Continuous basalt fiber wire drawing forming intelligent control method and system

Abstract

The invention relates to the technical field of intelligent control, in particular to an intelligent control method and system for continuous basalt fiber drawing forming. The method comprises the following steps: acquiring temperature measurement point data including temperature data and flow data; temperature control, energy supply strategy adjustment and bushing partition heating parameter adjustment are conducted according to the collected temperature measurement point data, and a fuzzy self-tuning algorithm is adopted to conduct linkage adjustment on the temperature of an uptake, the temperature of an access and the temperature before bushing; dynamically adjusting an energy supply strategy based on the energy supply sequence; and the partition heating parameters of the bushing are adjusted by using a PID control algorithm. According to the invention, a longitudinal partition heating mode and accurate temperature control are adopted for the bushing, and a strategy of dynamically adjusting the wire drawing speed and the partition temperature according to the average value of the wire diameter is combined, so that the wire diameter of basalt fibers drawn by the whole bushing can be effectively ensured to be more uniform.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to an intelligent control method and system for continuous basalt fiber drawing. Background Art

[0002] As a high-performance inorganic non-metallic material, continuous basalt fiber has shown great application potential in many fields in recent years. It is made of natural basalt as raw material, through high-temperature melting, wire drawing and other processes, and has a series of excellent characteristics such as high strength, high modulus, high temperature resistance, chemical corrosion resistance, good insulation and low density. In the aerospace field, it can be used to manufacture structural components of aircraft, effectively reducing weight while improving structural strength and reliability; in the construction industry, it can be used as a reinforcing material for concrete, composite materials, etc., significantly improving the performance of building materials and improving the earthquake and wind resistance of buildings; in the field of environmental protection, it can be used for filter materials, adsorption materials, etc., to help control environmental pollution.

[0003] However, in the production process of continuous basalt fiber, the wire drawing and forming process faces many technical challenges. Due to the unique physical and chemical properties and forming characteristics of basalt fiber glass, it is quite challenging to achieve stable and efficient production. For example, how to ensure that a continuous, stable and uniform high-temperature basalt melt can be obtained at the leak plate under different production conditions is the key to ensuring the uniformity of the fiber diameter. Traditional temperature control methods are difficult to accurately respond to complex and changeable production conditions. Fluctuations in melt temperature can easily lead to uneven fiber diameters, affecting product quality and performance.

[0004] In addition, the energy supply method and channel structure design of the glass channel also have an important impact on production efficiency and energy consumption. Unreasonable energy input combination and channel structure will not only increase energy costs, but may also affect the quality and stability of the melt. At the same time, when facing the production switch of products of different specifications, how to quickly and accurately adjust the production parameters to achieve efficient production change is also an urgent problem to be solved.

[0005] In summary, in order to give full play to the performance advantages of continuous basalt fiber and meet the growing market demand, it is urgent to develop an innovative continuous basalt fiber drawing forming intelligent control system and technical solution. By optimizing key links such as temperature control, energy supply, and plate parameter adjustment, it can effectively improve production efficiency, reduce production costs, improve product quality, and promote the high-quality development of the continuous basalt fiber industry. Summary of the invention

[0006] In order to solve the above-mentioned problems, the present invention provides an intelligent control method and system for continuous basalt fiber drawing.

[0007] In the first aspect, the present invention provides an intelligent control method for continuous basalt fiber drawing, which adopts the following technical solution: An intelligent control method for continuous basalt fiber drawing and forming, comprising: Obtain temperature measurement point data, including temperature data and flow data; According to the collected data of temperature measurement points, temperature control, energy supply strategy adjustment and leakage plate partition heating parameter adjustment are carried out respectively. Among them, the fuzzy self-tuning algorithm is used to jointly adjust the rising channel temperature, the passage temperature and the temperature in front of the leakage plate; the energy supply strategy is dynamically adjusted based on the energy supply sequence; and the leakage plate partition heating parameters are adjusted using the PID control algorithm.

[0008] Furthermore, the fuzzy self-tuning algorithm is used to linkage-adjust the riser temperature, passage temperature and temperature before the leak plate, including respectively determining the flow deviation, flow deviation change rate, temperature deviation and temperature deviation change rate according to the temperature data and flow data, and converting the determined data into fuzzy linguistic variables after fuzzy processing, and determining the degree of membership in each fuzzy subset based on the fuzzy linguistic variables to obtain the fuzzy processing result.

[0009] Furthermore, the use of a fuzzy self-tuning algorithm to linkage-adjust the riser temperature, the passage temperature and the temperature before the leak plate also includes constructing a complete fuzzy rule base according to fuzzy control rules, performing fuzzy reasoning in the fuzzy rule base according to the fuzzification processing results, obtaining fuzzy outputs of the adjustment amounts of the set values ​​of the riser temperature, the passage temperature and the temperature before the leak plate, and using a defuzzification method to convert the fuzzy outputs into precise numerical values, i.e., the temperature values ​​that actually need to be adjusted.

