Steel slag full-granularity using and blending method and system for road surface full-horizon application

Abstract

The invention discloses a steel slag full-granularity use blending method and system for pavement full-horizon application, and the method comprises the steps: sampling steel slag, obtaining the diameter of each particle material in the sample steel slag, dividing the diameter into a plurality of particle size sections, and extracting the particle size feature vector of each particle size section in the sample steel slag; setting a function field corresponding to each horizon of the pavement, confirming a response demand vector corresponding to each function field, and calculating a matching degree between the particle size feature vector of each particle size section and the response demand vector corresponding to each function field; and setting a matching degree threshold value corresponding to the layer position according to the number of the layer positions of the road surface, comparing the matching degree with the matching degree threshold value of each layer position, and if the matching degree exceeds the matching degree threshold value, using the steel slag of the corresponding particle size section at the corresponding layer position so as to complete the full-particle-size using and blending of the steel slag.

Description

Technical Field

[0001] The present invention belongs to the technical field of steel slag mixing and control during road paving, and more specifically, relates to a method and system for mixing steel slag of all particle sizes for application in all layers of a road surface. Background Art

[0002] Steel slag is a byproduct of the steelmaking process, accounting for approximately 10% to 15% of steel content. As a major industrial solid waste, it is in urgent need of resource utilization. Currently, through road resource utilization and technological innovation, steel slag can be transformed from an industrial solid waste into high-quality aggregate.

[0003] However, due to the limitations of technical paths and methods, steel slag of different particle sizes cannot be used 100% in the road application. After a highway is built with steel slag, there will be problems with residual steel slag of a certain or several particle sizes, and there will be technical problems such as poor volume stability for road use, resulting in waste of resources and road safety risks.

[0004] Therefore, there is an urgent need for a technical solution that can use steel slag of all particle sizes and improve the efficiency of steel slag use. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention proposes a method for using and preparing steel slag of all particle sizes for full-layer application in pavement, comprising:

[0006] The steel slag is sampled, the diameter of each particle in the sample steel slag is obtained, and the diameter is divided into multiple particle size segments, and the particle size feature vector of each particle size segment in the sample steel slag is extracted;

[0007] Set the functional field corresponding to each layer of the road surface, confirm the response demand vector corresponding to each functional field, and calculate the matching degree between the particle size characteristic vector of each particle size segment and the response demand vector corresponding to each functional field;

[0008] According to the number of layers of the road surface, a matching degree threshold corresponding to the layer is set, and the matching degree is compared with the matching degree threshold of each layer. If the matching degree exceeds the matching degree threshold, the steel slag of the corresponding particle size segment is used in the corresponding layer, thereby completing the full-size use of steel slag.

[0009] Furthermore, the diameter of each particle in the sample slag is obtained and divided into multiple particle size segments including:

[0010] The sample steel slag is evenly spread on a shallow trough flat plate, and the particles are independent of each other;

[0011] Use a multi-angle camera array looking down from above to capture images of the granular material;

[0012] Perform three-dimensional reconstruction on the granules on the granule image, identify the outer contour of each granule, and obtain the equivalent spherical diameter of each granule;

[0013] A plurality of particle size segments are set, and all granular materials are divided into corresponding particle size segments according to the equivalent sphere diameter.

[0014] Furthermore, before calculating the matching degree between the particle size characteristic vector of each particle size segment and the response requirement vector corresponding to each functional field, the following steps are also included:

[0015] Through a shallow feedforward neural network, the particle size feature vector and the response requirement vector are mapped to a unified response attribute space, where the unified response attribute space is composed of the anti-cracking performance score, the energy absorption / dissipation capacity score, the expansion control ability score, and the bonding and interface synergy score.

[0016] Furthermore, calculating the matching degree between the particle size characteristic vector of each particle size segment and the response requirement vector corresponding to each functional field includes:

[0017]

[0018] Among them, Θ ij is the matching degree between the particle size feature vector of the i-th particle size segment and the response requirement vector corresponding to the j-th functional field, α is the similarity weight, is the score corresponding to the particle size feature vector of the i-th particle size segment in the unified response attribute space, is the score of the response requirement vector corresponding to the jth functional field in the unified response attribute space, for and The similarity of , β is the weight of the collaboration, for and degree of coordination.

[0019] Further, calculation and Similarity for:

[0020]

[0021] calculate for and The degree of coordination is

[0022]

[0023] Among them, ∈ is an anti-zero constant.

