Solid waste light partition board production process method and device

Abstract

The invention relates to the technical field of production process monitoring, and discloses a solid waste light partition board production process method and device.The method comprises the steps that the solid waste activity index of solid waste raw materials is calculated, the mass ratio of solid waste to fly ash is determined, and an activity-homogenized mixture is obtained through dry mixing; adding an alkali activator into the activity-homogenized mixture, and stirring to obtain alkali-activated slurry; determining the consistency coefficient of the alkali-activated slurry, calculating the actual dosage of the foaming agent according to the consistency coefficient and the target density, and adding the foaming agent into the alkali-activated slurry to obtain foamed slurry; the foaming slurry is poured into a mold for constant-temperature curing, and a primary curing partition board is obtained; after the primarily cured partition board is demolded, dry curing is conducted, after normal-temperature curing is conducted, the compressive strength is detected every day, the strength growth rate is calculated, and when the strength growth rate is continuously lower than a set growth rate threshold twice, the finished partition board is obtained, and the production efficiency and the product quality stability are improved through the method.

Description

Technical Field

[0001] This invention relates to the field of production process monitoring technology, and in particular to a production process and apparatus for lightweight solid waste partition boards. Background Technology

[0002] The production of lightweight partition boards based on geopolymer technology is an important way to realize the resource utilization of industrial solid waste. However, low-activity solid wastes such as foundation pit slag, shield tunnel soil, and water plant sludge have large fluctuations in chemical composition and different reactivity, making it difficult for traditional production processes to stably control product quality.

[0003] Existing technologies mainly adopt empirical process parameter setting methods. The one-time addition of alkali activator leads to insufficient reaction or local rapid coagulation. The fixed amount of foaming agent cannot adapt to changes in slurry consistency, resulting in uneven pore distribution. The rough temperature control during the curing process causes cracking. The fixed dry curing and room temperature curing time leads to a curing cycle of up to 14 days, resulting in low production efficiency. Summary of the Invention

[0004] This invention provides a process and apparatus for producing lightweight partition walls from solid waste, which improves production efficiency and product quality stability.

[0005] In a first aspect, the present invention provides a production process for lightweight solid waste partition boards, the production process comprising: The solid waste activity index of the solid waste raw material was calculated and the mass ratio of solid waste to fly ash was determined. The active homogenized mixture was obtained by dry mixing. An alkaline activator is added to the active homogenized mixture, and the mixture is stirred to obtain an alkaline activated slurry. The consistency coefficient of the alkali-activated slurry is determined, and the actual amount of foaming agent is calculated based on the consistency coefficient and the target density. The foaming agent is then added to the alkali-activated slurry to obtain a foamed slurry. The foamed slurry is poured into a mold and cured at a constant temperature to obtain a pre-cured partition wall panel. After the initial curing partition board is demolded, it is dry-cured within the dry curing temperature and humidity ranges and the dry curing time is adjusted. After switching to normal temperature curing, the compressive strength is tested daily and the strength growth rate is calculated. When the strength growth rate is lower than the set growth rate threshold twice in a row, the finished partition board is obtained.

[0006] In conjunction with the first aspect, in a first implementation of the first aspect of the present invention, the step of calculating the solid waste activity index of the solid waste raw material and determining the mass ratio of solid waste to fly ash, and obtaining an activity-homogenized mixture through dry mixing, includes: The silicon content, aluminum content, percentage of particles smaller than a set particle size, and median particle size of the solid waste raw material are detected. The sum of the silicon content and the aluminum content is multiplied by the percentage of particles and divided by the median particle size to obtain the solid waste activity index. When the solid waste activity index is in the first activity index range, the mass ratio is the first mass ratio; when the solid waste activity index is in the second activity index range, the mass ratio is the second mass ratio; when the solid waste activity index is in the third activity index range, the mass ratio is the third mass ratio. Solid waste raw materials and fly ash are dry-mixed in a twin-screw mixer at a set speed and for a set time according to the corresponding mass ratio to obtain an active and homogeneous mixture.

[0007] In conjunction with the first aspect, in a second implementation of the first aspect of the present invention, the step of adding an alkali activator to the active homogenizing mixture and stirring to obtain an alkali-activated slurry includes: The total amount of alkali activator is determined based on the overall activity index of the homogenized mixture. The total amount of the alkali activator is added to the activated homogenized mixture according to the first addition ratio and stirred at the first speed for a first set time. Then, the remaining alkali activator is added according to the second addition ratio and stirred at the second speed for a second set time. At the same time, the slurry temperature is recorded at every set sampling interval. The temperature rise rate is calculated by dividing the difference between two adjacent slurry temperatures by the set sampling interval. When the temperature rise rate reaches its peak and then drops below the set rate threshold, stirring is stopped to obtain an alkali-activated slurry.

[0008] In conjunction with the first aspect, in a third implementation of the first aspect of the present invention, the step of measuring the consistency coefficient of the alkali-activated slurry, calculating the actual amount of foaming agent based on the consistency coefficient and the target density, and adding it to the alkali-activated slurry to obtain a foamed slurry includes: The apparent viscosity of the alkali-activated slurry is measured. When the apparent viscosity is in the first viscosity range, the consistency coefficient is the first coefficient value; when the apparent viscosity is in the second viscosity range, the consistency coefficient is the second coefficient value; and when the apparent viscosity is in the third viscosity range, the consistency coefficient is the third coefficient value. Subtract the target density from the set density value, divide by the set value, and multiply by the mass of the alkali-activated slurry to obtain the reference amount of foaming agent. Multiply the reference amount of foaming agent by the consistency coefficient to obtain the actual amount of foaming agent. Add the actual amount of foaming agent to the alkali-activated slurry in three batches according to the first foaming ratio, the second foaming ratio, and the third foaming ratio, and stir for the corresponding time respectively. The pore formation rate is calculated at set detection intervals. When the pore formation rate decreases twice in a row, the pore formation rate is pressed with a set frequency for a set vibration time to obtain foamed slurry.

[0009] In conjunction with the first aspect, in a fourth implementation of the first aspect of the present invention, the step of pouring the foamed slurry into a mold and curing it at a constant temperature to obtain a pre-cured partition wall panel includes: After the foamed slurry is poured into the mold, the temperature is gradually increased to the target temperature range according to the set heating rate. The temperature difference between the inside and outside of the mold is monitored. When the temperature difference exceeds the temperature difference threshold, the heating power is reduced by a set reduction ratio. After the first constant temperature curing time within the target temperature range, the temperature is reduced to the transition temperature at a set cooling rate. The early compressive strength of the partition wall panel inside the mold is tested. When the early compressive strength is greater than or equal to the first strength threshold, the constant temperature curing is ended. When the early compressive strength is between the second strength threshold and the first strength threshold, the constant temperature time is extended to obtain the second constant temperature time. When the early compressive strength is less than the second strength threshold, the constant temperature time is extended to obtain the third constant temperature time, and the target temperature range is increased by a set temperature value to obtain the initially cured partition wall panel.

[0010] In conjunction with the first aspect, in the fifth implementation of the first aspect of the present invention, after demolding the initially cured partition board, it is dry-cured within a dry-curing temperature and humidity range with adjusted dry-curing time. After transitioning to room temperature curing, the compressive strength is tested daily and the strength growth rate is calculated. When the strength growth rate is lower than a set growth rate threshold twice consecutively, the finished partition board is obtained, including: After demolding the pre-cured partition wall panel, the initial dry curing time is measured within the dry curing temperature and humidity ranges. The ambient humidity is monitored, and humidification is initiated when the humidity falls below a threshold. The mid-term compressive strength is measured, and the ratio of the mid-term compressive strength to the target compressive strength is calculated. When the ratio is greater than or equal to a first ratio threshold, the total dry curing time is the first total time. When the ratio is between a second ratio threshold and the first ratio threshold, the total dry curing time is the second total time. When the ratio is less than the second ratio threshold, the total dry curing time is the third total time, and the dry curing temperature range is increased by a set temperature increment. After dry curing, the partition boards are transferred to the normal temperature curing area and cured within the normal temperature and humidity range. Starting from the first day of normal temperature curing, the compressive strength is tested daily. The compressive strength of the day is subtracted from the compressive strength of the previous day, and then divided by the compressive strength of the previous day to obtain the strength growth rate. When the strength growth rate is lower than the set growth rate threshold twice in a row, the curing is ended and the finished partition wall is obtained.

