Full-automatic low-carbon UHPC mixing production line and gradient fiber dispersion method

Abstract

The invention provides a full-automatic low-carbon UHPC mixing production line and a gradient fiber dispersion method, and relates to the technical field of ultra-high performance concrete production equipment.The production line comprises a raw material premixing bin, a fiber gradient dispersion tower, a planetary vacuum mixer and a low-temperature curing tunnel; dynamic correction of the aggregate proportion is achieved through the microwave drying module, the laser particle size analyzer and the AI proportioning system interface which are arranged in the raw material premixing bin, and the aggregate particle size data collected by the laser particle size analyzer in real time and the water content data collected by the microwave drying module are utilized by the AI proportioning system, and the aggregate proportion is obtained through a dynamic correction algorithm of the aggregate proportion. The aggregate proportioning precision is improved to + / -0.5% from + / -3% of traditional experience proportioning, meanwhile, the raw material utilization rate is improved by 6%, UHPC strength fluctuation caused by proportioning deviation is effectively avoided through the improvement, and the problems that traditional production line raw material proportioning depends on artificial experience and is poor in adaptability are solved.

Description

Technical Field

[0001] This invention belongs to the technical field of ultra-high performance concrete production equipment, specifically relating to a fully automatic low-carbon UHPC mixing production line and a gradient fiber dispersion method. Background Technology

[0002] With the continuous improvement of the construction industry's requirements for material performance, ultra-high performance concrete (UHPC) has been widely used in bridges, high-rise buildings and special structural engineering due to its excellent mechanical properties and durability. However, the preparation process of UHPC is complex and has extremely high requirements for key aspects such as raw material ratio, fiber dispersion and curing conditions.

[0003] Traditional UHPC preparation technologies have several shortcomings. First, in terms of raw material proportioning, traditional methods rely mainly on manual experience and periodic sampling, making it difficult to achieve real-time and precise proportioning adjustments. This results in low raw material utilization and makes the final strength of UHPC susceptible to deviations in proportioning. Second, in the fiber dispersion stage, traditional methods lack effective dispersion control measures. The distribution of coarse, fine, and nanofibers in UHPC is often uneven, affecting the overall performance of UHPC. In particular, when processing nanofibers, due to their small diameter and tendency to agglomerate, traditional methods struggle to achieve efficient and uniform dispersion. Furthermore, traditional curing methods are energy-intensive and inefficient, making it difficult to meet the needs of large-scale industrial production.

[0004] In view of the problems of inaccurate raw material ratio, uneven fiber dispersion and low curing efficiency in traditional UHPC preparation technology, the present invention proposes a fully automated low-carbon UHPC mixing production line and a gradient fiber dispersion method, which is of particular importance. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a fully automated low-carbon UHPC mixing production line and gradient fiber dispersion method. It can achieve high precision, high efficiency and low carbonization in the UHPC preparation process by integrating advanced equipment such as raw material premixing silos, fiber gradient dispersion towers, planetary vacuum mixers and low-temperature curing tunnels, combined with core technologies such as AI proportioning system, fiber centrifugal speed adaptive adjustment algorithm, fine fiber suspension state feedback airflow pressure control technology based on high-speed image recognition and electrostatic voltage optimization algorithm.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: On the one hand, a fully automatic low-carbon UHPC mixing production line, which includes the following components: raw material premixing silo, fiber gradient dispersion tower, planetary vacuum mixer and low temperature curing tunnel; The raw material premixing bin has a built-in microwave drying module, laser particle size analyzer and AI proportioning system interface. The aggregate particle size data collected in real time by the laser particle size analyzer and the moisture content data collected by the microwave drying module can be transmitted to the AI ​​proportioning system for dynamic correction of aggregate proportions. The fiber gradient dispersion tower is equipped with a centrifugal sprayer, an airflow suspension chamber, and an electrostatic adsorption plate in sequence. The centrifugal sprayer is equipped with a speed adaptive adjustment interface, the airflow suspension chamber is equipped with an airflow pressure dynamic adjustment interface, and the electrostatic adsorption plate is equipped with an electrostatic voltage optimization interface, which are used for the precise dispersion control of coarse, fine, and nanofibers, respectively. The planetary vacuum mixer includes a double-revolving blade, a rotating blade, and a vacuum dewatering module. The double-revolving blade and the rotating blade share a speed coordination control interface. The vacuum dewatering module is equipped with a vacuum degree dynamic optimization interface to adjust the mixing parameters and dewatering parameters according to the state of the slurry. The low-temperature curing tunnel integrates a waste heat recovery system, temperature and humidity sensors, and a temperature and humidity coordinated control interface. The waste heat recovery system is equipped with a heat exchange efficiency optimization interface, which can adjust the heat exchange parameters based on motor waste heat and curing requirements. The data collected by the temperature and humidity sensors is used to control the curing temperature and humidity in real time.

