the capillary wall thickness adjustment method for hollow optical fibers provided in this application. Figure 6 ,like Figure 9 As shown, before S302, it also includes:

[0137] S901: Collects ambient temperature data through a temperature sensor.

[0138] Based on the scenario example, the temperature sensor can be a thermocouple or an infrared thermometer, and the ambient temperature data is the temperature of the environment where the capillary is located.

[0139] S902, Collects ambient air pressure data through an air pressure sensor.

[0140] Based on the scenario example, the pressure sensor can be a piezoresistive sensor used to detect the air pressure in the environment where the capillary is located.

[0141] S903. Based on ambient temperature and ambient air pressure data, a preset adaptive calibration algorithm is used to dynamically compensate the real-time vibration frequency data of multiple points on the capillary to obtain the compensated real-time vibration frequency data.

[0142] In a scenario example, fluctuations in temperature or air pressure affect the elastic modulus of a capillary, thus influencing its vibration frequency. An adaptive calibration algorithm determines frequency compensation values ​​for multiple points on the capillary based on the ambient temperature and air pressure. After obtaining real-time vibration frequency data for these points using a laser interferometer, the corresponding frequency compensation value is superimposed on the real-time vibration frequency data for each target point, thus obtaining the target vibration frequency data for each point. Subsequently, the change in vibration frequency for each target point can be determined using this target vibration frequency data. Based on the method provided in this example, by dynamically compensating for the real-time vibration frequency data of multiple points on the capillary, environmental interference with the capillary frequency can be eliminated, thereby improving the accuracy of the detected vibration frequency.

[0143] For example, the inner diameter of the support tube for anti-resonant hollow fiber can be 50μm to 120μm, the outer diameter of the support tube can be 150μm to 300μm, and the outer diameter of the capillary tube can be 10μm to 40μm.

[0144] Figure 10 , Figure 11 , Figure 12 The diagrams illustrate the relationship between resolution and capillary wall thickness when the support tube thickness is 0-80 μm and the capillary wall thickness is 1.10 μm, 1.15 μm, and 1.20 μm, respectively.

[0145] In a scenario with an inner diameter of 75 μm, an outer diameter of 220 μm, an outer diameter of 17 μm, and an initial capillary wall thickness of 1.10 μm, a schematic diagram illustrating the changes in resolution and capillary wall thickness can be found here. Figure 10 The figure illustrates that the frequency monitoring device can dynamically monitor capillary wall thickness changes of 10 nm (i.e., 0.01 μm). Table 1 shows five measurements of the capillary wall thickness when the initial capillary wall thickness is 1.10 μm, as well as the capillary wall thickness adjustment operation for the hollow fiber.

[0146] Table 1

[0147]

[0148] As shown in Table 1, the online wall thickness variation values ​​were completely consistent with the wall thickness variation measured by scanning electron microscopy (SEM). When the online wall thickness variation exceeded 1.10 μm, it was determined that the online wall thickness variation was positive, and the capillary wall thickness needed to be reduced. When the online wall thickness variation was below 1.10 μm, it was determined that the online wall thickness variation was negative, and the capillary wall thickness needed to be increased to ensure that the capillary wall thickness was always maintained at 1.10 μm, thus ensuring the uniformity of the capillary wall thickness and achieving long-distance, stable production of anti-resonant hollow fiber.

[0149] Additionally, for scenarios with a support tube inner diameter of 75 μm, a support tube outer diameter of 220 μm, a capillary outer diameter of 17 μm, and an initial capillary wall thickness of 1.15 μm, a schematic diagram illustrating the changes in resolution and capillary wall thickness can be found here. Figure 11 The figure illustrates that the frequency monitoring device can dynamically monitor capillary wall thickness changes of 10 nm (i.e., 0.01 μm). Table 2 shows five measurements of the capillary wall thickness when the initial capillary wall thickness is 1.15 μm, as well as the capillary wall thickness adjustment operation for the hollow fiber.