[0010] Furthermore, the energy replenishment strategy is dynamically adjusted based on the energy replenishment sequence, including starting the energy replenishment strategy according to the temperature data and the flow data when the temperature is lower than the set value and the flow data remains stable, wherein the heating power of the internal motor and the carbon silicon rod is increased until the temperature data gradually approaches the set value, and at the same time, in the process of the temperature data gradually approaching the set value, the heating power of the internal electrode and the carbon silicon rod is dynamically adjusted according to the rate of temperature change and the deviation from the set value to avoid temperature overshoot, wherein a three-stage power adjustment scheme is adopted to achieve temperature stability.

[0011] Furthermore, the PID control algorithm is used to adjust the heating parameters of the leak plate partitions, including setting the leak plate to a longitudinal 5-partition structure, and setting an initial target dimension and heating power range for each partition, adjusting the heating power of each partition by detecting the temperature of the partition, sampling and detecting the basalt fiber diameter at a set interval, and dynamically adjusting the drawing speed and partition temperature according to the change in the average value of the basalt fiber diameter.

[0012] In a second aspect, an intelligent control system for continuous basalt fiber drawing and forming includes: an upper management layer, an intermediate control layer and a lower execution layer, wherein the upper management layer includes an expert system, and the expert system performs algorithm control, strategy adjustment and parameter adjustment through an expert system decision center.

[0013] Furthermore, the upper management layer also includes a database management module and a human-computer interaction interface, wherein the database management module is used to store and manage all data in the production process, including real-time data of temperature, flow, pressure and wire diameter, as well as historical production data and equipment operation records.

[0014] Furthermore, the intermediate control layer includes a fuzzy self-tuning PID controller, an energy management unit and a leak plate partition temperature controller, wherein the fuzzy self-tuning PID controller adjusts the parameters of the PID controller in real time according to the algorithm results of the expert system decision center, and the energy management unit coordinates the heating power distribution of the internal electrodes and the silicon carbon rods according to the instructions of the expert system and actual production needs, follows the energy supply sequence of giving priority to the internal electrodes and then the upper space, and ensures that the respective energy output is not less than 15% of the total energy, and the leak plate partition temperature controller adjusts the heating power of each partition according to the algorithm results.

[0015] Furthermore, the lower execution layer includes a temperature sensor, a flow sensor, a heating device and a wire drawing device, wherein the temperature sensors are arranged at key positions of the ascending path, the passage, in front of the leak plate and in each partition of the leak plate, and are responsible for collecting temperature data in real time; the flow sensor is installed at the raw material conveying pipeline to monitor the flow of the raw materials in real time.

[0016] Furthermore, the heating device includes internal electrodes and silicon carbon rods in the glass passage, and heating elements in each partition of the leak plate; the wire drawing device draws the high-temperature basalt melt flowing out of the leak plate into fiber filaments according to a set wire drawing speed.

[0017] In the third aspect, a continuous basalt fiber drawing and forming intelligent control system includes a basalt melt channel, a heating device, a temperature measuring device and a leak plate device, wherein the basalt melt channel includes an ascending path, a passage channel and a channel in front of the leak plate, the heating device includes electrodes and carbon silicon rods, the leak plate device includes a leak plate, a leak plate brick is arranged between the leak plate and the channel in front of the leak plate, a plurality of leak holes are arranged on the leak plate, the temperature measuring device includes an ascending path temperature measuring point, a passage temperature measuring point and a temperature measuring point in front of the leak plate, the temperature measuring device adopts an R-type thermocouple, and the R-type thermocouple is respectively provided with an upper temperature measuring point, a middle temperature measuring point and a lower temperature measuring point, so as to realize 9-point temperature measurement together.

[0018] Furthermore, the electrode is arranged inside the basalt melt, and the carbon silicon rod is arranged above the basalt melt, wherein the carbon silicon rod adopts a 5-stage heating structure to heat both sides of the basalt melt; three-point wiring terminals are respectively arranged on both sides of the leak plate to prevent the basalt melt on both sides of the leak plate from cooling.

[0019] In summary, the present invention has the following beneficial technical effects: The present invention adopts a longitudinal partition heating method and precise temperature control through the bushing, combined with a strategy of dynamically adjusting the drawing speed and partition temperature according to the average value of the wire diameter, which can effectively ensure that the basalt fiber wire diameter drawn by the entire bushing is more uniform. In actual production, the wire diameter deviation can be controlled within a very small range. Compared with traditional processes, the standard deviation of the wire diameter is greatly reduced, thereby improving the quality stability and performance consistency of fiber products, and meeting the strict requirements of high-end application fields for material performance.

[0020] The fuzzy self-tuning algorithm is used to adjust the temperature of the riser, the passage temperature and the temperature before the leak plate in a linked manner, so that the leak plate can obtain continuous, stable and uniform high-temperature basalt melt. The stable temperature environment reduces the internal defects of the fiber caused by temperature fluctuations, such as bubbles and cracks, and improves the intrinsic quality of the fiber, thereby improving the strength and reliability of the fiber products.