[0007] As a preferred embodiment, the AI ​​proportioning system of the raw material premixing silo achieves high-precision raw material proportioning through a dynamic correction algorithm for aggregate proportioning. This algorithm addresses the problem of proportioning deviation caused by uneven aggregate particle size distribution and moisture content fluctuations in UHPC aggregates. It dynamically corrects the proportioning by using parameters collected in real time by a laser particle size analyzer and a microwave drying module to ensure that the aggregate mixing meets the rheological performance requirements of UHPC. The formula is: ,in For the first Real-time quality adjustment of aggregates For the first The initial design quality of the aggregate, For real-time monitoring of laser particle size analyzer Characteristic particle size of aggregates For the first Standard characteristic particle size of aggregate, The first real-time monitoring of the microwave drying module Moisture content of aggregates For the first The target moisture content of the aggregate, , The weighting coefficient has a range of values. , , This is a correction factor, and its value range is... The application of this algorithm can improve the aggregate proportioning accuracy from ±3% of the traditional experience proportioning to ±0.5%, increase the raw material utilization rate by 6%, and avoid the UHPC strength fluctuation caused by proportioning deviation. It effectively solves the problem that the raw material proportioning of traditional production lines relies on manual experience and has poor adaptability.

[0008] As a preferred embodiment, the adaptive speed adjustment interface of the fiber gradient dispersion tower centrifugal sprayer achieves dynamic speed control through a fiber centrifugal speed adaptive adjustment algorithm. This algorithm adjusts the speed according to the physical characteristics of the coarse steel fibers, avoiding the problem of coarse fiber clumping or over-dispersion at a fixed speed, and ensuring that the uniformity of coarse fiber dispersion is ≥98%. The formula is: ,in To adjust the speed of the centrifugal sprayer in real time. This is the actual length of the coarse steel fiber. The bulk density of the coarse steel fiber is... The air resistance coefficient of coarse steel fibers. This is the mechanical error correction factor. , Using weighted coefficients, this algorithm allows the centrifugal sprayer speed to be adjusted in real time according to fiber characteristics. When the length of coarse fibers decreases from 12mm to 10mm, the speed can be adaptively reduced from 650rpm to 580rpm to avoid fiber breakage due to excessive speed. When the fiber density decreases to 7.6g / cm³ due to corrosion, the speed is increased to 720rpm to compensate for the clumping problem caused by insufficient centrifugal force. Ultimately, the coarse fiber clumping rate is reduced from 8% at the traditional fixed speed to below 1.5%.

[0009] As a preferred embodiment, the dynamic adjustment interface for the airflow pressure of the fiber gradient dispersion tower airflow suspension chamber optimizes pressure through a fine fiber suspension state feedback-based airflow pressure control technology based on high-speed image recognition. This technology, through hardware detection and real-time feedback operation, avoids fine fiber settling or excessive disturbance, ensuring that the fine fiber suspension time is ≥3s and the dispersion uniformity is ≥97%. The specific implementation steps are as follows: a high-speed camera with a frame rate of 1000fps is installed in the middle of the airflow suspension chamber, directly opposite the fiber flow path, with the lens covering the effective area of ​​the suspension chamber, to capture the movement trajectory of the fine fibers in real time. Every 2 seconds, blurry frames are filtered out, and one effective image frame is captured. Image recognition software is used to process the effective images, and the fiber pixel coordinates are used to track and calculate the position of each fiber. The system measures the residence time in the effective area of ​​the suspension chamber and simultaneously analyzes the spatial distribution density deviation of fibers in the image. Preset judgment thresholds are used: suspension time ≥ 3s and distribution density deviation ≤ 5% are considered acceptable; suspension time < 3s indicates insufficient airflow pressure; distribution density deviation > 5% and local fiber stacking indicate excessive pressure. The PLC controller receives the judgment results and drives the electronic pressure regulating valve at the air inlet of the air suspension chamber. If the pressure is insufficient, it is finely adjusted upwards by 0.05-0.1MPa within the range of 0.5-1MPa; if the pressure is excessive, it is finely adjusted downwards by 0.03-0.08MPa. After adjustment, steps 1-4 are repeated after a 3-second interval until the fine fiber suspension state meets the acceptable threshold twice consecutively, at which point the adjustment stops, achieving dynamic optimization control of the airflow pressure.

