Manufacturing method of fiberglass cloth for power cables and power cables

Abstract

This invention relates to the field of glass fiber cloth manufacturing technology, specifically to a method for manufacturing glass fiber cloth for power cables and a power cable. The method involves obtaining the elastic modulus, count, and ply number of the glass fiber yarns, and setting an initial tension. Based on real-time tension data, a tension uniformity coefficient is calculated and the yarn breakage rate is predicted. If the breakage rate exceeds a threshold, the tension is adjusted to obtain the first tension data. Then, based on fabric flatness feedback optimization, a second tension data is obtained, achieving tension-flatness dual closed-loop control. This significantly reduces the yarn breakage rate, improves fabric quality, and meets the high strength and high uniformity requirements of glass fiber cloth for cables.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of glass fiber cloth manufacturing, in particular to a glass fiber cloth manufacturing method for power cables and a power cable. BACKGROUND

[0002] As the insulation and reinforcement material of power cables, the performance of glass fiber cloth directly affects the insulation, mechanical strength and long-term reliability of power cables. Glass fiber cloth is usually woven by warp yarns and weft yarns, and the weaving process needs to strictly control the yarn tension to ensure that the cloth surface structure is uniform and the strength meets the standard. However, due to the unique material properties of glass fiber yarns, significant process challenges are faced during weaving:

[0003] Glass fiber yarns are made of glass fibers as raw materials through processes such as drawing and twisting, and the core material properties are high rigidity, low elasticity and high brittleness. Specifically, the molecular structure of glass fibers is dense, and the intermolecular force is strong, resulting in a very small amount of deformation when the yarn is under stress (the elastic modulus is usually 70~90GPa, which is significantly higher than the 3~10GPa of ordinary chemical fibers), making it difficult to buffer the tension fluctuations during weaving through flexible deformation; the yarn can only produce a small amount of recoverable deformation after being stretched by external force (the elongation at break is usually 2%~4%, which is much lower than the 7%~10% of cotton fibers or the 15%~30% of polyester fibers), and once the tension exceeds its elastic limit, irreversible fracture is likely to occur; the surface of glass fiber is smooth and has no natural curling, the friction between fibers is weak, and there is also a lack of elastic buffering mechanism, so in the weaving process, if the local tension is concentrated (such as the release end of the warp yarn, the weft beating stage), or due to the shearing force when the yarns are interwoven, sudden breakage of single or multiple yarns (i.e. "broken yarns") is likely to occur.

[0004] The above characteristics of glass fiber yarns make them extremely sensitive to tension during weaving of glass fiber cloth - too low tension will result in loose interweaving of yarns, forming sparse areas on the cloth surface (insufficient density); too high tension will directly exceed the elastic load range of the yarns, causing broken yarns. SUMMARY

[0005] Therefore, the purpose of the present application is to overcome the problem of high broken yarn rate and uneven cloth surface density caused by improper tension control during weaving of glass fiber yarns in the prior art, and to provide a glass fiber cloth manufacturing method for power cables and a power cable. By dynamically distributing the initial tension, real-time monitoring the tension uniformity and broken yarn risk, and combining the cloth flatness feedback for multi-parameter collaborative optimization, the process problems of easy broken yarns and uneven cloth surface density of glass fiber yarns during weaving are fundamentally solved, and the production efficiency, quality stability and application reliability of the glass fiber cloth for power cables are improved.

[0006] The first aspect, to solve the above technical problems, the present application provides a kind of glass fiber cloth manufacturing method for power cable, comprising:

[0007] The elastic modulus and physical property parameters of the glass fiber yarn are obtained, and the initial tension data of the weaving yarn is distributed according to the elastic modulus and the physical property parameters;The physical property parameters include the number of yarn and the number of strands;

[0008] The operating parameters of the loom are set according to the initial tension data, and the real-time tension data of the yarn is obtained;

[0009] The tension uniformity coefficient of the weaving area is calculated according to the real-time tension data of the yarn, and the yarn breakage rate is predicted according to the elastic modulus and the tension uniformity coefficient;

[0010] If the yarn breakage rate prediction value exceeds the yarn breakage rate threshold value, the initial tension data is adjusted to obtain first tension data;

[0011] The operating parameters of the loom are updated according to the first tension data, and the cloth surface flatness of the weaving area is obtained, and if the cloth surface flatness is lower than the target flatness, the first tension data is adjusted to obtain second tension data;

[0012] The power cable glass fiber cloth manufacturing is carried out according to the second tension data.

[0013] Preferably, the initial tension data of the weaving yarn is distributed according to the elastic modulus and the physical property parameters, comprising: determining the equivalent diameter of the yarn according to the number of yarn and the number of strands;The reference tension value is determined according to the equivalent diameter and the elastic modulus;The tension distribution function along the length direction of the yarn is constructed according to the reference tension value, and the initial tension data is distributed according to the tension distribution function.

[0014] Preferably, the tension distribution function is:

[0015] ;

[0016] F (x) represents the initial tension value of the yarn at a distance of x from the reference position;X represents the distance of the current position of the yarn relative to the reference position;L represents the total path length of the yarn; The tension gradient coefficient is represented, and the value is ± (0.1-0.3), the positive value represents that the tension of back beam to loom mouth increases, and the negative value represents that the tension of back beam to loom mouth decreases;F0 represents the reference tension value.

[0017] Preferably, the yarn tension data in real time is used to calculate a tension uniformity coefficient of the weaving area, the yarn breakage rate is predicted according to the elastic modulus and the tension uniformity coefficient, and the method comprises the following steps: a plurality of tension detection points are arranged in the weaving area, and real-time tension values of the tension detection points are obtained; a yarn breakage rate prediction model is constructed, the real-time tension values and the elastic modulus are input into the yarn breakage rate prediction model, and a yarn breakage rate prediction value is obtained; wherein the yarn breakage rate prediction model comprises the following steps: calculating the average tension and the standard deviation of all tension detection points; calculating a tension uniformity coefficient according to the average tension and the standard deviation; and determining the yarn breakage rate prediction value according to the tension uniformity coefficient and the elastic modulus.

