A method and system for analyzing the results of a blast furnace grouting lining experiment

Abstract

This invention discloses a method and system for analyzing the results of blast furnace grouting lining experiments, relating to the field of blast furnace longevity and maintenance technology. This invention aims to address the lack of comprehensive and quantitative evaluation methods in existing technologies for grouting lining experiments in confined spaces. The method provided by this invention includes: obtaining a three-dimensional surface morphology model of the cured structure formed after the repair material has cured in a pre-set experimental container; calculating macroscopic evaluation parameters, including material coverage area, average cured thickness, and cured thickness uniformity, based on the model; sampling the cured structure to obtain comprehensive mechanical performance parameters; using image recognition to obtain local attachment capability evaluation parameters around the pre-set simulated component; and finally integrating the above macroscopic morphology and microscopic physical data through a weighted model to derive a comprehensive evaluation quantitative index. Through the above scheme, this invention achieves objective and multi-dimensional analysis of physical experimental results, effectively guiding the optimization of repair processes and reducing trial-and-error costs.

Description

Technical Field

[0001] This invention relates to the field of blast furnace longevity and maintenance technology, and in particular to a method and system for analyzing the experimental results of blast furnace grouting and lining. Background Technology

[0002] During normal production, the refractory lining of a blast furnace is subjected to harsh environments of high temperature, high pressure, chemical corrosion, and material erosion. Especially after the cooling walls gradually deteriorate, the cooling capacity of the cooling system begins to severely deteriorate. This leads to varying degrees of localized overheating and even red-hot cracking of the furnace shell in the furnace body, waist, and belly, resulting in a significant deterioration of the operating environment in front of the furnace. To ensure the cooling capacity of the blast furnace, grouting is currently a common method used at blast furnace production sites for periodic repairs of the lining.

[0003] Because current grouting lining operations generally lack controllability and rely heavily on experience, on-site operation control is prone to significant discrepancies with the final lining effect. Existing technologies aimed at improving the service life of blast furnace cooling walls typically focus on forcibly protecting the cooling walls through external monitoring methods such as hot surface temperature calculations and refrigeration systems. These solutions cannot guide subsequent closed-space repair processes after severe damage to the cooling walls. Other solutions propose on-site construction procedures for pressurized grouting lining or designs utilizing slightly damaged water pipes as grouting channels, but these technologies do not address the systematic analysis of the actual forming state and filling density of the grout after it enters the blast furnace.

[0004] Due to the complex and harsh internal environment of blast furnaces, it is impossible to directly monitor and analyze the flow and solidification state of slurry in a confined space using instruments on-site. Therefore, physical simulation experiments are necessary for research. However, the lack of scientific, comprehensive, and multi-dimensional methods for quantitatively evaluating experimental results prevents relevant personnel from systematically and efficiently extracting effective data from the solidified products of physical experiments. This leads to a state of blind trial and error, greatly increasing the number of experimental repetitions and the labor, economic, and time costs. Summary of the Invention

[0005] To address the shortcomings in the prior art, this invention provides a method and system for analyzing the experimental results of blast furnace grouting and lining. It aims to solve the core technical problem that the existing technology lacks systematic, comprehensive, and quantitative evaluation methods for grouting and lining repair experiments in confined spaces, resulting in low experimental efficiency and an inability to effectively guide the optimization of on-site grouting processes.

[0006] To solve the above-mentioned technical problems, in a first aspect, the present invention provides the following technical solution:

[0007] A method for analyzing the results of a blast furnace grouting lining experiment includes: acquiring a three-dimensional surface morphology model of a solidified structure formed after the repair material has cured in a pre-set experimental container; calculating macroscopic evaluation parameters of the solidified structure based on the three-dimensional surface morphology model, wherein the macroscopic evaluation parameters include at least the material coverage area, average cured thickness, and cured thickness uniformity; acquiring comprehensive mechanical performance evaluation parameters obtained by sampling and testing the solidified structure; acquiring a material distribution image around a pre-set simulated component in the solidified structure, extracting the hanging feature parameters of the pre-set simulated component based on the material distribution image, and calculating the hanging capacity evaluation parameters of the pre-set simulated component; calculating a comprehensive evaluation result based on the macroscopic evaluation parameters and the comprehensive mechanical performance evaluation parameters, and comprehensively evaluating the blast furnace grouting lining experiment results in conjunction with the hanging capacity evaluation parameters. By employing a technique that integrates feature extraction from a macroscopic three-dimensional model, recognition of local component distribution images, and microscopic sampling mechanical analysis, this invention can achieve multi-dimensional extraction of the forming state of the grouting solidification structure and integrate discrete feature data from various dimensions into a comprehensive evaluation result, completely changing the previous reliance on subjective judgment based on human experience.