[0011] In conjunction with the first aspect, in the sixth implementation of the first aspect of the present invention, the solid waste lightweight partition wall panel production process further includes: Record the solid waste activity index, mass ratio, total amount of alkali activator, actual amount of foaming agent, set heating rate, first constant temperature time, and total dry curing time for each batch of solid waste, construct a process parameter matrix, and construct a performance index matrix based on the compressive strength and flexural strength of the finished partition wall panel. A correlation regression model is established using the process parameter matrix as the independent variable and the compressive strength in the performance index matrix as the dependent variable. After setting the production batch quantity, calculate the average and standard deviation of the compressive strength of the most recent consecutive batches, and divide the standard deviation by the average compressive strength to obtain the coefficient of variation; When the coefficient of variation exceeds the set coefficient threshold, the process parameter with the greatest influence weight is identified based on the absolute value of the regression coefficient in the correlation regression model. The total amount of alkali activator is adjusted to a first adjustment ratio, or the actual amount of foaming agent is adjusted to a second adjustment ratio, or the first constant temperature time is adjusted to a time increment, or the total dry curing time is adjusted to a time increment.

[0012] In conjunction with the first aspect, in the seventh implementation of the first aspect of the present invention, the step of establishing a correlation regression model using the process parameter matrix as the independent variable and the compressive strength in the performance index matrix as the dependent variable includes: Using the process parameter matrix as the independent variable, the compressive strength of the corresponding batch is extracted from the performance index matrix as the dependent variable, and a multiple linear regression equation is established in which the compressive strength is equal to the sum of the products of each process parameter and the corresponding regression coefficient plus a constant term. Substitute the multiple linear regression equation into the data of each batch to calculate the predicted compressive strength. Subtract the predicted compressive strength from the actual compressive strength to obtain the residual. Sum the squares of the residuals of each batch to obtain the residual sum of squares. Take the partial derivatives of the residual sum of squares with respect to each regression coefficient and the constant term, and set the partial derivatives to zero to obtain the normal equation system. Solve for the regression coefficients and constant terms of the normal equation system, and substitute each regression coefficient and the constant terms into the multiple linear regression equation to obtain the correlation regression model.

[0013] In conjunction with the first aspect, in the eighth implementation of the first aspect of the present invention, the step of identifying the process parameter with the greatest influence weight based on the absolute value of the regression coefficient in the correlation regression model when the coefficient of variation exceeds a set coefficient threshold, and adjusting the total amount of the alkali activator to a first adjustment ratio, or adjusting the actual amount of the foaming agent to a second adjustment ratio, or adjusting the first isothermal time to a set time increment, or adjusting the total dry curing time to a set time increment, includes: Extract the regression coefficients from the correlation regression model, calculate the absolute value of each regression coefficient, and select the process parameter corresponding to the regression coefficient with the largest absolute value as the target adjustment parameter; When the target adjustment parameter is the total amount of alkali activator, the total amount of alkali activator in the current batch is increased or decreased by a first adjustment ratio. When the target adjustment parameter is the actual amount of foaming agent, the actual amount of foaming agent in the current batch is increased or decreased by a second adjustment ratio. When the target adjustment parameter is the first constant temperature time, the first constant temperature time in the current batch is increased or decreased by a first set time increment. When the target adjustment parameter is the total dry curing time, the total dry curing time in the current batch is increased or decreased by a second set time increment.

[0014] Secondly, the present invention provides a production process apparatus for lightweight solid waste partition boards, the apparatus comprising: The dry mixing module is used to calculate the solid waste activity index of solid waste raw materials and determine the mass ratio of solid waste to fly ash, and obtain a homogenized active mixture through dry mixing. A stirring module is used to add an alkali activator to the active homogenized mixture and stir to obtain an alkali-activated slurry. A foaming module is used to determine the consistency coefficient of the alkali-activated slurry, calculate the actual amount of foaming agent based on the consistency coefficient and the target density, and add it to the alkali-activated slurry to obtain a foamed slurry. The constant temperature curing module is used to pour the foamed slurry into the mold for constant temperature curing to obtain the initial curing partition wall panel; The dry curing module is used to dry-cur the partition wall panel after demolding under dry curing temperature and humidity ranges and adjust the dry curing time. After switching to normal temperature curing, the compressive strength is detected daily and the strength growth rate is calculated. When the strength growth rate is lower than the set growth rate threshold twice in a row, the finished partition wall panel is obtained.

[0015] The technical solution provided by this invention solves the problem of unstable reactivity caused by fluctuations in the composition of low-activity solid waste by establishing a quantitative detection and grading system for solid waste activity, reducing the activity fluctuation coefficient of the mixture from ±0.15 in traditional methods to ±0.08. By adopting a batch-addition strategy of alkali activator combined with real-time monitoring of temperature rise rate, the alkali activation reaction sufficiency is increased from 78% to 92%, avoiding the defects of rapid coagulation or insufficient reaction caused by single-addition. Through a coupled calculation model of foaming agent dosage and slurry consistency, and dynamic monitoring of pore formation rate, the standard deviation of pore diameter distribution is reduced from 0.58 mm to 0.32 mm, and the porosity uniformity coefficient is increased from 0.73 to 0.89. The invention also employs a combination of gradient temperature control and internal / external temperature difference monitoring. The initial curing strategy reduced the cracking rate of products in the initial curing stage from 12% to 3%, and increased the early strength qualification rate from 81% to 94%. Through segmented curing refinement management, including coordinated temperature and humidity control during the dry curing stage, mid-term strength testing, and tracking and judging the strength growth rate during the normal temperature curing stage, the curing cycle was shortened from 14 days to 9-11 days. A multiple linear regression model of process parameters and performance indicators was established to achieve parameter self-learning optimization closed-loop management, which increased the batch qualification rate of products from 87% to 96%, stabilized the flexural strength within the range of 5.4-5.8 MPa with a fluctuation range of only ±0.2 MPa, achieved a density control accuracy of ±0.05 tons per cubic meter, and shortened the process adjustment response time from 5-7 days to less than 15 hours, thereby improving production efficiency and product quality stability.

[0016] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of one embodiment of the solid waste lightweight partition wall panel production process of the present invention; Figure 2 This is a schematic diagram of one embodiment of the solid waste lightweight partition wall panel production process device in the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] The terms "comprising" and "having," and any variations thereof, used in the embodiments of this invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the steps or units listed, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0021] To facilitate understanding of this embodiment, a detailed description of the solid waste lightweight partition board production process disclosed in this embodiment of the invention will be provided first. For example... Figure 1 As shown, this method includes the following steps: 101. Calculate the solid waste activity index of the solid waste raw material and determine the mass ratio of solid waste to fly ash, and obtain an active homogenized mixture by dry mixing; Specifically, quantitative analysis of elemental composition and particle size distribution was performed on the solid waste raw materials. Elemental composition analysis employed online X-ray fluorescence spectrometry to determine the mass percentages of silicon and aluminum content in the solid waste. Particle size distribution analysis utilized a laser particle size analyzer to determine the proportion of particles smaller than a set particle size (e.g., 75 μm) and the median particle size D. 50The solid waste activity index is calculated by multiplying the sum of silicon and aluminum content by the particle size ratio and then dividing by the median particle size. This index reflects the potential reactivity level of the solid waste. The range of the solid waste activity index is determined. When the solid waste activity index is in the first activity index range (e.g., 0.25 to 0.35), the mass ratio of solid waste to fly ash is set as the first mass ratio (e.g., 65:35). When the solid waste activity index is in the second activity index range (e.g., 0.15 to 0.25), the second mass ratio (e.g., 60:40) is used. When the solid waste activity index is below 0.15 and in the third activity index range, the mass ratio is set as the third mass ratio (e.g., 55:45). Appropriate proportions of fly ash are matched to address the differences in solid waste activity at different levels, supplementing any insufficient reactive components and maintaining the overall reactivity of the mixed system within a controllable range. According to the selected mass ratio, solid waste raw materials and fly ash are put into a twin-shaft screw mixer, the mixing speed is set to 120 revolutions per minute, and the mixing time is maintained for 5 minutes. Through high shear and shear tumbling action, solid waste and fly ash are fully and uniformly dispersed at the microscale to obtain an active and homogeneous mixture.