[0024] Furthermore, the particle size ranges include 0-3 mm, 3-5 mm, 5-10 mm, and 10-15 mm.

[0025] Furthermore, it also includes: positioning and stacking the steel slag in batches according to the month of steel slag production, testing the steel slag pile for stability control indicators, and treating the steel slag pile that does not meet the stability control indicators by natural aging, natural aging combined with watering or immersion treatment until it meets the stability control indicators.

[0026] Furthermore, the stability control indicators are water expansion rate ≤ 2%, pressure steam pulverization rate ≤ 2%, and free calcium oxide ≤ 2%.

[0027] Furthermore, for the steel slag pile that meets the stability control index, the steel slag pile is crushed by jaw crushing, cone crushing and / or roller crushing.

[0028] The present invention also provides a steel slag full-size mixing system for full-layer application in pavement, comprising:

[0029] The steel slag feature extraction module is used to sample the steel slag, obtain the diameter of each particle in the sample steel slag, divide it into multiple particle size segments, and extract the particle size feature vector of each particle size segment in the sample steel slag;

[0030] The matching module is used to set the functional field corresponding to each layer of the road surface, confirm the response demand vector corresponding to each functional field, and calculate the matching degree between the particle size characteristic vector of each particle size segment and the response demand vector corresponding to each functional field;

[0031] The allocation module is used to set the matching degree threshold corresponding to the layer according to the number of layers of the road surface, and compare the matching degree with the matching degree threshold of each layer. If the matching degree exceeds the matching degree threshold, the steel slag of the corresponding particle size segment will be used in the corresponding layer, thereby completing the allocation of steel slag for full particle size use.

[0032] In general, the above technical solutions conceived by the present invention have the following beneficial effects compared with the prior art:

[0033] Through the above technical solutions, the present invention develops a cascade application technology covering all layers of the road, realizing the high-value utilization of steel slag in different application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is a flow chart of the method of embodiment 1 of the present invention;

[0035] Figure 2 This is a system structure diagram of Example 2 of the present invention. DETAILED DESCRIPTION

[0036] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0037] The method provided by the present invention can be implemented in the following terminal environment, wherein the terminal may include one or more of the following components: a processor, a storage medium, and a display screen. The storage medium stores at least one instruction, which is loaded and executed by the processor to implement the method described in the following embodiments.

[0038] A processor can include one or more processing cores. It connects various components within the terminal using various interfaces and circuits. It executes instructions, programs, code sets, or instruction sets stored in storage media, and accesses data stored in storage media to perform various terminal functions and process data.

[0039] The storage medium may include a random access memory (RAM) or a read-only memory (ROM). The storage medium may be used to store instructions, programs, codes, code sets, or instructions.

[0040] The display is used to show the user interface of each application.

[0041] In addition, those skilled in the art will appreciate that the structure of the terminal described above does not limit the terminal. The terminal may include more or fewer components, or a combination of certain components, or a different arrangement of components. For example, the terminal may also include a radio frequency circuit, an input unit, a sensor, an audio circuit, a power supply, and other components, which will not be described in detail here.

[0042] Example 1

[0043] like Figure 1 As shown, this embodiment proposes a method for using and preparing steel slag of all particle sizes for all layers of a road surface, including:

[0044] Step 101: sampling steel slag, obtaining the diameter of each particle in the sampled steel slag, dividing the particle into multiple particle size segments, and extracting the particle size feature vector of each particle size segment in the sampled steel slag;

[0045] Steel slag has excellent physical and mechanical properties, good adhesion to asphalt, and the characteristics of a high-quality road construction material. However, steel slag differs significantly from crushed stone in terms of specific gravity, surface pore characteristics, and thermal conductivity. It also suffers from technical issues such as poor volume stability (the surface is rich in free calcium oxide and magnesium oxide, which expands by more than double upon hydration) and poor homogeneity. Therefore, pretreatment of steel slag is necessary.

[0046] With the goal of having "aggregate characteristics", the control indicators of "stability" and "homogenization" were proposed, and the aging process of "positioning batch + graded treatment" and the pretreatment technology of "multi-stage crushing + shaping and screening" were formed to produce homogenized steel slag aggregate, thus achieving "graded quality and full particle size" application.

[0047] Stability control indicators: water expansion rate ≤2%, steam pulverization rate ≤2%, free calcium oxide ≤2%.