[0018] Preferably, the yarn breakage rate prediction model is:

[0019] ;

[0020] ;

[0021] K represents the tension uniformity coefficient; represents the tension standard deviation; represents the average tension; P represents the yarn breakage rate prediction value; Fmax represents the maximum tension value monitored in the weaving area; E represents the elastic modulus of the yarn; and A represents the cross-sectional area of the yarn. represents the yarn fatigue coefficient, and the value is 0.8-1.2.

[0022] Preferably, the initial tension data is adjusted to obtain first tension data, which comprises adjusting the initial tension data of the warp yarn to obtain the first tension data of the warp yarn; the adjustment of the initial tension data of the warp yarn comprises: calculating the deviation of the yarn breakage rate prediction value of the warp yarn from the yarn breakage rate threshold value to obtain a warp yarn breakage rate deviation value; calculating the ratio of the warp yarn breakage rate deviation value to the yarn breakage rate threshold value to obtain a warp yarn breakage rate deviation ratio; calculating the ratio of the elastic modulus to a reference elastic modulus to obtain a modulus correction factor; and reducing the initial tension according to the modulus correction factor and the warp yarn breakage rate deviation ratio to obtain the first tension of the warp yarn; wherein the adjustment mode of the warp yarn is:

[0023] ;

[0024] F1 represents the first tension of the warp yarn; Fa represents the initial tension of the warp yarn; Eref represents the reference elastic modulus; E represents the elastic modulus of the warp yarn; ΔP represents the warp yarn breakage rate deviation value; P th represents the yarn breakage rate threshold value.

[0025] Preferably, the adjusting the initial tension data to obtain the first tension data further comprises adjusting the initial tension data of the weft yarn to obtain the first tension data of the weft yarn, and the adjusting the initial tension data of the weft yarn comprises:

[0026] ;

[0027] F2 represents the first tension of the weft yarn; Fa represents the initial tension of the weft yarn; and AF represents the tension adjustment amount; wherein the tension adjustment amount is related to the weft yarn breakage rate deviation value, the weft insertion speed and the weft yarn flight path length.

[0028] Preferably, the adjusting the first tension data to obtain the second tension data comprises: acquiring a fabric surface image of the weaving area, analyzing the fabric surface image to obtain a defect type; and performing corresponding tension adjustment according to the defect type: if the defect type is a longitudinal stripe defect, increasing the tension of the warp yarn in the contact area with the guide component and decreasing the tension of the adjacent area; and if the defect type is a transverse weft bar defect, decreasing the weft yarn tension and reducing the weft insertion speed.

[0029] Preferably, the analyzing the fabric surface image to obtain the defect type comprises: performing directional Gabor filtering on the fabric surface image, and extracting warp direction characteristic components and weft direction characteristic components; calculating the length-width ratio of a stripe area according to the warp direction characteristic components and the weft direction characteristic components; if the length-width ratio is greater than 3:1, determining that the defect type is a longitudinal stripe defect; and if the length-width ratio is less than 1:3, determining that the defect type is a transverse weft bar defect.

[0030] In a second aspect, to solve the above technical problems, the present application provides a power cable comprising an insulating shielding layer, which is manufactured based on the glass fiber cloth manufacturing method for power cables.

[0031] The above technical solutions of the present application have the following beneficial effects compared with the prior art:

[0032] The glass fiber cloth manufacturing method for power cables and the power cable provided by the present application can dynamically distribute initial tension, monitor tension uniformity and yarn breakage risk in real time, and perform multi-parameter collaborative optimization in combination with fabric flatness feedback, thereby fundamentally solving the process problems of glass fiber yarn breakage and uneven fabric density in the weaving process, and improving the production efficiency, quality stability and application reliability of the glass fiber cloth for power cables.

[0033] The initial tension data is distributed according to the elastic modulus, the yarn count and the number of strands, so that the yarn can be in a relatively appropriate stress state at the initial stage of weaving, avoiding yarn breakage of thin count or low strand yarn due to excessive tension, or tight interweaving of thick count or high strand yarn due to insufficient tension, thereby ensuring the smooth progress of the weaving process.

[0034] In the weaving process, the tension data of the yarn is obtained in real time, and the tension uniformity coefficient of the weaving area is calculated, and the yarn elasticity modulus is combined to predict the yarn breaking probability. This kind of real-time monitoring and dynamic adjustment mode can timely find the potential yarn breaking risk, and reduce the yarn breaking probability by updating the initial tension data, so as to ensure the continuity of production and the stability of product quality.

[0035] On the basis of reducing the yarn breaking probability, the tension data is further adjusted according to the flatness of the cloth. The flatness of the cloth is one of the important quality indexes of the glass fiber cloth. By continuously optimizing the tension data, the woven glass fiber cloth can have both low yarn breaking rate and good flatness of the cloth, realizing multi-objective optimization and meeting the actual production demand. BRIEF DESCRIPTION OF DRAWINGS

[0036] In order to make the content of the application more easily understood, the application will be further described in detail below according to the specific embodiments of the application and in combination with the drawings.

[0037] Figure 1 Flow chart of the method for manufacturing the glass fiber cloth for power cable in the preferred embodiment of the application;

[0038] Figure 2 Flow chart of the method for distributing the initial tension data of the weaving yarn in the preferred embodiment of the application;

[0039] Figure 3 Flow chart of the method for adjusting the first tension data to obtain the second tension data in the preferred embodiment of the application. DETAILED DESCRIPTION

[0040] The application will be further described below in combination with the drawings and specific embodiments, so that those skilled in the art can better understand the application and implement it, but the embodiments are not as a limitation on the application.