[0150] Table 2

[0151]

[0152] Similarly, as shown in Table 2, the online detection wall thickness change values ​​are completely consistent with the scanning electron microscope (SEM) measured wall thickness change. When the online detection wall thickness value exceeds 1.15 μm, the online detection wall thickness change is positive, and the capillary wall thickness needs to be reduced. When the online detection wall thickness value is below 1.15 μm, the online detection wall thickness change is negative, and the capillary wall thickness needs to be increased to ensure that the capillary wall thickness is always maintained at 1.15 μm, thus ensuring the uniformity of the capillary wall thickness and achieving long-distance, stable production of anti-resonant hollow fiber.

[0153] Additionally, for a scenario with a support tube inner diameter of 75 μm, a support tube outer diameter of 220 μm, a capillary outer diameter of 17 μm, and an initial capillary wall thickness of 1.20 μm, a schematic diagram illustrating the changes in resolution and capillary wall thickness can be found here. Figure 12 The figure illustrates that the frequency monitoring device can dynamically monitor capillary wall thickness changes of 10 nm (i.e., 0.01 μm). Table 3 shows five measured values ​​of the capillary wall thickness when the initial capillary wall thickness is 1.20 μm, as well as the capillary wall thickness adjustment operation for the hollow fiber.

[0154] Similarly, as shown in Table 3, the online detection wall thickness change values ​​were completely consistent with the scanning electron microscope (SEM) measurements. When the online detection wall thickness value exceeded 1.20 μm, the online detection wall thickness change was positive, and the capillary wall thickness needed to be reduced. When the online detection wall thickness value was below 1.20 μm, the online detection wall thickness change was negative, and the capillary wall thickness needed to be increased to ensure that the capillary wall thickness remained at 1.20 μm, thus ensuring the uniformity of the capillary wall thickness and achieving long-distance, stable production of anti-resonant hollow fiber.

[0155] Table 3

[0156]

[0157] Figure 13 This is a schematic diagram of the capillary wall thickness adjustment device for hollow optical fiber provided in the embodiments of this application, as shown below. Figure 13 As shown, it includes:

[0158] Detection module 131 is used to non-contactly measure the real-time vibration frequency data of multiple points on the capillary along the capillary axis using a laser interferometer.

[0159] Processing module 132 is used to obtain the change in vibration frequency at multiple points on the capillary based on real-time vibration frequency data at multiple points on the capillary.

[0160] The processing module 132 is also used to generate a distribution map of the wall thickness change of the capillary based on the vibration frequency change of multiple points on the capillary and the preset target mathematical model, and in combination with the preset spatial mapping algorithm. The target mathematical model is the relationship model between the frequency change and the wall thickness change.

[0161] The processing module 132 is also used to adjust the wall thickness of the capillary based on the distribution map of the wall thickness variation corresponding to the capillary.

[0162] Optionally, the processing module 132 is specifically used to input the vibration frequency change of multiple points on the capillary into the preset target mathematical model to obtain the wall thickness change of multiple points on the capillary.

[0163] The processing module is also used to map the wall thickness variation at multiple points on the capillary to the spatial location of each point on the capillary based on a spatial mapping algorithm, so as to obtain a distribution map of the wall thickness variation.

[0164] Optionally, the processing module 132 is further used to determine the regions where the wall thickness increases and the regions where the wall thickness decreases on the capillary based on the distribution map of wall thickness variation.

[0165] The processing module 132 is also specifically used to reduce the capillary wall thickness in areas with increased wall thickness by increasing the gas pressure in those areas.

[0166] The processing module 132 is also used to increase the capillary wall thickness in areas where the wall thickness is reduced by decreasing the gas pressure in those areas.

[0167] Optionally, the processing module 132 is also used to obtain the initial vibration frequency, initial outer diameter, initial inner diameter and initial wall thickness corresponding to the capillary.

[0168] The processing module 132 is also used to determine the ratio between the initial vibration frequency of the capillary and the change in vibration frequency as the resolution;

[0169] The processing module 132 is also used to obtain the target mathematical model based on the correspondence between the construction resolution and the initial outer diameter, initial inner diameter, initial wall thickness and wall thickness change of the capillary.