[0048] Homogenization control index: Particle size distribution variation coefficient ≤ 5%.

[0049] Positioning batch + graded treatment: The slag is positioned and stacked in batches according to the production month, and treated using different technical paths such as "natural aging", "natural aging + watering" or "immersion treatment" according to the size of the stability control index test results.

[0050] Multi-stage crushing + shaping and screening pretreatment technology: According to the different steel slag production processes, a multi-stage combination crushing process of "jaw crushing + cone crushing + roller crushing" is adopted.

[0051] "Quality-graded grading, full-size granularity" application: According to the particle size distribution and performance characteristics of the pre-treated steel slag, it is divided into steel slag with different particle size levels such as 0-3mm, 3-5mm, 5-10mm, and 10-15mm.

[0052] Preferably, the particle size characteristic vector in this embodiment is as follows:

[0053]

[0054] The meanings of each are shown in the following table:

[0055] conform to Parameter name <![CDATA[φ i ]]> Free CaO content <![CDATA[η i ]]> Specific surface area <![CDATA[δ i ]]> Crushing value <![CDATA[ρ i ]]> Density coefficient

[0056] Specifically, the diameter of each particle in the sample steel slag is obtained and divided into multiple particle size segments including:

[0057] The sample steel slag is evenly spread on a shallow trough flat plate, and the particles are independent of each other;

[0058] Use a multi-angle camera array looking down from above to capture images of the granular material;

[0059] Perform three-dimensional reconstruction on the granules on the granule image, identify the outer contour of each granule, and obtain the equivalent spherical diameter of each granule;

[0060] A plurality of particle size segments are set, and all granular materials are divided into corresponding particle size segments according to the equivalent sphere diameter.

[0061] Step 102: Set a function field corresponding to each layer of the road surface, confirm the response requirement vector corresponding to each function field, and calculate the matching degree between the particle size characteristic vector of each particle size segment and the response requirement vector corresponding to each function field;

[0062] Preferably, the layers included in the road surface in this embodiment and the corresponding response requirement vectors are as follows:

[0063] Upper layer: high shear crack resistance layer, the corresponding response demand vector is:

[0064]

[0065] The meanings of each are shown in the following table:

[0066]

[0067]

[0068] Middle layer: energy absorption and diffusion layer, the corresponding response demand vector is:

[0069]

[0070]

[0071] Subbase: Anti-expansion layer, the corresponding response demand vector is:

[0072]

[0073]

[0074] Specifically, before calculating the matching degree between the particle size characteristic vector of each particle size segment and the response requirement vector corresponding to each functional field, the following steps are also included:

[0075] Through a shallow feedforward neural network, the particle size feature vector and the response requirement vector are mapped to a unified response attribute space, where the unified response attribute space is composed of the anti-cracking performance score, the energy absorption / dissipation capacity score, the expansion control ability score, and the bonding and interface synergy score.

[0076] Specifically, calculating the matching degree between the particle size characteristic vector of each particle size segment and the response requirement vector corresponding to each functional field includes:

[0077]

[0078] Among them, Θ ij is the matching degree between the particle size feature vector of the i-th particle size segment and the response requirement vector corresponding to the j-th functional field, α is the similarity weight, is the score corresponding to the particle size feature vector of the i-th particle size segment in the unified response attribute space, is the score of the response requirement vector corresponding to the jth functional field in the unified response attribute space, for and The similarity of , β is the weight of the collaboration, for and degree of coordination.

[0079] Scenario Recommended weight settings Preliminary screening, emphasizing spectral matching α＝0.6,β＝0.4 Engineering simulation or road surface feedback-guided design α＝0.3,β＝0.7 Prioritize responsiveness during the design phase α＝0.2,β＝0.8

[0080] Specifically, calculate and Similarity for:

[0081]

[0082] calculate for and The degree of coordination is

[0083]

[0084] Among them, ∈ is an anti-zero constant.

[0085] Step 103: According to the number of layers of the road surface, a matching degree threshold corresponding to each layer is set, and the matching degree is compared with the matching degree threshold of each layer. If the matching degree exceeds the matching degree threshold, the steel slag of the corresponding particle size segment is used in the corresponding layer, thereby completing the full-size use and deployment of steel slag.

