Ecological cement preparation process and system based on image processing

Abstract

The application relates to the technical field of ecological cement preparation, and particularly relates to an ecological cement preparation process and system based on image processing, which comprises the following steps: collecting and analyzing surface images of a to-be-paved road surface to obtain recessed parts on the to-be-paved road surface; collecting and analyzing surrounding substances to obtain analysis results; preliminarily adjusting preset proportions of raw materials according to the analysis results; respectively grinding the raw materials to detect particle diameters, stopping the grinding when the maximum diameter value is less than or equal to a preset diameter value, and then drying and mixing to obtain original cement; detecting initial setting time and final setting time of the original cement and adjusting the proportions of the raw materials according to the detection results; pouring the original cement into a mold to prepare a model and detecting a linear expansion rate, determining a final proportion according to adjustment of the preset proportion, a second proportion and a third proportion, and preparing cement for re-detection. The application improves resource comprehensive utilization rate in a cement production process.

Description

Technical Field

[0001] This invention relates to the field of eco-friendly cement preparation technology, and in particular to an eco-friendly cement preparation process and system based on image processing. Background Technology

[0002] In a narrow sense, eco-cement refers to a hydraulic cementitious material made primarily from municipal waste incineration ash and sewage sludge through firing and grinding. In a broader sense, eco-cement is not a single type of cement, but rather an evaluation of the "health, environmental protection, and safety" attributes of cement, encompassing both individual and comprehensive evaluations of five key aspects: raw material acquisition, production process, construction process, usage process, and waste disposal. Beyond its practical use as a building material, the fundamental functions of eco-cement lie in protecting human health and the environment.

[0003] Patent document CN115572142A discloses an eco-friendly and healthy cement, which comprises the following components by weight: 80-100 parts of anti-toxic and filtration environmentally friendly cement, 70-95 parts of air-purifying environmentally friendly cement, 60-80 parts of flame-retardant environmentally friendly cement, 60-85 parts of natural bacteria and ultraviolet-resistant environmentally friendly cement, 40-65 parts of latex environmentally friendly cement, 50-75 parts of antiviral environmentally friendly cement, 25-40 parts of inorganic industrial waste, 10-18 parts of functional additives, 20-22 parts of modified hair fiber, 6-10 parts of clinker, 5-7 parts of reinforcing agent, 8-10 parts of grinding aid, and 10-20 parts of hexavalent chromium ion reducing agent. The cement comprises, by weight, 5-10 parts of redispersible latex powder and 3-5 parts of defoamer; wherein, the anti-toxic and filtration environmentally friendly cement comprises, by weight, 5-6 parts of barite powder, 6-7 parts of iron oxide powder, 7-9 parts of olivine powder, 10-12 parts of slag and 52-76 parts of silicate cement; the air-purifying environmentally friendly cement comprises, by weight, 5-7 parts of fly ash, 7-8 parts of waste zinc-manganese slag powder, 9-10 parts of maifanite powder, 3-4 parts of tourmaline powder, 8-12 parts of gypsum powder, 32-44 parts of silicate cement and 6-10 parts of ceramic powder; the flame-retardant environmentally friendly cement comprises, by weight, 5-7 parts of glass fiber powder, 3-5 parts of gypsum powder and 5-6 parts of redispersible latex powder and 3-5 parts of defoamer; 4 parts, 27-33 parts of acid cement, 1-2 parts of organosilicon water-repellent agent, 6-9 parts of lime powder, 5-7 parts of manganese slag powder, 3-5 parts of sodium polyacrylate, 2-3 parts of aminobenzenesulfonic acid, 8-10 parts of ammonium dihydrogen phosphate; the natural bacteria ultraviolet-resistant environmentally friendly cement includes the following by weight: 1-2 parts of fly ash, 2-3 parts of volcanic slag sand, 3-4 parts of waste plastic bottle fiber, 2-4 parts of waste glass particles, 5-8 parts of rice husk ash, 3-5 parts of crushed shale ceramsite, 2-5 parts of calcium oxide expanding agent, 6-7 parts of superabsorbent resin, 2-4 parts of anti-ultraviolet additive, 2-3 parts of bio-based water-reducing agent, 1-2 parts of chitin fiber powder, silicate cement. 31-38 parts, wherein the UV-resistant additive and the bio-based water-reducing agent are mixed beforehand; the latex-based environmentally friendly cement comprises the following parts by weight: 1-2 parts far-infrared ceramic powder, 5-10 parts high-calcium cement, 3-4 parts asbestos powder, 2-3 parts coral fossil powder, 10-12 parts emulsified asphalt, 7-8 parts mummite powder, and 12-26 parts natural latex; the antiviral environmentally friendly cement comprises the following parts by weight: 2-3 parts nano silver, 3-5 parts carbonized cotton fiber powder, 2-4 parts sulfur powder, 6-8 parts zinc oxide, 1-2 parts chitosan fiber powder, 3-4 parts water glass powder, 5-7 parts sodium fluoride powder, and 28-42 parts silicate cement.