[0008] As a preferred embodiment of the present invention, the step of obtaining a three-dimensional surface morphology model of a solidified structure formed after the repair material in the preset experimental container has solidified includes: after the repair material has completely solidified, removing the covering plate of the preset experimental container and cleaning the surface of the solidified structure; performing a three-dimensional scan on the solidified structure to construct an initial three-dimensional model; obtaining the measured feature dimensions of key parts of the solidified structure, and comparing and verifying the corresponding model dimensions in the initial three-dimensional model with the measured feature dimensions; if the comparison error is less than or equal to a preset threshold, then the initial three-dimensional model is used as the three-dimensional surface morphology model; if the comparison error is greater than the preset threshold, then the three-dimensional scan and comparison verification operation are repeated until the comparison error meets the requirements. By further employing model verification, the present invention can also achieve high accuracy of the experimental basic digital model data, avoid the deviation of the analysis reference plane caused by scanning environment interference, and improve the confidence of the final analysis results.

[0009] As a preferred embodiment of the present invention, the step of calculating the macroscopic evaluation parameters of the cured structure based on the three-dimensional surface morphology model includes: dividing the cured structure into N equal regions along the height direction; obtaining the thickness of the center line of each equal region based on the three-dimensional surface morphology model; summing the thicknesses of all N equal regions and calculating the average value to obtain the average cured thickness δ. avgThe standard deviation of the solidified thickness is calculated based on the centerline thickness of all N equally divided regions, and combined with the preset maximum theoretical standard deviation, the uniformity γ of the solidified thickness is obtained. By further employing an algorithm that divides the height equally and integrates the standard deviations, this invention can also achieve quantitative capture of the thickness fluctuation pattern in space, effectively characterizing the uniformity of the final morphology of the material under the combined influence of gravity and flowability.

[0010] As a preferred embodiment of the present invention, the step of obtaining the comprehensive mechanical performance evaluation parameters includes: extracting test samples from multiple different locations of the solidified structure, and measuring the compressive strength, flexural strength, and material density of each test sample; based on the measured compressive strength, flexural strength, and material density, combined with the theoretical maximum values ​​of the corresponding indicators and the preset weight ratios of each indicator, calculating the comprehensive mechanical performance index λ as the comprehensive mechanical performance evaluation parameter. By further employing a weighted approach using the ternary mechanical parameters of compressive strength, flexural strength, and density, the present invention can also achieve a scientific characterization of the material's service endurance, ensuring that the analytical conclusions meet both the requirements of aesthetically pleasing molding geometry and inherent structural strength.

[0011] In a preferred embodiment of the present invention, the preset simulated component is a cooling column inserted into the experimental container. The hanging feature parameters include the average thickness of the slurry coating, the uniformity of slurry distribution, and the average gap width. The step of extracting the hanging feature parameters of the preset simulated component based on the material distribution image to calculate the hanging capability evaluation parameters of the preset simulated component includes: performing pixel classification processing on the material distribution image to calculate the average thickness of the slurry coating around the cooling column, the uniformity of slurry distribution, and the average gap width; performing a weighted integral operation on the average thickness of the slurry coating, the uniformity of slurry distribution, and the average gap width to obtain a total slurry coating capability integral reflecting the slurry coating capability of the cooling column, which serves as the hanging capability evaluation parameter. By further employing pixel feature extraction combining three local gap / coating dimensions, the present invention can also achieve precise review of key challenges in the lining process (the hanging and forming state of the cooling column surface), guiding the improvement of the shape of specific components.

[0012] As a preferred embodiment of the present invention, the method for calculating the average coating thickness of the slurry includes: taking a pixel on the perimeter of the cooling column cross-section as the initial starting point, extending a straight line along the normal direction of the arc it is located until the boundary of the preset background material is detected, and recording the pixel distance; converting the pixel distance into a real physical distance L' based on the ratio between the perimeter of the cooling column cross-section in the material distribution image and the actual perimeter of the cooling column cross-section. i The average physical distances corresponding to all pixels on the cross-sectional perimeter are averaged to obtain the average coating thickness L of the slurry. avgBy further employing normal edge finding and pixel physical mapping, this invention can also achieve the statistical analysis of the shortest force distance for irregularly distributed boundaries, greatly reflecting the true state of local package volume.

[0013] As a preferred embodiment of the present invention, the method for calculating the uniformity of slurry distribution includes: defining a circular image region with a preset radius, centered on the center point of the cooling column cross-section, and uniformly dividing the circular image region into multiple sector regions; identifying pixel classification information within each sector region, and calculating the percentage w of pixels belonging to the slurry in each sector region relative to the total number of pixels in that sector region. i The standard deviation of the percentage of all sector regions is calculated to obtain the uniformity β of the slurry distribution. By further employing the technical feature of center-radial partitioning dimensionality reduction statistics, this invention can also achieve accurate quantification of anisotropic slurry coating morphology, overcoming the limitations of the human eye in judging uniformity under complex morphologies.

[0014] As a preferred embodiment of the present invention, the method for calculating the average gap width includes: performing image detection along the cross-sectional boundary of the cooling column, identifying and connecting consecutive gap pixels to extract a complete gap structure region; dividing the extracted gap structure region into a preset number of segments along the length direction, and calculating the pixel width on the center line of each segment; and correcting the pixel width to the actual width h' based on a preset physical scaling ratio. i The average gap width h is obtained by calculating the average value. avg By further employing the technical features of continuous gap pixel connectivity and differential segment calculation of width, this invention can also achieve statistical stripping of complex crack defect morphology, thereby providing a reverse constraint index for sealing effect.