[0170] Optionally, the processing module 132 is also used to collect the vibration signals of the capillary at multiple resonant frequencies through multi-band vibration analysis technology, and to perform cross-validation based on the multi-band data fusion algorithm.

[0171] Optionally, the processing module 132 is also used to input the vibration frequency change of multiple points on the capillary into the wall thickness change prediction model to obtain the predicted wall thickness change corresponding to multiple points on the capillary.

[0172] The processing module 132 is also used to generate a distribution map of the predicted wall thickness change of the capillary based on the predicted wall thickness change of multiple points on the capillary and the spatial mapping algorithm.

[0173] The processing module 132 is also used to adjust the gas path pressure of the capillary based on the predicted distribution map of wall thickness variation.

[0174] Optionally, the processing module 132 is also used to collect ambient temperature data via a temperature sensor;

[0175] The processing module 132 is also used to collect ambient air pressure data through an air pressure sensor;

[0176] The processing module 132 is also used to dynamically compensate the real-time vibration frequency data of multiple points on the capillary based on ambient temperature data and ambient air pressure data, using a preset adaptive calibration algorithm, so as to obtain the compensated real-time vibration frequency data.

[0177] The capillary wall thickness adjustment device for hollow optical fiber provided in this embodiment can perform the capillary wall thickness adjustment method for hollow optical fiber provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0178] Figure 14 A schematic diagram of the capillary wall thickness adjustment device for hollow optical fibers provided in this application is shown below. Figure 14 As shown, the system includes: a drawing unit, a capillary wall thickness measurement and control unit, a coating unit, and a fiber collection unit. The drawing unit includes: 2-fiber preform, 3-high-temperature heating furnace, and 4-cooler. The capillary wall thickness measurement and control unit includes: 5-frequency detection component, 1-pressure control component, and control component. The coating unit includes: 6-coating component. The fiber collection unit includes: 7-power wheel and 8-fiber collection shaft. The drawing unit is used to fuse and cool a pre-set fiber preform to obtain the corresponding capillary. The coating unit is used to coat the capillary surface with one or more layers of polymer material. The fiber collection unit is used to provide traction force to the capillary to control the drawing speed and collect the capillary. The capillary wall thickness measurement and control unit is used to execute the steps of the capillary wall thickness adjustment method for hollow optical fibers provided in the above-described method embodiment.

[0179] In a scenario example, the control components include a programmable logic controller (PLC) (9) and a computer (10). The fiber optic preform, made of high-purity quartz glass, serves as the matrix material for the optical fiber. It is melted and drawn at high temperatures into a hair-thin fiber. A high-temperature furnace provides an environment of approximately 2000°C to heat the lower end of the fiber preform to a molten state, allowing it to be drawn into an optical fiber under gravity and tension. A cooler rapidly cools the freshly drawn, high-temperature fiber, solidifying it and stabilizing its optical properties to prevent deformation due to excessive temperature. A coating component coats the cooled bare fiber with one or more layers of polymer material (such as acrylate) to protect the fiber, increase its mechanical strength, and prevent microbending loss. A frequency detection component detects changes in the capillary wall thickness in real time and sends these changes to the PLC. The computer then controls a pressure control component to adjust the gas pressure in the capillary, thereby adjusting the capillary wall thickness. The drive wheel provides stable traction, controls the fiber drawing speed, and works in conjunction with the frequency detection device to ensure the uniformity of fiber diameter. The take-up spool neatly winds the coated fiber onto the take-up reel for easy transport and use.

[0180] Table 4 shows the data on single-stretch length and fiber attenuation when the capillary wall thickness measurement and control unit is turned on and off, under the example scenario with an initial capillary wall thickness of 1.10 μm. As shown in Table 4, the single-stretch length increased from 3 km to 10 km, while the attenuation decreased from 0.20 dB / m to 0.07 dB / m. The online monitoring unit improved the yield and effective length of hollow fiber.

[0181] Table 4

[0182]

[0183] Table 5 shows the data on single-stretch length and fiber attenuation when the capillary wall thickness measurement and control unit is turned on and off, under the example scenario of an initial capillary wall thickness of 1.15 μm. As shown in Table 5, the single-stretch length increased from 5 km to 14 km, while the attenuation decreased from 0.60 dB / m to 0.06 dB / m. The online monitoring unit improved the yield and effective length of hollow fiber.