[0004] In existing technologies, natural gypsum is used as a retarder in the cement manufacturing process, which results in poor retarding effect of the cement, makes production control difficult, and leads to low resource utilization rate in the cement production process. Summary of the Invention

[0005] Therefore, this invention provides an ecological cement preparation process and system based on image processing, which can solve the problem of low resource utilization rate in cement production.

[0006] To achieve the above objectives, the present invention provides an image processing-based eco-cement preparation process, comprising:

[0007] The surface image of the road surface to be paved is acquired by an image acquisition device, and the road surface image is analyzed to obtain the depressions on the road surface to be paved.

[0008] The material surrounding the recessed portion is collected and analyzed to obtain the analytical results.

[0009] Based on the analysis results of the substances, the preset proportions of several cement raw materials were initially adjusted;

[0010] Several raw materials are ground separately, and the particle diameter of the ground raw materials is detected to obtain several diameter values. The largest diameter value among the several diameter values ​​is compared with a preset diameter value. When the largest diameter value is less than or equal to the preset diameter value, the grinding is stopped. The ground raw materials are then dried and mixed to obtain raw cement.

[0011] The initial setting time and final setting time of the original cement were tested, and the specific gravity of some raw materials in the original cement was adjusted according to the test results to obtain a second specific gravity.

[0012] The original cement is poured into a mold to prepare a model. The linear expansion rate of the model is tested at each age after curing in water. Based on the test results, the specific gravity of some raw materials in the original cement is adjusted to obtain a third specific gravity.

[0013] The final specific gravity is determined by adjusting the preset specific gravity, the second specific gravity, and the third specific gravity. Cement is then remade based on the final specific gravity of several raw materials to obtain the final cement. The initial setting time, final setting time, and linear expansion rate of the final cement are then tested again. If the test results are different from the preset results, the final specific gravity of several raw materials in the final cement is readjusted, cement is made, and the tests are conducted again until the test results are the same as the preset results.

[0014] Further, analyzing the road surface image to obtain the depressions on the road surface to be paved includes:

[0015] Convert the road surface image into a grayscale image;

[0016] The road surface image is divided horizontally and vertically according to a preset distance to obtain several first regions;

[0017] Edge detection is performed on several of the first regions using an edge detection algorithm to obtain several edge contours;

[0018] The regions containing several edge contours are extracted to obtain several second regions;

[0019] The gray values ​​of several second regions are detected, and the regions with gray values ​​greater than a preset gray value are extracted to obtain the depressions on the road surface to be paved.

[0020] Furthermore, the material surrounding the recessed portion is analyzed, and the material analysis results include:

[0021] Extract the material around the recessed portion;

[0022] Grind the substance until it becomes a powder, then stop grinding.

[0023] The analytical results of the powdered substance were obtained by analyzing several constituent elements and their corresponding specific gravities using X-ray fluorescence analysis.