[0041] The purpose of the embodiment of the application is to overcome the problem of high yarn breaking rate and uneven cloth surface density caused by improper tension control in the process of weaving glass fiber cloth by glass fiber yarn in the prior art.

[0042] In the traditional glass fiber cloth manufacturing process, the yarn stress is usually controlled by the method of "fixed tension setting" or "empirical segmented tension adjustment". However, due to the significant differences in the count (reflecting the thickness of the yarn, unit tex), the number of strands (the number of single yarn or twisted yarn) and the elastic modulus (reflecting the rigidity of the material, unit GPa) of the glass fiber yarn (for example: thin count yarn is more prone to breakage due to tension fluctuation, and multi-strand yarn can withstand higher tension due to high structural strength), the existing method does not fully consider the differentiated influence of these physical characteristic parameters on tension demand, resulting in the following typical problems:

[0043] High yarn breakage rate: if the initial tension is set too high (especially for thin count or low ply yarns), the yarns will break at the beginning of weaving due to exceeding their elastic limit; if the tension is set too low (especially for thick count or high ply yarns), the yarns cannot be tightly engaged when interlacing, resulting in yarn breakage due to shear force concentration in the subsequent beating-up stage. In actual production, the yarn breakage rate of glass fiber cloth is often as high as 0.1-0.5 root / km (much higher than the 0.001-0.01 root / km of ordinary chemical fiber cloth), which seriously affects the production efficiency and material utilization.

[0044] Uneven fabric density: tension fluctuations will cause the arrangement density of yarns in the warp or weft direction to be inconsistent - the yarns in areas with excessive local tension are stretched too much, reducing the number of yarns per unit area (sparse areas); the yarns in areas with insufficient local tension are relaxed and accumulated, increasing the number of yarns per unit area (dense areas); this density non-uniformity will further worsen the insulation performance (weak insulation in sparse areas) and mechanical strength (stress concentration in dense areas) of the fabric, resulting in poor performance consistency of glass fiber cloth for power cables, which cannot meet the requirements of harsh application scenarios such as high voltage and high frequency.

[0045] Embodiment one: refer to Figure 1 The embodiment of the application discloses a method for manufacturing glass fiber cloth for power cables, comprising:

[0046] S100, obtaining the elastic modulus and physical property parameters of the glass fiber yarns, and assigning initial tension data for the weaving yarns according to the elastic modulus and physical property parameters; the physical property parameters include the count and ply of the yarns;

[0047] S200, setting the operating parameters of the loom according to the initial tension data, and obtaining real-time tension data of the yarns;

[0048] S300, calculating the tension uniformity coefficient of the weaving area according to the real-time tension data of the yarns, and predicting the yarn breakage rate according to the elastic modulus and the tension uniformity coefficient;

[0049] S400, if the predicted value of the yarn breakage rate exceeds the yarn breakage rate threshold, adjusting the initial tension data to obtain first tension data;

[0050] S500, updating the operating parameters of the loom according to the first tension data, and obtaining the fabric flatness of the weaving area; if the fabric flatness is lower than the target flatness, adjusting the first tension data to obtain second tension data;

[0051] S600, manufacturing the glass fiber cloth for power cables according to the second tension data.

[0052] In a specific application scenario, the number of yarns, the number of strands and the modulus of elasticity of the glass fiber yarn are obtained from the data provided by the supplier; or the number of yarns, the number of strands and the modulus of elasticity of the glass fiber yarn are obtained through detection equipment;

[0053] For example, using a universal material testing machine, the yarn is tested according to the standard, the stress-strain curve is recorded, and the modulus of elasticity is calculated by dividing the stress by the strain; the modulus of elasticity is an index to measure the ability of the yarn to resist elastic deformation. The modulus of elasticity of the glass fiber yarn reflects the size of its rigidity, the higher the modulus of elasticity, the more rigid the yarn, the more difficult it is to deform during weaving, but it is also more likely to break due to excessive tension; the lower the modulus of elasticity, the more flexible the yarn, it can withstand a certain degree of deformation without breaking, but it is more sensitive to changes in tension, and more precise tension control is required to ensure interweaving.

[0054] The number of yarns is measured based on the weighing method; the number of yarns represents the fineness of the yarn, the higher the number of yarns, the finer the yarn. Thin number of yarns single fiber is thin, its can bear the tension is relatively small, and in the weaving process is more easily affected by friction, collision and other factors and break; thick number of yarns is relatively more robust, can bear greater tension, but in the interweaving may need more tension to ensure close combination.

[0055] The number of strands of the yarn is measured based on visual recognition + single yarn tension separation test, the number of strands refers to the number of single yarns that make up the yarn; multi-strand yarns have higher overall structural strength than single-strand yarns due to the twisting of multiple single yarns together, and can withstand greater tension.

[0056] According to the modulus of elasticity, the number of yarns and the number of strands, the initial tension data is distributed, which can make the yarns in the initial stage of weaving be in a relatively appropriate stress state, avoid the breakage of thin number or low number of strands due to excessive tension, or the interweaving of thick number or high number of strands due to insufficient tension, so as to ensure the smooth progress of the weaving process.

