Method for preparing low-carbon cement pole from solid waste recycled aggregate

Abstract

The present application relates to the technical field of cement pole preparation, and particularly relates to a preparation method of low-carbon cement pole with solid waste recycled aggregate, which comprises the following steps: step one, product data collection and technical analysis; step two, decision output and artificial authentication; step three, material selection and pretreatment; step four, material strengthening and mixing treatment; step five, framework preparation and quality inspection treatment; step six, secondary mixing and overall casting forming; and step seven, product verification and data feedback. When the cement pole is prepared, the depth of the interface transition zone of the recycled aggregate can be strengthened and reconstructed at the material source, so that the old mortar on the surface of the recycled aggregate is effectively activated when a large proportion of the solid waste recycled aggregate is accommodated, and the interface bonding performance is significantly improved. Meanwhile, the melting bonding bridge effect of the hot-activated granulation polymerization particles in the framework layer and the self-expansion pressure densification effect of the filling layer can break through the technical bottleneck of the bearing capacity and durability degradation of the recycled aggregate cement pole.

Description

Technical Field

[0001] This invention relates to the field of cement pole preparation technology, specifically to a method for preparing low-carbon cement poles using recycled solid waste aggregates. Background Technology

[0002] Cement poles are ring-shaped concrete poles widely used in power transmission and distribution lines, communication, and lighting projects. They are mainly manufactured using centrifugal molding or vibration molding processes, with cement, sand, gravel, water, and admixtures as raw materials. Driven by the "dual carbon" goals and resource recycling, cement pole manufacturing is gradually incorporating environmentally friendly raw materials such as recycled aggregates, low-carbon cementitious materials, and industrial solid waste to reduce the consumption of natural resources and carbon emissions from products. However, ensuring the load-bearing capacity, durability, and process stability of cement poles while making significant use of solid waste remains a core technological challenge in this field.

[0003] Currently, several cement preparation methods have emerged in this field, such as a method for preparing low-carbon cement with application number CN202411347239.6 and publication date 20250211. This method includes the following steps: the proportions of raw materials are limestone 70% ± 5%, clay 10% ± 5%, and then, according to construction requirements, an appropriate amount of slag and fly ash 10% ± 5% is selected. The mixture is then homogenized through dry grinding to prepare cement raw meal, which is then calcined to prepare cement clinker. The prepared cement clinker is then conveyed into the interior of a roller press. This method of preparing low-carbon cement, through a pre-grinding component located at the top of the roller press, pre-grinds the cement clinker, avoiding the impact of excessive cement particle size on the fixed and movable rollers causing downtime. Simultaneously, iron impurities in the cement clinker are removed by magnetic rods, reducing the impact of iron impurities on the fixed and movable rollers, improving the grinding output and efficiency of the fixed and movable rollers, thereby reducing the power consumption of this invention and indirectly reducing the carbon emissions of the cement prepared by this invention.

[0004] For example, application number CN202410390753.1, with an authorized publication date of 20250211, discloses a high-strength cement pole composite material and its preparation method. The high-strength cement pole composite material comprises the following raw materials in parts by weight: 200-250 parts cement, 100-130 parts coarse aggregate, 45-55 parts fine aggregate, 20-30 parts metal pole, 70-90 parts composite fiber, 30-40 parts composite microcapsules, 5-10 parts water-reducing agent, and 180-220 parts water. By modifying the fibers in the high-strength cement pole composite material, composite fibers are obtained. These composite fibers possess good toughness and good adhesion to the cement substrate, resulting in good crack resistance and mechanical properties for the high-strength cement pole composite material. The addition of composite microcapsules, which use epoxy resin and attapulgite as self-healing materials, gives the high-strength cement pole composite material a certain degree of self-healing capability.

[0005] However, existing technologies and commonly used technologies that use recycled aggregates suffer from problems such as old mortar adhering to the aggregate surface and high porosity. Traditional molding methods cannot effectively improve the interface transition zone, resulting in a significant deterioration in the load-bearing capacity and durability of the products. It is difficult to balance the large-scale disposal of solid waste with performance assurance. Therefore, it is urgent to design a method for preparing low-carbon cement poles using recycled solid waste aggregates to solve the above problems. Summary of the Invention

[0006] The purpose of this invention is to provide a method for preparing low-carbon cement poles using recycled solid waste aggregates, so as to overcome the above-mentioned shortcomings in the prior art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A method for preparing low-carbon cement poles from recycled solid waste aggregates includes the following steps: Step 1. Product Data Collection and Technical Analysis: Collect product data, raw material data, and application location data. Subsequently, perform correlation analysis on the three types of data and build a product material selection calculation model through programming technology. It should be noted that: The product data includes the following: the specifications and model of the target cement pole, bearing capacity level, prestressing tension control stress, design service life of protective layer thickness, upper limit of density control, durability indicators such as frost resistance, impermeability and carbonation resistance, and applicable environment category; The application site data includes the following: the average annual temperature and humidity, extreme temperature difference, number of freeze-thaw cycles, soil corrosion level, basic wind pressure, seismic fortification intensity, and the types and annual output of local industrial solid waste. The raw material data includes recycled aggregate data and other component data, wherein: The recycled aggregate data includes: aggregate source type, particle size distribution, crushing index, apparent density, water absorption rate, content of fine powder and mud, chloride ion and alkali content, and proportion of old mortar adhering to the surface. The other component data include: the activity index and specific surface area of ​​the low-carbon cementitious material, the water reduction rate and retarding time of the admixture, the gas production rate and decomposition temperature window of the foaming agent, the triggering temperature and particle size distribution of the thermally activated granulated particles, the specifications and tensile strength of the reinforcing fiber, and the modulus and solid content of the alkali activator.

[0008] The correlation analysis of the three types of data is as follows: Using product performance indicators as the target variable, application environment data as boundary constraints, and raw material physicochemical parameters as independent variables, a multidimensional mapping model based on multiple regression was established to quantify the influence weight of each raw material characteristic on product performance and identify the threshold ranges of key raw material parameters. The multiple regression model uses a raw material-performance correlation prediction equation: ; In the formula: Y represents the target performance index (such as 28d compressive strength and flexural bearing capacity). X1, X2, ..., X n Key raw material parameters (such as crushing index of recycled aggregate, activity index of cementitious materials, and effective water-cement ratio); β is the influence weighting coefficient of each parameter; This is a model error correction term; The product material selection calculation model includes the following functional blocks: The system includes a data preprocessing and standardization module, a multi-objective optimization solution module (with cost, carbon emissions, and solid waste content as objectives), a process parameter matching and verification module, and a scheme risk labeling and multi-dimensional ranking output module. The multi-objective optimization solution module has a built-in normalized multi-objective optimization function: ; Constraints: ; Where x is the raw material ratio vector; the objective function F(x) is composed of normalized cost, carbon emissions, and solid waste utilization rate SW weighted; α, β, γ are weighting coefficients; f c To predict intensity.