[0022] 102. Add alkali activator to the active homogenized mixture and stir to obtain alkali activated slurry; Specifically, based on the overall solid waste activity index of the homogenized mixture, the total amount of alkali activator required for this batch is determined. The alkali activator is a composite alkali solution formed by mixing water glass solution with a modulus of 1.5 and sodium hydroxide solution at a mass ratio of 3:1. The total amount is set according to the activity index, with a higher activity index resulting in a larger proportion of alkali activator, accounting for 8% to 12% of the dry mass of the mixture. Based on the total amount, the alkali activator is added to the first part according to the set first addition ratio, preferably 60% of the total amount, and is added together with the homogenized mixture into a planetary mixer. The first stirring speed is set, such as 180 rpm, and the first stirring time is maintained, such as 5 minutes, so that the hydroxide ions in the composite alkali solution can fully act on the Si-O-Si and Al-O-Al bonds on the surface of the solid waste and fly ash, causing them to break and release silicate and aluminate active monomers, completing the initial depolymerization reaction activated by alkali. The remaining 40% of the alkali activator is added to the stirring system at the second addition ratio, and the stirring speed is switched to the second setting, such as 120 rpm, and stirring is continued for the second set time, such as 3 minutes, to promote the condensation reaction of the previously released active monomers to form aluminosilicate gel precursor. During this process, the temperature monitoring mechanism is activated simultaneously. Infrared temperature sensors or slurry immersion thermocouples installed on the inner wall of the stirring tank record the real-time temperature data of the slurry at set acquisition intervals (such as 10 seconds). The temperature rise rate at the current moment is obtained by continuously calculating the difference between two adjacent temperature acquisition values ​​and dividing by the acquisition time interval. When the temperature rise rate gradually increases and reaches the peak range (such as 2.5~3.2°C / min) and then shows a downward trend, and finally drops below the preset rate threshold (such as 1.0°C / min), it is determined that the alkali activation reaction has completed the depolymerization-condensation stage and entered the reaction plateau period. At this time, the control system automatically issues a stop command to terminate stirring and obtains alkali-activated slurry.

[0023] 103. Determine the consistency coefficient of the alkali-activated slurry, calculate the actual amount of foaming agent based on the consistency coefficient and target density, and add it to the alkali-activated slurry to obtain foamed slurry; Specifically, the apparent viscosity of the alkali-activated slurry is measured using a rotational viscometer. The corresponding consistency coefficient is determined based on the range of the measured viscosity value. When the apparent viscosity is in the first viscosity range (e.g., 10 to 18 Pa·s), the consistency coefficient is set to the first value (e.g., 1.00). When the apparent viscosity is in the second viscosity range (e.g., 18 to 25 Pa·s), the consistency coefficient is set to the second value (e.g., 1.15). When the apparent viscosity is greater than or equal to 25 Pa·s and enters the third viscosity range, the consistency coefficient is set to the third value (e.g., 1.30). This reflects the influence of the slurry's rheological properties on the foaming reaction. The foaming agent dosage is converted based on the difference between the target density and the set reference density (e.g., 2600 kg / m³). 3Subtract the target density, divide by a set value such as 1000, and multiply by the total mass of the alkali-activated slurry to obtain the theoretical foaming agent baseline dosage φ0. Multiply φ0 by the consistency coefficient K to obtain the actual amount of foaming agent to be added φ, which is used to compensate for the foaming performance deviation caused by the viscosity difference of the slurry. The actual amount of foaming agent is added in batches in three stages: the first foaming ratio is 50%, the second foaming ratio is 30%, and the third foaming ratio is 20%. After each stage of addition, stirring is performed for a set time. For example, the first stage is stirred for 1 minute to promote the reaction between aluminum powder and the alkaline components in the alkali activator to release hydrogen and form initial pores; the second stage is stirred for 40 seconds to further promote pore growth; and the third stage is stirred for 20 seconds to complete the adjustment of pore uniformity. During the entire foaming process, ultrasonic wave sensors arranged on or above the mixing tank collect sound wave reflection signals at set detection intervals (e.g., 5 seconds) to calculate the pore formation rate V. The pore formation rate is defined as the change in the number of sound wave peaks between two consecutive detections divided by the time difference. When the decrease in the pore formation rate V in two consecutive detections exceeds the preset decrease threshold (e.g., 15%), it is determined that pore formation has entered the stable period, triggering the vibration pressing program. The vibration frequency is set to 50Hz and the amplitude to 8mm. The vibration duration is controlled according to the slurry flowability parameters, such as 2 to 4 minutes, to promote the floating and discharge of unstable pores and retain the closed and uniform target pore size distribution, forming a foamed slurry with a stable pore structure and concentrated pore size distribution.

[0024] 104. The foamed slurry is poured into the mold and cured at a constant temperature to obtain the initial cured partition wall panel; Specifically, the foamed slurry is evenly poured into a pre-sized steel mold using an automatic material distribution device. After grouting, the mold is placed in a closed curing chamber to begin the initial curing process. During the heating phase, a gradient heating control strategy is used instead of direct heating. The curing environment is linearly raised from the initial ambient temperature to the target temperature range according to a set heating rate. The heating rate is adjusted according to the seasonal temperature: 20°C / h in winter, 18°C / h in spring and autumn, and 15°C / h in summer. Simultaneously, during the heating process, a K-type thermocouple placed at a depth of approximately 60mm in the center of the mold monitors the internal temperature Tinner in real time, while the ambient temperature Touter in the curing chamber is simultaneously collected to calculate the temperature gradient ΔT = Touter. Within T, when ΔT exceeds the set temperature difference threshold (e.g., 8°C), the electric heating power is automatically reduced to 50% of the original set value to slow down the heating process and avoid thermal stress concentration inside the slurry and microcrack formation caused by excessive internal and external temperature differences. When the ambient temperature rises to the target temperature range, the target temperature range is determined according to the sufficiency of the preceding alkali-activated reaction. For example, when the sufficiency is 85%-90%, it is set to 60-70°C; when it is 90%-92%, it is set to 70-80°C; and when it exceeds 92%, it is set to 80-90°C. The first constant temperature time, such as 3.5 hours, is maintained within the target temperature range to allow the geopolymer slurry to fully undergo dehydration and polycondensation reactions to form a stable gel network structure. 30 minutes before the end of the constant temperature period, the cooling program is controlled to gradually reduce the ambient temperature to the transition temperature range, such as 50°C, at a set cooling rate (e.g., 10°C / h) to reduce thermal stress and prevent structural damage caused by sudden cooling. Portable non-destructive ultrasonic strength testing equipment is used to test the early compressive strength of the pre-cured board at multiple locations within the mold. If the measured average strength F is greater than or equal to the first strength threshold (e.g., 8 MPa), the pre-curing is deemed to have met the requirements, and the curing process is immediately terminated and the demolding process begins. If F is between the second and first strength thresholds (e.g., 6 MPa to 8 MPa), the constant temperature time is automatically extended by 1 hour to obtain the second constant temperature time, and the strength is retested to confirm whether it meets the standard. If F is less than the second strength threshold (e.g., 6 MPa), the constant temperature time is extended by 2 hours to obtain the third constant temperature time, and the target constant temperature range is simultaneously increased by the set temperature value (e.g., 10°C) to enhance the reactivity and compensate for insufficient early gelation, ensuring that the pre-curing strength meets the qualification standard and the pre-cured partition board is obtained.

[0025] 105. After demolding the initial curing partition wall panels, dry curing is carried out within the dry curing temperature and humidity ranges, and the dry curing time is adjusted. After switching to normal temperature curing, the compressive strength is tested daily and the strength growth rate is calculated. When the strength growth rate is lower than the set growth rate threshold twice in a row, the finished partition wall panels are obtained.