[0184] Table 5

[0185]

[0186] Table 6 shows the data on single-stretch length and fiber attenuation when the capillary wall thickness measurement and control unit is turned on and off, under the example scenario of an initial capillary wall thickness of 1.20 μm. As shown in Table 6, the single-stretch length increased from 2 km to 12 km, while the attenuation decreased from 0.80 dB / m to 0.09 dB / m. The online monitoring unit improved the yield and effective length of hollow fiber.

[0187] Table 6

[0188]

[0189] The capillary wall thickness adjustment device for hollow optical fibers provided in this embodiment can perform the capillary wall thickness adjustment method for hollow optical fibers provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0190] This application embodiment also provides an anti-resonant hollow optical fiber, which includes a support tube and a capillary tube. The inner diameter of the support tube is larger than the outer diameter of the capillary tube. The capillary tube is fixed on the inner wall of the support tube. The thickness of the capillary tube is monitored and adjusted using the capillary wall thickness adjustment method for hollow optical fibers provided in the above-described method embodiment.

[0191] Combination Figure 1 In the example antiresonant hollow-core optical fiber, multiple capillaries are fixed on the inner wall of the support tube. The number of capillaries can be determined according to the actual situation. When multiple capillaries are present, they can be uniformly fixed on the inner wall of the support tube. The capillary wall thickness is one of the key structural parameters determining its transmission performance. If the capillary wall thickness deviates from the design value, it will cause leakage loss of light at a specific wavelength, significantly increasing the total loss of the optical fiber, and even leading to product failure. The thickness of the capillaries in the antiresonant hollow-core optical fiber provided in this embodiment is monitored and adjusted using the capillary wall thickness adjustment method for hollow-core optical fibers described above. The implementation principle and technical effect are similar, and will not be elaborated here.

[0192] Figure 15 A schematic diagram of the structure of the electronic device provided in this application. Figure 15 As shown, the electronic device 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the electronic device 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus.

[0193] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0194] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0195] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0196] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0197] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0198] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0199] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0200] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory, electrically erasable programmable read-only memory, erasable programmable read-only memory, programmable read-only memory, read-only memory, magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0201] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0202] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0203] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0204] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0205] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to related technologies, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0206] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0207] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for adjusting the capillary wall thickness of a hollow optical fiber, characterized in that, include: Real-time vibration frequency data of multiple points on the capillary were measured non-contactly along the capillary axis using a laser interferometer. Based on the real-time vibration frequency data of multiple points on the capillary, the change in vibration frequency of multiple points on the capillary is obtained. Obtain the initial vibration frequency, initial outer diameter, initial inner diameter, and initial wall thickness corresponding to the capillary; The ratio between the initial vibration frequency of the capillary and the change in vibration frequency is determined as the resolution. Based on the construction of the correspondence between the resolution and the initial outer diameter, initial inner diameter, initial wall thickness and wall thickness change of the capillary, a target mathematical model is obtained, wherein the target mathematical model is a relationship model between the frequency change and the wall thickness change. The vibration frequency change at multiple points on the capillary is input into the target mathematical model to obtain the wall thickness change at multiple points on the capillary. Based on a preset spatial mapping algorithm, the wall thickness variation at multiple points on the capillary is mapped to the spatial position of each point on the capillary to obtain a distribution map of the wall thickness variation. Based on the distribution map of the wall thickness variation corresponding to the capillary, the wall thickness of the capillary is adjusted.

2. The method according to claim 1, characterized in that, The adjustment of the capillary wall thickness based on the distribution map of the wall thickness variation corresponding to the capillary includes: Based on the wall thickness variation distribution map, the regions where the wall thickness increases and the regions where the wall thickness decreases on the capillary are determined. For the region with increased wall thickness, the capillary wall thickness in that region is reduced by increasing the gas pressure in that region. For the region where the wall thickness is reduced, the capillary wall thickness in that region is increased by reducing the gas pressure in that region.