[0086] Example 2

[0087] like Figure 2 As shown, this embodiment provides a system for mixing and distributing steel slag of all particle sizes for all layers of a road surface, including:

[0088] The steel slag feature extraction module is used to sample the steel slag, obtain the diameter of each particle in the sample steel slag, divide it into multiple particle size segments, and extract the particle size feature vector of each particle size segment in the sample steel slag;

[0089] Steel slag has excellent physical and mechanical properties, good adhesion to asphalt, and the characteristics of a high-quality road construction material. However, steel slag differs significantly from crushed stone in terms of specific gravity, surface pore characteristics, and thermal conductivity. It also suffers from technical issues such as poor volume stability (the surface is rich in free calcium oxide and magnesium oxide, which expands by more than double upon hydration) and poor homogeneity. Therefore, pretreatment of steel slag is necessary.

[0090] With the goal of having "aggregate characteristics", the control indicators of "stability" and "homogenization" were proposed, and the aging process of "positioning batch + graded treatment" and the pretreatment technology of "multi-stage crushing + shaping and screening" were formed to produce homogenized steel slag aggregate, thus achieving "graded quality and full particle size" application.

[0091] Stability control indicators: water expansion rate ≤2%, steam pulverization rate ≤2%, free calcium oxide ≤2%.

[0092] Homogenization control index: Particle size distribution variation coefficient ≤ 5%.

[0093] Positioning batch + graded treatment: The slag is positioned and stacked in batches according to the production month, and treated using different technical paths such as "natural aging", "natural aging + watering" or "immersion treatment" according to the size of the stability control index test results.

[0094] Multi-stage crushing + shaping and screening pretreatment technology: According to the different steel slag production processes, a multi-stage combination crushing process of "jaw crushing + cone crushing + roller crushing" is adopted.

[0095] "Quality-graded grading, full-size granularity" application: According to the particle size distribution and performance characteristics of the pre-treated steel slag, it is divided into steel slag with different particle size levels such as 0-3mm, 3-5mm, 5-10mm, and 10-15mm.

[0096] Specifically, the diameter of each particle in the sample steel slag is obtained and divided into multiple particle size segments including:

[0097] The sample steel slag is evenly spread on a shallow trough flat plate, and the particles are independent of each other;

[0098] Use a multi-angle camera array looking down from above to capture images of the granular material;

[0099] Perform three-dimensional reconstruction on the granules on the granule image, identify the outer contour of each granule, and obtain the equivalent spherical diameter of each granule;

[0100] A plurality of particle size segments are set, and all granular materials are divided into corresponding particle size segments according to the equivalent sphere diameter.

[0101] The matching module is used to set the functional field corresponding to each layer of the road surface, confirm the response demand vector corresponding to each functional field, and calculate the matching degree between the particle size characteristic vector of each particle size segment and the response demand vector corresponding to each functional field;

[0102] Specifically, before calculating the matching degree between the particle size characteristic vector of each particle size segment and the response requirement vector corresponding to each functional field, the following steps are also included:

[0103] Through a shallow feedforward neural network, the particle size feature vector and the response requirement vector are mapped to a unified response attribute space, where the unified response attribute space is composed of the anti-cracking performance score, the energy absorption / dissipation capacity score, the expansion control ability score, and the bonding and interface synergy score.

[0104] Specifically, calculating the matching degree between the particle size characteristic vector of each particle size segment and the response requirement vector corresponding to each functional field includes:

[0105]

[0106] Among them, Θ ij is the matching degree between the particle size feature vector of the i-th particle size segment and the response requirement vector corresponding to the j-th functional field, α is the similarity weight, is the score corresponding to the particle size feature vector of the i-th particle size segment in the unified response attribute space, is the score of the response requirement vector corresponding to the jth functional field in the unified response attribute space, for and The similarity of , β is the weight of the collaboration, for and degree of coordination.

[0107] Specifically, calculate and Similarity for:

[0108]

[0109] calculate for and The degree of coordination is

[0110]

[0111] Among them, ∈ is an anti-zero constant.

[0112] The allocation module is used to set the matching degree threshold corresponding to the layer according to the number of layers of the road surface, and compare the matching degree with the matching degree threshold of each layer. If the matching degree exceeds the matching degree threshold, the steel slag of the corresponding particle size segment will be used in the corresponding layer, thereby completing the allocation of steel slag for full particle size use.