[0009] Step 2. Decision Output and Manual Verification: Input the product parameters to be prepared into the model, the product material selection calculation model runs and outputs multiple raw material selection schemes, then uses intelligent AI to judge and analyze the schemes, and at the same time selects the optimal scheme based on manual quality inspection; It should be noted that: The product parameters include: Target bending bearing capacity grade, prestressing tension control stress, protective layer thickness, bar geometry and wall thickness, target density of skeleton layer and filling layer, mandatory durability performance indicators and unit product carbon emission limit, target slump at discharge, initial setting time requirement and demolding strength threshold after steam curing. The raw material selection scheme includes at least three or more schemes; The process by which the intelligent AI judges the solution is as follows: The AI ​​model accesses historical test databases and process rule bases to quantitatively score each scheme across multiple dimensions, including strength achievement rate, durability satisfaction, process compatibility, and cost. It automatically eliminates schemes that fail to meet standards or have timing conflicts (such as foaming peaks preceding initial slurry setting). Furthermore, it uses a TOPSIS-based comprehensive evaluation method to rank qualified schemes and provide risk warnings. ; Where represents the relative similarity (overall score) of the i-th scheme. These are the Euclidean distances between the proposed solution and the positive ideal solution (optimal performance) and the negative ideal solution (worst performance), respectively. The scoring criteria include strength achievement rate, durability satisfaction, cost deviation, and process feasibility. The manual quality inspection process is as follows: Technicians review the high-scoring solutions recommended by AI, focusing on the local availability of raw materials, the matching of key indicators (such as the crushing value of recycled aggregate and the triggering temperature of thermally activated particles) with the parameters of on-site equipment, and make a final verification and confirmation based on practical experience, or veto the solution.

[0010] Step 3. Material Selection and Pre-treatment: Select suitable raw materials based on the plan given in the previous step, and pre-treat the raw materials using the processing technology given in the plan. After pre-treatment, classify and store the various raw materials. It should be noted that: The processing technology for pretreatment of raw materials is as follows: The recycled aggregate is treated with "mechanical strengthening-interface modification". The adhering mortar is removed and the surface is activated by crushing and shaping and particle shaping. Then it is impregnated and coated with nano slurry or polymer slurry to pre-enhance the interface transition zone. The cementitious material is subjected to ultrafine grinding and homogenization to control the specific surface area ≥450m² / kg; The thermally activated granulated particles were screened and the integrity of the surface hydrophobic shell was checked. The foaming agent undergoes dilution, foam stabilization, and low-temperature storage pretreatment. The materials are classified into three categories: recycled materials, base materials, and additives. Each category of materials is stored in a sealed partition, and temperature and humidity sensitive materials are subject to independent constant temperature and humidity control.

[0011] Step 4. Material strengthening and mixing treatment: Select a portion of the raw materials pretreated in the previous step, and then strengthen them. After strengthening, add the selected materials to the mixing equipment for stirring and mixing. It should be noted that: The selected raw materials are the base material and some additives, used to prepare the supporting skeleton; The strengthening treatment is used to enhance the selected base material or some additives (so that the material can meet the requirements of thermally activated granulation polymerization). The strengthening treatment steps are as follows: By employing a melt blending and granulation process, low-melting-point thermoplastic resins (such as EVA), ultrafine mineral fillers, and processing aids are mixed at high speed, extruded by twin screws, cooled and granulated, and coated with hydrophobic coatings to produce thermally activated granulated polymer particles with a particle size of 2-5 mm, a core-shell structure, and a melt flow triggered at 65-75℃. The processing temperature is controlled below the trigger temperature throughout the entire process.

[0012] The mixing equipment operates in three stages, and the operating parameters for these three stages are as follows: The first stage, dry mixing stage: 20-30 r / min, 60-90 s, to mix the base material, recycled aggregate and fiber evenly; The second stage, wet mixing stage: rotation speed 35-45r / min, time 90-120s, add water and admixtures to form a slurry that uniformly coats the aggregate; The third stage, functional component addition stage: reduce the rotation speed to 15-25 r / min, time 30-60s, add thermally activated granulating polymer particles and foaming agent, disperse evenly at low speed and discharge immediately, and control the mixing temperature below 30℃ throughout the process. The process switching nodes for the three-stage mixing process are related to the stirring power, as detailed below: ; Where P is the real-time stirring power; N p ρ is the power index; n is the bulk density of the mixture; d is the stirring speed; when the fluctuation rate of the P value in the dry mixing stage drops below the set threshold, the material is determined to have reached the pre-homogenized state.

[0013] Step 5. Skeleton Preparation and Quality Inspection: After the mixing in the previous step is completed, the mixed materials are quickly poured into the molds. Then, the skeleton in the mold is formed by external heating technology to obtain a high-performance skeleton with gaps. The formed skeleton is then inspected to determine whether the product is qualified. If it is not qualified, the above steps and plans are adjusted until the product is qualified. Otherwise, if it is qualified, the next step is entered to continue production. It should be noted that: The mold is a special mold with a rigid locking mechanism and sealing structure, an adjustable temperature heating jacket or steam channel, and an internal coaxial positioning groove, which can withstand an internal pressure of not less than 0.3MPa. The material forming in the mold adopts a centrifugal forming and heating-assisted method, specifically as follows: A three-stage centrifugal process is adopted, consisting of low-speed fabrication, medium-speed compaction, and high-speed molding. The centrifugal parameters for each stage are controlled segmentally based on the centrifugal compaction index, wherein: ; Among them, G c The centrifugal compaction index is given by: n is the mold rotation speed (r / min); R is the skeleton forming radius; t is the action time at that rotation speed; k is an empirical coefficient related to the material rheology; G is controlled in segments. c This value enables a smooth transition from low-speed fabric to high-speed dense fabric. Simultaneously, auxiliary heating of the mold is started during the centrifugation process to carry out gradient temperature increase, so that the mold and material reach 65-70℃ at the end of high-speed molding, and simultaneously realize the centrifugal mechanical compaction and thermal activation of particle melting and polymerization. The uniformity of the skeleton wall thickness is controlled by the uniformity control equation: ; Where: δ is the wall thickness uniformity deviation; V is the feeding volume; L is the rod length; r o r i denoted as the outer and inner mold radii; Δg / g is the relative fluctuation rate of the centrifuge's gravitational acceleration; this formula is used for feedback control of the feed rate and mold coaxiality. The quality inspection of the formed skeleton includes: Visual inspection of appearance defects, measurement of geometric dimensions and wall thickness deviations, ultrasonic non-destructive testing of internal density, and verification of demolding strength; The adjustment process for non-compliance is as follows: The defect type and process deviation of the skeleton are fed back to the material selection calculation model in step one. The model analyzes the cause and provides solutions such as adjusting centrifugation parameters, optimizing the timing of particle feeding, or correcting the mixing ratio to guide the re-production.

[0014] Step 6. Secondary mixing and integral casting: Select the raw materials not selected in the previous step, and then pre-treat the raw materials. After the pre-treatment, pour them into the mixing equipment for mixing. After mixing, pour them into a secondary mold containing the skeleton for secondary molding. After molding, the composite cement rod is obtained. It should be noted that: The pretreatment process for the raw materials not selected in the previous step is as follows: The remaining recycled fine aggregate is screened to remove dust and pre-wetted. The filler gel powder is pre-homogenized; The foaming agent is diluted, stabilized, and subjected to constant temperature treatment to ensure stable gas production at a steam curing temperature of 70-80℃. The resulting self-generated expansion pressure is calculated based on a modified ideal gas model, as shown below: ; Among them, P internal V is the self-expansion pressure; n is the number of moles of foaming agent produced; R is the ideal gas constant; T is the steam curing trigger temperature; V cavity V represents the total volume of the mold sealing cavity. solid and V liquid These represent the solid and liquid phase volumes, respectively; by controlling n and T, P... internal Maintaining a pressure of 0.1-0.3 MPa achieves self-compaction; The operating parameters of the mixing equipment are as follows: Using a low-speed mixing device with a rotation speed of 40-60 r / min, the material is added in the following order: dry mixing of solid materials, wet mixing with water, and finally slow mixing with foaming liquid. The total mixing time is controlled at 120-180 s to obtain a uniform foaming slurry. During the secondary molding process, the skeleton is placed at the center of the secondary molding mold, and the secondary molding process adopts centrifugal molding and constrained foaming assistance, as detailed below: The qualified skeleton prepared in step five is coaxially fixed in the secondary molding mold through the end positioning slot, and the mold is closed tightly. After injecting the foaming slurry, first centrifuge at low speed (100-150 r / min) to distribute the material, then stop centrifugation and keep the mold sealed; The foaming agent reacts and generates gas within the confined cavity, producing a self-expanding internal pressure of 0.1-0.3 MPa, which pushes the slurry to fill the skeleton interface and mold edges, achieving constrained foaming and self-compacting. The mold is then sent into a steam curing kiln and heated to 65-70℃, which triggers the melting of thermally activated particles to form bonding bridges, thereby achieving densification and integrated composite of the filling layer.

