Fiber forming process window dynamic adjustment control method for coping with fluctuation of coal-based solid waste components

Abstract

The invention relates to a fiber forming process window dynamic adjustment control method for coping with coal-based solid waste component fluctuation. The method comprises the following steps: capturing raw material components, melt viscosity, temperature, fiber diameter and equipment operation state in real time; on the basis of a component-process coupling model, sensed multi-dimensional data are input, operation is carried out according to component intervals and working conditions, and adaptation rules are quantified; in the actual machining process, when the melt viscosity exceeds 1500 Pas, the heating power of the electric melting furnace is increased through an instruction, and if the melt viscosity does not reach the standard in 5 min, the rotating speed of the centrifugal machine is increased in a linkage mode; when the diameter of the fiber exceeds 20 microns, firstly adjusting the atmospheric flow air pressure, and then finely adjusting the temperature of the electric melting furnace; the finished product detection unit collects density, strength and fiber diameter data in real time.

Description

Technical Field

[0001] This invention relates to the field of fiber forming technology from coal-based solid waste, and more particularly to a method for dynamically adjusting and controlling the fiber forming process window to cope with fluctuations in the composition of coal-based solid waste. Background Technology

[0002] my country's annual industrial solid waste production exceeds 2 billion tons, of which coal-based solid waste (power plant slag, fly ash, etc.) accounts for over 50%. Its high-value utilization is a core requirement under the "dual-carbon" strategy. Of the over 1 billion tons of coal-based solid waste emitted annually, only 30% is recycled. Fiber fiber utilization, due to its high added value, has become a key development path. The sources of coal-based solid waste are dispersed, with significant differences in composition between different power plants and coal seams. This leads to drastic fluctuations in key components (SiO2, Al2O3, CaO, Fe2O3), with CaO content fluctuating by ±5% and Fe2O3 content by ±3%, directly resulting in insufficient rigidity in the fiber fiber processing window.

[0003] Existing fiber-forming technologies are mostly based on fixed process parameters designed for single coal types, which cannot adapt to dynamic changes in composition. These technologies lead to frequent shutdowns of production lines due to poor melt flowability and high fiber breakage rates, severely restricting the large-scale promotion of solid waste fiber forming. Summary of the Invention

[0004] In response to the aforementioned technical problems, a method for dynamically adjusting and controlling the fiber forming process window to address fluctuations in the composition of coal-based solid waste is provided.

[0005] The technical means employed in this invention are as follows: A method for dynamically adjusting and controlling the fiber forming process window to cope with fluctuations in the composition of coal-based solid waste includes the following steps: S1: Detection units are deployed at the mixing silo outlet, electric melting furnace flow channel, centrifuge inlet, and fiber collection channel to capture raw material composition, melt viscosity, temperature, fiber diameter, and equipment operating status in real time; data with compositional mutations exceeding ±2% are directly replaced with the average value of similar operating conditions; deviations in batching ratios exceeding ±2% are corrected by adjusting the operating frequency of the feeding equipment; and abnormal melt viscosity data are cross-validated with the temperature detection unit to ensure that the perceived data matches the actual production situation. S2: Based on the composition-process coupling model, it inputs multi-dimensional data from the sensor, performs calculations according to the composition range and working conditions, quantifies the adaptation rules, and increases the heating power of the electric furnace by 5% for every 1% increase in CaO, increases the airflow fan pressure by 0.03MPa for every 1% increase in Fe2O3, and increases the centrifuge speed by 50r / min for every 0.2 decrease in the SiO2 / Al2O3 ratio. It outputs the baseline commands for electric furnace power, centrifuge speed, airflow pressure, and ingredient ratio. S3: In actual processing, the melt viscosity exceeds 1500 Pa. When the time is s, first increase the heating power of the electric melting furnace through the command. If the target is not met in 5 minutes, then increase the speed of the centrifuge in conjunction with the command. When the fiber diameter exceeds 20μm, first increase the airflow pressure, and then fine-tune the temperature of the electric melting furnace. S4: The finished product testing unit collects density, strength, and fiber diameter data in real time. If the strength is less than 1.5 MPa, the curing oven temperature and the viscosity control range of the electric melting furnace are adjusted retrospectively. The composition, operation, and quality correlation data are added to the database daily, the coupling model is retrained, and the operation thresholds for different composition ranges are updated to adapt to subsequent production fluctuations.