[0010] As a preferred embodiment, the electrostatic voltage optimization interface of the electrostatic adsorption plate of the fiber gradient dispersion tower achieves voltage regulation through an electrostatic voltage optimization algorithm. This algorithm adjusts the voltage according to the characteristics of nanofibers and environmental parameters to improve the directional adsorption efficiency of nanofibers, avoiding problems such as fiber breakdown due to excessively high voltage and insufficient adsorption due to excessively low voltage, ensuring that the nanofiber adsorption rate is ≥95% and the aggregation rate is ≤3%. The formula is: ,in To adjust the voltage of the electrostatic adsorption plate in real time. The actual diameter of the nanofiber. Let be the relative permittivity of the air in the adsorption environment. To adsorb the relative humidity of the environment, , These are the weighting coefficients. As the electrode distance correction coefficient, this algorithm allows the electrostatic voltage to be adjusted in real time according to the nanofiber characteristics and environment. When the nanofiber diameter decreases from 30μm to 20μm, the voltage decreases from 4.5kV to 3.8kV to avoid excessive voltage causing fiber breakdown. When the RH increases from 50% to 60%, the voltage increases to 5.2kV to compensate for the decrease in adsorption force caused by the decrease in dielectric constant. Ultimately, the nanofiber adsorption rate increases from 85% under traditional fixed voltage to 96%, and the aggregation rate decreases from 12% to 2.8%.

[0011] As a preferred embodiment, the rotational speed coordinated control interface of the planetary vacuum mixer's dual blades achieves speed optimization through dual blade speed control technology based on dual parameter feedback of slurry viscosity and fiber content. This technology avoids uneven slurry mixing or insufficient fiber agglomeration by real-time acquisition of key parameters and dynamic adjustment of the speed, ensuring that the slurry porosity is ≤1.5% and the fiber dispersion uniformity is ≥95%. The specific implementation steps are as follows: a rotational rheometer is installed on the inner wall of the mixer to collect the real-time viscosity of the UHPC slurry every 15 seconds, simultaneously receiving the total fiber mass fraction of the slurry transmitted from the feeding system, combined with the vacuum dewatering module... Real-time vacuum degree; preset judgment rules: when viscosity > 800 Pa·s, the revolution speed needs to be increased to enhance macroscopic flow; when fiber mass fraction > 3%, the rotation speed needs to be increased to enhance shearing and crushing; when vacuum degree < -0.08 MPa, the rotation speed needs to be finely adjusted to compensate for slurry fluidity; the PLC controller drives the dual-blade speed regulator according to the judgment results, adjusting the revolution speed by 2-3 rpm each time and the rotation speed by 5-8 rpm each time; after adjustment, repeat steps 1-3 after 10 seconds until the slurry viscosity and fiber dispersion uniformity meet the target requirements twice in a row, then stop adjusting the speed to achieve synergistic optimization of the dual-blade speed.

[0012] As a preferred embodiment, the vacuum degree dynamic optimization interface of the planetary vacuum mixer's vacuum dehydration module achieves vacuum degree control through a dynamic optimization algorithm. This algorithm adjusts the vacuum degree based on the real-time moisture content and temperature of the slurry, avoiding insufficient or excessive dehydration caused by a fixed vacuum degree, ensuring a dehydration rate ≥8% and a slurry flowability ≥650mm. The formula is: ,in To adjust the vacuum level of the vacuum dehydration module in real time, The initial moisture content of the slurry. This refers to the real-time moisture content of the slurry. The real-time temperature of the slurry. , These are the weighting coefficients. As a leakage correction coefficient for the vacuum system, this algorithm allows the vacuum degree to be adjusted in real time according to the slurry state. When the real-time moisture content of the slurry drops from 22% to 18%, the vacuum degree drops from -0.075MPa to -0.085MPa, accelerating the dewatering rate. When the slurry temperature rises from 25℃ to 40℃, the vacuum degree is adjusted back to -0.08MPa to avoid excessive dewatering that would cause the slurry fluidity to drop below 600mm. Finally, the dewatering time is shortened from 15 minutes under the traditional fixed vacuum degree to 10 minutes, the dewatering rate is stabilized at 8.5%~9%, and the slurry fluidity deviation is ≤20mm.

[0013] As a preferred embodiment, the heat exchange efficiency optimization interface of the low-temperature curing tunnel waste heat recovery system adjusts the heat exchange parameters through a heat exchange efficiency optimization algorithm. This algorithm optimizes the heat exchange efficiency based on the motor waste heat power and curing temperature requirements, avoiding the excessive energy consumption problem caused by traditional curing relying on external steam heat sources. It ensures a heat exchange efficiency ≥ 65% and power consumption per ton of UHPC curing ≤ 8 kWh, as shown in the formula: ,in Real-time heat exchange efficiency of the waste heat recovery system. This refers to the real-time waste heat power of the planetary vacuum mixer motor. The target thermal power required for UHPC maintenance The exhaust temperature is the waste heat temperature of the motor. The target temperature for UHPC curing. , These are the weighting coefficients. This is the scaling correction factor for the heat exchanger.

[0014] As a preferred embodiment, the temperature and humidity coordinated control interface of the low-temperature curing tunnel achieves precise temperature and humidity control through a maintenance linkage control technology of fiber optic grating sensing + multi-point temperature and humidity feedback. The specific steps are as follows: 3 sets of fiber optic grating stress sensors and 5 temperature and humidity sensors are installed in the tunnel to collect intensity, real-time humidity, and current temperature every hour; Determination: Delayed strength development, RH < 85% prone to cracking, and RH > 95% affecting strength are considered abnormal; Adjustment: When the strength is delayed and the RH is qualified, T is increased by 3-5℃ from 40-60℃; If the RH is insufficient, humidify to 88%-92% first and then decrease T by 2-3℃; If the RH is too high, ventilate and adjust the humidity to 90%-92%; 4. Cycle detection every 30 minutes, and stop adjusting when the strength meets the standard and the RH is 85%-92% for two consecutive times.