[0021] Through real-time monitoring and precise control of parameters such as temperature and flow, combined with advanced algorithms and control strategies, the entire production process can be managed in a refined manner. From the melting of raw materials to the drawing and forming of fibers, the parameters of each link can be precisely controlled to ensure that the production process is always in the best state, further improving the level of intelligent production and the stability of product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 Schematic diagram of an intelligent control method for continuous basalt fiber drawing and forming according to Example 1 of the present invention; Figure 2 It is a schematic diagram of an intelligent control system for continuous basalt fiber drawing and forming according to Example 2 of the present invention.

[0023] Figure 3 It is a cross-sectional view of an intelligent control system for continuous basalt fiber drawing and forming according to Example 2 of the present invention.

[0024] Figure 4 It is a schematic diagram of the leak plate structure of Example 2 of the present invention.

[0025] Figure 5 This is another schematic diagram of an intelligent control system for continuous basalt fiber drawing and forming according to Example 2 of the present invention.

[0026] Among them, 1. carbon silicon rod; 2. electrode; 3. leak plate; 4. leak plate brick; 5. rising channel temperature measuring point; 6. passage temperature measuring point; 7. temperature measuring point in front of the leak plate; 8. heating section; 9. basalt melt; 10. chamfer structure; 11. first terminal; 12. second terminal; 13. third terminal. DETAILED DESCRIPTION

[0027] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0028] Example 1 Reference Figure 1 , a continuous basalt fiber drawing forming intelligent control method of this embodiment includes: Obtain temperature measurement point data, including temperature data and flow data; According to the collected data of temperature measurement points, temperature control, energy supply strategy adjustment and leakage plate partition heating parameter adjustment are carried out respectively. Among them, the fuzzy self-tuning algorithm is used to jointly adjust the rising channel temperature, the passage temperature and the temperature in front of the leakage plate; the energy supply strategy is dynamically adjusted based on the energy supply sequence; and the leakage plate partition heating parameters are adjusted using the PID control algorithm.

[0029] Specifically, First, the fuzzy self-tuning algorithm of this embodiment is based on traditional PID control. Through fuzzy logic reasoning, the parameters of the PID controller (proportional coefficient Kp, integral coefficient Ki, differential coefficient Kd) are adjusted in real time according to the current operating status of the system (such as flow rate, temperature deviation, etc.) to adapt to the control requirements under different working conditions and improve the control performance and stability of the system.

[0030] Input variable determination Flow deviation (E_flow): The difference between the actual measured flow value and the set flow value. For example, if the set flow is 100L / min and the current actual flow is 105L / min, the flow deviation E_flow = 105 - 100 = 5L / min.

[0031] Flow deviation change rate (EC_flow): The rate at which flow deviation changes over time. The flow deviation change rate is calculated by continuously measuring the flow deviation values ​​at multiple time points. Assuming that at two adjacent time points t1 and t2 (with a time interval of 1s), the flow deviations are E_flow1 = 5L / min and E_flow2 = 7L / min, respectively, then the flow deviation change rate EC_flow = (E_flow2 - E_flow1) / (t2 - t1) = (7 - 5) / 1 = 2L / (min・s).

[0032] Temperature deviation (taking the temperature before the leak plate as an example, E_temp): The difference between the actual measured temperature before the leak plate and the set temperature. For example, if the set temperature before the leak plate is 1500℃ and the actual measured value is 1505℃, the temperature deviation E_temp = 1505 - 1500 = 5℃.

[0033] Temperature deviation change rate (taking the temperature before the leak plate as an example, EC_temp): The rate at which the temperature deviation before the leak plate changes over time. Similar to the calculation method of the flow deviation change rate, it is calculated by continuously measuring the temperature deviation values ​​at multiple time points.

[0034] Fuzzy processing The above input variables are fuzzified and converted into fuzzy linguistic variables. For example, for flow deviation (E_flow), it can be divided into fuzzy subsets such as negative large (NB), negative medium (NM), negative small (NS), zero (Z), positive small (PS), positive medium (PM), and positive large (PB). The domain of flow deviation is set to [-10, 10] L / min. When E_flow = 5L / min, according to the pre-set membership function, it may have a higher membership on the "positive medium (PM)" fuzzy subset.

[0035] Similarly, similar fuzzification processing is performed on the flow deviation change rate (EC_flow), temperature deviation (E_temp) and temperature deviation change rate (EC_temp) to determine their membership in their respective fuzzy subsets.

[0036] Fuzzy rule making Based on process experience and expertise, fuzzy control rules are developed. Here are some example rules: If the flow deviation (E_flow) is positive large (PB) and the flow deviation change rate (EC_flow) is positive small (PS), and the temperature deviation before the leak plate (E_temp) is zero (Z) and the temperature deviation change rate (EC_temp) is zero (Z), then increase the rising channel temperature setting value appropriately, increase the passage temperature setting value significantly, and increase the temperature setting value before the leak plate slightly.