[0024] Furthermore, based on the analysis results of the aforementioned substances, the preliminary adjustment of the preset proportions of several raw materials in the original cement includes:

[0025] The specific gravities of the limestone, slag, and fly ash substances extracted from the substances are a1, b1, and c1, respectively.

[0026] Compare it with the preset specific gravity of limestone, slag and fly ash in the original cement, which are a2, b2 and c2 respectively, and obtain the comparison results;

[0027] Based on the comparison results, the first correction coefficient k1 is calculated as follows:

[0028] The preset proportions of limestone, slag and fly ash in the original cement are adjusted according to the first correction coefficient k1 to obtain the initial proportions of limestone, slag and fly ash in the original cement as a3, b3 and c3, where a3 = k1 × a2, b3 = k1 × b2 and c3 = k1 × c2.

[0029] Further, the raw materials are ground separately, and the particle diameter of the ground raw materials is detected to obtain several diameter values. The largest diameter value among the several diameter values ​​is compared with a preset diameter value, including:

[0030] The raw materials selected from the original cement include clinker, limestone, slag, fly ash and phosphogypsum;

[0031] The initial specific gravities of the clinker, limestone, slag, fly ash, and phosphogypsum are selected as d1, a3, b3, c3, and e1, respectively.

[0032] The clinker, limestone, slag, fly ash, and phosphogypsum are ground separately using a grinding mill at a first speed for a first time period, and then the grinding is stopped.

[0033] The diameter of the ground particles was measured using a laser particle size analyzer to obtain several diameter values.

[0034] If the largest diameter value among the plurality of diameter values ​​is greater than the preset diameter value, grinding is performed again. Grinding is stopped after grinding at the second speed for a second time period. The diameter value of the ground particles is detected again. Grinding is stopped when the total maximum diameter value of the plurality of diameter values ​​is less than or equal to the preset diameter value. The second speed is greater than the first speed, and the second time period is equal to the first time period.

[0035] Further, drying and mixing the milled raw materials includes:

[0036] The ground clinker, limestone, slag, fly ash, and phosphogypsum are dried using a drying device. The actual moisture content of the clinker, limestone, slag, fly ash, and phosphogypsum is detected and compared with a preset moisture content. If the actual moisture content is less than or equal to the preset moisture content, the drying process is stopped.

[0037] The dried clinker, limestone, slag, fly ash, and phosphogypsum are placed in a mixing device and stirred until they are evenly mixed. After the first stirring time period, stirring is stopped to obtain the original cement.

[0038] Furthermore, the detection of the initial setting time and final setting time of the original cement includes:

[0039] Several resistivity values ​​of the original cement were measured in real time using a resistivity meter.

[0040] Establish a rectangular coordinate system with time as the horizontal axis and resistivity as the vertical axis;

[0041] Several resistivity values ​​are plotted as points in the rectangular coordinate system, and adjacent points are connected to obtain a resistivity image.

[0042] The resistivity difference between two adjacent points is calculated sequentially from left to right to obtain several resistivity difference values.

[0043] The resistivity differences are compared sequentially with a preset resistivity difference. When the resistivity difference is greater than or equal to the preset resistivity difference, two points corresponding to the resistivity difference are extracted. The maximum time corresponding to the two points is the initial setting time of the original cement.

[0044] Analyzing the resistivity image, when the resistivity image reaches an inflection point, the latter half of the image shows a stable trend, and the time corresponding to the inflection point is the final setting time of the original cement.