[0006] Furthermore, the composition detection unit is positioned directly opposite the center of the raw material conveying coal flow to avoid material obstruction; the viscosity detection unit is inserted at an angle into the melt flow channel to avoid dead corners in the flow channel; and the fiber diameter detection unit is deployed in the horizontal section at the outlet of the airflow drawing channel to reduce airflow interference.

[0007] Furthermore, in step S2, each component range is trained independently as a sub-model. During computation, historical operation data of the same component fluctuation range are called first to ensure that the output command is directly adapted to the current raw material characteristics without additional debugging.

[0008] Furthermore, in step S3, the dynamic adjustment of operation priorities adapts to the needs of continuous production. When the melt viscosity is abnormal, the electric melting furnace is adjusted first; when the fiber morphology is abnormal, the centrifuge and airflow valve are adjusted first; when the batching ratio is abnormal, the feeding equipment is adjusted slowly. All operation instructions are issued at the process-permitted rate to prevent equipment impact.

[0009] Furthermore, when the raw material composition suddenly increases by more than ±8%, an emergency command is immediately triggered to open the electric valve of the heat storage tank to release 30% of the stable melt to buffer the impact. At the same time, the proportion of bauxite slag additives is increased, the high composition fluctuation adaptation process is called, the electric melting furnace power is increased to the upper limit, the centrifuge speed is increased to 2300 r / min, and the airflow pressure is adjusted to 0.7 MPa. After the composition fluctuation is ≤ ±5%, it will transition to normal adjustment. During this process, the operation instructions for the heat storage tank and the electric melting furnace are issued simultaneously, and the addition of auxiliary materials and the detection of components are linked in real time.

[0010] Compared with existing technologies, this invention has the following advantages: By deeply coupling control logic with production conditions, this invention solves the problem of unstable fiber-forming processes caused by fluctuations in the composition of coal-based solid waste, achieving continuous and efficient production. This invention can process coal-based solid waste with CaO content of 5%-15% and Fe2O3 content of 2%-8%, with a wide adaptability range for composition fluctuations, high solid waste utilization rate, and expanded adaptability to various types of coal-based solid waste. It is compatible with arbitrary proportions of power plant slag, fly ash, and gasification slag, solving the problem of unstable supply of single solid waste. The fiber diameter fluctuation range is reduced from ±5μm to ±2μm, resulting in significantly improved fiber mechanical strength. It can process more than 15,000 tons of coal-based solid waste annually, reducing the land occupation and environmental pollution associated with solid waste storage. Detailed Implementation

[0011] It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of this invention can be combined with each other. The technical solutions in the embodiments of this invention are clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0012] This invention discloses a method for dynamically adjusting and controlling the fiber forming process window to cope with fluctuations in the composition of coal-based solid waste, comprising the following steps: S1: Detection units are deployed at the mixing silo outlet, electric melting furnace flow channel, centrifuge inlet, and fiber collection channel to capture raw material composition, melt viscosity, temperature, fiber diameter, and equipment operating status in real time. Data with compositional mutations exceeding ±2% are directly replaced with the average value of similar operating conditions. Deviations in batching ratios exceeding ±2% are corrected by adjusting the operating frequency of the feeding equipment. Abnormal melt viscosity data are cross-validated with the temperature detection unit to ensure that the perceived data matches the actual production. The similar operating conditions referred to in this invention refer to production periods with similar raw material composition fluctuation ranges, equipment operating status, and ambient temperature. The average value is the arithmetic mean of similar operating condition data within the most recent 30 days.