[0037] If the flow deviation (E_flow) is negative small (NS) and the flow deviation change rate (EC_flow) is negative large (NB), and the temperature deviation before the leak plate (E_temp) is positive small (PS) and the temperature deviation change rate (EC_temp) is positive large (PB), then appropriately reduce the rising channel temperature setting value, significantly reduce the passage temperature setting value, and slightly reduce the temperature setting value before the leak plate.

[0038] A complete fuzzy rule base is constructed through a large number of similar rules.

[0039] Fuzzy Reasoning and Defuzzification According to the fuzzification results of the input variables, fuzzy reasoning is performed in the fuzzy rule base to obtain the fuzzy output of the adjustment value of the riser temperature, the passage temperature and the temperature before the leak plate. Then, a suitable defuzzification method (such as the centroid method) is used to convert the fuzzy output into an accurate value, that is, the actual temperature value that needs to be adjusted.

[0040] This embodiment uses the centroid method for defuzzification, where the fuzzy output results for the temperature adjustment amount of the ascending track are: the membership degree at the discrete point of "increase by 2°C" (\mu(2)=0.3), the membership degree at the discrete point of "increase by 3°C" (\mu(3)=0.6), and the membership degree at the discrete point of "increase by 4°C" (\mu(4)=0.1). The domain here is the set of possible temperature adjustment values, that is, ({2, 3, 4}) (unit: °C).

[0041] Calculate the molecular part According to the centroid method formula, first calculate the numerator (\sum_{i = 1}^{n}x_i\mu(x_i)): [2\times0.3 + 3\times0.6 + 4\times0.1] [=0.6 + 1.8 + 0.4] [=2.8] Calculate the denominator Then calculate the denominator (\sum_{i = 1}^{n}\mu(x_i)): [0.3 + 0.6 + 0.1 = 1] Get the exact adjustment value Finally, divide the numerator by the denominator to get the exact adjustment for the ramp temperature: [x^*=\frac{2.8}{1}=2.8℃] That is, after defuzzification according to the centroid method, the ascending track temperature needs to be increased (2.8°C).

[0042] The calculation of the adjustment values ​​of the passage temperature and the temperature before the leak plate is also carried out in a similar manner. For the passage temperature adjustment, it is assumed that the fuzzy output result is the membership degree on "increase by 4°C" (\mu(4)=0.2), the membership degree on "increase by 5°C" (\mu(5)=0.7), and the membership degree on "increase by 6°C" (\mu(6)=0.1).

[0043] Calculate the numerator: [4\times0.2 + 5\times0.7 + 6\times0.1] [=0.8 + 3.5 + 0.6] [=4.9] Calculate the denominator: [0.2 + 0.7 + 0.1 = 1] Then the precise adjustment value of the channel temperature is: [x^=\frac{4.9}{1}=4.9℃] Similarly, for the temperature adjustment before the leak plate, assume that the fuzzy output results are membership on "increase by 1°C" (\mu(1)=0.4), membership on "increase by 2°C" (\mu(2)=0.5), and membership on "increase by 3°C" (\mu(3)=0.1).

[0044] Calculate the numerator: [1\times0.4 + 2\times0.5 + 3\times0.1] [=0.4 + 1 + 0.3] [=1.7] Calculate the denominator: [0.4 + 0.5 + 0.1 = 1] Then the precise adjustment value of the temperature before the leak plate is: [x^=\frac{1.7}{1}=1.7℃].

[0045] Real-time adjustment implementation: The control system adjusts the power of the heating device in the ascending path, the passage and the front of the leak plate in real time according to the calculated temperature adjustment value. For example, by adjusting the current or voltage of the heating element of the ascending path, its temperature can be increased by 3°C; by adjusting the heating power distribution of the silicon carbon rods and electrodes in the passage, the passage temperature can be increased by 5°C; by changing the working state of the heating device in front of the leak plate, the temperature in front of the leak plate can be increased by 2°C.

[0046] Continuously monitor the changes in parameters such as flow rate and temperature, and repeat the above fuzzy self-tuning process to achieve dynamic and precise linkage adjustment of the riser temperature, passage temperature and temperature in front of the leak plate, ensuring that under different working conditions, the leak plate can obtain a stable high-temperature basalt melt temperature that meets the process requirements.

[0047] Secondly, the energy replenishment strategy of this embodiment is adjusted. Initial setup and monitoring The initial conditions for energy replenishment are set as follows: the total energy output of the internal electrodes and silicon carbon rods (upper space heating) is 100kW, and the lower limit of each is 15% of the total energy, that is, the minimum output of the internal electrodes is 15kW, and the minimum output of the silicon carbon rods is 15kW.

[0048] Real-time monitoring of the temperature and flow rate of the basalt melt and the actual energy consumption of each heating device. Assume that at a certain moment, the temperature of the basalt melt is lower than the set value and the flow rate remains stable.