[0045] Furthermore, adjusting the proportions of certain raw materials in the original cement based on the test results includes:

[0046] When the initial setting time is less than the preset initial setting time, let the initial setting time be t1 and the preset initial setting time be t2, then the second correction coefficient is:

[0047] When the final setting time is less than the preset final setting time, let the final setting time be t3 and the preset final setting time be t4, then the third correction coefficient k3 is:

[0048] The initial specific gravity of phosphogypsum in the original cement is adjusted to e2 according to the second correction coefficient k2, where e2 = e1 + k2 × e1;

[0049] The initial specific gravity of phosphogypsum in the original cement is adjusted to e3 according to the third correction coefficient k3, where e3 = e1 + k3 × e1;

[0050] The initial specific gravity of clinker in the original cement is adjusted to d2 according to the second correction coefficient k2, where d2 = d1 - k2 × d1;

[0051] The initial specific gravity of clinker in the original cement is adjusted to d2 according to the third correction coefficient k3, where d3 = d1 - k3 × d1.

[0052] Furthermore, the linear expansion rate of the model cured in water at various ages was tested, and the specific gravity of certain raw materials in the original cement was adjusted based on the test results, including:

[0053] Measure the initial length, initial width, and initial height of the model, and calculate the initial volume of the model based on the initial length, initial width, and initial height.

[0054] The model was placed in water for maintenance, with constant water temperature and humidity conditions.

[0055] On the 7th day, the model is taken out, and the first length, first width and first height of the model are measured. The first volume of the model is calculated based on the first length, first width and first height.

[0056] Let the initial volume be V1 and the first volume be V2, then the first linear expansion rate α1 of the model on day 7 is:

[0057] On the 28th day, the model was removed, and the second length, second width, and second height of the model were measured. The second volume of the model was then calculated based on the second length, second width, and second height.

[0058] Let the initial volume be V1 and the second volume be V3, then the second linear expansion rate α2 of the model on day 28 is:

[0059] When the first linear expansion rate is less than the preset linear expansion rate, let the preset linear expansion rate be α3, then the fourth correction coefficient k4 is...

[0060] The initial specific gravity of limestone in the original cement is adjusted to a4 according to the fourth correction coefficient k4, where a4 = a3 + k4 × a3;

[0061] When the second linear expansion rate is less than the preset linear expansion rate, let the preset linear expansion rate be α3, then the fifth correction coefficient k5 is:

[0062] The initial specific gravity of limestone in the original cement is adjusted to a5 according to the fifth correction coefficient k5, where a5 = a3 + k5 × a3.

[0063] Furthermore, a system for an image processing-based eco-cement preparation process, the system comprising:

[0064] The image acquisition module acquires surface images of the road surface to be paved through an image acquisition device, obtains road surface images, analyzes the road surface images, and obtains the depressions on the road surface to be paved.

[0065] The material analysis module is connected to the image acquisition module to collect and analyze the material around the recessed portion and obtain the analysis results of the material.

[0066] The first adjustment module is connected to the material analysis module and adjusts the preset proportions of several cement raw materials based on the analysis results of the material.

[0067] The cement acquisition module is connected to the first adjustment module. It grinds several raw materials separately, detects the particle diameter of the several raw materials after grinding, obtains several diameter values, and compares the largest diameter value among the several diameter values ​​with a preset diameter value. When the largest diameter value is less than or equal to the preset diameter value, grinding is stopped. The several raw materials after grinding are dried and mixed to obtain raw cement.

[0068] The time detection module detects the initial setting time and final setting time of the original cement, and adjusts the proportion of some raw materials in the original cement according to the detection results to obtain a second proportion.

[0069] The linear expansion rate detection module pours the original cement into a mold to prepare a model, detects the linear expansion rate of the model after curing it in water to various ages, and adjusts the specific gravity of some raw materials in the original cement according to the detection results to obtain a third specific gravity.

[0070] The second adjustment module determines the final specific gravity based on the adjustment of the preset specific gravity, the second specific gravity, and the third specific gravity. It then re-processes cement based on the final specific gravity of several raw materials to obtain the final cement. The module also re-detects the initial setting time, final setting time, and linear expansion rate of the final cement. If the detection results differ from the preset results, the module readjusts the final specific gravity of several raw materials in the final cement, processes the cement, and conducts further detection until the detection results match the preset results.