[0015] On the other hand, a fully automated low-carbon UHPC mixing gradient fiber dispersion method, the specific steps of which are as follows: S1. Microwave drying of aggregates: The UHPC aggregates are dried using the microwave drying module built into the raw material premixing bin of the production line until the aggregate moisture content is ≤0.5%. S2. Fiber gradient dispersion: Coarse fibers, fine fibers, and nanofibers are fed into the fiber gradient dispersion tower of the production line, and are dispersed in layers through centrifugal sprayers, airflow suspension chambers, and electrostatic adsorption plates arranged in sequence inside the tower. S3. Planetary vacuum mixing and dewatering: The dried aggregate and dispersed fiber are fed into the planetary vacuum mixer of the production line. Through the mixing of double-revolutionary blades and self-rotating blades and the dewatering module, the porosity of the slurry is reduced to ≤1.5%. S4. Waste heat recovery curing: The mixed slurry is sent to the low-temperature curing tunnel of the production line. The tunnel is integrated with a waste heat recovery system for curing. The curing temperature is controlled at 40-60℃ and the curing time is 6-8 hours to complete the UHPC mixing and gradient fiber dispersion.

[0016] Compared with the prior art, the present invention has the following beneficial effects: (1) This invention realizes dynamic correction of aggregate ratio by using the microwave drying module, laser particle size analyzer and AI proportioning system interface built into the raw material premixing bin. The AI ​​proportioning system uses the aggregate particle size data collected in real time by the laser particle size analyzer and the moisture content data collected by the microwave drying module. Through the dynamic correction algorithm of aggregate ratio, the aggregate ratio accuracy is improved from ±3% of the traditional experience ratio to ±0.5%. At the same time, the raw material utilization rate is increased by 6%. This improvement effectively avoids the fluctuation of UHPC strength caused by the ratio deviation and solves the problem that the raw material ratio of the traditional production line relies on manual experience and has poor adaptability.

[0017] (1) The fiber gradient dispersion tower of the present invention achieves precise dispersion control of coarse, fine and nanofibers through the combined design of centrifugal sprayer, airflow suspension chamber and electrostatic adsorption plate. The centrifugal sprayer uses a fiber centrifugal speed adaptive adjustment algorithm to dynamically adjust the speed according to the physical characteristics of coarse steel fiber to ensure that the dispersion uniformity of coarse fiber is ≥98%. The airflow suspension chamber uses a high-speed image recognition-based feedback airflow pressure control technology to ensure that the suspension time of fine fiber is ≥3s and the dispersion uniformity is ≥97%. The electrostatic adsorption plate uses an electrostatic voltage optimization algorithm to adjust the voltage according to the characteristics of nanofiber and environmental parameters to ensure that the adsorption rate of nanofiber is ≥95% and the agglomeration rate is ≤3%. The comprehensive application of these technologies significantly improves the dispersion effect of fibers, optimizes the production process and improves the overall production efficiency. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0019] Figure 1 Flowchart of a fully automated low-carbon UHPC mixing production line; Figure 2 This is a flowchart illustrating the fully automated low-carbon UHPC mixing and gradient fiber dispersion method. Detailed Implementation

[0020] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0021] Example 1 : The various aggregates required for UHPC in bridge engineering are fed into the raw material premixing silo of the production line. The built-in microwave drying module in the silo is then activated to dry the aggregates. Figure 1 As shown, during the drying process, the microwave drying module collects the moisture content data of each aggregate in real time, while the laser particle size analyzer in the raw material premixing silo simultaneously collects the characteristic particle size data of each aggregate in real time. Both types of data are transmitted to the AI ​​proportioning system. The system dynamically corrects the real-time adjustment quality of each aggregate through a dynamic correction algorithm for aggregate proportioning. The formula is: ,in For the first Real-time quality adjustment of aggregates For the first The initial design quality of the aggregate, For real-time monitoring of laser particle size analyzer Characteristic particle size of aggregates For the first Standard characteristic particle size of aggregate, The first real-time monitoring of the microwave drying module Moisture content of aggregates For the first The target moisture content of the aggregate, , These are the weighting coefficients. To correct the coefficients and ensure the accuracy of the raw material proportions, the aggregates were dried continuously until the moisture content of all aggregates was ≤0.5%, thus completing the aggregate pretreatment.