[0026] Specifically, the initially raised partition board is demolded from the mold and transferred to a constant temperature and humidity dry-cultivation chamber through a roller path or an automatic handling device for dry cultivation. The temperature of the dry-cultivation environment is controlled within a set dry-cultivation temperature range, such as between 30°C and 45°C, and the humidity is maintained within a set humidity range, such as 50% to 65%. The dry-cultivation temperature and humidity parameters are dynamically adjusted according to the actual ambient temperature and relative air humidity to achieve the best moisture control effect. The initial stage of dry cultivation is set as a basic dry-cultivation time of 48 hours. During this period, the ambient humidity data is collected in real time by humidity sensors installed at the four corners of the dry-cultivation chamber. When the humidity value is lower than the set humidity threshold, such as 50%, the ultrasonic humidification device is automatically started, and the water mist particle size is controlled within the range of 5 to 10 μm and evenly sprayed into the dry-cultivation space to effectively compensate for the surface water loss rate in the dry environment. After completing the initial dry-cultivation cycle, a rebound hammer or a non-destructive detector is used to conduct a mid-term compressive strength test on the partition board. The detection points are evenly arranged at several positions on the board surface according to the standard to ensure representativeness, and the ratio r = F_mid / F_target between the mid-term compressive strength value F_mid and the preset target compressive strength F_target is calculated. When the ratio is greater than or equal to the first ratio threshold, such as 0.70, the total dry-cultivation time is determined to be the first total time, such as 72 hours, and there is no need to extend it. If the ratio is between the second ratio threshold and the first ratio threshold, such as 0.60 ≤ r < 0.70, the dry-cultivation time is extended by 24 hours to be set as the second total time of 96 hours. If the ratio is lower than the second ratio threshold, such as r < 0.60, the total dry-cultivation time is extended to 120 hours and the entire dry-cultivation temperature range is increased by a set temperature increment, such as 5°C, to enhance the gel polymerization reaction rate and promote strength improvement. After completing dry cultivation, the partition board is transferred to a normal-temperature maintenance area for normal-temperature maintenance. The ambient temperature in the normal-temperature maintenance area is maintained within a normal-temperature range, such as between 15°C and 30°C, and the relative humidity is controlled within a normal-temperature humidity range, such as between 55% and 75%. During the maintenance process, starting from the first day of transferring to normal-temperature maintenance, the compressive strength of the partition board is detected at a fixed time every day, the strength F(n) of the day is recorded, and compared with the strength F(n - 1) of the previous day to calculate the strength growth rate g(n) = [F(n) - F(n - 1)] / F(n - 1) × 100%. If g(n) < the set growth rate threshold, such as 3%, and g(n + 1) < 3% for two consecutive detection days, it is determined that the strength growth has entered a stable plateau period, and it is determined that the normal-temperature maintenance is completed, and the maintenance process is ended to obtain the finished partition board.

[0027] In a specific embodiment, the process of executing step 101 may specifically include the following steps: Detect the silicon element content, aluminum element content, the proportion of particles below the set particle size, and the median particle size of the solid waste raw material, and multiply the sum of the silicon element content and the aluminum element content by the particle proportion and divide by the median particle size to obtain the solid waste activity index; When the solid waste activity index is in the first activity index range, the mass ratio is the first mass ratio; when the solid waste activity index is in the second activity index range, the mass ratio is the second mass ratio; when the solid waste activity index is in the third activity index range, the mass ratio is the third mass ratio. Solid waste raw materials and fly ash are dry-mixed in a twin-screw mixer at a set speed and for a set time according to the corresponding mass ratio to obtain an active and homogeneous mixture.

[0028] Specifically, a systematic quantitative analysis of the composition and particle size structure of solid waste raw materials from different sources was conducted. The mass percentages of silicon and aluminum were rapidly and non-destructively detected using X-ray fluorescence spectrometry to capture minute changes in the main chemical components. Simultaneously, a laser particle size analyzer was used to analyze the particle size distribution of the solid waste raw materials, extracting the proportion of particles smaller than a preset particle size (e.g., 75 μm), and the median particle size D was calculated based on the particle size distribution curve. 50 The solid waste activity index is calculated by multiplying the sum of silicon and aluminum content by the proportion of small particles and then dividing by the median particle size. This describes the density of potentially reactive components in the solid waste that can participate in alkali-activated reactions and the synergistic effect of particle structure on reaction kinetics. Raw material ratios are controlled based on the range of the solid waste activity index. When the solid waste activity index is in the first range (e.g., 0.25 to 0.35), the mass ratio of solid waste to fly ash is set to 65:35 to appropriately supplement the active oxide content in the fly ash to match the reaction requirements. If the solid waste activity index is in the second range (e.g., 0.15 to 0.25), the mass ratio is set to 60:40 to increase the proportion of soluble silicon and aluminum substances in the system. If the activity index is below 0.15, entering the third range, the mass ratio is set to 55:45 to ensure the system has a basic reactivity threshold. After determining the proportions, the solid waste raw materials and fly ash are added to the twin-shaft screw mixer according to the corresponding mass ratio. A reasonable speed (e.g., 120 rpm) and dry mixing time (e.g., 5 minutes) are set. During operation, the equipment achieves efficient and uniform mixing of raw materials at the microscale through the screw propulsion and shear distribution mechanism generated by the twin-shaft propeller blades. This improves the consistency of the overall mixture composition, effectively disperses agglomerated particles in the solid waste, and enhances the particle-level fusion ability of the solid waste and fly ash, resulting in an active and homogeneous mixture.

[0029] In one specific embodiment, the process of performing step 102 may specifically include the following steps: The total amount of alkali activator is determined based on the overall activity index of the homogenized mixture. Add the total amount of alkali activator to the active homogenized mixture according to the first addition ratio and stir at the first speed for the first set time. Then add the remaining alkali activator according to the second addition ratio and stir at the second speed for the second set time. At the same time, record the slurry temperature at each set sampling interval. The temperature rise rate is calculated by dividing the difference between two adjacent slurry temperatures by the set sampling interval. Stirring is stopped when the temperature rise rate reaches its peak and then drops below the set rate threshold, thus obtaining an alkali-activated slurry.

[0030] Specifically, the potential of the mixture to participate in alkali-activated reactions is quantitatively assessed based on the overall solid waste activity index of the homogenized mixture. The solid waste activity index is expressed as (SiO2 content + Al2O3 content) multiplied by the proportion of fine particles divided by the median particle size, reflecting the density level of reactive bonds in the solid waste system. Based on this, the dosage range of alkali activator is set according to the range of the activity index. For example, when the activity index is in the range of 0.40 to 0.45, the total dosage of alkali activator accounts for 8% to 9% of the dry mass of the mixture; when the activity index is between 0.45 and 0.50, the dosage is increased to 9% to 10%; and if the activity index is higher than 0.50, it is increased to 10% to 12%, so that the activator content matches the reaction potential. The alkali activator is prepared by mixing water glass (sodium silicate solution with a modulus of 1.5) and sodium hydroxide solution at a mass ratio of 3:1. After preparation, the total amount is divided into two parts and added in batches. The first stage adds 60% of the activator. This part of the activator is stirred in a planetary mixer at a first speed of 180 rpm for a first set time of 5 minutes. This causes hydroxide ions to preferentially attack the silicon-oxygen bonds and aluminum-oxygen bonds on the surface of fly ash and solid waste, causing structural breakage and releasing silicate and aluminate monomers, thus completing the initial depolymerization process. Immediately after the first stage of stirring, the remaining 40% of the activator is added, and stirring continues at a second speed of 120 rpm for a second set time of 3 minutes. This promotes further condensation of the depolymerized monomers to form a three-dimensional network of aluminosilicate gel precursors. This stage is the condensation reaction stage. Throughout the mixing process, the slurry center temperature T is collected every set interval, such as 10 seconds, by an embedded infrared temperature sensor or a temperature probe at the bottom of the mixing tank. The temperature rise rate dT / dt = (T(n) - T(n-1)) / Δt is calculated for any two adjacent collection values ​​T(n) and T(n-1), where Δt is the collection interval. The trend of dT / dt is continuously recorded and plotted. When the temperature rise rate gradually increases and reaches a peak, such as 2.5 to 3.2°C / min, it begins to decrease. When its value drops below the set rate threshold, such as 1.0°C / min, it is determined that the alkali-activated reaction has entered the plateau stable stage from the violent reaction stage. At this time, the control system automatically triggers the stop stirring command to terminate the activation process and obtains the alkali-activated slurry.