[0015] Step 7. Finished Product Verification and Data Feedback: Verify and test the cement poles obtained in Step 6. Determine whether the product parameters are qualified based on the test results. If qualified, put them in the warehouse for shipment. If unqualified, analyze the cement pole products and feed the data back to the calculation model in Step 1 based on the analysis. It should be noted that: The verification detection includes: Appearance quality and geometric dimension deviation inspection, mechanical property tests such as bending bearing capacity and crack resistance, durability tests such as freeze-thaw resistance and carbonization resistance, ultrasonic or core sampling inspection of internal density and interface bonding state, and carbon emission accounting per unit product. The analysis of the cement pole products includes: For non-conforming products, failure source tracing is carried out. Through microscopic morphology analysis (such as SEM), it is determined that the failure originates from fluctuations in raw material performance, deviations in process parameters, or interface adhesion failure, and the problem process or material is accurately located. The specific data feedback is as follows: The complete test data, failure modes, and microscopic analysis results of the finished product are structured and correlated with the process parameters of the production process to form a complete case data package, which is then sent back to the product material selection calculation model in step one. The model uses an iterative error correction function to update the ratio and process parameters. The iterative error correction function: ; Where: X new This refers to the corrected raw material ratio or process parameters; X old The parameters are those of the original scheme; Y measured Y represents the actual measured performance of the product (such as actual flexural strength). predicted Model prediction; η is the learning rate; The model updates the database accordingly, corrects the influence coefficients and boundary conditions, and iteratively optimizes the formulas and process parameters for subsequent production, forming a closed-loop quality control system of "production-testing-feedback-optimization".

[0016] In the above technical solution, the present invention provides a method for preparing low-carbon cement rods from recycled solid waste aggregates, which has the following beneficial effects: (1) When preparing cement poles, the present invention constructs a collaborative process system of “data-driven material selection model - recycled aggregate interface modification pretreatment - skeleton thermal activation particle melt polymerization - filling layer constrained foaming self-compacting”, which can achieve deep strengthening and reconstruction of the interface transition zone of recycled aggregates at the source of materials. When a large proportion of recycled aggregates from solid waste are disposed of, the old mortar on the surface of the aggregates is effectively activated, and the interface bonding performance is significantly improved. At the same time, in combination with the melt bonding bridge effect of the skeleton thermal activation granulation polymer particles and the densification effect of the self-generated expansion pressure of the filling layer, the technical bottleneck of the deterioration of the bearing capacity and durability of recycled aggregate cement poles can be overcome, realizing the unity of solid waste resource utilization and high-performance cement pole preparation, effectively reducing the consumption of natural resources and promoting the green and low-carbon construction of power and communication infrastructure.

[0017] (2) This invention constructs a two-layer composite densification system with the core of skeleton thermally activated particle melting polymerization and filling layer constrained foaming self-compacting. Combined with three-stage centrifugal molding and heating-assisted process and secondary casting constrained foaming molding process, it realizes the whole process defect control of cement pole from skeleton layer to filling layer. The thermally activated granulated polymer particles are simultaneously heated and melted in centrifugal molding to form polymer three-dimensional bonding bridge to eliminate voids and microcracks in the skeleton. The foaming slurry generates self-expansion pressure in the confined cavity to push the slurry filling interface and corners to eliminate the loose filling layer and interface debonding defects. Thus, it meets the high standard requirements of power transmission and distribution lines for cement pole bearing capacity, crack resistance and long-term durability, and improves the reliability and service life of the product.

[0018] (3) When preparing cement poles, the present invention can use a multi-objective optimization material selection calculation model and TOPSIS comprehensive evaluation method to quantitatively optimize the raw material ratio scheme. Then, through AI intelligent multi-dimensional quantitative scoring and manual quality inspection review, the risk marking and ranking of the scheme are realized, so that the utilization rate of recycled aggregate, material cost and carbon emission are controlled within the target window. At the same time, the full-volume test data of finished products and the failure traceability analysis results form a closed loop iterative correction with the material selection model, so that the formula design and process parameters are transformed from experience trial mixing to data-driven precise decision-making, which significantly improves the product performance hit rate and batch consistency.

[0019] (4) When preparing composite cement poles, the present invention performs interface modification pretreatment by mechanically strengthening and impregnating the recycled aggregate with nano slurry, and combines centrifugal molding gradient heating system and constrained foaming steam curing triggering process. In the subsequent skeleton molding and filling layer densification, the interference of high porosity of recycled aggregate and old mortar adhesion on interface bonding can be eliminated. Together with the low temperature melting triggering mechanism of thermally activated particles and the self-expansion pressure densification of foaming agent, a triple structure quality assurance mechanism of interface strengthening, skeleton densification and filling compaction is formed. Under the premise of ensuring high load-bearing capacity and high durability of cement poles, the goal of large-scale solid waste disposal and low carbonization of products is achieved. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0021] Figure 1 This is a schematic diagram of the process flow for an embodiment of the present invention, which provides a method for preparing low-carbon cement poles using recycled solid waste aggregates.

[0022] Figure 2 This is a comparative example and a schematic diagram showing the comparison curves of the compressive strength after steam curing and demolding of the embodiment of the method for preparing low-carbon cement poles using recycled solid waste aggregates according to the present invention.

[0023] Figure 3 This is a comparative example and a schematic diagram showing the chloride ion diffusion coefficient comparison curves of the embodiment of the method for preparing low-carbon cement rods from recycled solid waste aggregates according to the present invention.

[0024] Figure 4 This is a comparative example and a schematic diagram showing the comparison of the frost resistance levels of the embodiments provided in the present invention for the preparation method of low-carbon cement poles using recycled solid waste aggregates.

[0025] Figure 5This is a comparative example and a schematic diagram showing the ultimate bending load comparison curves of the embodiment of the method for preparing low-carbon cement poles using recycled solid waste aggregates according to the present invention.

[0026] Figure 6 This is a comparative example and an example of the power flux comparison curve provided for an embodiment of the method for preparing low-carbon cement poles using recycled solid waste aggregates according to the present invention.