[0015] As a preferred embodiment of the present invention, the calculation model for the total integral A of the slurry coating capacity is the result of aggregation based on the calculated average slurry coating thickness, the calculated uniformity of slurry distribution, and the calculated average gap width, after assigning different empirical scaling factors. By further employing a multivariate composite integral equation, the present invention can also achieve an absolute ranking of the superiority and inferiority of different cooling column structures under experimental conditions, facilitating intuitive selection by technical personnel.

[0016] As a preferred embodiment of the present invention, the calculation of the comprehensive evaluation result based on the macroscopic evaluation parameters and the comprehensive mechanical performance evaluation parameters includes: outputting a comprehensive evaluation index Z through a preset comprehensive evaluation function. The comprehensive evaluation function uses the calculated material coverage area, the deviation between the average cured thickness and the ideal thickness, the uniformity of the cured thickness, and the comprehensive mechanical performance index as its main parameters, supplemented by pre-configured corresponding evaluation weight coefficients for weighting. By further employing a full-scale evaluation model combining macroscopic deviations and material properties, the present invention can also achieve a comprehensive diagnosis of a single physical repair experiment, making the experimental results historically comparable and traceable.

[0017] To solve the above-mentioned technical problems, in a second aspect, the present invention provides the following technical solution:

[0018] An analysis system for blast furnace grouting lining experiment results includes: a model building module configured to acquire a three-dimensional surface morphology model of a solidified structure formed after the repair material has solidified in a preset experimental container; a macroscopic feature analysis module configured to calculate macroscopic evaluation parameters of the solidified structure based on the three-dimensional surface morphology model, wherein the macroscopic evaluation parameters include at least material coverage area, average solidification thickness, and solidification thickness uniformity; a mechanical property acquisition module configured to acquire comprehensive mechanical property evaluation parameters obtained by sampling and testing the solidified structure; a bonding capability analysis module configured to acquire a material distribution image around a preset simulated component in the solidified structure, extract bonding feature parameters of the preset simulated component based on the material distribution image, and calculate bonding capability evaluation parameters of the preset simulated component; and a comprehensive evaluation module configured to calculate a comprehensive evaluation result based on the macroscopic evaluation parameters and the comprehensive mechanical property evaluation parameters, and, in conjunction with the bonding capability evaluation parameters, comprehensively evaluate the blast furnace grouting lining experiment results.

[0019] By employing software-based and modular deployment techniques, this invention enables automated operation of analysis algorithms and centralized management of experimental data, greatly reducing secondary errors caused by manual intervention.

[0020] In a preferred embodiment of the present invention, the macroscopic feature analysis module includes: a thickness extraction submodule, configured to divide the three-dimensional surface topography model into multiple equally divided regions in the height direction and extract the thickness data of the center line of each equally divided region; and a macroscopic calculation submodule, configured to perform mean calculation on the thickness data of the multiple equally divided regions to obtain the average cured thickness, calculate the standard deviation of the thickness data, and output the uniformity of the cured thickness based on a set dispersion benchmark. By further employing model mesh slicing and hierarchical statistical algorithms, the present invention can also achieve rapid dimensionality reduction solutions for complex surfaces of macroscopic three-dimensional models.

[0021] As a preferred embodiment of the present invention, the mounting capability analysis module includes: an image recognition submodule, configured to use an edge detection algorithm to perform boundary segmentation and pixel classification on different material regions in the material distribution image, and extract the wrapping distance distribution, polarization degree of material pixel proportion, and pore pixel distribution morphology around the preset simulated component; and a parameter conversion submodule, configured to map and calculate the wrapping distance distribution, polarization degree of material pixel proportion, and pore pixel distribution morphology into the average slurry wrapping thickness, slurry distribution uniformity, and average gap width. By further employing an intelligent machine vision and mapping conversion architecture, the present invention can also achieve automated and accurate picking of minute defects and irregular fillers, breaking through the limits of traditional caliper measurement.

[0022] In a preferred embodiment of the present invention, the comprehensive evaluation module stores a multi-dimensional evaluation model library with pre-calibrated weights. This multi-dimensional evaluation model library includes at least a macroscopic weight equation for the overall lining effect and a component grouting integral equation for local forming quality. The comprehensive evaluation module executes the macroscopic weight equation and the component grouting integral equation in parallel, outputting quantitative evaluation indicators to guide the optimization of on-site grouting process parameters. By further employing a parallel processing architecture for the model library, the present invention can also achieve consistency in the evaluation system under multiple experimental operating parameters, improving the platform's scalability and compatibility.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] 1. The method provided by this invention applies three-dimensional model mapping and image recognition technology to the reverse disassembly of the repair filler in a closed space at the forefront, breaking the barrier that conventional methods can only guess the internal forming quality through external appearance, and constructing a three-in-one system dissection mechanism of "macroscopic large-area distribution morphology - microscopic features of local component hanging - intrinsic mechanical strength of materials".