[0057] The running parameters of the loom are set according to the initial tension data, and the real-time tension data of the yarn is obtained; by installing different types of tension sensors at key positions of the loom, the tension of the yarn is sensed in real time, for example, in the warp yarn area, a tension sensor is installed near the release end of the warp beam to monitor the initial tension of the warp yarn when it is released from the warp beam, ensuring that the warp yarn enters the weaving area with appropriate tension; a sensor is installed at the front end of the weaving mouth, i.e. a position before the warp yarn and weft yarn interweave, to measure the tension of the warp yarn in the weaving process in real time, so as to adjust in time and ensure good interweaving of the warp yarn and weft yarn; in the weft yarn area, a sensor is installed near the weft yarn introduction device to monitor the tension when the weft yarn is introduced, ensuring that the weft yarn can smoothly enter the shed; in the beating-up stage, a sensor is installed near the reed to measure the tension change of the weft yarn during beating-up, which is crucial to ensure the close interweaving of the weft yarn and warp yarn.

[0058] In the weaving process, the tension data of the yarn is obtained in real time, and a tension uniformity coefficient of the weaving area is calculated, which reflects the uniformity of the tension distribution in the weaving area; the lower the tension uniformity coefficient, the more uneven the tension distribution, and some yarns may bear excessive tension, while some yarns may have insufficient tension;

[0059] The yarn breakage probability is predicted in combination with the tension uniformity coefficient and the elastic modulus of the yarn, and if the yarn breakage rate prediction value exceeds the yarn breakage rate threshold value, the initial tension data is adjusted to obtain first tension data; the yarn breakage rate threshold value is a safety limit set in advance, representing the maximum yarn breakage rate allowed under the premise of ensuring normal production and product quality. When the yarn breakage rate exceeds this threshold value, it indicates that there is a problem with the current weaving conditions (mainly the tension setting) that needs to be adjusted in a timely manner. The yarn breakage rate threshold value can be determined based on statistical analysis: under stable process conditions, continuously produce at least 100,000 meters of yarn, record the number of yarn breaks, calculate the reference yarn breakage rate, and set the yarn breakage rate threshold value as the sum of the reference yarn breakage rate and three times the standard deviation of the yarn breakage rate.

[0060] By predicting the yarn breakage rate, potential risks can be discovered before actual yarn breakage occurs. When it is predicted that the yarn breakage rate in a certain area may exceed the threshold value, measures can be taken to adjust the tension in a timely manner to avoid yarn breakage and reduce production interruptions and waste. According to the prediction results, the tension parameters of each area of the loom can be adjusted specifically and accurately to make the tension distribution more uniform and reduce the risk of yarn breakage. For example, for areas with a high tension non-uniformity coefficient, the tension in that area can be appropriately reduced or the tension distribution method can be adjusted to ensure the safety of the yarn, reduce defects on the cloth surface caused by yarn breakage and tension non-uniformity, improve the overall quality of the glass fiber cloth, and meet the strict requirements of power cables for product quality.

[0061] Although the yarn breakage probability can be predicted based on the tension uniformity coefficient and the elastic modulus, this prediction method has certain limitations. For example, the elastic modulus may fluctuate due to factors such as yarn production process, environmental temperature and humidity, etc., leading to inaccurate prediction results; at the same time, errors may exist in the calculation of the tension uniformity coefficient, and these factors combined may cause deviations in the tension adjustment based on the yarn breakage rate, resulting in over-adjustment or under-adjustment.

[0062] The effects of over-adjustment include: if the tension is excessively increased to reduce the yarn breakage rate, the yarn will be excessively stretched, which may cause uneven stretching deformation on the cloth surface, resulting in excessive yarn spacing in local areas and forming a concave-convex phenomenon, reducing the flatness of the cloth surface. In addition, excessive stretching may also cause yarn breakage, which may affect production efficiency and product quality.

[0063] The effects of under-adjustment include: if the tension adjustment is insufficient, i.e. under-adjustment occurs, the yarns will be relatively loose during weaving and cannot be tightly interwoven, which will cause wrinkles and loose areas on the cloth surface, irregular arrangement between the yarns, and also poor flatness of the cloth surface, affecting the overall quality and appearance of the glass fiber cloth.

[0064] To solve this problem, in the real-time scheme of the application, after obtaining the first tension data according to the yarn breakage prediction result, the operating parameters of the loom are updated according to the first tension data, and the flatness of the cloth surface in the weaving area is obtained, if the flatness of the cloth surface is lower than the target flatness, the first tension data is adjusted to obtain the second tension data, and the power cable glass fiber cloth is manufactured according to the second tension data.

[0065] The glass fiber cloth manufacturing method for power cables provided by the application solves the process problems of easy yarn breakage and uneven cloth surface density of glass fiber yarns during weaving by dynamically distributing the initial tension, real-time monitoring the tension uniformity and yarn breakage risk, and multi-parameter collaborative optimization combined with cloth surface flatness feedback, thereby improving the production efficiency, quality stability and application reliability of the glass fiber cloth for power cables.

[0066] Based on the above embodiments, referring to Figure 2 the initial tension data of the weaving yarn is distributed according to the elastic modulus and physical property parameters, including: determining the equivalent diameter of the yarn according to the number of yarns and the number of strands; determining the reference tension value according to the equivalent diameter and the elastic modulus; constructing a tension distribution function along the length direction of the yarn according to the reference tension value, and distributing the initial tension data according to the tension distribution function.

[0067] In specific application scenarios, the actual physical form of the yarn (such as the single yarn diameter and the overall thickness after twisting of the strand) directly affects the contact friction, stress area and tightness during interweaving with the loom components (such as the heald, reed and warp beam); but the geometric shape of the glass fiber yarn (especially the multi-strand yarn) is irregular (such as an ellipse or a non-standard circle after twisting), it is difficult and limited to directly measure the true diameter, therefore, the equivalent diameter is introduced, that is, the number of yarns and the number of strands are converted into a diameter value equivalent to an ordinary circular cross-section yarn, and the calculation method is as follows:

[0068] ;

[0069] D represents the equivalent diameter of the yarn; represents a shape correction coefficient, and the value is 0.8-1.2; represents the density of the yarn; M represents the number of strands of the yarn; and N represents the number of decitex of the yarn.