3. The method according to claim 1, characterized in that, Also includes: Vibration signals of capillaries at multiple resonant frequencies were collected using multi-band vibration analysis technology, and cross-validation was performed based on a multi-band data fusion algorithm.

4. The method according to claim 1, characterized in that, Also includes: The vibration frequency changes at multiple points on the capillary are input into the wall thickness change prediction model to obtain the predicted wall thickness changes at multiple points on the capillary. Based on the predicted wall thickness change at multiple points on the capillary and the spatial mapping algorithm, a distribution map of the predicted wall thickness change corresponding to the capillary is generated. The gas pressure in the capillary is adjusted based on the predicted wall thickness variation distribution map.

5. The method according to claim 1, characterized in that, Before obtaining the change in vibration frequency at multiple points on the capillary based on real-time vibration frequency data at multiple points on the capillary, the method further includes: Ambient temperature data is collected using a temperature sensor; Ambient air pressure data is collected using a barometric pressure sensor; Based on the ambient temperature and ambient air pressure data, a preset adaptive calibration algorithm is used to dynamically compensate the real-time vibration frequency data of multiple points on the capillary to obtain the compensated real-time vibration frequency data.

6. A capillary wall thickness adjustment device for hollow optical fibers, characterized in that, include: The detection module is used to non-contactly measure the real-time vibration frequency data of multiple points on the capillary along the capillary axis using a laser interferometer. The processing module is used to obtain the change in vibration frequency at multiple points on the capillary based on real-time vibration frequency data at multiple points on the capillary. The processing module is also used to obtain the initial vibration frequency, initial outer diameter, initial inner diameter and initial wall thickness of the capillary. The processing module is also used to determine the ratio between the initial vibration frequency of the capillary and the change in vibration frequency as the resolution; The processing module is also used to obtain a target mathematical model based on the correspondence between the resolution and the initial outer diameter, initial inner diameter, initial wall thickness and wall thickness change of the capillary, wherein the target mathematical model is a relationship model between the frequency change and the wall thickness change. The processing module is also used to input the vibration frequency change of multiple points on the capillary into the target mathematical model to obtain the wall thickness change of multiple points on the capillary. The processing module is also used to map the wall thickness variation at multiple points on the capillary to the spatial position of each point on the capillary based on a preset spatial mapping algorithm, so as to obtain the wall thickness variation distribution map. The processing module is also used to adjust the wall thickness of the capillary based on the distribution map of the wall thickness variation corresponding to the capillary.

7. A device for adjusting the capillary wall thickness of a hollow optical fiber, characterized in that, include: The fiber drawing unit includes an optical fiber preform, a high-temperature heating furnace, and a cooler; the capillary wall thickness measurement and control unit includes a frequency detection component, a voltage control component, and a control component; the coating unit includes a coating component; and the fiber take-up unit includes a power wheel and a take-up shaft. The drawing unit is used to fuse and cool the preset optical fiber preform to obtain the corresponding anti-resonant hollow optical fiber. The coating unit is used to coat one or more layers of polymer material onto the surface of the anti-resonant hollow optical fiber. The fiber collection unit is used to provide traction force for the anti-resonant hollow fiber to control the drawing speed of the anti-resonant hollow fiber and to collect the anti-resonant hollow fiber. The capillary wall thickness measurement and control unit is used to perform the steps of the capillary wall thickness adjustment method for hollow optical fibers as described in any one of claims 1-5.

8. An anti-resonant hollow-core optical fiber, characterized in that, It includes a support tube and a capillary tube, wherein the inner diameter of the support tube is larger than the outer diameter of the capillary tube, the capillary tube is fixed on the inner wall of the support tube, and the thickness of the capillary tube is monitored and adjusted using the capillary wall thickness adjustment method for hollow optical fibers as described in any one of claims 1-5.

9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the capillary wall thickness adjustment method for hollow optical fibers as described in any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the capillary wall thickness adjustment method for hollow optical fibers as described in any one of claims 1-5.

11. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the capillary wall thickness adjustment method for hollow optical fibers as described in any one of claims 1-5.

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