[0113] Example 3

[0114] This embodiment also proposes a method, which is specifically as follows:

[0115] (1) Selection of steel slag particle size specifications

[0116] In the water-stable base, crushed stone is used for coarse particles and steel slag is used for fine particles. The reasons are as follows:

[0117] ① As a semi-rigid material, water-stable bases are more sensitive to stress concentration and localized uneven expansion damage. Research on the volumetric stability of steel slag reveals that as slag particle size increases, f-CaO enrichment increases, increasing the probability of stress concentration and the risk. Therefore, fine aggregate should be used for steel slag in water-stable bases to avoid stress concentration caused by f-CaO enrichment in coarse aggregates, which can lead to localized expansion damage.

[0118] ② To address the expansion problem caused by fine aggregate in steel slag, fly ash is introduced to regulate its "suspended volume expansion." This is because fly ash, as a flexible material, has room for expansion and can form a gelling reaction with the dicalcium silicate and tricalcium silicate on the surface of the steel slag, further improving the strength of the steel slag water-stabilized base.

[0119] (2) Mix ratio design of steel slag water-stable base

[0120] Through the mix ratio design of steel slag water-stabilized base, the key control parameters of the mix ratio design of steel slag water-stabilized base, "ash-slag ratio" and "particle size control threshold" are proposed.

[0121] It is proposed that the particle size control threshold of steel slag in the base mixture should be ≤5mm and the ash-slag ratio of fly ash to steel slag should be 0.4-0.6.

[0122] Therefore, when the pavement structure consists of an asphalt surface layer and a cement-stable base layer, a systematic study of steel slag and its mixture has led to the proposal to use coarse-grained steel slag in the asphalt surface layer, with a particle size control threshold of 3mm or greater, and fine-grained steel slag in the cement-stable base layer, with a particle size control threshold of 5mm or less. The selection of particle size specifications within the threshold range should be combined with the gradation requirements of the concrete type used in each pavement structural layer to determine the range of values ​​for each particle size.

[0123] At the same time, in road construction, the particle size distribution of steel slag can be combined with the selection of particle size specifications within the particle size threshold range of each structural layer, forming a complementary and dynamic adjustment relationship with the particle size distribution of steel slag to achieve the full particle size application of steel slag in all layers of the road surface. Calculated in square meters, the full particle size application plan is shown in the following table:

[0124]

[0125]

[0126] in:

[0127] The mass of each grade of steel slag is: the mass of a certain grade of steel slag used in a certain structural layer within a unit volume;

[0128] m and: the mass of steel slag at a certain level in each structural layer;

[0129] MA design: the mass of a certain level of steel slag in each structural layer and / the mass of all levels of steel slag in each structural layer;

[0130] M benchmark: distribution pattern of each size range of steel slag aggregate;

[0131] M Deviation: m Design - M Benchmark

[0132] Example 4

[0133] An embodiment of the present invention further provides a storage medium storing a plurality of instructions, wherein the instructions are used to implement the method for using and preparing steel slag of all particle sizes for application in all layers of a road surface.

[0134] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0135] Optionally, in this embodiment, the storage medium is configured to store program codes for executing the following steps: Step 101, sampling steel slag, obtaining the diameter of each particle in the sampled steel slag, dividing the particle diameter into a plurality of particle size segments, and extracting a particle size feature vector of each particle size segment in the sampled steel slag;

[0136] Steel slag has excellent physical and mechanical properties, good adhesion to asphalt, and the characteristics of a high-quality road construction material. However, steel slag differs significantly from crushed stone in terms of specific gravity, surface pore characteristics, and thermal conductivity. It also suffers from technical issues such as poor volume stability (the surface is rich in free calcium oxide and magnesium oxide, which expands by more than double upon hydration) and poor homogeneity. Therefore, pretreatment of steel slag is necessary.

[0137] With the goal of having "aggregate characteristics", the control indicators of "stability" and "homogenization" were proposed, and the aging process of "positioning batch + graded treatment" and the pretreatment technology of "multi-stage crushing + shaping and screening" were formed to produce homogenized steel slag aggregate, thus achieving "graded quality and full particle size" application.

[0138] Stability control indicators: water expansion rate ≤2%, steam pulverization rate ≤2%, free calcium oxide ≤2%.

[0139] Homogenization control index: Particle size distribution variation coefficient ≤ 5%.

[0140] Positioning batch + graded treatment: The slag is positioned and stacked in batches according to the production month, and treated using different technical paths such as "natural aging", "natural aging + watering" or "immersion treatment" according to the size of the stability control index test results.

[0141] Multi-stage crushing + shaping and screening pretreatment technology: According to the different steel slag production processes, a multi-stage combination crushing process of "jaw crushing + cone crushing + roller crushing" is adopted.