[0025] 2. The comprehensive evaluation system and quantitative formula designed in this invention fundamentally eliminate the result drift caused by the subjective experience of technical personnel. By making full use of the data generated from each physical model simulation experiment, the system intuitively reflects the merits of the experimental scheme in terms of physical property matching, layout structure, and operational pressure through mathematical modeling. This greatly reduces the number of blind trials and errors required to find the best construction scheme, and significantly saves time, labor, and material costs in research and development. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments disclosed in this invention, the accompanying drawings of the embodiments will be briefly described below. These drawings are for illustrative purposes only and are not intended to limit the scope of protection of this invention.

[0027] Figure 1 This is a schematic diagram of the flow structure of an analysis method provided in an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of the main experimental container structure provided in an embodiment of the present invention;

[0029] Figure 3 This is a schematic diagram illustrating the calculation of the average coating thickness of the slurry provided in an embodiment of the present invention;

[0030] Figure 4 This is a schematic diagram of slurry distribution uniformity calculation provided in an embodiment of the present invention;

[0031] Figure 5 This is a schematic diagram illustrating the calculation of the average gap width provided in an embodiment of the present invention;

[0032] Figure 6 This is a schematic diagram illustrating the calculation of average lining thickness provided in an embodiment of the present invention;

[0033] Figure 7 This is a schematic diagram of the grouting lining experiment layout provided in this embodiment of the invention; each cooling column and grouting port shown in the figure is a preset simulation component in this embodiment. Detailed Implementation

[0034] The technical solutions (including preferred technical solutions) of the present invention will be further described in detail below with reference to the accompanying drawings and by way of listing some optional embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0035] Example 1

[0036] This embodiment provides an analytical method for the experimental results of blast furnace grouting and lining. It aims to solve the problem that the lining effect in existing confined spaces is difficult to evaluate intuitively through systematic physical experimental dissection and digital model quantification.

[0037] like Figure 1 , Figure 2 as well as Figure 7 As shown. In this embodiment, the analysis method includes the following steps:

[0038] Step S100: Obtain a three-dimensional surface morphology model of the cured structure 109 formed after the repair material in the preset experimental container has cured.

[0039] In the implementation phase of a specific physical experiment, a closed, confined space is first established. For example... Figure 2As shown, the main experimental container consists of a top steel plate 102, side steel plates 103, front steel plate 104, bottom steel plate 105, and back steel plate 106, with grouting holes 107 and pressure relief holes 101 arranged on the steel plates. The repair material (in this implementation scenario, it is manifested as lining grout, specifically including high-strength ceramic wear-resistant material and binder) is injected into a sealed container filled with background filler (such as high-temperature coke) through the grouting holes 107 via a grouting device. A simulated component 108 is preset inside (in actual scenarios, it is a cooling column of various shapes, such as...). Figure 7 Under the flow-blocking and traction effects shown in the figure, the repair material gradually spreads, fills, and eventually solidifies.

[0040] After the solidified structure 109 has fully formed and cooled, the top steel plate 102, back steel plate 106, etc., surrounding the container are removed, and any unbonded coke and other debris scattered on the surface are cleaned. The solidified component obtained in the experiment is now exposed in the field of view. A high-precision 3D scanner (such as an optical tracking scanner) is then used to perform panoramic cloud capture of the surface morphology, constructing an initial three-dimensional geometric model. To ensure the confidence level of this basic model, operators select some key protruding features on-site and use calipers to measure and record the physical measured values. The virtual dimensions measured in 3D software (such as MeshLab) are compared with the measured values. If the calculation error is >3%, it is considered a calibration bias and a rescan is necessary; this process continues until the error of the 3D model at all sampling points is reduced to within a preset threshold (e.g., <3%). The model that passes this verification is then considered a valid 3D surface morphology model.

[0041] Of course, the data acquisition of the three-dimensional surface morphology model is not limited to structured light scanning. In some harsh environments with a lot of dust, phased array ultrasonic non-destructive testing instruments can also be used in combination with tomographic imaging technology (CT imaging) to construct a three-dimensional spatial model of the material. The macroscopic distribution information of the outer surface can also be extracted, all of which fall within the scope of the superior protection of this invention.

[0042] Step S200: Based on the three-dimensional surface morphology model, calculate the macroscopic evaluation parameters of the cured structure 109. The macroscopic evaluation parameters include at least the material coverage area, average cured thickness, and cured thickness uniformity.

[0043] For calculating the coverage area, 3D model analysis software can be used to project the irregular mesh onto the surface, calculate the effective projected pixels on the plane of the bonding substrate (i.e., the front steel plate 104), and then calculate the total slurry coverage area S. Regarding thickness assessment, since the actual flow injection state results in varying thicknesses at different locations, a software tool is used to uniformly cut N layers (equally divided regions) along the height Z-axis of the 3D surface topography model. The distance from the centerline of each layer to the reference surface on the thickness Y-axis is automatically extracted as the thickness δ of that region. i (See details) Figure 6 The average cured thickness is obtained by averaging the N extracted thicknesses, and its dispersion (standard deviation) is calculated. This standard deviation is then compared with the set extreme theoretical dispersion (maximum standard deviation) for normalization calculation, ultimately obtaining the cured thickness uniformity parameter used to characterize the overall spreading morphology stability of the model. For detailed formula derivation, please refer to Example 3 below.