[0013] S2: Based on the composition-process coupling model, multi-dimensional data is input, and calculations are performed according to the composition range and working conditions. Quantitative adaptation rules are applied: for every 1% increase in CaO, the heating power of the electric furnace increases by 5%; for every 1% increase in Fe2O3, the airflow fan pressure increases by 0.03MPa; for every 0.2 decrease in the SiO2 / Al2O3 ratio, the centrifuge speed increases by 50r / min. The output is the baseline command for the electric furnace power, centrifuge speed, airflow pressure, and ingredient ratio. The composition-process coupling model is a multiple linear regression model trained based on historical production data. The least squares method is used to fit the quantitative relationship between each component and process parameters. The model is retrained quarterly using the latest production data.

[0014] Specifically, based on the CaO content, the model is divided into three intervals: 5%-8%, 8%-12%, and 12%-15%, with each interval having its own independently trained sub-model.

[0015] S3: In actual processing, the melt viscosity exceeds 1500 Pa. When the time is s, first increase the heating power of the electric melting furnace through the command. If the target is not met in 5 minutes, then increase the speed of the centrifuge in conjunction with the command. When the fiber diameter exceeds 20μm, first increase the airflow pressure, and then fine-tune the temperature of the electric melting furnace. S4: The finished product testing unit collects density, strength, and fiber diameter data in real time. If the strength is less than 1.5 MPa, the curing oven temperature and the viscosity control range of the electric melting furnace are adjusted retrospectively. The composition, operation, and quality correlation data are added to the database daily, the coupling model is retrained, and the operation thresholds for different composition ranges are updated to adapt to subsequent production fluctuations.

[0016] Furthermore, the composition detection unit is positioned directly opposite the center of the raw material conveying coal flow to avoid material obstruction; the viscosity detection unit is inserted at an angle into the melt flow channel to avoid dead corners in the flow channel; and the fiber diameter detection unit is deployed in the horizontal section at the outlet of the airflow drawing channel to reduce airflow interference.

[0017] Furthermore, in step S2, each component range is trained independently as a sub-model. During computation, historical operation data of the same component fluctuation range are called first to ensure that the output command is directly adapted to the current raw material characteristics without additional debugging.

[0018] Furthermore, in step S3, the dynamic adjustment of operation priorities adapts to the needs of continuous production. When the melt viscosity is abnormal, the electric melting furnace is adjusted first; when the fiber morphology is abnormal, the centrifuge and airflow valve are adjusted first; when the batching ratio is abnormal, the feeding equipment is adjusted slowly. All operation instructions are issued at the process-permitted rate to prevent equipment impact.

[0019] Furthermore, when the raw material composition suddenly increases by more than ±8%, an emergency command is immediately triggered to open the electric valve of the heat storage tank to release 30% of the stable melt to buffer the impact. At the same time, the proportion of bauxite slag additives is increased, the high composition fluctuation adaptation process is called, the electric melting furnace power is increased to the upper limit, the centrifuge speed is increased to 2300 r / min, and the airflow pressure is adjusted to 0.7 MPa. After the composition fluctuation is ≤ ±5%, it will transition to normal adjustment. During this process, the operation instructions for the heat storage tank and the electric melting furnace are issued simultaneously, and the addition of auxiliary materials and the detection of components are linked in real time.

[0020] In actual production, coal-based solid waste needs to be managed separately by type. Cold slag is stored in a cold slag silo, crushed by a jaw crusher, and then screened by a vibrating screen to a particle size of less than 50mm, with the undersize accounting for more than 95%. Hot slag is directly fed into the same type of screen without additional crushing, reducing energy waste. The crushed and screened cold and hot slags are then mixed with fly ash and fed to a mixing silo by a frequency converter in a preset ratio of 40% cold slag, 30% hot slag, and 30% fly ash.