[0027] Figure 7 This is a comparative example and a schematic diagram showing the comparison curves of the standard curing compressive strength of the embodiment provided in the present invention for the preparation method of low-carbon cement poles using recycled solid waste aggregate. Detailed Implementation

[0028] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0029] like Figure 1-7 As shown in the figure, an embodiment of the present invention provides a method for preparing low-carbon cement poles from recycled solid waste aggregates, comprising the following steps: Step 1. Product Data Collection and Technical Analysis: Collect product data, raw material data, and application location data. Subsequently, perform correlation analysis on the three types of data and build a product material selection calculation model through programming technology. It should be noted that: The product data includes the following: the specifications and model of the target cement pole, bearing capacity level, prestressing tension control stress, design service life of protective layer thickness, upper limit of density control, durability indicators such as frost resistance, impermeability and carbonation resistance, and applicable environment category; The application site data includes the following: the average annual temperature and humidity, extreme temperature difference, number of freeze-thaw cycles, soil corrosion level, basic wind pressure, seismic fortification intensity, and the types and annual output of local industrial solid waste. The raw material data includes recycled aggregate data and other component data, wherein: The recycled aggregate data includes: aggregate source type, particle size distribution, crushing index, apparent density, water absorption rate, content of fine powder and mud, chloride ion and alkali content, and proportion of old mortar adhering to the surface. The other component data include: the activity index and specific surface area of ​​the low-carbon cementitious material, the water reduction rate and retarding time of the admixture, the gas production rate and decomposition temperature window of the foaming agent, the triggering temperature and particle size distribution of the thermally activated granulated particles, the specifications and tensile strength of the reinforcing fiber, and the modulus and solid content of the alkali activator.

[0030] The correlation analysis of the three types of data is as follows: Using product performance indicators as the target variable, application environment data as boundary constraints, and raw material physicochemical parameters as independent variables, a multidimensional mapping model based on multiple regression was established to quantify the influence weight of each raw material characteristic on product performance and identify the threshold ranges of key raw material parameters. The multiple regression model uses a raw material-performance correlation prediction equation: ; In the formula: Y represents the target performance index (such as 28d compressive strength and flexural bearing capacity). X1, X2, ..., X n Key raw material parameters (such as crushing index of recycled aggregate, activity index of cementitious materials, and effective water-cement ratio); β is the influence weighting coefficient of each parameter; This is a model error correction term; The product material selection calculation model includes the following functional blocks: The system includes a data preprocessing and standardization module, a multi-objective optimization solution module (with cost, carbon emissions, and solid waste content as objectives), a process parameter matching and verification module, and a scheme risk labeling and multi-dimensional ranking output module. The multi-objective optimization solution module has a built-in normalized multi-objective optimization function: ; Constraints: ; Where x is the raw material ratio vector; the objective function F(x) is composed of normalized cost, carbon emissions, and solid waste utilization rate SW weighted; α, β, γ are weighting coefficients; f c To predict intensity.

[0031] Step 2. Decision Output and Manual Verification: Input the product parameters to be prepared into the model, the product material selection calculation model runs and outputs multiple raw material selection schemes, then uses intelligent AI to judge and analyze the schemes, and at the same time selects the optimal scheme based on manual quality inspection; It should be noted that: The product parameters include: Target bending bearing capacity grade, prestressing tension control stress, protective layer thickness, bar geometry and wall thickness, target density of skeleton layer and filling layer, mandatory durability performance indicators and unit product carbon emission limit, target slump at discharge, initial setting time requirement and demolding strength threshold after steam curing. The raw material selection scheme includes at least three or more schemes; The process by which the intelligent AI judges the solution is as follows: The AI ​​model accesses historical test databases and process rule bases to quantitatively score each scheme across multiple dimensions, including strength achievement rate, durability satisfaction, process compatibility, and cost. Evaluation factors cover mixture slurry stability, the strengthening potential of the recycled aggregate interface transition zone, and the matching degree between foaming pressure and mold clamping force. Schemes that fail to meet standards or have timing conflicts (such as foaming peaks preceding initial slurry setting) are automatically eliminated. A TOPSIS-based comprehensive evaluation method is used to rank qualified schemes and provide risk warnings. ; Where represents the relative similarity (overall score) of the i-th scheme. These are the Euclidean distances between the proposed solution and the positive ideal solution (optimal performance) and the negative ideal solution (worst performance), respectively. The scoring criteria include strength achievement rate, durability satisfaction, cost deviation, and process feasibility. The manual quality inspection process is as follows: Technicians review the high-scoring solutions recommended by AI, focusing on whether the quality of recycled aggregates meets the requirements of Class II or above in the JGJ / T240 standard, whether the activity of solid waste cementitious materials meets the standard, whether the foaming sequence matches the slurry setting time, and whether the triggering temperature of thermally activated particles is compatible with the steam curing regime. They then conduct a final verification and confirmation based on practical experience, or reject the solution outright.

[0032] Step 3. Material Selection and Pre-treatment: Select suitable raw materials based on the plan given in the previous step, and pre-treat the raw materials using the processing technology given in the plan. After pre-treatment, classify and store the various raw materials. It should be noted that: The processing technology for pretreatment of raw materials is as follows: The recycled aggregate is treated with "mechanical strengthening (jaw crushing + impact crushing + water washing and classification) - interface modification (interface modification by impregnation and coating with nano silica or polymer slurry)". The surface is activated by crushing and shaping and particle shaping to remove the attached mortar and activate the surface. Then, it is impregnated and coated with nano slurry or polymer slurry to pre-enhance the interface transition zone. The cementitious material is subjected to ultrafine grinding and homogenization to control the specific surface area ≥450m² / kg; The thermally activated granulated particles were screened and the integrity of the surface hydrophobic shell was checked. The foaming agent undergoes dilution, foam stabilization, and low-temperature storage pretreatment. The materials are classified and stored according to three categories: recycled materials, base materials, and additives. Recycled materials include recycled coarse aggregate, recycled fine aggregate, and recycled micro powder; base materials include cement, slag powder, and fly ash; and additives include water-reducing agents, foaming agents, thermally activated granulated particles, and fibers. Each category of materials is stored in a sealed compartment, and temperature and humidity-sensitive materials are subject to independent constant temperature and humidity control.

[0033] Step 4. Material strengthening and mixing treatment: Select a portion of the raw materials pretreated in the previous step, and then strengthen them. After strengthening, add the selected materials to the mixing equipment for stirring and mixing. It should be noted that: The selected raw materials are the base material and some additives, used to prepare the supporting skeleton; The strengthening treatment is used to enhance the selected base material or some additives (so that the material can meet the requirements of thermally activated granulation polymerization). The strengthening treatment steps are as follows: By employing a melt blending and granulation process, low-melting-point thermoplastic resins (such as EVA), ultrafine mineral fillers, and processing aids are mixed at high speed, extruded by twin screws, cooled and granulated, and coated with hydrophobic coatings to produce thermally activated granulated polymer particles with a particle size of 2-5 mm, a core-shell structure, and a melt flow triggered at 65-75℃. The specific process is as follows: The first step is to prepare thermally activated granulated polymer particles: low-melting-point ethylene-vinyl acetate copolymer (EVA, VA content 28%-33%, melting point 68-72℃) and ultrafine fly ash are premixed in a high-speed mixer at a mass ratio of 65:35; the particles are rolled into balls using a disc granulator, and anhydrous ethanol is sprayed as a temporary binder. The raw particles are dried at a low temperature of 45℃ and baked at 60℃ for a short time to form a core-shell structure. Then, molten petroleum resin is sprayed at 55℃ to perform hydrophobic coating on the surface, thus obtaining thermally activated granulated polymer particles with a particle size of 2-5mm and a trigger temperature of 65-75℃. The second step is the activation pretreatment of the base material: slag powder and recycled powder are put into a high-energy planetary ball mill at a mass ratio of 3:1 and ground for 30 minutes at a speed of 500 rpm and a ball-to-material ratio of 10:1 to produce fresh active broken bonds on the surface. The third step is particle-powder composite reinforcement: the activated powder and the thermally activated granulated polymer particles are mixed at a mass ratio of 100:5 and preheated at 60°C for 10 minutes to slightly melt the particle surface and form a semi-encapsulated structure with the activated powder, thereby enhancing dispersibility and interfacial bonding; the temperature of the entire process is controlled below the trigger temperature.