[0070] The reference tension value F0 is calculated in the following manner:

[0071] ;

[0072] F0 represents the reference tension value; C represents the tension adjustment coefficient, which is related to the type of loom, and the value of C for a rapier loom is 0.2-0.3; the value of C for an air-jet loom is 0.1-0.2; E represents the elastic modulus of the yarn; and D represents the equivalent diameter of the yarn.

[0073] The initial tension data is assigned according to the tension distribution function, which is:

[0074] ;

[0075] F(x) represents the initial tension value of the yarn at a distance x from the reference position; x represents the distance of the current position of the yarn relative to the reference position; and L represents the total path length of the yarn, which is used to normalize the scale of tension change. F(x) represents the initial tension value of the yarn at a distance x from the reference position; x represents the distance of the current position of the yarn relative to the reference position; and L represents the total path length of the yarn, which is used to normalize the scale of tension change.

[0076] The tension distribution function describes the relationship between the initial tension value of the yarn along its length direction (from a certain reference position to the target position) and the position change during the weaving process, reflecting the non-uniform change of the initial tension along the length direction due to the influence of the force of the loom components (such as the heald, the reed), the friction between the yarns, and the requirements of the weaving process; the core purpose is to accurately match the actual tension requirements of the weaving position:

[0077] High-tension key positions ensure tight interweaving: at positions where the yarn tension requirement is high, such as the front end of the loom and the beating-up stage, i.e., positions where x is large, due to the large value of x / L, the initial tension value F(x) according to the tension distribution function will be significantly greater than the reference tension value, which means that the yarn can obtain greater tension in these key areas, thereby ensuring that the warp and weft yarns can be tightly interwoven, reducing the occurrence of sparse or gap on the cloth surface, and improving the density uniformity and overall strength of the cloth surface. For example, during the beating-up stage, the reed exerts a large impact force on the weft yarn, at which time the weft yarn needs higher tension to resist the impact and maintain close contact with the warp yarn, and the higher tension assigned by the tension distribution function can meet this demand.

[0078] Non-critical position low tension avoids excessive stress: in the beam release end, the initial stage of weft yarn introduction, and other positions where the tension requirement is relatively low, that is, the position where x is small, x / L is small, and F(x) is relatively close to the reference tension value or even slightly lower. This avoids excessive stretching, breakage, or wear of the yarn due to bearing excessive tension in these positions, especially for glass fiber yarns which are rigid, have low elasticity, and are prone to breakage. Lower tension can reduce the risk of yarn breakage and help protect the physical properties of the yarn, extending its service life.

[0079] Compared with the traditional uniform tension distribution method, the embodiment of the application performs dynamic gradient distribution of initial tension data based on a tension distribution function, which can better adapt to the differentiated requirements of different components of the loom for yarn tension, reduce problems such as yarn vibration and increased friction caused by sudden changes in tension, and thus improve the stability and reliability of the weaving process.

[0080] On the basis of the above embodiments, the tension uniformity coefficient of the weaving area is calculated according to the real-time tension data of the yarn, and the yarn breakage rate is predicted according to the elastic modulus and the tension uniformity coefficient, including: configuring a plurality of tension detection points in the weaving area, and obtaining the real-time tension values of each tension detection point; constructing a yarn breakage rate prediction model, inputting the real-time tension values and the elastic modulus into the yarn breakage rate prediction model to obtain a yarn breakage rate prediction value; wherein the yarn breakage rate prediction model includes obtaining the yarn breakage rate prediction value by: calculating the average tension and the standard deviation of all tension detection points; calculating the tension uniformity coefficient according to the average tension and the standard deviation; and determining the yarn breakage rate prediction value according to the tension uniformity coefficient and the elastic modulus.

[0081] In specific application scenarios, a plurality of tension sensors are arranged at the beam release end of the warp yarn, the heald wire area, the front end of the shed, or the introduction area of the weft yarn, and the beating-up area to cover the key positions where the yarn may bear high stress, with the purpose of ensuring that the detection data can reflect the overall tension distribution characteristics; the tension sensor real-time collects yarn tension data of each monitoring point to capture the dynamic changes of tension during the weaving process.

[0082] The arithmetic mean of the real-time tension values of all detection points is calculated to reflect the overall tension level of the weaving area; and the tension standard deviation of all detection points is calculated to measure the dispersion degree of the tension values of each detection point relative to the average tension, reflecting the uniformity of the tension distribution; the uniformity of the tension distribution is quantified by the ratio of the standard deviation to the average tension, the smaller the tension uniformity coefficient, the closer the tension of each point to the average value, and the more uniform the distribution; on the contrary, the larger the tension uniformity coefficient, the more likely there are areas with significantly higher or lower local tension, which can easily cause yarn breakage or poor interlacing.

[0083] A mapping relationship between the tension uniformity coefficient K, the elastic modulus E and the broken yarn rate P is established through experimental calibration or theoretical derivation to construct a broken yarn rate prediction model.

[0084] ;

[0085] ;

[0086] K represents the tension uniformity coefficient; represents the standard deviation of tension; represents the average tension; P represents the broken yarn rate prediction value; Fmax represents the maximum tension value monitored in the weaving area; E represents the elastic modulus of the yarn; A represents the cross-sectional area of the yarn, which is determined according to the equivalent diameter of the yarn; represents the yarn fatigue coefficient, and the value is 0.8-1.2.