[0044] Step S300: Obtain the comprehensive mechanical performance evaluation parameters obtained by sampling and testing the solidified structure 109.

[0045] Core drilling or cutting samples were taken from different locations (e.g., around the grouting inlet, at the bottom, and at the far end) of the exposed solidified structure 109 to prepare standard test blocks. The actual compressive strength and flexural strength were obtained using a universal testing machine, and the actual material density was determined using the drainage method or a densitometer. These three data points were then compared with the theoretical maximum values ​​achievable by the corresponding formulation under ideal conditions, and a weighted multiplier was introduced for summation. This yielded a comprehensive evaluation index of the microstructural density and mechanical load-bearing capacity of the structure in the current batch's formed state.

[0046] Step S400: Obtain a material distribution image around the preset simulated component in the solidified structure, and extract the hanging feature parameters of the preset simulated component based on the material distribution image to calculate the hanging capability evaluation parameters of the preset simulated component.

[0047] This step focuses on the analysis of the bonding effect at the microscopic level. Using a demolition tool, the outer slurry is carefully peeled away layer by layer until the bonding interface around the pre-designed simulated component 108 (cooling columns of different configurations) is exposed. High-resolution images are used to record the slurry encapsulation state of this section and output the images. Image processing software (such as the open-source framework ilastik) is used to perform multi-class pixel segmentation on the images. Due to the differences in reflectivity and texture among different materials (cooling column metal, bonding slurry, pores, coke impurities), the algorithm can accurately delineate the actual geometric contour of the material encapsulation around the cooling column.

[0048] like Figure 3 As shown, in the segmented image, the nearest coke boundary 110 is detected from the center of the cooling column outward along the normal guide using a pixel coordinate system. The number of pixels is calculated and proportionally reduced, and the "average coating thickness of the slurry" is obtained by averaging multiple points. Figure 4 As shown, the area around the cooling column is divided into multiple sector-shaped regions using polar coordinates. The proportion of pixels covered by slurry is calculated, and the "slurry distribution uniformity" is obtained by solving the variance of the distribution difference between the sectors. Figure 5As shown, a connected component search algorithm is used to remove voids and gaps at the surface of the cooling column, and a segmentation method is used to estimate the average gap width. These three microscopic local indicators are then input into a pre-set integral evaluation model to provide a quantitative score for the structural grouting performance of the pre-simulated component 108.

[0049] Step S500: Calculate the comprehensive evaluation result based on the macroscopic evaluation parameters and the comprehensive mechanical performance evaluation parameters, and combine the hanging capacity evaluation parameters to comprehensively evaluate the blast furnace grouting lining experiment results.

[0050] This step integrates the external macroscopic morphological quality (area, thickness, uniformity) extracted in step S200 with the internal physical quality (mechanical properties) extracted in step S300 into an equation with a weighted offset factor to derive an absolute index representing the overall experimental lining effect. Then, referring to the design optimization integral feedback for specific simulated components in step S400, it is determined whether the slurry ratio, pressure, and component structural design used in this experiment represent the optimal combination.

[0051] Example 2

[0052] This embodiment provides an analysis system architecture for the experimental results of blast furnace grouting and lining, which corresponds to the method flow of Embodiment 1.

[0053] This analysis system consists of several hardware-supported logic modules and can be deployed on industrial control terminals or cloud data processing servers. The system mainly includes:

[0054] Model Building Module: This module includes a high-configuration rendering graphics processor that receives raw dense point clouds from 3D scanning hardware via an external interface. It incorporates surface reconstruction and voxelization filtering algorithms to smoothly fuse discrete point cloud data into a solidified 3D surface topography model. The module also features interactive verification, allowing users to input measured verification distances and adaptively determine the error confidence rate.

[0055] Macroscopic Feature Analysis Module: This module can automatically mesh the imported 3D model. By using a script program, it can define layered regions at fixed vertical distances and automatically capture three macroscopic data points: material coverage area, average cured thickness, and cured thickness uniformity by calculating the mean and variance matrix of point coordinates.

[0056] Mechanical property acquisition module: This module provides an interactive UI input interface or supports direct connection to comprehensive mechanical testing equipment via API to capture arrays of compressive strength, flexural strength and density test results of test specimens. The module internally stores the optimal theoretical library of common refractory materials and automatically performs regularization ratio calculation on the input test values.

[0057] The bonding capability analysis module integrates machine vision AI components and is mainly responsible for importing high-definition distribution images acquired after peeling and cutting. The internally embedded image recognition submodule can mask different background clutter (such as coke) through a pre-trained segmentation model, highlighting the actual slurry and pore distribution around the core cooling column. The parameter conversion submodule uses edge tracking to quickly convert the mask shape into the physical thickness of the slurry coating, the radial uniformity distribution ratio around the column, and the absolute value of the surface debonding gap distance.

[0058] Comprehensive Evaluation Module: This module serves as the final decision-making engine. Its underlying architecture stores a library of multi-dimensional evaluation models with pre-calibrated weights. The module concurrently calls macroscopic feature scoring threads and microscopic component integration threads, outputting intuitive dashboard data and radar charts. This visually maps existing construction plan improvement bottlenecks to technical decision-makers. For example, if the evaluation results indicate extremely uneven thickness but sufficient coverage area, it suggests that the grouting pressure decays too rapidly, requiring adjustments to pressure relief or the grouting point layout.