[0034] The entire processing temperature is controlled below the trigger temperature; The mixing equipment operates in three stages, and the operating parameters for these three stages are as follows: The first stage, dry mixing stage: rotation speed 20-30 r / min, time 60-90s, mix the base material, recycled aggregate and fiber evenly. The endpoint of this stage is determined by the fluctuation rate of the stirring power. When the fluctuation rate of the real-time stirring power P drops below the set threshold, the material is determined to have reached the pre-homogenized state. The second stage, wet mixing stage: rotation speed 35-45r / min, time 90-120s, add water and admixtures to form a slurry that uniformly coats the aggregate; The third stage, the functional component addition stage: reduce the rotation speed to 15-25 r / min, time 30-60s, add the thermally activated granulation polymer particles and foaming agent, disperse evenly at low speed and discharge immediately, control the total mixing time within 180s, and control the mixing temperature throughout the process below 30℃. The process switching nodes for the three-stage mixing process are related to the stirring power, as detailed below: ; Where P is the real-time stirring power; N p ρ is the power index; n is the bulk density of the mixture; d is the stirring speed; when the fluctuation rate of the P value in the dry mixing stage drops below the set threshold, the material is determined to have reached the pre-homogenized state.

[0035] Step 5. Skeleton Preparation and Quality Inspection: After the mixing in the previous step is completed, the mixed materials are quickly poured into the molds. Then, the skeleton in the mold is formed by external heating technology to obtain a high-performance skeleton with gaps. The formed skeleton is then inspected to determine whether the product is qualified. If it is not qualified, the above steps and plans are adjusted until the product is qualified. Otherwise, if it is qualified, the next step is entered to continue production. It should be noted that: The mold is a special mold with a rigid locking mechanism and sealing structure, an adjustable temperature heating jacket or steam channel, and a coaxial positioning slot inside. The inner wall of the mold is provided with exhaust grooves with a depth of 0.5-1mm and a spacing of 100-150mm, and is lined with a polyurethane elastic layer, which can withstand an internal pressure of not less than 0.3MPa. The material forming in the mold adopts a centrifugal forming and heating-assisted method, specifically as follows: A three-stage centrifugal process is adopted, consisting of low-speed fabrication, medium-speed compaction, and high-speed molding. The centrifugal parameters for each stage are controlled segmentally based on the centrifugal compaction index, wherein: ; Among them, G cThe centrifugal compaction index is given by: n is the mold rotation speed (r / min); R is the skeleton forming radius; t is the action time at that rotation speed; k is an empirical coefficient related to the material rheology; G is controlled in segments. c This value enables a smooth transition from low-speed fabric to high-speed dense fabric. Low-speed fabric feeding stage: rotation speed 150-200 r / min, lasting 2-3 min; Medium-speed compaction stage: 400-500 r / min, for 4-6 minutes; High-speed compaction and thermal activation stage: rotation speed 700-900 r / min, lasting 8-12 min; Simultaneously, auxiliary heating of the mold is started during the centrifugation process to carry out gradient temperature increase, so that the mold and material reach 65-70℃ at the end of high-speed molding, and simultaneously realize the centrifugal mechanical compaction and thermal activation of particle melting and polymerization. The uniformity of the skeleton wall thickness is controlled by the uniformity control equation: ; Where: δ is the wall thickness uniformity deviation; V is the feeding volume; L is the rod length; r o r i denoted as the outer and inner mold radii; Δg / g is the relative fluctuation rate of the centrifuge's gravitational acceleration; this formula is used for feedback control of the feed rate and mold coaxiality. The quality inspection of the formed skeleton includes: Visual inspection of appearance defects, measurement of geometric dimensions and wall thickness deviations, ultrasonic non-destructive testing of internal density, and demolding strength testing of test blocks cured under the same conditions are required, with the demolding strength not less than 70% of the design strength; The adjustment process for non-compliance is as follows: If the density is insufficient, increase the speed of the high-speed stage to 800-900 r / min and extend the duration; If thermally activated particles agglomerate prematurely, lower the preheating temperature in the medium-speed stage and optimize the timing of particle feeding. If the wall thickness deviation exceeds the limit, adjust the feeding amount and correct the mold coaxiality; The defect types and process deviations of the skeleton are fed back to the material selection calculation model in step one. The model analyzes the causes and provides adjustment solutions to guide the re-production.

[0036] Step 6. Secondary mixing and integral casting: Select the raw materials not selected in the previous step, and then pre-treat the raw materials. After the pre-treatment, pour them into the mixing equipment for mixing. After mixing, pour them into a secondary mold containing the skeleton for secondary molding. After molding, the composite cement rod is obtained. It should be noted that: The pretreatment process for the raw materials not selected in the previous step is as follows: The remaining recycled fine aggregate is screened to remove dust and pre-wetted. The filler gel powder is pre-homogenized; The foaming agent is diluted, stabilized, and subjected to constant temperature treatment to ensure stable gas production at a steam curing temperature of 70-80℃. The resulting self-generated expansion pressure is calculated based on a modified ideal gas model, as shown below: ; Among them, P internal V is the self-expansion pressure; n is the number of moles of foaming agent produced; R is the ideal gas constant; T is the steam curing trigger temperature; V cavity V represents the total volume of the mold sealing cavity. solid and V liquid These represent the solid and liquid phase volumes, respectively; by controlling n and T, P... internal Maintaining a pressure of 0.1-0.3 MPa achieves self-compaction; The operating parameters of the mixing equipment are as follows: Using a low-speed mixing device with a rotation speed of 40-60 r / min, the material is added in the following order: dry mixing of solid materials, wet mixing with water, and finally slow mixing with foaming liquid. The total mixing time is controlled at 120-180 s to obtain a uniform foaming slurry. During the secondary molding process, the skeleton is placed at the center of the secondary molding mold, and the secondary molding process adopts centrifugal molding and constrained foaming assistance, as detailed below: The qualified skeleton prepared in step five is coaxially fixed in the secondary molding mold through the end positioning slot, and the mold is closed tightly. After injecting the foaming slurry, first centrifuge at low speed (100-150 r / min) to distribute the material, then stop centrifugation and keep the mold sealed; The foaming agent reacts and generates gas within the confined cavity, producing a self-expanding internal pressure of 0.1-0.3 MPa, which pushes the slurry to fill the skeleton interface and mold edges, achieving constrained foaming and self-compacting. The mold is then sent into a steam curing kiln and heated to 65-70℃, which triggers the melting of thermally activated particles to form bonding bridges, thereby achieving densification and integrated composite of the filling layer.

[0037] Step 7. Finished Product Verification and Data Feedback: Verify and test the cement poles obtained in Step 6. Determine whether the product parameters are qualified based on the test results. If qualified, put them in the warehouse for shipment. If unqualified, analyze the cement pole products and feed the data back to the calculation model in Step 1 based on the analysis. It should be noted that: The verification detection includes: Appearance quality and geometric dimension deviation inspection, mechanical property tests such as bending bearing capacity and crack resistance, durability tests such as freeze-thaw resistance and carbonization resistance, ultrasonic or core sampling inspection of internal density and interface bonding state, and carbon emission accounting per unit product. The analysis of the cement pole products includes: For non-conforming products, failure source tracing is carried out. Through microscopic morphology analysis (such as SEM), it is determined that the failure originates from fluctuations in raw material performance, deviations in process parameters, or interface adhesion failure, and the problem process or material is accurately located. The specific data feedback is as follows: The complete test data, failure modes, and microscopic analysis results of the finished product are structured and correlated with the process parameters of the production process to form a complete case data package, which is then sent back to the product material selection calculation model in step one. The model uses an iterative error correction function to update the ratio and process parameters. The iterative error correction function: ; Where: X new This refers to the corrected raw material ratio or process parameters; X old The parameters are those of the original scheme; Y measured Y represents the actual measured performance of the product (such as actual flexural strength). predicted Model prediction; η is the learning rate; The model updates the database accordingly, corrects the influence coefficients and boundary conditions, and iteratively optimizes the formulas and process parameters for subsequent production, forming a closed-loop quality control system of "production-testing-feedback-optimization".