[0087] represents the tensile stiffness of the yarn (unit: N), reflecting the overall ability of the yarn to resist deformation; quantifies the relative deformation degree of the yarn, and when approaches the breaking strain of the yarn, the broken yarn probability sharply rises.

[0088] The warp yarn is a yarn that runs longitudinally through the fabric, and mainly bears the beating impact force from the steel reed at the weaving port and the winding stress when the warp beam is released during the weaving process; during beating, the steel reed exerts a transverse extrusion on the warp yarn, so that the warp yarn bears a large instantaneous tension near the weaving port; at the same time, when the warp yarn is wound on the warp beam, due to the influence of winding density and mode, the warp yarn near the release end of the warp beam may have an initial tension that is not uniform. Therefore, the tension change of the warp yarn is mainly related to the beating action and the warp beam release process, and the stress direction is mainly a combination of transverse impact and longitudinal stretching.

[0089] The weft yarn is a yarn that is inserted transversely into the warp yarn shed, and mainly bears the friction during the introduction process and the shear force during the beating stage; during the introduction, the weft yarn enters the shed through the guide, and will be subjected to the friction of the guide and the warp yarn; during beating, the steel reed exerts a shear force on the weft yarn to press it tightly on the warp yarn. The tension change of the weft yarn is mainly related to the introduction process and the beating action, and the stress direction is mainly a combination of longitudinal stretching and transverse shearing;

[0090] The above, the force characteristics of the warp yarn and the weft yarn are different, so that the tension requirements of the warp yarn and the weft yarn are different in different weaving stages, in order to solve this problem, in the embodiment scheme of the present application, when the broken yarn rate prediction value exceeds the broken yarn rate threshold value, the initial tension of the warp yarn and the weft yarn is adjusted separately, which can more accurately adjust the respective force characteristics, avoids the situation that part of the yarn tension is not suitable due to unified adjustment, thereby reducing the risk of broken yarn.

[0091] Specifically, adjusting the initial tension data of the warp yarn includes: calculating a deviation of the yarn breakage rate prediction value of the warp yarn from the yarn breakage rate threshold value to obtain a yarn breakage rate deviation value; calculating a ratio of the yarn breakage rate deviation value to the yarn breakage rate threshold value to obtain a yarn breakage rate deviation ratio; calculating a ratio of the elastic modulus to the reference elastic modulus to obtain a modulus correction factor; and reducing the initial tension according to the modulus correction factor and the yarn breakage rate deviation ratio to obtain a first tension of the warp yarn; wherein the adjustment mode of the warp yarn is:

[0092] ;

[0093] F1 represents the first tension of the warp yarn; Fa represents the initial tension of the warp yarn; Eref represents the reference elastic modulus; E represents the elastic modulus of the warp yarn; ΔP represents the yarn breakage rate deviation value; P th represents the yarn breakage rate threshold value.

[0094] In a specific application scenario, the deviation of the yarn breakage rate prediction value of the warp yarn from the yarn breakage rate threshold value is calculated to obtain a yarn breakage rate deviation value ΔP, which quantitatively reflects the "excess degree" of the current yarn breakage risk of the warp yarn - a positive deviation value indicates that the actual predicted yarn breakage rate is higher than the safety limit value and immediate intervention is required; the greater the deviation value, the more urgent the yarn breakage risk. The ratio of the yarn breakage rate deviation value ΔP to the yarn breakage rate threshold value P th is calculated to obtain a yarn breakage rate deviation ratio, which standardizes the deviation value into a relative proportion (dimensionless) and eliminates the influence of different threshold settings on the adjustment amplitude. The ratio of the elastic modulus to the reference elastic modulus (the reference modulus of glass fiber is 70 GPa) is calculated to obtain a modulus correction factor; the modulus correction factor corrects the tension adjustment requirement caused by the rigidity difference of the yarn material, and the higher the elastic modulus (the harder the yarn), the more likely it is to be brittle under the same tension, and the tension needs to be reduced more significantly; otherwise, the elastic modulus is lower (the yarn is slightly more flexible), and the tension adjustment amplitude can be appropriately reduced. The modulus correction factor reflects the dynamic influence of material properties on the tension safety threshold.

[0095] Adjusting the initial tension data of the weft yarn includes:

[0096] ;

[0097] F2 represents the first tension of the weft yarn; Fa represents the initial tension of the weft yarn; ΔF represents the tension adjustment amount; wherein the tension adjustment amount is related to the weft yarn breakage rate deviation value, the weft insertion speed and the weft flight path length.

[0098] The weft yarn breakage rate deviation refers to the difference between the breakage rate prediction value and the breakage rate threshold, reflecting the actual breakage risk degree of the current weft yarn; the weft yarn leading speed refers to the average speed of the weft yarn from the leading-in device to the opposite side through the shed in a certain time, reflecting the kinetic energy state of the weft yarn in the flight process; the weft yarn flight path length refers to the straight-line flight distance of the weft yarn from the leading-in point to the complete beating-up, which is related to the size of the shed of the loom and the arrangement density of the warp yarns, the longer the path, the longer the weft yarn flight time, and the higher the risk of tension decay, which requires higher initial tension compensation.

[0099] On the basis of the above embodiments, referring to Figure 3 the first tension data is adjusted to obtain second tension data, including: acquiring a cloth surface image of the weaving area, analyzing the cloth surface image to obtain a defect type; performing corresponding tension adjustment according to the defect type: if it is a longitudinal stripe defect, increasing the tension of the contact area of the warp yarn and the yarn guide component and decreasing the tension of the adjacent area; if it is a transverse weft bar defect, decreasing the weft yarn tension and reducing the weft leading speed.