[0022] The coarse steel fibers, fine fibers, and nanofibers required for bridge engineering are fed into the fiber gradient dispersion tower of the production line according to process requirements for precise layering and dispersion. Figure 2 As shown, for coarse steel fibers, dispersion is achieved through centrifugal sprayers within the tower. The adaptive speed adjustment interface of the centrifugal sprayers employs a fiber centrifugal speed adaptive adjustment algorithm, the formula of which is: ,in To adjust the speed of the centrifugal sprayer in real time. This is the actual length of the coarse steel fiber. The bulk density of the coarse steel fiber is... The air resistance coefficient of coarse steel fibers. This is the mechanical error correction factor. , The rotation speed is dynamically controlled based on parameters such as the actual length, bulk density, and air resistance coefficient of the coarse steel fiber, using a weighting coefficient, to achieve uniform dispersion of the coarse fiber.

[0023] For fine fibers, after being introduced into the airflow suspension chamber, a high-speed camera with a frame rate of 1000fps installed inside is activated. The lens covers the effective area of ​​the suspension chamber, capturing the movement trajectory of the fine fibers in real time. Every 2 seconds, blurry frames are filtered out, and one valid image frame is captured. The image is processed by image recognition software to calculate the residence time of a single fiber and statistically analyze the spatial distribution density deviation. The PLC controller determines the state based on a preset qualified threshold. If the pressure is insufficient, it is finely adjusted upwards by 0.05-0.1MPa within the range of 0.5-1MPa; if the pressure is too high, it is finely adjusted downwards by 0.03-0.08MPa. After adjustment, the detection is repeated after a 3-second interval until the fine fiber suspension state meets the qualified threshold twice consecutively. For nanofibers, dispersion is achieved through an electrostatic adsorption plate. The electrostatic voltage optimization interface of the electrostatic adsorption plate uses an electrostatic voltage optimization algorithm, the formula of which is: ,in To adjust the voltage of the electrostatic adsorption plate in real time. The actual diameter of the nanofiber. Let be the relative permittivity of the air in the adsorption environment. To adsorb the relative humidity of the environment, , These are the weighting coefficients. The electrode distance correction coefficient is used to adjust the electrostatic voltage by combining parameters such as the actual diameter of the nanofiber, the relative permittivity of the air in the adsorption environment, and the relative humidity of the environment, so as to achieve precise adsorption and dispersion of nanofibers and avoid aggregation.

[0024] The dried aggregate and three types of fibers that have undergone gradient dispersion treatment are fed into a planetary vacuum mixer. The mixer is activated with dual-revolutionary and rotary blades, while the vacuum dewatering module is simultaneously engaged. During mixing, a rotational rheometer on the inner wall of the mixer collects the real-time viscosity of the UHPC slurry every 15 seconds. Simultaneously, the total fiber mass fraction of the slurry transmitted from the feeding system is received. Combined with the real-time vacuum level of the vacuum dewatering module, a dual-blade speed control technology using slurry viscosity and fiber content feedback is employed. When the viscosity > 800 Pa·s, the revolutionary speed is increased; when the fiber mass fraction > 3%, the rotary speed is increased; and when the vacuum level < -0.08 MPa, the rotary speed is fine-tuned to compensate for slurry fluidity. The vacuum dewatering module utilizes a dynamic vacuum optimization algorithm, the formula of which is: ,in To adjust the vacuum level of the vacuum dehydration module in real time, The initial moisture content of the slurry. This refers to the real-time moisture content of the slurry. The real-time temperature of the slurry. , These are the weighting coefficients. The vacuum system leakage correction coefficient is used to adjust the vacuum level based on parameters such as the initial moisture content, real-time moisture content, and real-time temperature of the slurry. The stirring and dehydration operations are continued until the slurry porosity is ≤1.5%, thus completing the slurry preparation.

[0025] The properly mixed slurry is then fed into the low-temperature curing tunnel, and the tunnel's integrated waste heat recovery system is activated. The heat exchange efficiency optimization interface of this system uses a heat exchange efficiency optimization algorithm, the formula of which is: ,in Real-time heat exchange efficiency of the waste heat recovery system. This refers to the real-time waste heat power of the planetary vacuum mixer motor. The target thermal power required for UHPC maintenance The exhaust temperature is the waste heat temperature of the motor. The target temperature for UHPC curing. , These are the weighting coefficients. To correct for scale buildup in the heat exchanger, heat exchange parameters were adjusted based on parameters such as the real-time waste heat power of the planetary vacuum mixer motor, the target heat power required for UHPC curing, the exhaust temperature of the motor waste heat, and the target curing temperature. This fully utilized the motor waste heat for curing. Three sets of fiber optic stress sensors and five temperature and humidity sensors were installed inside the tunnel to collect data on slurry strength, real-time humidity, and current temperature every hour. Abnormal conditions were identified according to the following rules: if the strength was lagging and the RH was within acceptable limits, the temperature was increased by 3-5℃ within the 40-60℃ range; if the RH was insufficient, the humidity was first increased to 88%-92% and then the temperature was decreased by 2-3℃; if the RH was too high, the humidity was adjusted to 90%-92% through ventilation. The process was repeated every 30 minutes, and adjustments were stopped when the strength met the standard and the RH remained within the 85%-92% range for two consecutive tests. The curing temperature was maintained at 40-60℃ for 6-8 hours, thus completing the production of high-strength UHPC mixture for bridge engineering.