[0059] Furthermore, the computation of the above system modules can be fully realized through industrial IoT technology combined with a distributed edge computing architecture. For example, edge computing boxes can be set up at the metallurgical site to collect and calculate the complex pixel classification matrix in the image analysis module in real time, calculate various evaluation indicators, and package and encrypt them before uploading them to the comprehensive evaluation cloud brain. This allows the headquarters research institution to overcome spatial limitations and achieve parallel evaluation and decision-making for multiple furnaces and batches of experimental schemes.

[0060] Example 3 To demonstrate in detail the feasibility and rigor of the computational logic of this invention, this embodiment further elaborates on the specific formula principles and related Tables 1, 2, and 3.

[0062] In this specific simulation experiment, the main experimental container was designed as a cuboid measuring 1 m × 3 m × 1 m (width × height × thickness), filled with high-temperature coke heated to over 500°C. Eight grouting holes, each 110 mm in diameter, were pre-filled on the front steel plate 104. Figure 7 The simulation components with different shapes shown (e.g., hexagonal cooling columns, spiral groove cooling columns, etc.) were disassembled to obtain the solidified structure after the lining slurry was pressed in and solidified for 20 hours.

[0063] Calculation Item 1: Mathematical Calculation Mechanism for Macroscopic Thickness and Uniformity

[0064] Regarding the aforementioned thickness uniformity, the 3D model shows a coverage area of ​​2.86 m. 2 (The base area of ​​the steel plate is 3.0 m) 2(Coverage rate 95.3%). In this embodiment, the height direction of the solidified structure is divided into N=10 equal regions.

[0065] Based on the algorithm: Average lining thickness formula: Extract the average length of the centerline.

[0066] Formula for uniformity of lining thickness: , where max(σ δ The theoretical maximum standard deviation is 50.

[0067] Table 1 below is generated based on the specific thickness data extracted from the model:

[0068] Table 1. Thickness variation of each equally divided region along the height direction of the solidified structure.

[0069]

[0070] Based on this algorithm, the average curing thickness of this simulation experiment was accurately quantified as δ. avg =29.8 cm, thickness standard deviation σ δ =6.53; therefore, the uniformity of the lining thickness in the height direction of this structure is calculated to be γ=0.87.

[0071] As shown in Table 1, the discrete surface was transformed into data in 10 dimensions using an algorithm. It can be seen that the thickness is thinnest at a height of 2.25m (21.9 cm), while the thickness is greatest at the bottom 2.85m due to the influence of gravity (44.2 cm). Finally, the global average solidification thickness was accurately quantified to be 29.8 cm, with a uniformity as high as 0.87.

[0072] Calculation Item Two: Calculation of Comprehensive Mechanical Performance Parameters

[0073] Specimens were taken from different locations and subjected to compressive strength (M) tests. c ), flexural strength (M) s The material's theoretical maximum parameters were set at 100 MPa, 20 MPa, and 3.5 g / cm³, and its density (ρ) was measured. 3 The formula defines the comprehensive mechanical performance index:

[0074]

[0075] (weighting percentage ε) c , and ε s 0.4, ε ρ Take 0.2).

[0076] Six core samples were drilled from six representative locations of the solidified structure 109 for independent testing. The average value was then substituted into the above equation, and the specific data were compiled into Table 2.

[0077] Table 2. Comprehensive mechanical performance test results and index table of test samples at different locations.

[0078]

[0079] As shown in Table 2, the material density near the multi-directional grouting inlet is the highest (index reaches 0.84), while the stress performance near the bottom of the wall is the weakest (0.71). The arithmetic mean of the six local mechanical indices yields the overall comprehensive mechanical performance evaluation parameter λ for this physical simulation experiment, which is 0.77. This parameter objectively reflects the intrinsic strength level of the grout after it has formed in a closed, complex flow field.

[0080] Calculation Item 3: Evaluation of Cooling Column Slurry Coating Capacity (Computerized System)

[0081] For local components, the image identifies:

[0082] Formula for average package thickness: ;like Figure 3 As shown, the algorithm finds the nearest preset background material boundary 110 on the circumferential normal, records the pixel coordinate difference, and multiplies it by the physical calibration ratio to obtain L'. i .

[0083] Formula for uniformity of slurry distribution: (where the theoretical maximum standard deviation is assumed to be max(σ)) w (The value is 0.5, and N is divided into 8-12 segments). See also... Figure 4 The area surrounding the cooling column is divided into N (e.g., 10) sector-shaped regions. The proportion w of slurry pixels to the total cross-sectional pixels in this region is calculated. i Calculate the standard deviation σ w .

[0084] Formula for average gap width: See also Figure 5 Identify the black hole pixels stripped from the interface, cut them into N segments (e.g., 15 segments), and take the average physical width.