[0071] Compared with existing technologies, the beneficial effects of this invention are as follows: by acquiring and analyzing road surface images using image acquisition equipment, the depressions in the road surface can be accurately identified, improving the accuracy and efficiency of the analysis. Analysis of the material surrounding the depressions provides a basis for adjusting the preset proportion of cement raw materials, making the prepared cement more suitable for the needs of the road surface to be paved. Adjusting the preset proportion of the original cement raw materials based on the analysis results makes the cement ratio more reasonable, ensuring that the cement composition matches the geological conditions of the road surface to be paved, thus improving the adaptability and durability of the cement. The raw materials are ground separately, and the particle diameter of the ground raw materials is detected to obtain the diameter value. The maximum diameter value is compared with the preset diameter value. Grinding is stopped when the maximum diameter value is less than or equal to the preset diameter value, thus ensuring the raw materials... The particle size meets the requirements, improving the quality and performance of subsequent cement production. The initial and final setting times of the original cement are tested, and the proportions of some raw materials are adjusted based on the test results to obtain a second proportion that better meets actual needs. This improves the retarding effect of the original cement, enhancing its workability and later strength. The original cement is poured into a mold to prepare a model, and the linear expansion rate of the model is tested at each age after curing in water. Based on the test results, the proportions of some raw materials are adjusted to obtain a third proportion, further optimizing the performance of the original cement and improving its adaptability and durability. The proportions of the raw materials are adjusted again based on the test results, and the cement is then tested again to ensure that the prepared cement meets the requirements, improving its reliability and stability and resulting in high resource utilization in the cement production process.

[0072] In particular, by converting the road surface image into a grayscale image, the concave parts in the road surface image are made clearer, avoiding interference from other noise, and making the detection of the concave parts more accurate. By dividing the road surface image horizontally and vertically, the analysis of the road surface image is more detailed, and the acquisition of road surface information is more comprehensive and accurate. By performing edge detection on the first region using an edge detection algorithm, clearer and more accurate edge contours are obtained, improving the detection accuracy of the concave parts. By extracting the region containing the edge contour, the detection range of the concave parts is further narrowed, improving the detection accuracy. By detecting the grayscale value of the second region and extracting the region with a grayscale value greater than a preset grayscale value, the concave parts on the road surface to be paved are obtained more accurately, providing an accurate location for subsequent collection of materials around the road surface concave parts, and improving the efficiency of subsequent material extraction.

[0073] In particular, by extracting the material around the recessed portion, a richer and more accurate analytical sample is obtained, improving the accuracy of the analysis of the material around the recessed portion. By grinding the material into powder, the constituent elements inside the material are better exposed, improving the accuracy of subsequent analysis. By using X-ray fluorescence analysis, multiple constituent elements and their corresponding specific gravities are determined simultaneously, improving the efficiency and effectiveness of the analysis. The obtained material analysis results provide an important reference for the subsequent adjustment of the preset specific gravities of cement raw materials, improving the adaptability and durability of cement.

[0074] In particular, adjusting the preset specific gravity based on the material analysis results better adapts to the geological conditions of the road surface to be paved, improving the adaptability and durability of the cement. By comparing the difference between the preset specific gravity and the actual specific gravity, the preset specific gravity is corrected more accurately, improving the accuracy and reliability of the preset specific gravity of the raw materials in the original cement. By calculating the first correction coefficient, the adjustment of the preset specific gravity becomes more accurate and precise. The adjusted initial specific gravity provides an important reference for subsequent batching and preparation, improving the quality and performance of the prepared cement.

[0075] In particular, by grinding and testing the particle diameter of different raw materials separately, the particle size of the raw materials can be better controlled, thereby improving the quality and performance of cement. By setting the first speed and the second speed, the grinding intensity can be better controlled, avoiding over-grinding that results in overly fine particles, while also improving grinding efficiency. By setting the second speed to be greater than the first speed and the second time period to be equal to the first time period, the uniformity and stability of grinding can be ensured, so that the particle diameter reaches the preset requirements. The raw materials after grinding and testing can be dried and mixed to prepare higher quality cement, thereby improving the quality and durability of the road surface.