[0026] Example 2 : The precast panels are fed into the raw material premixing silo using UHPC aggregate, and the microwave drying module is activated to perform low-carbon drying treatment on the aggregate. Figure 1 As shown, to avoid the high energy consumption of traditional drying methods, during the drying process, the laser particle size analyzer collects the characteristic particle size data of various aggregates in real time, and the microwave drying module collects the moisture content data of each aggregate simultaneously. Both types of data are transmitted to the AI ​​proportioning system in real time. The system uses a dynamic correction algorithm for aggregate proportioning, combined with parameters such as the standard characteristic particle size and target moisture content of the aggregates, to dynamically correct the real-time adjustment quality of each aggregate, ensuring high precision in raw material proportioning. The drying continues until the moisture content of all aggregates is ≤0.5%, completing the aggregate pretreatment.

[0027] According to the mechanical performance requirements of the precast panels, coarse fibers, fine fibers, and nanofibers are quantitatively fed into a fiber gradient dispersion tower, and then sequentially dispersed in layers through a centrifugal sprayer, an airflow suspension chamber, and an electrostatic adsorption plate. Figure 2 As shown, during the coarse fiber dispersion stage, the centrifugal sprayer dynamically adjusts its rotation speed based on key parameters such as the actual length, bulk density, and air resistance coefficient of the coarse fibers using an adaptive fiber centrifugal speed adjustment algorithm. This ensures that the coarse fibers are evenly distributed within the dispersion area without localized accumulation. After the fine fibers enter the airflow suspension chamber, a high-speed camera captures one effective image frame every 2 seconds to collect the fiber motion status. Image recognition software tracks and calculates the fiber residence time using pixel coordinates and statistically analyzes the distribution density deviation. The PLC controller judges the airflow pressure status based on the qualified threshold. If the pressure is insufficient, it is increased by 0.05-0.1 MPa within the 0.5-1 MPa range; if the pressure is too high, it is decreased by 0.03-0.08 MPa. This process is repeated until the fine fibers meet the requirements of suspension time ≥3s and distribution density deviation ≤5% twice consecutively. During nanofiber dispersion, the electrostatic adsorption plate uses an electrostatic voltage optimization algorithm. Combining parameters such as the actual diameter of the nanofibers, the relative permittivity of air, and the relative humidity of the environment, it precisely controls the electrostatic voltage to achieve uniform adsorption and dispersion of the nanofibers, ensuring good bonding between the fibers and the slurry.

[0028] The pretreated aggregate and the dispersed three types of fibers are fed into a planetary vacuum mixer. The mixing and dewatering system is started. During the mixing process, a rotational rheometer collects slurry viscosity data every 15 seconds, and simultaneously acquires the total fiber mass fraction and vacuum degree data. The mixing parameters are optimized using a dual-impeller speed control technology with dual parameter feedback of slurry viscosity and fiber content: when the slurry viscosity is >800 Pa·s, the revolution speed is increased by 2-3 rpm each time to enhance macroscopic fluidity; when the fiber mass fraction is >3%, the rotation speed is increased by 5-8 rpm each time to enhance the shearing and crushing effect; when the vacuum degree is <-0.08 MPa, the rotation speed is finely adjusted to compensate for fluidity. The vacuum dewatering module adjusts the vacuum degree according to parameters such as the initial moisture content, real-time moisture content and real-time temperature of the slurry through a dynamic optimization algorithm to efficiently remove moisture from the slurry. The operation continues until the slurry porosity is ≤1.5% to ensure the density of the formed board.

[0029] After the mixed slurry is injected into the precast slab mold, it is sent into a low-temperature curing tunnel for curing. The waste heat recovery system in the tunnel fully recovers the waste heat of the mixer motor through a heat exchange efficiency optimization algorithm. The heat exchange efficiency is adjusted according to the target heat power and temperature parameters required for curing to achieve low-carbon curing. During the curing period, three sets of fiber optic stress sensors and five temperature and humidity sensors collect data on slab strength, ambient humidity and temperature every hour. Precise control is carried out for abnormal conditions: when the strength development is lagging and the RH is qualified, the temperature is increased by 3-5℃ in the range of 40-60℃; when RH < 85%, the humidity is first increased to 88%-92%, and then the temperature is reduced by 2-3℃ to avoid cracking; when RH > 95%, the humidity is adjusted to 90%-92% through ventilation to ensure strength development. The system is cycled and tested every 30 minutes. After two consecutive tests that meet the strength standard and the RH requirement of 85%-92%, the control is stopped. The curing temperature of 40-60℃ is maintained for 6-8 hours to complete the mass production of low-carbon UHPC slabs in the precast component plant.