[0085] The empirical formula for the total integral of the coating is derived by combining the following:

[0086]

[0087] The corresponding integrals were obtained to evaluate the slurry-coating ability of various types of cooling columns. The specific calculation results are shown in Table 3. It can be seen that the spiral groove cooling column has the best slurry-coating effect, followed by the octagonal cooling column and the 60 mm circular cooling column, while the parallel groove cooling column has the worst slurry-coating effect.

[0088] Table 3 Test results of grouting performance of different types of cooling columns

[0089]

[0090] Through rigorous integral equation calculations, errors caused by visual judgment were eliminated. Table 3 clearly shows that the spiral groove cooling column, with the largest surface area, has the thickest coating and the smallest gaps, achieving a total integral of 96.3, thus exhibiting the best slurry-coating capacity. In contrast, the parallel groove cooling column, due to hydrodynamic hindrance, has gaps as high as 3.5mm, resulting in a total integral of only 70.2, making it the least effective. This quantitative result directly provides solid data support for the design and selection of the blast furnace cooling column's shape.

[0091] Calculation Item 4: Comprehensive Evaluation Model of Global Experimental Results

[0092] Based on all the derived data mentioned above, import all core dimensions into the overall final evaluation function:

[0093]

[0094] In this batch of system evaluations, since all four dimensions (coverage, thickness fit, morphological uniformity, and damage resistance) are equally important, the system assigns a weighting coefficient ϕ to each of the four evaluation dimensions. s ϕ δ ϕ γ ϕ λ The value is uniformly set to 0.25.

[0095] The ideal lining thickness δ0 for this repair is set at 32 cm.

[0096] Extract the values ​​obtained from the aforementioned examples:

[0097] S = 2.86 m 2 Sq = 3.0 m 2 ;

[0098] δ avg = 29.8 cm;

[0099] γ = 0.87;

[0100] λ = 0.77;

[0101] Strictly substitute the above core data into the evaluation equation:

[0102] Coverage term: (2.86 / 3.0) * 0.25 ≈ 0.238;

[0103] Thickness deviation penalty: (1 - |29.8 – 32| / 32) * 0.25 = (1 - 0.06875) * 0.25 ≈ 0.233;

[0104] Morphological uniformity: 0.87 * 0.25 = 0.2175;

[0105] Combined mechanics terms: 0.77 * 0.25 = 0.1925;

[0106] The final comprehensive evaluation index Z = 0.88 was obtained by summing and calculating the results of this round of blast furnace grouting and lining simulation experiments.

[0107] This index value is extremely close to the theoretical perfect value of 1.0, proving that the "high-strength ceramic wear-resistant material + 10wt% binder" formula used in this scheme, combined with the current grouting pressure, achieves excellent molding quality. When further exploration of alternative grouts to reduce costs is needed, the above analysis procedure can be repeated. If the final index Z of the new grout shows a significant decrease (e.g., below 0.75), the shortcomings (insufficient flow coverage or a sharp drop in strength) can be immediately identified by comparing the integrals of each sub-item, thus pointing to a clear R&D optimization path and completely ending the history of long-term blind trial and error.

[0108] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Those skilled in the art can make various improvements and modifications without departing from the spirit and principles of the invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

[0109] It will be readily understood by those skilled in the art that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, combinations, substitutions, improvements, etc., made under the spirit and principles of the present invention are included within the protection scope of the present invention.

Claims

1. A method for analyzing the experimental results of blast furnace grouting and lining, characterized in that, include: Obtain a three-dimensional surface morphology model of the cured structure formed after the repair material in the preset experimental container has cured; Based on the three-dimensional surface morphology model, the macroscopic evaluation parameters of the cured structure are calculated. The macroscopic evaluation parameters include at least the material coverage area, average cured thickness, and cured thickness uniformity. Obtain comprehensive mechanical performance evaluation parameters by sampling and testing the solidified structure; Obtain a material distribution image around a preset simulated component in the solidified structure, and extract the hanging feature parameters of the preset simulated component based on the material distribution image to calculate the hanging capability evaluation parameters of the preset simulated component; The comprehensive evaluation results are calculated based on the macroscopic evaluation parameters and the comprehensive mechanical performance evaluation parameters, and the results of the blast furnace grouting and lining experiment are comprehensively evaluated in conjunction with the hanging capacity evaluation parameters.

2. The analytical method according to claim 1, characterized in that, The process of obtaining a three-dimensional surface morphology model of the cured structure formed after the repair material in the preset experimental container has cured includes: After the repair material has completely cured, the cover plate of the preset experimental container is removed and the surface of the cured structure is cleaned; the cured structure is then scanned in three dimensions to construct an initial three-dimensional model. Obtain the measured feature dimensions of key parts of the solidified structure, and compare and verify the corresponding model dimensions in the initial three-dimensional model with the measured feature dimensions; If the comparison error is less than or equal to a preset threshold, the initial three-dimensional model is used as the three-dimensional surface morphology model.