[0049] Energy replenishment strategy activated Since the temperature is low, it is necessary to increase the energy input. First, check the energy output of the internal electrode. If the current internal electrode output is 20kW, which does not meet the lower limit requirement of 15kW, and there is still room for improvement, then give priority to increasing the energy output of the internal electrode, for example, increasing its power to 30kW, to quickly increase the internal temperature of the melt.

[0050] Continuously monitor the temperature changes. If after a period of time, the temperature rises slowly and the internal electrode output has reached the lower limit of 15kW, but still does not meet the temperature increase requirements, then start the silicon carbon rod heating for supplementation.

[0051] Gradually increase the heating power of the silicon carbon rod, starting from the initial 15kW, and increase by 5kW each time, and observe the temperature change. When the power of the silicon carbon rod is increased to 25kW, it is found that the melt temperature begins to rise at a suitable speed and gradually approaches the set value.

[0052] Dynamic adjustment and stabilization phase In the process of the temperature approaching the set value, the energy output of the internal electrode and silicon carbon rod is dynamically adjusted according to the rate of temperature change and the deviation from the set value. For example, when the temperature is close to the set value and the rising speed is fast, the power of the internal electrode and silicon carbon rod is appropriately reduced to avoid excessive temperature. Among them, the temperature target and the initial power are set. Assuming that the target temperature of the basalt melt is 1500℃, the initial total power of the internal electrode and silicon carbon rod is 80kW, of which the internal electrode power is 30kW and the silicon carbon rod power is 50kW.

[0053] Real-time temperature monitoring, the current temperature is 1480℃, which is 20℃ away from the target temperature.

[0054] Temperature change rate and deviation analysis The temperature data was recorded every 1 minute. After a period of monitoring, it was found that the temperature rose from 1460°C to 1480°C in the past 5 minutes, that is, the temperature change rate was 4°C / minute.

[0055] According to the temperature deviation and the rate of change, determine whether the current heating power is appropriate. At this time, the temperature deviation is large, but the rate of change is fast. If the current heating power is maintained, the temperature may exceed the target value.

[0056] First power adjustment It was decided to appropriately reduce the heating power. Considering that the internal electrode has a greater impact on the temperature uniformity inside the melt, the power of the silicon carbon rod was adjusted first. The power of the silicon carbon rod was reduced from 50kW to 45kW, and the power of the internal electrode remained unchanged for the time being.

[0057] The temperature change was continuously monitored. After 10 minutes, the temperature rose to 1490°C. At this time, the temperature deviation was reduced to 10°C and the temperature change rate was reduced to 1°C / minute.

[0058] Second power adjustment As the temperature change rate further decreases and is closer to the target value, the power needs to be adjusted more finely. At this time, the internal electrode power is reduced by 5kW to 25kW, and the silicon carbon rod power is reduced by another 3kW to 42kW.

[0059] The temperature was continuously observed. After 5 minutes, the temperature reached 1495°C, the temperature deviation was only 5°C, and the rate of change was very slow.

[0060] The third power adjustment and stabilization phase In order to make the temperature reach the target value accurately and keep it stable, the power is fine-tuned again. The power of the silicon carbon rod is reduced by 2kW to 40kW, and the power of the internal electrode is kept at 25kW.

[0061] After a period of monitoring, the temperature stabilized at around 1500°C. At this time, the process of dynamically adjusting the heating power according to temperature changes was completed, ensuring that when approaching the target temperature, it can quickly reach the set value and avoid temperature overshoot, thereby ensuring the stability of the production process and product quality.

[0062] When the melt temperature is stable within the set value range, maintain the current energy replenishment combination, that is, the internal electrode output is 30kW and the silicon carbon rod output is 25kW, while continuing to monitor in real time so as to adjust the energy replenishment strategy in time when the working conditions change.

[0063] Third aspect, the embodiment of the control of the parameters of the leakage plate Leakage plate structure and initial parameter setting The bushing used is a 5-partition structure in the longitudinal direction, and each partition is equipped with an independent high-precision temperature sensor and an adjustable heating device. The bushing is designed to produce basalt fibers with a wire diameter of 10μm.

[0064] The target temperature of each zone is initially set to 1520℃, and the heating power range is 0 - 60kW. Based on past experience, the heating power of each zone is initially set to: 35kW for zone 1, 38kW for zone 2, 40kW for zone 3, 38kW for zone 4, and 35kW for zone 5. At the same time, the initial drawing speed is set to 5m / min.

[0065] Temperature monitoring and adjustment The temperature of each zone was monitored in real time. After a period of time after the start of production, it was found that the temperature of zone 3 was 1510°C, 10°C lower than the target value. Through analysis, it was judged that the heat dissipation in this area was faster or the efficiency of the heating element was slightly reduced.

[0066] In order to make the temperature of zone 3 reach the target value, the heating power of this area was gradually increased from 40kW to 45kW. After 15 minutes of monitoring, the temperature rose to 1518℃, close to the target value. The heating power was fine-tuned to 46kW, and the temperature stabilized at 1520℃.