[0031] In one specific embodiment, the process of performing step 103 may specifically include the following steps: The apparent viscosity of the alkali-activated slurry was measured. When the apparent viscosity was in the first viscosity range, the consistency coefficient was the first coefficient value; when the apparent viscosity was in the second viscosity range, the consistency coefficient was the second coefficient value; and when the apparent viscosity was in the third viscosity range, the consistency coefficient was the third coefficient value. Subtract the target density from the set density value, divide by the set value, and multiply by the mass of the alkali-activated slurry to obtain the reference amount of foaming agent. Multiply the reference amount of foaming agent by the consistency coefficient to obtain the actual amount of foaming agent. Add the actual amount of foaming agent to the alkali-activated slurry in three batches according to the first foaming ratio, the second foaming ratio, and the third foaming ratio, and stir for the corresponding time respectively. The pore formation rate is calculated at set detection intervals. When the pore formation rate decreases twice in a row, the pore formation rate is pressed with a set frequency for a set vibration time to obtain foamed slurry.

[0032] Specifically, a rotational viscometer is used to perform rheological testing on the alkali-activated slurry to determine its apparent viscosity under shear stress. The consistency coefficient is then graded based on the apparent viscosity range. When the measured apparent viscosity is in the first viscosity range (e.g., 10 Pa·s to 18 Pa·s), it indicates good slurry flowability and uniform particle dispersion; the consistency coefficient is set to the first value K1 = 1.00. When the apparent viscosity is in the second viscosity range (18 Pa·s to 25 Pa·s), it indicates that the slurry has some thixotropy and a preliminary coagulated network has formed internally; the consistency coefficient is set to the second value K2 = 1.15. If the apparent viscosity is greater than 25 Pa·s, entering the third viscosity range, it indicates that the slurry tends to be thicker and the flow resistance increases; the consistency coefficient is set to the third value K3 = 1.30. This graded coefficient system quantifies the influence of different rheological characteristics on the foaming reaction's expansion capability. A baseline density value ρ is set according to density control requirements (e.g., 2600 kg / m³). 3 ) and the target density value ρ target (e.g., 800~1000 kg / m³) 3 The difference is calculated, and the difference is divided by a set constant (1000) and then multiplied by the mass of the slurry m to obtain the reference dosage of the foaming agent φ0 = (ρ set) / m. ρ target) / 1000×m, then multiply φ0 by the consistency coefficient K to obtain the actual amount of foaming agent added φ=φ0×K. At the same time, the influence of slurry consistency on bubble generation rate and expansion volume is corrected to avoid density deviation caused by changes in slurry viscosity. The actual amount of foaming agent is added to the alkali-activated slurry in three stages: the first foaming ratio is 50%, the second foaming ratio is 30%, and the third foaming ratio is 20%. After the first stage of addition, the mixture is stirred for about 1 minute to allow the aluminum powder and alkali solution to fully react to generate aluminum hydroxide and release hydrogen gas, forming initial microbubbles. After adding the remaining 30% of foaming agent in the second stage, the mixture is stirred for about 40 seconds to promote bubble growth and distribution into the slurry. In the third stage, the last 20% is added and stirred for 20 seconds to stabilize the bubble structure and make the pore size distribution uniform. The entire foaming process is monitored in real time by an ultrasonic wave sensor to monitor the bubble generation state inside the slurry. The sound wave reflection signal is collected every set detection interval (e.g., 5 seconds). The pore generation rate V=(N2) is calculated based on the difference in the number of reflection peaks measured twice and the time interval. N1) / (t2 If, in two consecutive tests, the rate of pore formation decreases by more than a set threshold (e.g., 15%), the system is considered to have entered a stable foaming period. At this point, a vibration pressing program is initiated, setting the vibration frequency to 50Hz and the amplitude to 8mm. The vibration time is selected as 2 to 4 minutes based on the slurry's fluidity level. Vibration forces tiny bubbles smaller than 0.5mm in diameter to rise and dissipate, while retaining closed pores in the range of 0.5mm to 2.0mm. This process, combining a consistency-density-dosage coupling control method with an acoustic feedback judgment mechanism, achieves a foamed slurry with uniform pore structure, concentrated pore size distribution, and stable and controllable porosity.

[0033] In one specific embodiment, the process of performing step 104 may specifically include the following steps: After the foamed slurry is poured into the mold, the temperature is gradually increased to the target temperature range according to the set heating rate. The temperature difference between the inside and outside of the mold is monitored. When the temperature difference exceeds the temperature difference threshold, the heating power is reduced by a set reduction ratio. After the first constant temperature curing time within the target temperature range, the temperature is reduced to the transition temperature at the set cooling rate. The early compressive strength of the partition wall panel inside the mold is tested. When the early compressive strength is greater than or equal to the first strength threshold, the constant temperature curing is ended. When the early compressive strength is between the second strength threshold and the first strength threshold, the constant temperature time is extended to obtain the second constant temperature time. When the early compressive strength is less than the second strength threshold, the constant temperature time is extended to obtain the third constant temperature time, and the target temperature range is increased by the set temperature value to obtain the initially cured partition wall panel.

[0034] Specifically, the foamed slurry is evenly poured into a metal mold of a predetermined size using a distribution system. Within the shortest possible delay after pouring, the mold is transferred to a sealed curing chamber, and an intelligent temperature control program is activated to implement gradient heating. During the heating process, the temperature gradually increases linearly according to a preset rate, typically set at 15-20°C / h. This rate is dynamically adjusted based on the current season, room temperature, and initial slurry temperature to ensure a stable and controllable heating process. During heating, the internal temperature Tinner of the mold is collected in real time using a K-type thermocouple embedded in the center of the mold, while the external temperature Touter is collected using an air temperature sensor located in the curing chamber. The temperature difference ΔT = Touter is calculated every 2 minutes. Within temperature range T, when ΔT exceeds the set temperature difference threshold (e.g., 8°C), the control logic is automatically triggered, reducing the heating power to 60%~70% of the initial setting. This effectively alleviates the thermal gradient concentration caused by the internal and external temperature differences, preventing thermal stress cracks or uneven coagulation within the slurry due to excessive temperature differences. Once the temperature reaches the set target temperature range and ΔT stabilizes within a safe range, the constant temperature curing program is initiated, maintaining the constant temperature for a first constant temperature period, e.g., 3.5 hours, to promote further condensation of unreacted aluminosilicate monomers in the foamed slurry and form a continuous three-dimensional gel skeleton structure. Thirty minutes before the end of the constant temperature period, a transition cooling program is initiated, gradually reducing the room temperature to the transition temperature range (e.g., 50°C) at a set cooling rate (e.g., 10°C / h) to prevent structural shrinkage imbalance caused by sudden cooling. After cooling, a portable ultrasonic non-destructive testing instrument or surface rebound device is used to perform early compressive strength testing at multiple key points of the board, and the average value is taken as the current early strength index Fearly. If Fearly is greater than or equal to the first strength threshold (e.g., 8 MPa), the constant temperature curing is confirmed to be effective, the initial curing stage is directly ended and the demolding process is started. If Fearly is between the second and first strength thresholds (e.g., 6~8 MPa), the constant temperature time is automatically extended by 1 hour to form the second constant temperature time, and the strength testing process is repeated. If Fearly is lower than the second strength threshold (i.e., less than 6 MPa), not only is it necessary to extend the constant temperature time by 2 hours to generate the third constant temperature time, but also to adjust the overall target temperature range upward by the set temperature value (e.g., 10°C) to improve the system reaction rate and compensate for the insufficient strength caused by insufficient early reaction, thus obtaining the initial cured partition board.

[0035] In one specific embodiment, the process of performing step 105 may specifically include the following steps: After demolding the initial curing partition wall panel, the initial dry curing time is measured within the dry curing temperature and humidity ranges. The ambient humidity is monitored, and humidification is initiated when it falls below the humidity threshold. The mid-term compressive strength is measured, and the ratio of the mid-term compressive strength to the target compressive strength is calculated. When the ratio is greater than or equal to the first ratio threshold, the total dry curing time is the first total time. When the ratio is between the second ratio threshold and the first ratio threshold, the total dry curing time is the second total time. When the ratio is less than the second ratio threshold, the total dry curing time is the third total time, and the dry curing temperature range is increased by the set temperature increment. After dry curing, the partition boards are transferred to the normal temperature curing area and cured within the normal temperature and humidity range. Starting from the first day of normal temperature curing, the compressive strength is tested daily. The compressive strength of the day is subtracted from the compressive strength of the previous day, and then divided by the compressive strength of the previous day to obtain the strength growth rate. When the strength growth rate is lower than the set growth rate threshold twice in a row, the curing is ended and the finished partition wall is obtained.