[0021] Inside the mixing silo, a double-spiral agitator continuously stirs the material at a speed of 30 r / min for at least 5 minutes to ensure uniform mixing. Above the sealed belt conveyor at the mixing silo outlet, an online component detection device is installed to monitor the content of SiO2, Al2O3, CaO, and Fe2O3 in the mixed raw materials in real time. If any component deviates from the target value by 2% (e.g., CaO drops from 8% to 6%), the corresponding feeder frequency is immediately adjusted: the hot slag feeder frequency is increased from 40Hz to 45Hz, and the cold slag feeder frequency is decreased from 45Hz to 42Hz. Simultaneously, the agitator speed is increased to 35 r / min to enhance the mixing effect until the component deviation is controlled within 1%. An electromagnetic separator is also installed in the middle of the belt conveyor to remove metallic impurities from the raw materials, preventing damage to the electrodes of the subsequent electric melting furnace. The material level sensor at the end of the belt controls the feeding rate to remain stable at 10-15 t / h, precisely matching the processing capacity of the electric melting furnace to prevent material interruption or accumulation.

[0022] In the melt-fiber stage, the pretreated raw materials enter the electric melting furnace, where they are heated by three graphite electrodes. Temperature is controlled by zone: the melting zone is maintained at 1500-1600℃, and the homogenization zone at 1450-1500℃. The raw materials remain in the furnace for at least 30 minutes to ensure complete melting. Temperature detection elements installed in the upper, middle, and lower layers of the furnace cavity monitor temperature fluctuations in real time. If the temperature in the melting zone drops below 1500℃, the electrode insertion depth is immediately increased via a command to raise the heating power and prevent insufficient melt flowability. The molten melt is then transported to a centrifuge via a flow channel made of high-temperature resistant material and encased in a natural gas heating system to maintain a temperature of 1500-1550℃ with fluctuations not exceeding 50℃ to prevent the melt from cooling and agglomerating. An electromagnetic flowmeter at the end of the flow channel controls the melt flow rate at 460-780 kg / h. If the flow rate fluctuation exceeds 5%, the feed rate of the electric melting furnace is adjusted synchronously. A viscosity detection element installed in the middle of the flow channel monitors the melt viscosity in real time, which must be controlled within 800-1500 Pa. The optimal range for fiber formation of s is reached when the viscosity increases to 1500 Pa. First, increase the power of the electric melting furnace. If the target is not met within 5 minutes, increase the speed of the centrifuge to ensure that the melt meets the requirements for fiber formation.

[0023] After the melt flows into the four-roll centrifuge, the roller surface temperature is maintained at 1200-1300℃. The melt is spun into primary fibers of 20-30μm at a rotation speed of 1500-2500 r / min. These primary fibers then enter the airflow drawing channel, where a high-temperature airflow of 30-50 m / s and 800-1000℃ is introduced to refine the fibers to 5-20μm and extend their length to 10-30cm. A wind speed detection element at the channel outlet adjusts the fan pressure in real time to ensure stable drawing performance. If a fiber diameter exceeding 20μm is detected, the air pressure is increased first, followed by a fine-tuning of the electric melting furnace temperature to prevent excessively coarse fibers from affecting subsequent molding processes.

[0024] After being drawn, the fibers enter the negative pressure cotton collector with the airflow. If the negative pressure detection element at the top of the cotton collector detects a deviation of 50Pa from the target value, the frequency of the induced draft fan is immediately adjusted, and the moving speed of the cotton collecting plate is also adjusted to prevent the cotton layer from being too thick or too thin. The collected cotton layer is then conveyed to the pendulum machine via a conveyor belt, and the formed cotton blank enters the curing oven for cutting after forming.

[0025] After cutting, the finished products enter the testing line, and all test data are transmitted to the central control system in real time. If the strength of the finished product is only 1.4MPa (below the B-grade standard), the parameters of the curing oven are traced back. If the temperature of the curing section is found to have dropped from 250℃ to 240℃, the heating tube power is immediately adjusted to raise the temperature to 255℃, while extending the curing time by 5 minutes. If the fiber diameter is too coarse, the process is traced back to the melt fiber formation stage, and the temperature of the electric melting furnace or the speed of the centrifuge is finely adjusted to optimize subsequent production parameters.