[0142] "Quality-graded grading, full-size granularity" application: According to the particle size distribution and performance characteristics of the pre-treated steel slag, it is divided into steel slag with different particle size levels such as 0-3mm, 3-5mm, 5-10mm, and 10-15mm.

[0143] Specifically, the diameter of each particle in the sample steel slag is obtained and divided into multiple particle size segments including:

[0144] The sample steel slag is evenly spread on a shallow trough flat plate, and the particles are independent of each other;

[0145] Use a multi-angle camera array looking down from above to capture images of the granular material;

[0146] Perform three-dimensional reconstruction on the granules on the granule image, identify the outer contour of each granule, and obtain the equivalent spherical diameter of each granule;

[0147] A plurality of particle size segments are set, and all granular materials are divided into corresponding particle size segments according to the equivalent sphere diameter.

[0148] Step 102: Set a function field corresponding to each layer of the road surface, confirm the response requirement vector corresponding to each function field, and calculate the matching degree between the particle size characteristic vector of each particle size segment and the response requirement vector corresponding to each function field;

[0149] Specifically, before calculating the matching degree between the particle size characteristic vector of each particle size segment and the response requirement vector corresponding to each functional field, the following steps are also included:

[0150] Through a shallow feedforward neural network, the particle size feature vector and the response requirement vector are mapped to a unified response attribute space, where the unified response attribute space is composed of the anti-cracking performance score, the energy absorption / dissipation capacity score, the expansion control ability score, and the bonding and interface synergy score.

[0151] Specifically, calculating the matching degree between the particle size characteristic vector of each particle size segment and the response requirement vector corresponding to each functional field includes:

[0152]

[0153] Among them, Θ ij is the matching degree between the particle size feature vector of the i-th particle size segment and the response requirement vector corresponding to the j-th functional field, α is the similarity weight, is the score corresponding to the particle size feature vector of the i-th particle size segment in the unified response attribute space, is the score of the response requirement vector corresponding to the jth functional field in the unified response attribute space, for and The similarity of , β is the weight of the collaboration, for and degree of coordination.

[0154] Specifically, calculate and Similarity for:

[0155]

[0156] calculate for and The degree of coordination is

[0157]

[0158] Among them, ∈ is an anti-zero constant.

[0159] Step 103: According to the number of layers of the road surface, a matching degree threshold corresponding to each layer is set, and the matching degree is compared with the matching degree threshold of each layer. If the matching degree exceeds the matching degree threshold, the steel slag of the corresponding particle size segment is used in the corresponding layer, thereby completing the full-size use and deployment of steel slag.

[0160] Example 5

[0161] An embodiment of the present invention also proposes an electronic device, including a processor and a storage medium connected to the processor, wherein the storage medium stores multiple instructions, and the instructions can be loaded and executed by the processor to enable the processor to execute the method for using and preparing steel slag of all particle sizes for full-layer application in pavement.

[0162] Specifically, the electronic device of this embodiment may be a computer terminal, which may include: one or more processors, and a storage medium.

[0163] Among them, the storage medium can be used to store software programs and modules, such as the method for using and preparing steel slag of all particle sizes for full-layer application in a pavement in an embodiment of the present invention, and the corresponding program instructions / modules. The processor executes various functional applications and data processing by running the software programs and modules stored in the storage medium, that is, realizing the above-mentioned method for using and preparing steel slag of all particle sizes for full-layer application in a pavement. The storage medium may include high-speed random access storage media, and may also include non-volatile storage media, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium may further include storage media remotely located relative to the processor, and these remote storage media may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0164] The processor can call the information and application programs stored in the storage medium through the transmission system to execute the method steps of Example 1.

[0165] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0166] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0167] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the system embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, and can be electrical or other forms.

[0168] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0169] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0170] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only storage medium (ROM, Read-Only Memory), random access storage medium (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0171] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will readily appreciate that other variations or modifications based on the above descriptions are possible. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. A method for using and preparing steel slag of all particle sizes for all layers of a road surface, characterized in that: include: The steel slag is sampled, the diameter of each particle in the sample steel slag is obtained, and the diameter is divided into multiple particle size segments, and the particle size feature vector of each particle size segment in the sample steel slag is extracted; Set the functional field corresponding to each layer of the road surface, confirm the response demand vector corresponding to each functional field, and calculate the matching degree between the particle size characteristic vector of each particle size segment and the response demand vector corresponding to each functional field; According to the number of layers of the road surface, a matching degree threshold corresponding to the layer is set, and the matching degree is compared with the matching degree threshold of each layer. If the matching degree exceeds the matching degree threshold, the steel slag of the corresponding particle size segment is used in the corresponding layer, thereby completing the full-size use of steel slag.