3. The analytical method according to claim 1, characterized in that, The specific calculation methods for the macroscopic evaluation parameters include: The solidified structure is divided into N equal regions along the height direction, and the thickness of the center line of each equal region is obtained based on the three-dimensional surface morphology model. The average cured thickness δ is obtained by summing the thicknesses of all N equally divided regions and calculating the average value. avg The calculation formula is as follows: , where δ i The thickness of the center line of the i-th equally divided region; The standard deviation of the curing thickness is calculated based on the centerline thickness of all N equally divided regions, and combined with the preset maximum theoretical standard deviation, the curing thickness uniformity γ is calculated using the following formula: , where σ δ Let be the standard deviation of the centerline thickness of N equally divided regions, and max(σ) δ ) represents the theoretical maximum standard deviation.

4. The analytical method according to claim 1, characterized in that, The calculation method for the comprehensive mechanical performance evaluation parameters includes: Test samples were extracted from the solidified structure at multiple different locations, and the compressive strength, flexural strength and material density of each test sample were measured. Based on the measured compressive strength, flexural strength, and material density, combined with the theoretical maximum values ​​of the corresponding indicators and the preset weight ratios of each indicator, the comprehensive mechanical performance index λ is calculated as the comprehensive mechanical performance evaluation parameter, as shown in the following formula: Among them, M c M s ρ and M represent the actual compressive strength, actual flexural strength, and actual material density of the test sample, respectively; c,max M s,max and ρ max These represent the maximum theoretical parameter values ​​corresponding to the materials; ε c ε s and ε ρ These represent the weights assigned to each parameter.

5. The analytical method according to claim 1, characterized in that, The preset simulation component is a cooling column inserted into the experimental container, and the hanging characteristic parameters include the average thickness of the slurry coating, the uniformity of slurry distribution, and the average gap width. The method includes: performing pixel classification processing on the material distribution image to extract the average coating thickness of the slurry, the uniformity of the slurry distribution, and the average gap width; performing a weighted integral operation on the above three hanging feature parameters to obtain the total slurry hanging capacity integral that reflects the slurry hanging capacity of the cooling column.

6. The analytical method according to claim 5, characterized in that, The specific calculation method for the attachment characteristic parameters is as follows: The average coating thickness of the slurry L avg Calculation method: Starting from the pixel point on the perimeter of the cooling column cross-section, draw a straight line along the normal direction of the arc to the boundary of the preset background material and record the pixel distance. Then, convert it to the actual physical distance L' proportionally. i And calculate the average value. ; The calculation method for the uniformity β of the slurry distribution is as follows: Multiple fan-shaped regions are evenly divided with the center point of the cooling column cross-section as the center, and the proportion w of the pixels belonging to the slurry in each fan-shaped region is calculated. i Solving for the standard deviation yields ; The average gap width h avg Calculation method: Detect and extract the complete gap structure region along the boundary of the cooling column section, divide it into a preset number of segments along its length, calculate the pixel width on the center line of each segment, and convert it into the actual width h'. i Calculate the average value. .

7. The analytical method according to claim 6, characterized in that, The calculation model for the total integral A of the slurry-coating capacity is as follows: .

8. The analytical method according to claim 1, characterized in that, The step of calculating the comprehensive evaluation result based on the macroscopic evaluation parameters and the comprehensive mechanical performance evaluation parameters includes: outputting the comprehensive evaluation index Z through a preset comprehensive evaluation function, wherein the comprehensive evaluation function is as follows: Where S is the calculated material coverage area, S q Based on the area, δ avg The average cured thickness is calculated, δ0 is the preset ideal cured thickness, γ is the calculated cured thickness uniformity, and λ is the comprehensive mechanical property index; ϕ s ϕ δ ϕ γ and ϕ λ These are the corresponding evaluation weight coefficients.

9. An analytical system for the experimental results of blast furnace grouting and lining, characterized in that, include: The model building module is configured to acquire a three-dimensional surface morphology model of the solidified structure formed after the repair material in the preset experimental container has solidified. The macroscopic feature analysis module is configured to calculate the macroscopic evaluation parameters of the cured structure based on the three-dimensional surface morphology model. The macroscopic evaluation parameters include at least the material coverage area, average cured thickness, and cured thickness uniformity. The mechanical property acquisition module is configured to acquire comprehensive mechanical property evaluation parameters obtained by sampling and testing the solidified structure. The mounting capability analysis module is configured to acquire a material distribution image around a preset simulated component in the solidified structure, extract mounting feature parameters of the preset simulated component based on the image, and calculate mounting capability evaluation parameters. The comprehensive evaluation module is configured to calculate the comprehensive evaluation result based on the macroscopic evaluation parameters and the mechanical parameters, and to evaluate the experimental results in conjunction with the hanging capacity evaluation parameters.

10. The analysis system according to claim 9, characterized in that: The macroscopic feature analysis module includes: a thickness extraction submodule, used to divide the three-dimensional surface morphology model into multiple equally divided regions in the height direction to extract centerline thickness data; and a macroscopic calculation submodule, used to perform mean and standard deviation calculations on the thickness data to output the average cured thickness and cured thickness uniformity. The mounting capability analysis module includes: an image recognition submodule, used to segment the boundaries of different material regions in the image using an edge detection algorithm; and a parameter conversion submodule, used to map and calculate the identified pixel distribution pattern into the average coating thickness of the slurry, the uniformity of the slurry distribution, and the average gap width.

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