[0100] In a specific application scenario, the cloth surface image of the weaving area (usually covering a local area where the warp and weft yarns are interwoven, such as sampling once every 10-20 meters) is collected in real time by an industrial camera, and the image is analyzed by using an image processing algorithm (such as edge detection, texture analysis, and color contrast recognition) to identify the defect type existing on the cloth surface:

[0101] The longitudinal stripe defect is a periodic light and dark stripe on the cloth surface along the warp direction (the longitudinal direction of the yarn), which is usually caused by the difference in interweaving density due to the uneven distribution of the warp yarn tension along the longitudinal direction; the transverse weft bar defect is a transverse bar (such as a sudden change in color depth, yarn accumulation or sparseness) with different widths on the cloth surface along the weft direction (the transverse direction of the yarn), which is usually caused by the difference in interweaving tightness due to the abnormal weft yarn tension (too high or too low), unstable weft leading speed or poor weft yarn flight state.

[0102] The essence of the longitudinal stripe is that the tension gradient of the warp yarn along the longitudinal direction is too large, resulting in uneven interweaving density of the warp yarn, and by increasing the tension of the contact area (strengthening the stability of the tight area) and decreasing the tension of the adjacent area (relieving the relaxation of the loose area), the tension distribution of the warp yarn along the longitudinal direction can be balanced, the interweaving density tends to be uniform, and thus the stripe is eliminated.

[0103] The transverse weft bar is usually caused by the weft yarn tension being too high (causing the weft yarn to be stretched too much and interweave too tightly with the warp yarn) or too low (causing the weft yarn to be relaxed and interweave too loosely with the warp yarn), and the weft leading speed being too fast (the weft yarn flight time being insufficient and the impact being too large). Reducing the weft yarn tension can reduce the extrusion or relaxation effect of the weft yarn on the warp yarn, making the interweaving more uniform; reducing the weft leading speed reduces the kinetic energy of the weft yarn, prolongs the flight time, and ensures that the weft yarn enters the shed smoothly and interweaves tightly with the warp yarn, thereby eliminating the weft bar.

[0104] Specifically, the fabric surface image is analyzed to obtain a defect type, including: performing directional Gabor filtering on the fabric surface image, and extracting warp direction feature components and weft direction feature components; calculating a length-width ratio of a stripe area according to the warp direction feature components and the weft direction feature components; if the length-width ratio is greater than 3:1, determining that the defect is a longitudinal stripe defect; and if the length-width ratio is less than 1:3, determining that the defect is a transverse barrier defect.

[0105] In a specific application scenario, the Gabor filter is a linear filter simulating human visual perception, and can extract texture information of a specific direction and frequency in an image. In fabric surface detection, two sets of directional Gabor filters (one set of directions is parallel to the warp yarn, i.e., warp direction; and the other set of directions is parallel to the weft yarn, i.e., weft direction) are used to perform convolution operations on the collected fabric surface image. The warp direction Gabor filter is set to have a direction parameter consistent with the arrangement direction of the warp yarn, and the weft direction Gabor filter is set to have a direction parameter consistent with the arrangement direction of the weft yarn. After Gabor filtering, the texture components in the image consistent with the filter direction are enhanced, and the interference components in other directions are suppressed. The warp direction feature components (reflecting the texture intensity, contrast, or periodic change in the warp direction) and the weft direction feature components (reflecting the texture intensity, contrast, or periodic change in the weft direction) are extracted from the filtering result.

[0106] Based on the difference between the warp direction feature components and the weft direction feature components, the area with abnormal texture in the fabric surface is located, and the length-width ratio of the area is measured. If the length-width ratio is greater than 3:1 (i.e., the length direction is much larger than the width direction, for example, the stripe extends very long in the warp direction but very narrow in the width direction), it is determined that the defect is a longitudinal stripe defect. If the length-width ratio is less than 1:3 (i.e., the width direction is much larger than the length direction, for example, the transverse barrier extends very wide in the weft direction but very short in the length direction), it is determined that the defect is a transverse weft barrier defect. Through directional texture feature extraction and geometric morphology analysis, accurate recognition and classification of common defects (longitudinal stripe and transverse weft barrier) in the fabric surface are realized. The directional Gabor filtering effectively suppresses the texture interference in non-target directions, and in combination with the quantitative judgment of the length-width ratio, the recognition accuracy of the longitudinal stripe and the transverse weft barrier can be improved to more than 90%, and the error tension adjustment caused by misjudgment is reduced.

[0107] Embodiment Two: The embodiment of the present application and the embodiment are based on the same inventive concept, and disclose a power cable comprising an insulating shielding layer, which is manufactured based on the power cable glass fiber cloth manufacturing method in Embodiment One.

[0108] The embodiment of the present application and Embodiment One are based on the same inventive concept and have the same technical effects, which will not be repeated here.

[0109] In conclusion, the manufacturing method of the glass fiber cloth for power cable and the power cable can solve the process problems of the glass fiber yarn in the weaving process, such as the broken yarn and the uneven density of the cloth surface, by dynamically distributing the initial tension, monitoring the tension uniformity and the broken yarn risk in real time, and performing the multi-parameter collaborative optimization combined with the flatness feedback of the cloth surface, so as to improve the production efficiency, the quality stability and the application reliability of the glass fiber cloth for power cable.

[0110] Obviously, the above embodiments are only examples for clearly illustrating, and are not intended to limit the embodiments. Based on the above description, other different forms of changes or variations can be made by those skilled in the art. Here, all the embodiments are not required to be exhausted, and the obvious changes or variations derived therefrom are still within the protection scope of the present application.