[0038] Example 1: Medium replacement rate of recycled aggregate, lower limit of matching window for thermally activated particles and foaming pressure; industrial trial production adapted for 190×9m utility pole specifications. A method for preparing a low-carbon double-layer composite cement pole using recycled solid waste aggregate includes the following steps: Data-driven material selection and solution decision-making: Target product: 190×9m prestressed cement pole, bearing capacity grade L, matrix design strength C50; recycled aggregate is construction waste crushed recycled aggregate, crushing index 22%.

[0039] The calculation model output scheme is as follows: 40% replacement rate of recycled aggregate, 5% content of thermally activated granulated particles, and target gas production pressure of foaming agent of 0.15MPa.

[0040] Material pretreatment: The recycled aggregate is mechanically strengthened and ground in sequence, and then impregnated with nano-silica slurry to complete the interface modification of the aggregate.

[0041] The cementitious material was ultrafinely ground to a specific surface area of ​​460 m² / kg.

[0042] Preparation of the framework layer: Prepare the skeleton concrete according to the mix proportion, and add thermally activated granules with a trigger temperature of 70℃; after three-stage mixing, put it into the mold for centrifugal molding, and simultaneously control the temperature to 68℃, so that the thermally activated granules partially melt and polymerize to form a load-bearing skeleton.

[0043] The average measured compressive failure load of the skeleton demolded specimen after steam curing was 477kN, and the converted demolding strength reached 72% of the design strength. The ultrasonic compaction test was qualified.

[0044] Secondary casting and constrained foaming: Prepare the foaming slurry for the filling layer and inject it into a sealed mold with an internal skeleton; after low-speed centrifugal feeding, stop and the chemical foaming inside the cavity generates a self-expansion pressure of 0.18MPa to achieve self-compacting of the slurry.

[0045] The material is placed in a steam curing kiln and steamed at a constant temperature for 4 hours. When the temperature inside the kiln rises to 70°C, the thermally activated particles in the filling layer are triggered to bond again, and the filling layer and the skeleton interface are integrated to form a double-layer composite rod.

[0046] Finished product verification and data feedback: Finished products that pass inspection are put into storage; all process and mechanical data are fed back to the calculation model for iterative optimization.

[0047] Example 2: High replacement rate of recycled aggregate, with process parameters matching the lower limit of the window; industrial trial production of 190×12m utility poles. A method for preparing a low-carbon double-layer composite cement pole using recycled solid waste aggregate includes the following steps: Data-driven material selection and solution decision-making: The calculation model output scheme is as follows: the total replacement rate of recycled aggregate (recycled aggregate from construction waste + fly ash ceramsite) is 60%, the content of thermally activated granulated particles is 8%, and the target gas production pressure of foaming agent is 0.25MPa.

[0048] Material pretreatment: After mechanical strengthening of recycled aggregates, interface modification is carried out by polymer slurry coating and impregnation.

[0049] The cementitious material is ultra-finely ground to a specific surface area of ​​480 m² / kg, and an alkali activator is added to enhance the activity of the cementitious system.

[0050] Preparation of the framework layer: Prepare the skeleton material and add thermally activated granulation particles with a trigger temperature of 72℃; after three-stage mixing, centrifuge molding is carried out, with a high-speed stage speed of 850r / min and the mold temperature controlled synchronously at 70℃.

[0051] The measured average compressive failure load of the steam-cured skeleton specimen was 564kN, the demolding strength reached 78% of the design strength, and the wall thickness deviation of the rod was ≤1.5mm.

[0052] Secondary casting and constrained foaming: The foaming slurry is injected into a closed cavity, and the self-expansion pressure of the foam is 0.26MPa. The self-compactment of the filling layer is achieved by relying on the expansion pressure.

[0053] Steam curing at a constant temperature for 4 hours, with a kiln temperature of 72℃, allows the thermally activated particles to melt and form interfacial bonding bridges, achieving a strong composite of the skeleton layer and the filling layer.

[0054] Finished product verification and data feedback: Qualified finished products are put into storage; test data is fed back to the raw material selection calculation model for continuous optimization.

[0055] Example 3: Ultra-high replacement rate of recycled aggregate, upper limit of process parameter matching window; trial production of heavy-duty cement poles adapted to 310×6m specifications. A method for preparing a low-carbon double-layer composite cement pole using recycled solid waste aggregate includes the following steps: Data-driven material selection and solution decision-making: The calculation model output scheme is as follows: total replacement rate of recycled aggregate is 80%, thermally activated granulated particle content is 10%, and the target gas generation pressure of foaming agent is 0.30MPa.

[0056] Material pretreatment: Deep interfacial modification of recycled aggregates is achieved using a composite impregnation process of nano-silica slurry + polymer emulsion.

[0057] Cementitious materials are ultra-finely ground, with a specific surface area controlled at 500 m² / kg.

[0058] Preparation of the framework layer: High-dosage thermally activated granules with a trigger temperature of 75℃ are incorporated, and after three-stage stirring, they are centrifuged at high speed with a centrifugal speed of 900 r / min. The material temperature inside the mold is kept stable at 74℃, forming a continuous three-dimensional bonding bridge.

[0059] The measured average compressive failure load of the steam-cured skeleton specimen was 663 kN, and the demolding strength reached 81% of the design strength.

[0060] Secondary casting and constrained foaming: The foaming slurry generates gas in a confined, closed cavity, with a self-expanding pressure of 0.29 MPa, which fully fills the gaps in the skeleton and eliminates internal void defects.

[0061] The steam curing kiln is heated to 74℃ for constant temperature curing, the filling layer matrix is ​​densified, and the double-layer structure is formed as a whole.

[0062] Finished product verification and data feedback: Qualified finished products are put into storage; measured mechanical property data form a closed loop to continuously optimize raw material ratios and molding parameters.

[0063] Comparative Example 1: Traditional Low-Carbon Cement Single-Layer Centrifugal Molding Pole Solution A method for preparing a cement pole includes the following steps: Raw material ratio: limestone 70%, clay 10%, slag and fly ash 10%, the remainder are corrective materials.

[0064] Raw meal preparation: The raw materials are dry-milled and homogenized to prepare cement raw meal, which is then calcined to obtain cement clinker.

[0065] Grinding enhancement: Cement clinker is fed into a roller press equipped with a pre-grinding component for pre-grinding and magnetic separation to remove iron, thereby producing low-carbon silicate cement.

[0066] Concrete preparation and molding: Low-carbon cement is mixed with natural sand and gravel aggregates, mixing water, and polycarboxylate superplasticizer in a conventional manner, and cement bars are prepared using a traditional single-layer one-time casting centrifugal molding process.

[0067] Curing: Steam curing at a constant temperature for 4 hours.

[0068] Comparative Example 2: Single-layer fiber self-healing reinforced composite material pole design A method for preparing a cement pole includes the following steps: Raw material ratio (parts by weight): 200 parts cement, 130 parts natural coarse aggregate, 55 parts natural fine aggregate, 30 parts main reinforcement, 90 parts composite fiber, 40 parts composite microcapsules, 10 parts water-reducing agent, and 220 parts water.