[0030] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A fully automatic low-carbon UHPC mixing production line, characterized in that, The production line comprises the following components: a raw material premixing silo, a fiber gradient dispersion tower, a planetary vacuum mixer, and a low-temperature curing tunnel. The raw material premixing bin has a built-in microwave drying module, laser particle size analyzer and AI proportioning system interface. The aggregate particle size data collected in real time by the laser particle size analyzer and the moisture content data collected by the microwave drying module can be transmitted to the AI ​​proportioning system for dynamic correction of aggregate proportions. The fiber gradient dispersion tower is equipped with a centrifugal sprayer, an airflow suspension chamber, and an electrostatic adsorption plate in sequence. The centrifugal sprayer is equipped with a speed adaptive adjustment interface, the airflow suspension chamber is equipped with an airflow pressure dynamic adjustment interface, and the electrostatic adsorption plate is equipped with an electrostatic voltage optimization interface, which are used for the precise dispersion control of coarse, fine, and nanofibers, respectively. The planetary vacuum mixer includes a double-revolving blade, a rotating blade, and a vacuum dewatering module. The double-revolving blade and the rotating blade share a speed coordination control interface. The vacuum dewatering module is equipped with a vacuum degree dynamic optimization interface to adjust the mixing parameters and dewatering parameters according to the state of the slurry. The low-temperature curing tunnel integrates a waste heat recovery system, temperature and humidity sensors, and a temperature and humidity coordinated control interface. The waste heat recovery system is equipped with a heat exchange efficiency optimization interface, which can adjust the heat exchange parameters based on motor waste heat and curing requirements. The data collected by the temperature and humidity sensors is used to control the curing temperature and humidity in real time.

2. The fully automated low-carbon UHPC mixing production line according to claim 1, characterized in that: The AI proportioning system of the raw material premixing bin realizes high-precision raw material proportioning through an aggregate proportioning dynamic correction algorithm, and the formula is: Wherein is the real-time adjustment quality of the th aggregate, is the initial design quality of the th aggregate, is the characteristic particle size of the th aggregate monitored in real time by a laser particle size analyzer, is the standard characteristic particle size of the th aggregate, is the moisture content of the th aggregate monitored in real time by a microwave drying module, is the target moisture content of the th aggregate, , is a weight coefficient, is a correction coefficient.

3. The fully automated low-carbon UHPC mixing production line according to claim 1, characterized in that: The rotational speed adaptive adjustment interface of the fiber gradient dispersion tower centrifugal thrower realizes dynamic control of the rotational speed through a fiber centrifugal rotational speed adaptive adjustment algorithm, and the formula is: Wherein is the real-time adjustment rotational speed of the centrifugal thrower, is the actual length of the coarse steel fiber, is the bulk density of the coarse steel fiber, is the air resistance coefficient of the coarse steel fiber, is a mechanical error correction coefficient, , is a weight coefficient.

4. The fully automatic low-carbon UHPC mixing production line according to claim 1, characterized in that: The airflow pressure dynamic adjustment interface of the fiber gradient dispersion tower airflow suspension chamber achieves pressure optimization through a fine fiber suspension state feedback airflow pressure control technology based on high-speed image recognition. This technology, through hardware detection and real-time feedback operation, avoids fine fiber settling or excessive disturbance. The specific implementation steps are as follows: a high-speed camera with a frame rate of 1000fps is installed in the middle of the airflow suspension chamber, directly opposite the fiber flow path, with the lens covering the effective area of ​​the suspension chamber. The camera captures the movement trajectory of the fine fibers in real time, filtering out blurry frames every 2 seconds and capturing one effective image frame. Image recognition software is used to process the effective images, and the residence time of a single fiber in the effective area of ​​the suspension chamber is calculated by tracking the fiber pixel coordinates. The system measures the spatial distribution density deviation of fibers in the image. A preset threshold is set: a suspension time ≥ 3s and a distribution density deviation ≤ 5% is considered acceptable; a suspension time < 3s indicates insufficient airflow pressure; a distribution density deviation > 5% and localized fiber stacking indicate excessive pressure. The PLC controller receives the judgment results and drives the electronic pressure regulating valve at the air inlet of the airflow suspension chamber. If the pressure is insufficient, it is slightly adjusted upwards by 0.05-0.1MPa within the range of 0.5-1MPa; if the pressure is excessive, it is slightly adjusted downwards by 0.03-0.08MPa. After adjustment, steps 1-4 are repeated after a 3-second interval until the fine fiber suspension state meets the acceptable threshold twice consecutively, at which point the adjustment stops.