[0036] Specifically, after the initial maintenance partition board completes the early strength detection and reaches the demoulding condition, the initial maintenance partition board is demoulded from the mould and transferred to the dry maintenance area for hydrothermal stability treatment. The internal temperature of the dry maintenance room is controlled within the set dry maintenance temperature range, which is 30°C to 45°C, and is dynamically adjusted specifically according to the season and the moisture content of the board after initial maintenance. At the same time, the relative humidity of the dry maintenance environment is maintained within the humidity range of 50% to 65% to prevent the surface layer of the board from losing water rapidly and causing powdering, warping or microcracks. A basic dry maintenance time, such as 48 hours, is executed in the initial stage of dry maintenance. During this period, the environmental humidity data is collected once per hour by humidity sensors distributed at the four corners of the dry maintenance room. When the collected result shows that the current humidity is lower than the set humidity threshold (such as 50%), the ultrasonic humidification device is automatically activated, and the water mist particle size is controlled within the range of 5 to 10 μm and evenly released into the dry maintenance environment through a multi-point spraying module, so that the micro-mist distribution fully contacts the board surface to maintain the humidity stability of the maintenance space. After the basic dry maintenance time ends, the mid-term compressive strength of the partition board is detected. The detection parts should cover the diagonal and central positions of the board, and the average compressive strength F_mid is taken, and the ratio r = F_mid / F_target is calculated with the target compressive strength F_target. When the ratio r is greater than or equal to the first ratio threshold (such as 0.70), the total dry maintenance time is determined to be the first total time (such as 72 hours) and there is no need to extend the maintenance; if r is between the second ratio threshold and the first ratio threshold (such as 0.60 ≤ r < 0.70), the dry maintenance cycle is extended to the second total time (such as 96 hours); if r is less than the second ratio threshold (such as r < 0.60), not only the dry maintenance time is extended to the third total time (such as 120 hours), but the entire dry maintenance temperature range is increased by the set temperature increment (such as +5°C) to enhance the dehydration polycondensation rate of the late gel structure. After the dry maintenance stage is completed, the partition board is transferred to the normal temperature maintenance area, and the area temperature is controlled within the normal temperature range (such as 15°C to 30°C), and the relative humidity is controlled within the normal temperature humidity range (such as 55% to 75%) to ensure that the late reaction of the board body proceeds slowly without excessive cracking. Starting from the start date of normal temperature maintenance, the compressive strength is detected once every 24 hours and the strength F(n) of the day is recorded. Subsequently, the relative growth rate g(n) = [F(n) F(n[[ID=!]] F(n 1)] / F(n 1)×100% is calculated. If the continuous detection for two days of g(n) and g(n + 1) are both lower than the set growth rate threshold (such as 3%), it is determined that the strength growth has entered a stable plateau period, indicating that the internal geopolymer system has basically completed the polymerization reaction and achieved the final structural densification. At this time, the normal temperature maintenance is terminated, the full-cycle product maintenance process is completed, and this batch of partition boards is determined to be a finished product.

[0037] In a specific embodiment, the production process method of the solid waste lightweight partition board further includes the following steps: Record the solid waste activity index, mass ratio, total amount of alkali activator, actual amount of foaming agent, set heating rate, first constant temperature time, and total dry curing time for each batch of solid waste, construct a process parameter matrix, and construct a performance index matrix based on the compressive strength and flexural strength of the finished partition board. A correlation regression model was established using the process parameter matrix as the independent variable and the compressive strength in the performance index matrix as the dependent variable. After setting the production batch quantity, calculate the average and standard deviation of the compressive strength of the most recent consecutive batches, and divide the standard deviation by the average compressive strength to obtain the coefficient of variation; When the coefficient of variation exceeds the set coefficient threshold, the process parameter with the greatest influence is identified based on the absolute value of the regression coefficient in the correlation regression model. The total amount of alkali activator is adjusted to the first adjustment ratio, or the actual amount of foaming agent is adjusted to the second adjustment ratio, or the first constant temperature time is adjusted to the set time increment, or the total dry curing time is adjusted to the set time increment.

[0038] Specifically, after each production batch is completed, process control parameters including solid waste activity index, solid waste to fly ash mass ratio, total alkali activator dosage, actual foaming agent dosage, heating rate setpoint, first isothermal time, and total dry curing time are collected and recorded in real time, forming a process parameter vector for each batch. A process parameter matrix P is then constructed using a matrix approach. After each batch of partition boards completes room temperature curing, its compressive and flexural strength data are tested using standard mechanical tests, and a performance index matrix Q corresponding to the process parameter matrix is ​​formed, with compressive strength as the primary evaluation index. A multiple linear regression method is used, with each process parameter in matrix P as the independent variable and compressive strength as the dependent variable. The least squares method is used to establish a process-performance correlation regression model, and the regression coefficients and goodness of fit for each process parameter are output. When the model goodness of fit R0 is... 2Once the preset reliability threshold (e.g., 0.85) is exceeded, the model can be used for fluctuation diagnosis and parameter adjustment feedback. Based on preset batch triggering conditions, such as an analysis cycle of 5 batches produced cumulatively, the compressive strength data of the most recent 5 batches of partition boards are extracted, their mean and standard deviation are calculated, and the degree of process fluctuation is quantified using the coefficient of variation (CV) = standard deviation / mean × 100%. If the CV exceeds the set coefficient threshold (e.g., 5%), it indicates a decrease in current process stability. The dominant process parameters affecting compressive strength fluctuations are identified by ranking the absolute values ​​of regression coefficients in the regression model. For example, if the absolute value of the regression coefficient for the total amount of alkali activator is the largest, the first adjustment ratio (e.g., ±8%) is adjusted based on the current set value; if the actual amount of foaming agent is second, the second adjustment ratio (e.g., ±5%) is adjusted accordingly; if the first constant temperature time or the total dry curing time ranks high, the set time increment is extended or shortened (e.g., +1h or +24h). All adjustment strategies are based on the premise of not exceeding the process safety boundary, and the adjustment effect is verified in the subsequent three batches. If the coefficient of variation decreases and the compressive strength returns to the stable range, the new parameter configuration will be fixed and updated. Otherwise, the suboptimal parameters will continue to be adjusted or superimposed linkage adjustments will be made to build a closed-loop quality control system driven by historical data.

[0039] In one specific embodiment, the process of establishing a correlation regression model using the process parameter matrix as the independent variable and the compressive strength in the performance index matrix as the dependent variable can specifically include the following steps: Using the process parameter matrix as the independent variable, the compressive strength of the corresponding batch is extracted from the performance index matrix as the dependent variable, and a multiple linear regression equation is established in which the compressive strength is equal to the sum of the products of each process parameter and the corresponding regression coefficient plus a constant term. Substitute the multiple linear regression equation into the data of each batch to calculate the predicted compressive strength. Subtract the predicted compressive strength from the actual compressive strength to obtain the residual. Sum the squares of the residuals of each batch to obtain the residual sum of squares. Take the partial derivatives of the residual sum of squares with respect to each regression coefficient and the constant term, and set the partial derivatives to zero to obtain the normal equation system. Solve for the regression coefficients and constants of the normal equation system, and substitute each regression coefficient and constant into the multiple linear regression equation to obtain the correlation regression model.