Claims

1. A method for manufacturing a glass fiber cloth for power cables, characterized by, The method comprises the following steps: obtaining the elastic modulus and physical characteristic parameters of the glass fiber yarn, and assigning initial tension data of the weaving yarn according to the elastic modulus and the physical characteristic parameters; the physical characteristic parameters include the number of yarns and the number of strands; setting the operating parameters of the loom according to the initial tension data, and obtaining real-time tension data of the yarns; calculating the tension uniformity coefficient of the weaving area according to the real-time tension data of the yarns, and predicting the yarn breakage rate according to the elastic modulus and the tension uniformity coefficient; if the predicted value of the yarn breakage rate exceeds the yarn breakage rate threshold, adjusting the initial tension data to obtain first tension data; updating the operating parameters of the loom according to the first tension data, and obtaining the flatness of the weaving area, if the flatness of the weaving area is lower than the target flatness, adjusting the first tension data to obtain second tension data; manufacturing the power cable glass fiber cloth according to the second tension data; wherein assigning the initial tension data of the weaving yarn according to the elastic modulus and the physical characteristic parameters comprises: determining the equivalent diameter of the yarn according to the number of yarns and the number of strands; determining the reference tension value according to the equivalent diameter and the elastic modulus; constructing a tension distribution function along the length direction of the yarn according to the reference tension value, and assigning the initial tension data according to the tension distribution function; the tension distribution function is: ； F(x) represents the initial tension value of the yarn at a distance x from the reference position; x represents the distance of the current position of the yarn relative to the reference position; L represents the total path length of the yarn; represents the tension gradient coefficient, with a value of ± (0.1-0.3), a positive value indicating that the tension increases from the back rest to the fell, and a negative value indicating that the tension decreases from the back rest to the fell; F0 represents the reference tension value.

2. The method of manufacturing a glass fiber cloth for power cables according to claim 1, characterized by, calculating the tension uniformity coefficient of the weaving area according to the real-time tension data of the yarns, and predicting the yarn breakage rate according to the elastic modulus and the tension uniformity coefficient, comprising: a plurality of tension detection points are arranged in the weaving area, and real-time tension values of each tension detection point are obtained; a yarn breakage rate prediction model is constructed, the real-time tension values and the elastic modulus are input into the yarn breakage rate prediction model, and a yarn breakage rate prediction value is obtained; wherein the yarn breakage rate prediction model comprises obtaining the yarn breakage rate prediction value by the following way: calculating the average tension and standard deviation of all tension detection points; calculating the tension uniformity coefficient according to the average tension and the standard deviation; determining the yarn breakage rate prediction value according to the tension uniformity coefficient and the elastic modulus.

3. The method of manufacturing a glass fiber cloth for power cables according to claim 2, characterized by, the yarn breakage rate prediction model is: ； ； K represents the coefficient of uniformity of tension; represents the standard deviation of tension; represents the average tension; P represents the prediction value of the broken-end rate; Fmax represents the maximum tension value monitored in the weaving area; E represents the elastic modulus of the yarn; and A represents the cross-sectional area of the yarn; represents the yarn fatigue coefficient, and the value is 0.8-1.

2.

4. The method of manufacturing a glass fiber cloth for power cables according to claim 1, characterized by, adjusting the initial tension data to obtain first tension data, including adjusting the initial tension data of the warp yarn to obtain the first tension data of the warp yarn; adjusting the initial tension data of the warp yarn comprises: calculating the deviation of the warp yarn breakage rate prediction value and the yarn breakage rate threshold to obtain the warp yarn breakage rate deviation value; calculating the ratio of the warp yarn breakage rate deviation value and the yarn breakage rate threshold to obtain the warp yarn breakage rate deviation ratio; calculating the ratio of the elastic modulus and the reference elastic modulus to obtain the modulus correction factor; decreasing the initial tension according to the modulus correction factor and the warp yarn breakage rate deviation ratio to obtain the first tension of the warp yarn; wherein the adjustment mode of the warp yarn is: ； F1 represents the first tension of the warp yarn; Fa represents the initial tension of the warp yarn; Eref represents the reference modulus of elasticity; E represents the modulus of elasticity of the warp yarn; ΔP represents the deviation value of the warp yarn breakage rate; P th represents the breakage rate threshold value.

5. The method of manufacturing a glass fiber cloth for power cables according to claim 1 or 4, characterized in that, adjusting the initial tension data to obtain first tension data, further comprising adjusting the initial tension data of the weft yarn to obtain the first tension data of the weft yarn; adjusting the initial tension data of the weft yarn comprises: ; F2 represents a first tension of weft yarns; Fa represents an initial tension of weft yarns; ΔF represents a tension adjustment amount; wherein the tension adjustment amount is related to weft yarn breakage deviation value, weft insertion speed and weft yarn flight path length.

6. The method of manufacturing a glass fiber cloth for power cables according to claim 1, characterized by, adjusting the first tension data to obtain second tension data, comprising: obtaining a fabric surface image of the weaving area, and analyzing the fabric surface image to obtain a defect type; performing corresponding tension adjustment according to the defect type: if it is a longitudinal stripe defect, increasing the tension of the warp yarns in the contact area with the guide member and decreasing the tension of the adjacent area; if it is a horizontal weft bar defect, decreasing the weft yarn tension and reducing the weft insertion speed.

7. The method of manufacturing a glass fiber cloth for power cables according to claim 6, characterized by, analyzing the fabric surface image to obtain a defect type, comprising: performing directional Gabor filtering on the fabric surface image, and extracting warp direction characteristic components and weft direction characteristic components; calculating the length-width ratio of the stripe area according to the warp direction characteristic components and the weft direction characteristic components: if the length-width ratio is greater than 3:1, it is determined to be a longitudinal stripe defect; if the length-width ratio is less than 1:3, it is determined to be a horizontal weft bar defect.

8. A power cable comprising an insulation shield, characterized in that The insulating shielding layer is manufactured based on the method for manufacturing a glass fiber fabric for power cables according to any one of claims 1-7.

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