5. The fully automated low-carbon UHPC mixing production line according to claim 1, characterized in that: The electrostatic voltage optimization interface of the fiber gradient dispersion tower electrostatic adsorption plate realizes voltage regulation through an electrostatic voltage optimization algorithm, and the formula is: Wherein is the real-time adjustment voltage of the electrostatic adsorption plate, is the actual diameter of the nanofiber, is the relative dielectric constant of the air in the adsorption environment, is the relative humidity of the adsorption environment, , is the weight coefficient, is the electrode distance correction coefficient.

6. The fully automatic low-carbon UHPC mix production line according to claim 1, characterized in that: The planetary vacuum mixer's dual-blade speed control interface optimizes speed through dual-blade speed regulation technology based on slurry viscosity and fiber content feedback. The specific implementation steps are as follows: A rotational rheometer is installed on the inner wall of the mixer to collect the real-time viscosity of the UHPC slurry every 15 seconds, simultaneously receiving the total fiber mass fraction of the slurry transmitted from the feeding system, combined with the real-time vacuum degree of the vacuum dewatering module; preset judgment rules are established: when viscosity > 800 Pa·s, the revolution speed needs to be increased to enhance macroscopic flow; when fiber mass fraction > 3%, the rotation speed needs to be increased to enhance shearing and crushing; when vacuum degree < -0.08 MPa, the rotation speed needs to be finely adjusted to compensate for slurry fluidity; the PLC controller drives the dual-blade speed regulator according to the judgment results, adjusting the revolution speed by 2-3 rpm each time and the rotation speed by 5-8 rpm each time; after adjustment, steps 1-3 are repeated after a 10-second interval until the slurry viscosity and fiber dispersion uniformity meet the target requirements twice consecutively, at which point speed adjustment stops.

7. The fully automated low-carbon UHPC mixing production line according to claim 1, characterized in that: The vacuum degree dynamic optimization interface of the planetary vacuum mixer vacuum dewatering module realizes vacuum degree regulation and control through a vacuum degree dynamic optimization algorithm, and the formula is: wherein is the real-time adjustment of the vacuum degree of the vacuum dewatering module, is the initial water content of the slurry, is the real-time water content of the slurry, is the real-time temperature of the slurry, , is a weight coefficient, is a vacuum system leakage correction coefficient.

8. The fully automated low-carbon UHPC mixing production line according to claim 1, characterized in that: The heat exchange efficiency optimization interface of the low-temperature curing tunnel waste heat recovery system adjusts the heat exchange parameters through a heat exchange efficiency optimization algorithm. The formula is as follows: ,in Real-time heat exchange efficiency of the waste heat recovery system. This refers to the real-time waste heat power of the planetary vacuum mixer motor. The target thermal power required for UHPC maintenance The exhaust temperature is the waste heat temperature of the motor. The target temperature for UHPC curing. , These are the weighting coefficients. This is the scaling correction factor for the heat exchanger.

9. The fully automated low-carbon UHPC mixing production line according to claim 1, characterized in that: The temperature and humidity coordinated control interface of the low-temperature maintenance tunnel achieves precise temperature and humidity control through the maintenance linkage control technology of fiber optic grating sensing + multi-point temperature and humidity feedback. The specific steps are as follows: three sets of fiber optic grating stress sensors and five temperature and humidity sensors are installed in the tunnel to collect intensity, real-time humidity and current temperature every hour. Judgment: Delayed strength development, easy cracking when RH < 85%, and negative impact on strength when RH > 95% are considered abnormal. Control measures: When intensity lags and RH is within acceptable limits, increase T by 3-5℃ from 40-60℃; if RH is insufficient, first increase humidification to 88%-92% and then decrease T by 2-3℃; if RH is too high, ventilate and adjust humidity to 90%-92%; 4. Cycle and test every 30 minutes. If the intensity meets the standard and RH is 85%-92% for two consecutive tests, stop adjusting.

10. A fully automated method for dispersing gradient fibers in low-carbon UHPC blending, applicable to the fully automated low-carbon UHPC blending production line described in any one of claims 1-9, characterized in that, The specific steps of this method are as follows: S1. Microwave drying of aggregates: The UHPC aggregates are dried using the microwave drying module built into the raw material premixing bin of the production line until the aggregate moisture content is ≤0.5%. S2. Fiber gradient dispersion: Coarse fibers, fine fibers, and nanofibers are fed into the fiber gradient dispersion tower of the production line, and are dispersed in layers through centrifugal sprayers, airflow suspension chambers, and electrostatic adsorption plates arranged in sequence inside the tower. S3. Planetary vacuum mixing and dewatering: The dried aggregate and dispersed fiber are fed into the planetary vacuum mixer of the production line. Through the mixing of double-revolutionary blades and self-rotating blades and the dewatering module, the porosity of the slurry is reduced to ≤1.5%. S4. Waste heat recovery curing: The mixed slurry is sent to the low-temperature curing tunnel of the production line. The tunnel is integrated with a waste heat recovery system for curing. The curing temperature is controlled at 40-60℃ and the curing time is 6-8 hours to complete the UHPC mixing and gradient fiber dispersion.

Images