2. The method for preparing steel slag of all particle sizes for full-layer application in a road surface as claimed in claim 1, characterized in that: Obtain the diameter of each particle in the sample steel slag and divide it into multiple particle size segments including: The sample steel slag is evenly spread on a shallow trough flat plate, and the particles are independent of each other; Use a multi-angle camera array looking down from above to capture images of the granular material; Perform three-dimensional reconstruction on the granules on the granule image, identify the outer contour of each granule, and obtain the equivalent spherical diameter of each granule; A plurality of particle size segments are set, and all granular materials are divided into corresponding particle size segments according to the equivalent sphere diameter.

3. The method for preparing steel slag of all particle sizes for full-layer application in a road surface as claimed in claim 1, characterized in that: Before calculating the matching degree between the particle size characteristic vector of each particle size segment and the response requirement vector corresponding to each functional field, the following steps are also included: Through a shallow feedforward neural network, the particle size feature vector and the response requirement vector are mapped to a unified response attribute space, where the unified response attribute space is composed of the anti-cracking performance score, the energy absorption / dissipation capacity score, the expansion control ability score, and the bonding and interface synergy score.

4. The method for using and preparing steel slag of all particle sizes for full-layer application in a road surface as claimed in claim 3, characterized in that: Calculating the matching degree between the particle size characteristic vector of each particle size segment and the response demand vector corresponding to each functional field includes: Among them, Θ ij is the matching degree between the particle size feature vector of the i-th particle size segment and the response requirement vector corresponding to the j-th functional field, α is the similarity weight, is the score corresponding to the particle size feature vector of the i-th particle size segment in the unified response attribute space, is the score of the response requirement vector corresponding to the jth functional field in the unified response attribute space, for and The similarity of , β is the weight of the cooperation degree, for and degree of coordination.

5. The method for preparing steel slag of all particle sizes for full-layer application in a road surface as claimed in claim 4, characterized in that: calculate and Similarity for: calculate for and The degree of coordination is Among them, ∈ is an anti-zero constant.

6. The method for using and preparing steel slag of all particle sizes for full-layer application in a road surface as claimed in claim 1, characterized in that: The particle size ranges include 0-3 mm, 3-5 mm, 5-10 mm, and 10-15 mm.

7. The method for using and preparing steel slag of all particle sizes for full-layer application in a road surface as claimed in claim 1, characterized in that: Also includes: The steel slag is stacked in batches according to the month of steel slag production, and the steel slag piles are tested for stability control indicators. For steel slag piles that do not meet the stability control indicators, they are treated by natural aging, natural aging combined with water sprinkling or immersion treatment until they meet the stability control indicators.

8. The method for using and preparing steel slag of all particle sizes for all layers of a road surface as claimed in claim 7, characterized in that: The stability control indicators are: water expansion rate ≤ 2%, pressure steam pulverization rate ≤ 2%, and free calcium oxide ≤ 2%.

9. The method for using and preparing steel slag of all particle sizes for full-layer application in a road surface as claimed in claim 8, characterized in that: For steel slag piles that meet the stability control indicators, jaw crushing, cone crushing and / or roller crushing are used to crush the steel slag piles.

10. A system for mixing and distributing steel slag of all particle sizes for all layers of a road surface, characterized in that: include: The steel slag feature extraction module is used to sample the steel slag, obtain the diameter of each particle in the sample steel slag, divide it into multiple particle size segments, and extract the particle size feature vector of each particle size segment in the sample steel slag; The matching module is used to set the functional field corresponding to each layer of the road surface, confirm the response demand vector corresponding to each functional field, and calculate the matching degree between the particle size characteristic vector of each particle size segment and the response demand vector corresponding to each functional field; The allocation module is used to set the matching degree threshold corresponding to the layer according to the number of layers of the road surface, and compare the matching degree with the matching degree threshold of each layer. If the matching degree exceeds the matching degree threshold, the steel slag of the corresponding particle size segment will be used in the corresponding layer, thereby completing the allocation of steel slag for full particle size use.

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