[0076] In particular, by drying clinker, limestone, slag, fly ash, and phosphogypsum to remove moisture, the water content is reduced, thereby improving the quality and stability of the raw materials. By comparing the actual water content with the preset water content, it is ensured that the water content of the raw materials meets the mixing requirements, avoiding production problems caused by inaccurate water content. By placing the dried raw materials into a mixing device for stirring, the raw materials are fully and evenly mixed, ensuring the quality and stability of the original cement. Through drying and mixing, the original cement raw materials are quickly mixed, saving the production time of the original cement and improving the production efficiency of the original cement.

[0077] In particular, by measuring resistivity values ​​in real time, the cement setting process can be monitored more accurately, improving the reliability and accuracy of the detection. By establishing a rectangular coordinate system and plotting the resistivity values ​​as points on the coordinate system, the trend of resistivity value changes can be presented intuitively, facilitating the analysis and judgment of the cement setting state. By calculating the resistivity difference between two adjacent points and comparing it with a preset resistivity difference, the initial setting time can be determined more accurately, improving the accuracy of the detection. By analyzing the resistivity image, the cement setting process can be understood more comprehensively, and the final setting time can be accurately determined, providing a data basis for adjusting the proportion of certain raw materials in the original cement. Attached Figure Description

[0078] Figure 1 A schematic flowchart of an image processing-based eco-cement preparation process provided in an embodiment of the present invention;

[0079] Figure 2 A structural diagram of a grinding device for an image processing-based ecological cement preparation process provided in an embodiment of the present invention;

[0080] Figure 3 This is a structural block diagram of an image processing-based cement preparation system provided in an embodiment of the present invention. Detailed Implementation

[0081] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0082] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0083] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0084] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0085] Please see Figure 1 As shown, this embodiment of the invention provides an image processing-based eco-cement preparation process, which includes:

[0086] Step S100: Acquire a surface image of the road surface to be paved using an image acquisition device, obtain a road surface image, analyze the road surface image, and obtain the depression portion on the road surface to be paved.

[0087] Step S200: Collect and analyze the material around the recessed portion to obtain the analysis results of the material;

[0088] Step S300: Based on the analysis results of the substance, the preset proportions of several raw materials for cement are initially adjusted;

[0089] Step S400: Grind several raw materials separately, detect the particle diameter of several raw materials after grinding, obtain several diameter values, and compare the largest diameter value among several diameter values ​​with a preset diameter value. When the largest diameter value is less than or equal to the preset diameter value, stop grinding, and dry and mix the several raw materials after grinding to obtain raw cement.

[0090] Step S500: The initial setting time and final setting time of the original cement are detected, and the specific gravity of some raw materials in the original cement is adjusted according to the detection results to obtain a second specific gravity.

[0091] Step S600: Pour the original cement into a mold to prepare a model, test the linear expansion rate of the model after curing in water at various ages, and adjust the specific gravity of some raw materials in the original cement according to the test results to obtain a third specific gravity.

[0092] Step S700: Determine the final specific gravity based on the adjustment of the preset specific gravity, the second specific gravity, and the third specific gravity; re-make cement based on the final specific gravity of several raw materials to obtain final cement; and re-detect the initial setting time, final setting time, and linear expansion rate of the final cement. If the detection results are different from the preset results, readjust the final specific gravity of several raw materials for the final cement, make cement, and detect again until the detection results are the same as the preset results.

[0093] Specifically, in this embodiment of the invention, the cement raw materials are clinker, limestone, slag, fly ash, and phosphogypsum, which conforms to the basic characteristics of ecological cement: its production uses as few natural resources as possible and makes extensive use of tailings, slag, garbage, waste liquid, and other waste materials. In this embodiment of the invention, the process of acquiring road surface images and analyzing the images to obtain the concave parts, and collecting and analyzing the materials around the concave parts to obtain the analysis results of the materials, and initially adjusting the preset proportions of several cement raw materials based on the analysis results of the materials, adopts an image processing method.