[0067] Wire drawing speed and wire diameter monitoring During the continuous production process, the diameter of the drawn basalt fiber was sampled and tested every 10 minutes. After one hour of production, the test found that the fiber diameter had slightly thickened, with an average value of 10.5μm.

[0068] After analyzing the cause, it was initially determined that the wire drawing speed was too slow, resulting in insufficient stretching of the melt at the exit of the bushing. In order to adjust the wire diameter, the wire drawing speed was increased from 5m / min to 5.5m / min.

[0069] The wire diameter was continuously monitored and samples were taken for testing again 30 minutes later. The average wire diameter dropped to 10.2 μm, which still did not fully reach the target wire diameter of 10 μm.

[0070] Comprehensive parameter adjustment Considering that both temperature and wire drawing speed have an impact on wire diameter, it was decided to fine-tune the temperature of the leak plate again. The temperature of all partitions was reduced by 2°C, that is, the target temperature of each partition was adjusted to 1518°C. At the same time, the wire drawing speed was further increased to 5.8m / min.

[0071] After a period of production and continuous monitoring, the wire diameter stabilized at about 10μm, meeting production requirements. During this process, the heating power and drawing speed of the bushing were dynamically adjusted based on the feedback of temperature and wire diameter to ensure that the bushing was always in the best working state and produce high-quality basalt fibers with uniform wire diameter.

[0072] Parameter adjustment to cope with emergencies Assume that during the production process, there is a sudden external voltage fluctuation, which causes the overall temperature of the leak board to drop. Real-time monitoring shows that the temperature of each partition has dropped by about 5°C.

[0073] In order to quickly restore the temperature, the heating power of each zone was immediately increased by 10kW. At the same time, the drawing speed was temporarily reduced to 5m / min to avoid poor fiber forming due to low temperature.

[0074] Continuously monitor the temperature and wire diameter. When the temperature returns to a value close to the target value (between 1515℃ - 1520℃), gradually reduce the heating power to an appropriate level, and adjust the wire drawing speed again according to the wire diameter to restore production to a normal and stable state.

[0075] Example 2 This embodiment provides an intelligent control system for continuous basalt fiber drawing, including: 1. Upper management Expert system decision center: This is the core brain of the entire intelligent control system. It integrates a large amount of process knowledge, production experience and advanced algorithm models. By analyzing, mining and learning the massive data generated during the production process, the expert system can formulate the best production strategy. For example, according to different product specification requirements, combined with the current equipment status and raw material characteristics, the best temperature control curve, energy supply plan, wire drawing speed and other key parameters are determined.

[0076] Database management module: responsible for storing and managing all data in the production process, including real-time data such as temperature, flow, pressure, wire diameter, as well as historical production data, equipment operation records, etc. These data not only provide a basis for the expert system's decision-making, but can also be used for production process traceability, quality analysis, and equipment maintenance prediction. Through in-depth mining of historical data, potential production problems and optimization space can be discovered, providing support for continuous improvement of production processes.

[0077] Human-machine interface (HMI): provides an intuitive and convenient operating platform for operators. Operators can use HMI to monitor various parameters in the production process in real time, view equipment operating status, alarm information, etc. At the same time, they can also set parameters, issue production tasks, and configure the system on the HMI. The design of HMI focuses on user experience and uses a graphical interface to display data, allowing operators to quickly understand and grasp the production situation.

[0078] 2. Middle control layer Fuzzy self-tuning PID controller: According to the control instructions issued by the upper management, combined with the real-time collected process variables such as temperature and flow, the fuzzy self-tuning algorithm is used to adjust the parameters of the PID controller in real time. For example, in the face of complex working conditions such as flow fluctuations and temperature changes, the fuzzy self-tuning PID controller can respond quickly and automatically adjust the temperature of the riser, the passage temperature, and the temperature before the leak plate to ensure that the leak plate obtains a stable and satisfactory high-temperature basalt melt temperature.

[0079] Energy management unit: responsible for precise control of energy supply to the glass channel. According to the instructions of the expert system and actual production needs, the energy management unit coordinates the heating power distribution of the internal electrodes and silicon carbon rods, follows the order of energy supply of the internal electrodes first and then the upper space, and ensures that the energy output of each is not less than 15% of the total energy. At the same time, it monitors energy consumption in real time to achieve efficient energy utilization and cost control.

[0080] Partition temperature controller for the plate: In view of the longitudinal partition structure of the plate, the partition temperature controller for the plate controls the temperature of each partition independently and accurately. Through real-time interaction with the temperature sensor, the actual temperature value of each partition is obtained, and the heating power of each partition is adjusted according to the set target temperature using advanced control algorithms. The temperature uniformity of the entire plate is ensured, so as to draw basalt fibers with uniform wire diameter.