[0069] Composite fiber preparation: Fiber surface impregnation modification to improve the bond strength between fiber and cement matrix.

[0070] Composite microcapsule preparation: Self-healing microcapsules for cracks were prepared using epoxy resin and attapulgite as repair core materials.

[0071] Mixing and blending: Cement, sand and gravel aggregates, main reinforcement, modified fibers, self-healing microcapsules, water-reducing agent and water are thoroughly mixed evenly.

[0072] Molding and Curing: Traditional single-layer centrifugal one-time molding, using factory constant temperature 4h steam curing.

[0073] The mechanical properties and durability of the cement poles prepared in the above comparative examples and embodiments were tested, and the results are shown in the table below: Performance Verification Table It can be seen from the above table: Comparative Example 1 only optimized the cementitious material system, without strengthening the interface of recycled aggregates or the rod structure. Its overall mechanical and durability properties were the worst; its steam-cured release strength, 28-day strength, freeze-thaw resistance, and chloride ion penetration resistance all failed to meet the requirements for heavy-duty cement rods.

[0074] Comparative Example 2 relies on composite fibers and self-healing microcapsules to improve the toughness of single-layer concrete, and the mechanical properties basically meet the standards; however, the single-layer structure cannot solve the porosity defects caused by high recycled aggregate content, and the electrical flux and chloride ion diffusion coefficient meet the critical standards, but the durability reserve under long-term salt corrosion environment is insufficient.

[0075] Examples 1, 2, and 3 all employ a synergistic process of recycled aggregate interface modification, skeleton thermal activation melt polymerization, and filler layer constrained foaming self-compacting. The dual-layer composite structure offers significant advantages. Furthermore, within the recycled aggregate replacement rate range of 40%-80%, with optimization of process parameters, steam curing demolding strength, 28-day compressive strength, flexural strength, and crack resistance are simultaneously improved. At the same time, the matrix porosity is continuously optimized by the foaming self-compacting effect, resulting in continuous improvement in resistance to chloride ion penetration and freeze-thaw durability. Even with a large proportion of construction waste recycled solid waste, this solution can still stably achieve the industrial production of high-performance dual-layer composite cement poles, balancing the goals of solid waste resource utilization and low-carbon development with the long-term reliability of power poles.

[0076] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for preparing low-carbon cement poles using recycled solid waste aggregate, characterized in that, Includes the following steps: Step 1. Product Data Collection and Technical Analysis: Collect product data, raw material data, and application location data. Subsequently, perform correlation analysis on the three types of data and build a product material selection calculation model through programming technology. Step 2. Decision Output and Manual Verification: Input the product parameters to be prepared into the model, the product material selection calculation model runs and outputs multiple raw material selection schemes, then uses intelligent AI to judge and analyze the schemes, and at the same time selects the optimal scheme based on manual quality inspection; Step 3. Material Selection and Pre-treatment: Select suitable raw materials based on the plan given in the previous step, and pre-treat the raw materials using the processing technology given in the plan. After pre-treatment, classify and store the various raw materials. Step 4. Material strengthening and mixing treatment: Select a portion of the raw materials pretreated in the previous step, and then strengthen them. After strengthening, add the selected materials to the mixing equipment for stirring and mixing. Step 5. Skeleton Preparation and Quality Inspection: After the mixing in the previous step is completed, the mixed materials are quickly poured into the molds. Then, the skeleton in the mold is formed by external heating technology to obtain a high-performance skeleton with gaps. The formed skeleton is then inspected to determine whether the product is qualified. If it is not qualified, the above steps and plans are adjusted until the product is qualified. Otherwise, if it is qualified, the next step is entered to continue production. Step 6. Secondary mixing and integral casting: Select the raw materials not selected in the previous step, and then pre-treat the raw materials. After the pre-treatment, pour them into the mixing equipment for mixing. After mixing, pour them into a secondary mold containing the skeleton for secondary molding. After molding, the composite cement rod is obtained. Step 7. Finished Product Verification and Data Feedback: Verify and test the cement poles obtained in Step 6. Determine whether the product parameters are qualified based on the test results. If qualified, place the product in the warehouse for shipment. If unqualified, analyze the cement pole products and feed the data back to the calculation model in Step 1 based on the analysis.

2. The method for preparing low-carbon cement poles from recycled solid waste aggregate according to claim 1, characterized in that, In step one: The product data includes the following: the specifications and model of the target cement pole, bearing capacity level, prestressing tension control stress, design service life of protective layer thickness, upper limit of density control, durability indicators such as frost resistance, impermeability and carbonation resistance, and applicable environment category; The application site data includes the following: the average annual temperature and humidity, extreme temperature difference, number of freeze-thaw cycles, soil corrosion level, basic wind pressure, seismic fortification intensity, and the types and annual output of local industrial solid waste. The raw material data includes recycled aggregate data and other component data, wherein: The recycled aggregate data includes: aggregate source type, particle size distribution, crushing index, apparent density, water absorption rate, content of fine powder and mud, chloride ion and alkali content, and proportion of old mortar adhering to the surface. The other component data include: the activity index and specific surface area of ​​the low-carbon cementitious material, the water reduction rate and retarding time of the admixture, the gas production rate and decomposition temperature window of the foaming agent, the triggering temperature and particle size distribution of the thermally activated granulated particles, the specifications and tensile strength of the reinforcing fiber, and the modulus and solid content of the alkali activator.

3. The method for preparing low-carbon cement poles from recycled solid waste aggregate according to claim 1, characterized in that, In step one: The correlation analysis of the three types of data is as follows: Using product performance indicators as the target variable, application environment data as boundary constraints, and raw material physicochemical parameters as independent variables, a multidimensional mapping model based on a multiple regression model is established to represent the "raw material parameters - process conditions - finished product performance," where: The multiple regression model uses a raw material-performance correlation prediction equation: ； In the formula: Y represents the target performance index (such as 28d compressive strength and flexural bearing capacity). X1, X2, ..., X n Key raw material parameters; β is the influence weighting coefficient of each parameter; This is a model error correction term; The product material selection calculation model includes the following functional blocks: The system includes modules for data preprocessing and standardization, multi-objective optimization, process parameter matching and verification, and scheme risk labeling and multi-dimensional ranking output. The multi-objective optimization solution module has a built-in normalized multi-objective optimization function: ； Constraints: ； Where x is the raw material ratio vector; the objective function F(x) is composed of normalized cost, carbon emissions, and solid waste utilization rate SW weighted; α, β, γ are weighting coefficients; f c To predict intensity.

4. The method for preparing low-carbon cement poles using recycled solid waste aggregates according to claim 1, characterized in that, In step two: The product parameters include: Target bending bearing capacity grade, prestressing tension control stress, protective layer thickness, bar geometry and wall thickness, target density of skeleton layer and filling layer, mandatory durability performance indicators and carbon emission limit per unit product, target slump at discharge, initial setting time requirement and demolding strength threshold after steam curing. The raw material selection scheme includes at least three or more schemes; The process by which the intelligent AI judges the solution is as follows: The AI ​​model accesses historical test databases and process rule bases to quantitatively score each scheme across multiple dimensions, including strength achievement rate, durability satisfaction, process compatibility, and cost. Evaluation factors cover mixture slurry stability, the strengthening potential of the recycled aggregate interface transition zone, and the matching degree between foaming pressure and mold clamping force. Schemes that fail to meet standards or have timing conflicts are automatically eliminated. A TOPSIS-based comprehensive evaluation method is used to rank qualified schemes and provide risk warnings. ； Where is the relative similarity of the i-th scheme. These are the Euclidean distances between the proposed solution and the positive ideal solution and the negative ideal solution, respectively. The manual quality inspection process is as follows: Technicians review the high-scoring solutions recommended by AI, focusing on the local availability of raw materials, the matching of key indicators with on-site equipment parameters, and make a final verification and confirmation based on practical experience, or veto the solution.