[0026] Qualified finished products are stored according to quality grade (Grade A strength ≥ 2.0 MPa, Grade B 1.5-2.0 MPa). Unqualified products are crushed to below 50 mm and then recycled at a rate not exceeding 10% in the raw material pretreatment stage. More than 1000 sets of raw material composition, process parameters, and finished product quality data are added to the database daily to retrain the composition-process coupling model and adjust the correlation coefficient between CaO and the electric melting furnace temperature. This improves the process adaptation accuracy during subsequent composition fluctuations by 5%-10%, forming a closed-loop production process of detection-correction-optimization.

[0027] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for dynamically adjusting and controlling the fiber forming process window to cope with fluctuations in the composition of coal-based solid waste, characterized in that, Comprise the following steps: S1: At the outlet of the mixing bin, the flow channel of the electric melting furnace, the inlet of the centrifuge, and the fiber collection channel, deploy detection units to capture real-time data on raw material composition, melt viscosity, temperature, fiber diameter, and equipment operating status. For data with composition mutations exceeding ±2%, replace them with the average value of similar working conditions. For data with a deviation in the proportion of ingredients exceeding ±2%, adjust the operating frequency of the feeding equipment to correct it. For abnormal melt viscosity data, cross-verify with the temperature detection unit to ensure that the sensed data match the actual production. S2: Based on the composition-process coupling model, input the sensed multi-dimensional data, operate according to the composition interval, and quantify the adaptation rules. For every 1% increase in CaO, increase the heating power of the electric melting furnace by 5%. For every 1% increase in Fe2O3, increase the air pressure of the airflow fan by 0.03 MPa. For every 0.2 decrease in the SiO2 / Al2O3 ratio, increase the speed of the centrifuge by 50 r / min. Output the baseline instructions for the electric melting furnace power, centrifuge speed, airflow pressure, and ingredient proportion. S3: In the actual processing, the melt viscosity exceeds 1500 Pa s, first through the command to improve the power of the electric melting furnace, 5 min does not reach the standard to improve the linkage speed of centrifuge; fiber diameter exceeds 20 μm, first adjust the air pressure, and then fine-tune the electric melting furnace temperature; S4: The finished product detection unit collects real-time data on density, strength, and fiber diameter. If the strength is less than 1.5 MPa, backtrack and adjust the solidification furnace temperature and the viscosity control interval of the electric melting furnace. Daily, supplement the composition, operation, and quality correlation data to the database, retrain the coupling model, and update the operation thresholds for different composition intervals to adapt to subsequent production fluctuations.

2. The method of claim 1, wherein, The composition detection unit is directly opposite the raw material conveying coal stream center to avoid material obstruction. The viscosity detection unit is inserted obliquely into the melt flow channel to avoid dead corners. The fiber diameter detection unit is deployed at the horizontal section of the airflow drafting channel outlet to reduce airflow interference.

3. The method of claim 1, wherein, In step S2, each composition interval independently trains a sub-model. When operating, preferentially call historical operation data within the same composition fluctuation range to ensure that the output instructions directly adapt to the current raw material characteristics without additional debugging.

4. The method of claim 1, wherein, In step S3, the dynamically adjusted operation priority adapts to the continuous production demand. When the melt viscosity is abnormal, prioritize adjusting the electric melting furnace. When the fiber morphology is abnormal, prioritize adjusting the centrifuge and airflow valve. When the ingredient proportion is abnormal, slowly adjust the feeding equipment. The instructions for all operations are issued at the process allowed rate to prevent equipment impact.

5. The method of claim 1, wherein, When the raw material composition suddenly increases by more than ±8%, immediately trigger the emergency instruction, open the electric valve of the heat accumulator to release 30% of the stable melt buffer impact, simultaneously increase the proportion of bauxite slag auxiliary materials, call the high composition fluctuation adaptation process, increase the electric melting furnace power to the upper limit, increase the centrifuge speed to 2300 r / min, and adjust the airflow pressure to 0.7 MPa. After the composition fluctuation is ≤±5%, transition to regular adjustment. During this process, the operation instructions of the heat accumulator and the electric melting furnace are issued synchronously, and the auxiliary material addition is linked in real time with the composition detection.

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