[0081] 3. Lower execution layer Temperature sensors: distributed in key locations such as the riser, passage, in front of the leak plate and in each partition of the leak plate, responsible for real-time temperature data collection. These sensors have the characteristics of high precision, high sensitivity and fast response, and can accurately measure the temperature changes of the basalt melt and transmit the data to the controller of the intermediate control layer in a timely manner. Flow sensor: Installed in raw material delivery pipelines and other locations to monitor the flow of raw materials in real time. Flow data is crucial to the control of the entire production process. It is one of the important bases for the fuzzy self-tuning PID controller to adjust temperature parameters and the energy management unit to allocate energy.

[0082] Heating device: including internal electrodes and silicon carbon rods in the glass channel, as well as heating elements in each partition of the bushing. These heating devices accurately adjust the heating power according to the instructions of the intermediate control layer to provide the required heat for the melting and molding of the basalt melt. The heating device has the ability of rapid response and precise control to meet the strict temperature requirements in the production process.

[0083] Wire drawing device: According to the set wire drawing speed, the high-temperature basalt melt flowing out of the leaking plate is drawn into fiber wires. The speed control accuracy of the wire drawing device directly affects the uniformity of the wire diameter of the basalt fiber. Through communication with the intermediate control layer, the wire drawing device can dynamically adjust the wire drawing speed according to the real-time monitoring data of the wire diameter to ensure the production of basalt fibers that meet quality standards.

[0084] Example 3. The present embodiment discloses an intelligent control system for continuous basalt fiber drawing, including a basalt melt channel, a heating device, a temperature measuring device and a leak plate device, wherein the basalt melt channel includes an ascending channel, a passage channel and a leak plate front channel, the heating device includes electrodes and carbon silicon rods, the leak plate device includes a leak plate, a leak plate brick is arranged between the leak plate and the leak plate front channel, and a plurality of leak holes are arranged on the leak plate, the temperature measuring device includes an ascending channel temperature measuring point, a passage temperature measuring point and a leak plate front temperature measuring point, the temperature measuring device adopts an R-type thermocouple, and the R-type thermocouple is respectively provided with an upper temperature measuring point, a middle temperature measuring point and a lower temperature measuring point, so as to realize 9-point temperature measurement together. The electrode is arranged inside the basalt melt, and the carbon silicon rod is arranged above the basalt melt, wherein the carbon silicon rod adopts a 5-stage heating structure to heat both sides of the basalt melt; three-point wiring terminals are respectively arranged on both sides of the leak plate to prevent the basalt melt on both sides of the leak plate from cooling.

[0085] Specifically, like Figure 2 As shown, after the basalt melt enters the ascending channel, it is heated and melted by the electrode, and then passes through the passage in sequence and enters the leak plate for wire drawing and heating and melting. Among them, the ascending channel temperature measuring point 5, the channel temperature measuring point 6, and the temperature measuring point before the leak plate respectively measure the temperature of the basalt melt. Figure 3 As shown, three temperature measuring points are set in the basalt melt 9, wherein each temperature measuring point is provided with three measuring points, namely, a lower measuring point, a middle measuring point and an upper measuring point. When the liquid level of the basalt melt fluctuates, it will affect the thermocouple measurement values ​​at these three points. At the same time, a chamfer structure 10 is also provided, which can effectively avoid the crystallization phenomenon of the basalt melt.

[0086] like Figure 4 The structure of the leak plate 3 is shown, which includes a plurality of leak nozzles 11 arranged on the leak plate. At the same time, three wiring terminals are respectively arranged on both sides of the leak plate 3, namely the first wiring terminal 12, the second wiring terminal 13 and the third wiring terminal 14, which are used to ensure that the two sides of the leak plate are not cooled and solidified during the basalt melt fiber drawing process.

[0087] Figure 5 The figure shows a cross-sectional screenshot of the system, in which the carbon silicon rod 1 adopts a 5-section heating structure, with two heating sections symmetrically arranged in the middle, a non-heating section between the two heating sections, and non-heating sections on both sides of the two heating sections. By setting up the 5-section heating structure, the central position of the basalt melt with a higher temperature is not heated, and only the two sides of the basalt melt are heated by the two heating sections, which can ensure that the basalt melt is heated evenly. At the same time, carbon silicon rod heating and electrode heating are respectively arranged above and inside the basalt melt, which also greatly improves the heating efficiency.

[0088] The above are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent control method for continuous basalt fiber drawing, characterized in that: include: Obtain temperature measurement point data, including temperature data and flow data; According to the collected data of temperature measurement points, temperature control, energy supply strategy adjustment and leakage plate partition heating parameter adjustment are carried out respectively. Among them, the fuzzy self-tuning algorithm is used to jointly adjust the rising channel temperature, the passage temperature and the temperature in front of the leakage plate; the energy supply strategy is dynamically adjusted based on the energy supply sequence; and the leakage plate partition heating parameters are adjusted using the PID control algorithm.