5. The method for preparing low-carbon cement poles from recycled solid waste aggregate according to claim 1, characterized in that, In step three: The processing technology for pretreatment of raw materials is as follows: The recycled aggregate is treated with "mechanical strengthening-interface modification". The adhering mortar is removed and the surface is activated by crushing and shaping and particle shaping. Then it is impregnated and coated with nano slurry or polymer slurry to pre-enhance the interface transition zone. Cementitious materials are subjected to ultrafine grinding and homogenization; The thermally activated granulated particles were screened and the integrity of the surface hydrophobic shell was checked. The foaming agent undergoes dilution, foam stabilization, and low-temperature storage pretreatment. The materials are classified into three categories: recycled materials, base materials, and additives, and each category of materials is stored separately in sealed containers.

6. The method for preparing low-carbon cement poles from recycled solid waste aggregate according to claim 1, characterized in that, In step four: The selected raw materials are the base material and some additives, used to prepare the supporting skeleton; The strengthening treatment is used to strengthen the selected base material or some additives. The strengthening treatment steps are as follows: By employing a melt blending and granulation process, low-melting-point thermoplastic resin, ultrafine mineral filler, and processing aids are mixed at high speed, extruded by twin screws, cooled and granulated, and coated with hydrophobic coatings to produce thermally activated granulated polymer particles with a particle size of 2-5 mm, a core-shell structure, and a melt flow triggered at 65-75℃.

7. The method for preparing low-carbon cement poles from recycled solid waste aggregate according to claim 1, characterized in that, In step four: The mixing equipment operates in three stages, and the operating parameters for these three stages are as follows: The first stage, dry mixing stage: 20-30 r / min, 60-90 s, to mix the base material, recycled aggregate and fiber evenly; The second stage, wet mixing stage: rotation speed 35-45r / min, time 90-120s, add water and admixtures to form a slurry that uniformly coats the aggregate; The third stage, functional component addition stage: reduce the rotation speed to 15-25 r / min, time 30-60s, add thermally activated granulating polymer particles and foaming agent, disperse evenly at low speed and discharge immediately, and control the mixing temperature below 30℃ throughout the process. The process switching nodes for the three-stage mixing process are related to the stirring power, as detailed below: ； Where P is the real-time stirring power; N p ρ is the power index; n is the bulk density of the mixture; d is the stirring speed; when the fluctuation rate of the P value in the dry mixing stage drops below the set threshold, the material is determined to have reached the pre-homogenized state.

8. The method for preparing low-carbon cement poles from recycled solid waste aggregate according to claim 1, characterized in that, In step five: The mold is a special mold with a rigid locking mechanism and sealing structure, an adjustable temperature heating jacket or steam channel, and a coaxial positioning slot inside. The material forming in the mold adopts a centrifugal forming and heating-assisted method, specifically as follows: A three-stage centrifugal process is adopted, consisting of low-speed fabrication, medium-speed compaction, and high-speed molding. The centrifugal parameters for each stage are controlled segmentally based on the centrifugal compaction index, wherein: ； Among them, G c is the centrifugal compaction index; n is the mold rotation speed; R is the skeleton forming radius; t is the action time at that rotation speed; k is an empirical coefficient related to the rheological properties of the material; Simultaneously, auxiliary heating of the mold is started during the centrifugation process to carry out gradient temperature increase, so that the mold and material reach 65-70℃ at the end of high-speed molding, and simultaneously realize the centrifugal mechanical compaction and thermal activation of particle melting and polymerization. The uniformity of the skeleton wall thickness is controlled by the uniformity control equation: ； Where: δ is the wall thickness uniformity deviation; V is the feeding volume; L is the rod length; r o r i Where is the outer and inner mold radius; Δg / g is the relative fluctuation rate of the centrifuge's gravitational acceleration; The quality inspection of the formed skeleton includes: Visual inspection of appearance defects, measurement of geometric dimensions and wall thickness deviations, ultrasonic non-destructive testing of internal density, and verification of demolding strength; The adjustment process for non-compliance is as follows: The defect type and process deviation of the skeleton are fed back to the material selection calculation model in step one. The model analyzes the cause and provides solutions such as adjusting centrifugation parameters, optimizing the timing of particle feeding, or correcting the mixing ratio to guide the re-production.

9. A method for preparing low-carbon cement poles from recycled solid waste aggregates according to claim 1, characterized in that, In step six: The pretreatment process for the raw materials not selected in the previous step is as follows: The remaining recycled fine aggregate is screened to remove dust and pre-wetted. The filler gel powder is pre-homogenized; The foaming agent is diluted, stabilized, and subjected to constant temperature treatment to ensure stable gas production at a steam curing temperature of 70-80℃. The resulting self-generated expansion pressure is calculated based on a modified ideal gas model, as shown below: ； Among them, P internal V is the self-expansion pressure; n is the number of moles of foaming agent produced; R is the ideal gas constant; T is the steam curing trigger temperature; V cavity V represents the total volume of the mold sealing cavity. solid and V liquid These are the solid and liquid phase volumes, respectively. The operating parameters of the mixing equipment are as follows: Using a low-speed mixing device with a rotation speed of 40-60 r / min, the material is added in the following order: dry mixing of solid materials, wet mixing with water, and finally slow mixing with foaming liquid. The total mixing time is controlled at 120-180 s to obtain a uniform foaming slurry. During the secondary molding process, the skeleton is placed at the center of the secondary molding mold, and the secondary molding process adopts centrifugal molding and constrained foaming assistance, as detailed below: The qualified skeleton prepared in step five is coaxially fixed in the secondary molding mold through the end positioning slot, and the mold is closed tightly. After injecting the foaming slurry, first perform low-speed centrifugal spreading, then stop centrifugation and keep the mold sealed; The foaming agent reacts and generates gas within the confined cavity, producing a self-expanding internal pressure of 0.1-0.3 MPa, which pushes the slurry to fill the skeleton interface and mold edges, achieving constrained foaming and self-compacting. The mold is then sent into a steam curing kiln and heated to 65-70℃, which triggers the melting of thermally activated particles to form bonding bridges, thereby achieving densification and integrated composite of the filling layer.

10. A method for preparing low-carbon cement poles from recycled solid waste aggregates according to claim 1, characterized in that, In step seven: The verification detection includes: Mechanical performance tests such as appearance quality and geometric dimension deviation inspection, bending load capacity and crack resistance inspection, durability tests such as freeze-thaw resistance and carbonization resistance, ultrasonic or core sampling inspection of internal density and interface bonding state, and carbon emission accounting per unit product. The analysis of the cement pole products includes: For non-conforming products, failure source tracing is carried out. Through microscopic morphology analysis, it is determined that the failure originates from fluctuations in raw material performance, deviations in process parameters, or interface adhesion failure, and the problem process or material is accurately located. The specific data feedback is as follows: The complete test data, failure modes, and microscopic analysis results of the finished product are structured and correlated with the process parameters of the production process to form a complete case data package, which is then sent back to the product material selection calculation model in step one. The iterative error correction function: ； Where: X new This refers to the corrected raw material ratio or process parameters; X old The parameters are those of the original scheme; Y measured For actual product performance; Y predicted Model prediction; η is the learning rate; The model updates the database accordingly, corrects the influence coefficients and boundary conditions, and iteratively optimizes the formulas and process parameters for subsequent production.

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