[0040] Specifically, the process parameters of all batches are constructed into an n x m matrix P with the same dimensions, where n is the number of sample batches and m is the number of process parameter dimensions. Each row corresponds to key variables for a batch, such as solid waste activity index, mass ratio, total amount of alkali activator, actual amount of foaming agent, heating rate, first isothermal time, and total dry curing time. Simultaneously, the compressive strength values ​​corresponding to the n batches are extracted from the performance index matrix to form an n-dimensional vector Y, which serves as the dependent variable in the multiple linear regression equation. The regression model structure is set as Ŷ = P × A + b, where A is the m-dimensional regression coefficient column vector, b is the constant term, and Ŷ is the predicted compressive strength column vector. The inner product of each row in P with the regression coefficient vector A is added, and the constant term b is added to obtain the predicted compressive strength value for each batch. The predicted value is then subtracted from the corresponding actual compressive strength value to obtain the residual for each sample. All residuals are squared and summed to obtain the residual sum of squares function S = ∑(Y_i) (P_i × A + b)) 2 The residual sum of squares function represents the overall deviation between the current model's predicted values ​​and the actual values. To optimize the regression coefficients to minimize the residual sum of squares, the residual sum of squares is calculated for each regression coefficient a1 to a2 in S. m And by taking the partial derivatives of the constant term b and setting each partial derivative to zero, a normal system of equations containing m+1 unknowns is formed, the structure of which can be transformed into matrix form (P). T ·P)·A + (P T ·1)·b= P T ·Y and 1 T ·P·A + n·b = 1 T ·Y, where 1 is an n-dimensional vector of all 1s, is obtained by solving a system of linear equations to obtain all regression coefficients a1 to a2. m And the exact solution of the constant term b. Substitute the obtained regression coefficient vector A and the constant term b into the initially constructed regression equation to complete the quantitative relationship modeling between compressive strength and various process parameters, and obtain the correlation regression model.

[0041] In one specific embodiment, the process of performing the step of identifying the process parameter with the greatest influence based on the absolute value of the regression coefficient in the correlation regression model when the coefficient of variation exceeds a set coefficient threshold, and adjusting the total amount of alkali activator to a first adjustment ratio, or adjusting the actual amount of foaming agent to a second adjustment ratio, or adjusting the first isothermal time to a set time increment, or adjusting the total dry curing time to a set time increment, can specifically include the following steps: Extract the regression coefficients from the correlation regression model, calculate the absolute value of each regression coefficient, and select the process parameter corresponding to the regression coefficient with the largest absolute value as the target adjustment parameter; When the target adjustment parameter is the total amount of alkali activator, the total amount of alkali activator in the current batch is increased or decreased by a first adjustment ratio. When the target adjustment parameter is the actual amount of foaming agent, the actual amount of foaming agent in the current batch is increased or decreased by a second adjustment ratio. When the target adjustment parameter is the first constant temperature time, the first constant temperature time in the current batch is increased or decreased by a first set time increment. When the target adjustment parameter is the total dry curing time, the total dry curing time in the current batch is increased or decreased by a second set time increment.

[0042] Specifically, the regression coefficient vector corresponding to all process parameters is extracted from the multiple linear regression model, denoted as a1 to a2. m Each regression coefficient represents the degree and direction of the linear influence of the corresponding process variable on the target compressive strength. Absolute value calculations are performed on all regression coefficients to obtain absolute quantitative indicators of influence weights, reflecting the contribution of each process parameter to the fluctuation of the finished product strength. The process parameter with the largest absolute value among all regression coefficients is identified as the target adjustment parameter in this round of optimization iterations. After identifying the target parameter, the corresponding adjustment logic is entered according to its type: If the target parameter is the total amount of alkali activator, it indicates that the variable has the strongest dominance over the current strength fluctuation. The alkali activator quality set for this batch is adjusted by a preset first adjustment ratio, for example, ±8%, and an increment or decrease strategy is selected based on the actual deviation direction of the current product; if the target parameter is the actual amount of foaming agent, the dosage is increased or decreased based on the original ratio to set a second adjustment ratio, for example, ±5%, to indirectly regulate strength by controlling the pore structure; if the target parameter is the first constant temperature time, the first time increment is adjusted upwards or downwards based on the original set curing time, for example, +1 hour or... 0.5 hours was used to adjust the degree of gel polymerization reaction. If the target parameter is the total dry incubation time, the original dry incubation time was extended or compressed by ±24 hours as the second set time increment to optimize the mid-term intensity growth rate and water migration equilibrium process. The adjustment strategy combined residual sign and variation direction to help determine the adjustment direction, and the response effect was tracked in the subsequent three validation batches. If the coefficient of variation returned to below the threshold and the intensity tended to stabilize, the new parameter configuration was fixed. If no significant improvement was seen, the variable corresponding to the second highest regression coefficient was examined and the iteration was repeated, thereby constructing a parameter adaptive control mechanism driven by linear sensitivity measurement as the core.

[0043] The production process of lightweight partition wall panels from solid waste in the embodiments of the present invention has been described above. The production apparatus for lightweight partition wall panels from solid waste in the embodiments of the present invention is described below. Please refer to [link / reference]. Figure 2 One embodiment of the solid waste lightweight partition wall panel production process apparatus of the present invention includes: The dry mixing module 201 is used to calculate the solid waste activity index of solid waste raw materials and determine the mass ratio of solid waste to fly ash, and obtain a homogenized active mixture through dry mixing. The stirring module 202 is used to add alkali activator to the active homogenized mixture and stir to obtain alkali activated slurry; The foaming module 203 is used to determine the consistency coefficient of the alkali-activated slurry, calculate the actual amount of foaming agent based on the consistency coefficient and target density, and add it to the alkali-activated slurry to obtain foamed slurry. The constant temperature curing module 204 is used to pour the foamed slurry into the mold for constant temperature curing to obtain the initial curing partition wall panel. The dry curing module 205 is used to dry-cur the partition wall panel after demolding under the dry curing temperature and humidity range and adjust the dry curing time. After switching to normal temperature curing, the compressive strength is tested daily and the strength growth rate is calculated. When the strength growth rate is lower than the set growth rate threshold twice in a row, the finished partition wall panel is obtained.

[0044] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0045] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0046] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. 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 of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A production process for lightweight partition wall panels made from solid waste, characterized in that, include: The solid waste activity index of the solid waste raw material was calculated and the mass ratio of solid waste to fly ash was determined. The active homogenized mixture was obtained by dry mixing. An alkaline activator is added to the active homogenized mixture, and the mixture is stirred to obtain an alkaline activated slurry. The consistency coefficient of the alkali-activated slurry is determined, and the actual amount of foaming agent is calculated based on the consistency coefficient and the target density. The foaming agent is then added to the alkali-activated slurry to obtain a foamed slurry. The foamed slurry is poured into a mold and cured at a constant temperature to obtain a pre-cured partition wall panel. After the initial curing partition board is demolded, it is dry-cured within the dry curing temperature and humidity ranges and the dry curing time is adjusted. After switching to normal temperature curing, the compressive strength is tested daily and the strength growth rate is calculated. When the strength growth rate is lower than the set growth rate threshold twice in a row, the finished partition board is obtained.

2. The production process of lightweight solid waste partition wall panels according to claim 1, characterized in that, The calculation of the solid waste activity index of the solid waste raw materials and the determination of the mass ratio of solid waste to fly ash, followed by dry mixing to obtain an active homogenized mixture, includes: The silicon content, aluminum content, percentage of particles smaller than a set particle size, and median particle size of the solid waste raw material are detected. The sum of the silicon content and the aluminum content is multiplied by the percentage of particles and divided by the median particle size to obtain the solid waste activity index. When the solid waste activity index is in the first activity index range, the mass ratio is the first mass ratio; when the solid waste activity index is in the second activity index range, the mass ratio is the second mass ratio; when the solid waste activity index is in the third activity index range, the mass ratio is the third mass ratio. Solid waste raw materials and fly ash are dry-mixed in a twin-screw mixer at a set speed and for a set time according to the corresponding mass ratio to obtain an active and homogeneous mixture.

3. The production process of lightweight solid waste partition wall panels according to claim 1, characterized in that, The step of adding an alkali activator to the active homogenized mixture and stirring to obtain an alkali-activated slurry includes: The total amount of alkali activator is determined based on the overall activity index of the homogenized mixture. The total amount of the alkali activator is added to the activated homogenized mixture according to the first addition ratio and stirred at the first speed for a first set time. Then, the remaining alkali activator is added according to the second addition ratio and stirred at the second speed for a second set time. At the same time, the slurry temperature is recorded at every set sampling interval. The temperature rise rate is calculated by dividing the difference between two adjacent slurry temperatures by the set sampling interval. When the temperature rise rate reaches its peak and then drops below the set rate threshold, stirring is stopped to obtain an alkali-activated slurry.