2. The intelligent control method for continuous basalt fiber drawing according to claim 1 is characterized in that: The fuzzy self-tuning algorithm is used to jointly adjust the riser temperature, the passage temperature and the temperature before the leak plate, including determining the flow deviation, the flow deviation change rate, the temperature deviation and the temperature deviation change rate according to the temperature data and the flow data respectively, and converting the determined data into fuzzy linguistic variables after fuzzy processing, and determining the membership degree on the respective fuzzy subsets based on the fuzzy linguistic variables to obtain the fuzzy processing result.

3. The intelligent control method for continuous basalt fiber drawing according to claim 2 is characterized in that: The method of using a fuzzy self-tuning algorithm to jointly adjust the riser temperature, the passage temperature and the temperature before the leak plate also includes constructing a complete fuzzy rule base according to fuzzy control rules, performing fuzzy reasoning in the fuzzy rule base according to the fuzzification processing results, obtaining fuzzy outputs of the adjustment amounts of the set values ​​of the riser temperature, the passage temperature and the temperature before the leak plate, and using a defuzzification method to convert the fuzzy outputs into accurate numerical values, i.e., the temperature values ​​that actually need to be adjusted.

4. The intelligent control method for continuous basalt fiber drawing according to claim 3 is characterized in that: The energy replenishment strategy is dynamically adjusted based on the energy replenishment sequence, including starting the energy replenishment strategy according to temperature data and flow data when the temperature is lower than the set value and the flow data remains stable, wherein the heating power of the internal motor and the carbon silicon rod is increased until the temperature data gradually approaches the set value, and at the same time, in the process of the temperature data gradually approaching the set value, the heating power of the internal electrode and the carbon silicon rod is dynamically adjusted according to the rate of temperature change and the deviation from the set value to avoid temperature overshoot, wherein a three-stage power adjustment scheme is adopted to achieve temperature stability.

5. The intelligent control method for continuous basalt fiber drawing according to claim 4 is characterized in that: The PID control algorithm is used to adjust the partition heating parameters of the leak plate, including setting the leak plate to a longitudinal 5-partition structure, and setting an initial target dimension and heating power range for each partition, adjusting the heating power of each partition by detecting the temperature of the partition, sampling and detecting the basalt fiber diameter at a set interval, and dynamically adjusting the drawing speed and partition temperature according to the change in the average value of the basalt fiber diameter.

6. An intelligent control system for continuous basalt fiber drawing, characterized in that: include: The upper management layer, the middle control layer and the lower execution layer, wherein the upper management layer includes an expert system, and the expert system performs algorithm control, strategy adjustment and parameter adjustment through the expert system decision center; the upper management layer also includes a database management module and a human-computer interaction interface, and the database management module is used to store and manage all data in the production process, including real-time data of temperature, flow, pressure and wire diameter, as well as historical production data and equipment operation records.

7. The intelligent control system for continuous basalt fiber drawing according to claim 6, characterized in that: The intermediate control layer includes a fuzzy self-tuning PID controller, an energy management unit and a leak plate partition temperature controller, wherein the fuzzy self-tuning PID controller adjusts the parameters of the PID controller in real time according to the algorithm results of the expert system decision center, the energy management unit coordinates the heating power distribution of the internal electrodes and the silicon carbon rods according to the instructions of the expert system and the actual production needs, follows the energy supply sequence of giving priority to the internal electrodes and then the upper space, and ensures that the respective energy output is not less than 15% of the total energy, and the leak plate partition temperature controller adjusts the heating power of each partition according to the algorithm results.

8. The intelligent control system for continuous basalt fiber drawing according to claim 7, characterized in that: The lower execution layer includes temperature sensors, flow sensors, heating devices and wire drawing devices, wherein the temperature sensors are arranged at key positions of the ascending path, the passage, in front of the leak plate and in each partition of the leak plate, and are responsible for collecting temperature data in real time; the flow sensors are installed at the raw material conveying pipeline to monitor the flow of raw materials in real time.

9. An intelligent control system for continuous basalt fiber drawing, characterized in that: It includes a basalt melt channel, a heating device, a temperature measuring device and a leak plate device, wherein the basalt melt channel includes an ascending channel, a passage channel and a channel in front of the leak plate, the heating device includes electrodes and carbon silicon rods, the leak plate device includes a leak plate, a leak plate brick is arranged between the leak plate and the channel in front of the leak plate, a plurality of leak holes are arranged on the leak plate, the temperature measuring device includes an ascending channel temperature measuring point, a passage temperature measuring point and a temperature measuring point in front of the leak plate, the temperature measuring device adopts an R-type thermocouple, and the R-type thermocouple is respectively provided with an upper temperature measuring point, a middle temperature measuring point and a lower temperature measuring point, so as to realize 9-point temperature measurement together.

10. The intelligent control system for continuous basalt fiber drawing according to claim 9, characterized in that: The electrodes are arranged inside the basalt melt, and the carbon silicon rods are arranged above the basalt melt, wherein the carbon silicon rods adopt a 5-stage heating structure to heat both sides of the basalt melt; three-point wiring terminals are respectively arranged on both sides of the leak plate to prevent the basalt melt on both sides of the leak plate from cooling.

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