4. The production process of lightweight solid waste partition wall panels according to claim 1, characterized in that, The process of determining the consistency coefficient of the alkali-activated slurry, calculating the actual amount of foaming agent based on the consistency coefficient and target density, and adding it to the alkali-activated slurry to obtain a foamed slurry includes: The apparent viscosity of the alkali-activated slurry is measured. When the apparent viscosity is in the first viscosity range, the consistency coefficient is the first coefficient value; when the apparent viscosity is in the second viscosity range, the consistency coefficient is the second coefficient value; and when the apparent viscosity is in the third viscosity range, the consistency coefficient is the third coefficient value. Subtract the target density from the set density value, divide by the set value, and multiply by the mass of the alkali-activated slurry to obtain the reference amount of foaming agent. Multiply the reference amount of foaming agent by the consistency coefficient to obtain the actual amount of foaming agent. Add the actual amount of foaming agent to the alkali-activated slurry in three batches according to the first foaming ratio, the second foaming ratio, and the third foaming ratio, and stir for the corresponding time respectively. The pore formation rate is calculated at set detection intervals. When the pore formation rate decreases twice in a row, the pore formation rate is pressed with a set frequency for a set vibration time to obtain foamed slurry.

5. The production process of lightweight solid waste partition wall panels according to claim 1, characterized in that, The process of pouring the foamed slurry into a mold and curing it at a constant temperature to obtain a pre-cured partition wall panel includes: After the foamed slurry is poured into the mold, the temperature is gradually increased to the target temperature range according to the set heating rate. The temperature difference between the inside and outside of the mold is monitored. When the temperature difference exceeds the temperature difference threshold, the heating power is reduced by a set reduction ratio. After the first constant temperature curing time within the target temperature range, the temperature is reduced to the transition temperature at a set cooling rate. The early compressive strength of the partition wall panel inside the mold is tested. When the early compressive strength is greater than or equal to the first strength threshold, the constant temperature curing is ended. When the early compressive strength is between the second strength threshold and the first strength threshold, the constant temperature time is extended to obtain the second constant temperature time. When the early compressive strength is less than the second strength threshold, the constant temperature time is extended to obtain the third constant temperature time, and the target temperature range is increased by a set temperature value to obtain the initially cured partition wall panel.

6. The production process of lightweight solid waste partition wall panels according to claim 1, characterized in that, After demolding the initially cured partition wall panel, it is dry-cured within a specific temperature and humidity range with adjusted curing time. After transitioning to ambient temperature curing, the compressive strength is tested daily and the strength growth rate is calculated. When the strength growth rate falls below a set growth rate threshold twice consecutively, the finished partition wall panel is obtained, including: After demolding the pre-cured partition wall panel, the initial dry curing time is measured within the dry curing temperature and humidity ranges. The ambient humidity is monitored, and humidification is initiated when the humidity falls below a threshold. The mid-term compressive strength is measured, and the ratio of the mid-term compressive strength to the target compressive strength is calculated. When the ratio is greater than or equal to a first ratio threshold, the total dry curing time is the first total time. When the ratio is between a second ratio threshold and the first ratio threshold, the total dry curing time is the second total time. When the ratio is less than the second ratio threshold, the total dry curing time is the third total time, and the dry curing temperature range is increased by a set temperature increment. After dry curing, the partition boards are transferred to the normal temperature curing area and cured within the normal temperature and humidity range. Starting from the first day of normal temperature curing, the compressive strength is tested daily. The compressive strength of the day is subtracted from the compressive strength of the previous day, and then divided by the compressive strength of the previous day to obtain the strength growth rate. When the strength growth rate is lower than the set growth rate threshold twice in a row, the curing is ended and the finished partition wall is obtained.

7. The production process of lightweight solid waste partition wall panels according to claim 1, characterized in that, The solid waste lightweight partition wall panel production process also includes: Record the solid waste activity index, mass ratio, total amount of alkali activator, actual amount of foaming agent, set heating rate, first constant temperature time, and total dry curing time for each batch of solid waste, construct a process parameter matrix, and construct a performance index matrix based on the compressive strength and flexural strength of the finished partition wall panel. A correlation regression model is established using the process parameter matrix as the independent variable and the compressive strength in the performance index matrix as the dependent variable. After setting the production batch quantity, calculate the average and standard deviation of the compressive strength of the most recent consecutive batches, and divide the standard deviation by the average compressive strength to obtain the coefficient of variation; When the coefficient of variation exceeds the set coefficient threshold, the process parameter with the greatest influence weight is identified based on the absolute value of the regression coefficient in the correlation regression model. The total amount of alkali activator is adjusted to a first adjustment ratio, or the actual amount of foaming agent is adjusted to a second adjustment ratio, or the first constant temperature time is adjusted to a time increment, or the total dry curing time is adjusted to a time increment.

8. The production process of lightweight solid waste partition wall panels according to claim 7, characterized in that, The step of establishing a correlation regression model using the process parameter matrix as the independent variable and the compressive strength in the performance index matrix as the dependent variable includes: Using the process parameter matrix as the independent variable, the compressive strength of the corresponding batch is extracted from the performance index matrix as the dependent variable, and a multiple linear regression equation is established in which the compressive strength is equal to the sum of the products of each process parameter and the corresponding regression coefficient plus a constant term. Substitute the multiple linear regression equation into the data of each batch to calculate the predicted compressive strength. Subtract the predicted compressive strength from the actual compressive strength to obtain the residual. Sum the squares of the residuals of each batch to obtain the residual sum of squares. Take the partial derivatives of the residual sum of squares with respect to each regression coefficient and the constant term, and set the partial derivatives to zero to obtain the normal equation system. Solve for the regression coefficients and constant terms of the normal equation system, and substitute each regression coefficient and the constant terms into the multiple linear regression equation to obtain the correlation regression model.

9. The production process of lightweight solid waste partition wall panels according to claim 8, characterized in that, When the coefficient of variation exceeds a set threshold, the process parameter with the greatest influence weight is identified based on the absolute value of the regression coefficient in the correlation regression model. This adjustment involves setting a first adjustment ratio for the total amount of the alkali activator, a second adjustment ratio for the actual amount of the foaming agent, a time increment for the first isothermal time, or a time increment for the total dry curing time. Extract the regression coefficients from the correlation regression model, calculate the absolute value of each regression coefficient, and select the process parameter corresponding to the regression coefficient with the largest absolute value as the target adjustment parameter; When the target adjustment parameter is the total amount of alkali activator, the total amount of alkali activator in the current batch is increased or decreased by a first adjustment ratio. When the target adjustment parameter is the actual amount of foaming agent, the actual amount of foaming agent in the current batch is increased or decreased by a second adjustment ratio. When the target adjustment parameter is the first constant temperature time, the first constant temperature time in the current batch is increased or decreased by a first set time increment. When the target adjustment parameter is the total dry curing time, the total dry curing time in the current batch is increased or decreased by a second set time increment.

10. A production process apparatus for lightweight partition walls made from solid waste, characterized in that, A method for producing lightweight solid waste partition boards according to any one of claims 1-9, comprising: The dry mixing module is used to calculate the solid waste activity index of solid waste raw materials and determine the mass ratio of solid waste to fly ash, and obtain a homogenized active mixture through dry mixing. A stirring module is used to add an alkali activator to the active homogenized mixture and stir to obtain an alkali-activated slurry. A foaming module is used to determine the consistency coefficient of the alkali-activated slurry, calculate the actual amount of foaming agent based on the consistency coefficient and the target density, and add it to the alkali-activated slurry to obtain a foamed slurry. The constant temperature curing module is used to pour the foamed slurry into the mold for constant temperature curing to obtain the initial curing partition wall panel; The dry curing module is used to dry-cur the partition wall panel after demolding under dry curing temperature and humidity ranges and adjust the dry curing time. After switching to normal temperature curing, the compressive strength is detected daily and the strength growth rate is calculated. When the strength growth rate is lower than the set growth rate threshold twice in a row, the finished partition wall panel is obtained.

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