Claims

1. An image processing-based eco-cement preparation process, characterized in that, include: The surface image of the road surface to be paved is acquired by an image acquisition device, and the road surface image is analyzed to obtain the depressions on the road surface to be paved. The material surrounding the recessed portion is collected and analyzed to obtain the analytical results. Based on the analysis results of the substances, the preset proportions of several cement raw materials were initially adjusted; Several raw materials are ground separately, and the particle diameter of the ground raw materials is detected to obtain several diameter values. The largest diameter value among the several diameter values ​​is compared with a preset diameter value. When the largest diameter value is less than or equal to the preset diameter value, the grinding is stopped. The ground raw materials are then dried and mixed to obtain raw cement. The initial setting time and final setting time of the original cement were tested, and the specific gravity of some raw materials in the original cement was adjusted according to the test results to obtain a second specific gravity. The original cement is poured into a mold to prepare a model. The volume expansion rate of the model is tested at each age after curing in water. Based on the test results, the specific gravity of some raw materials in the original cement is adjusted to obtain a third specific gravity. The final specific gravity is determined by adjusting the preset specific gravity, the second specific gravity, and the third specific gravity. Cement is remade based on the final specific gravity of several raw materials to obtain the final cement. The initial setting time, final setting time, and volume expansion rate of the final cement are tested again. If the test results are different from the preset results, the final specific gravity of several raw materials of the final cement is readjusted, cement is made, and tested again until the test results are the same as the preset results. Analyzing the road surface image to obtain the depressions on the road surface to be paved includes: Convert the road surface image into a grayscale image; The road surface image is divided horizontally and vertically according to a preset distance to obtain several first regions; Edge detection is performed on several of the first regions using an edge detection algorithm to obtain several edge contours; The regions containing several edge contours are extracted to obtain several second regions; Detect the grayscale values ​​of several second regions, extract the regions with grayscale values ​​greater than a preset grayscale value, and obtain the depressions on the road surface to be paved; The material surrounding the recessed portion was analyzed, and the material analysis results included: Extract the material around the recessed portion; Grind the substance until it becomes a powder, then stop grinding. The analytical results of the powdered substance were obtained by analyzing several constituent elements and their corresponding specific gravities using X-ray fluorescence analysis.

2. The image processing-based eco-cement preparation process according to claim 1, characterized in that, Based on the analysis results of the aforementioned substances, the preliminary adjustment of the preset proportions of several raw materials in the original cement includes: The specific gravities of the limestone, slag, and fly ash substances extracted from the substances are a1, b1, and c1, respectively. Compare it with the preset specific gravity of limestone, slag and fly ash in the original cement, which are a2, b2 and c2 respectively, and obtain the comparison results; Based on the comparison results, the first correction coefficient k1 is calculated as follows: ; The preset proportions of limestone, slag and fly ash in the original cement are adjusted according to the first correction coefficient k1 to obtain the initial proportions of limestone, slag and fly ash in the original cement as a3, b3 and c3, where a3=k1×a2, b3=k1×b2 and c3=k1×c2.

3. The image processing-based eco-cement preparation process according to claim 2, characterized in that, Several raw materials are ground separately, and the particle diameter of the ground raw materials is measured to obtain several diameter values. The largest diameter value among the several diameter values ​​is compared with a preset diameter value, including: The raw materials selected from the original cement include clinker, limestone, slag, fly ash, and phosphogypsum; The initial specific gravities of the clinker, limestone, slag, fly ash, and phosphogypsum are selected as d1, a3, b3, c3, and e1, respectively. The clinker, limestone, slag, fly ash, and phosphogypsum are ground separately using a grinding mill at a first speed for a first time period, and then the grinding is stopped. The diameter of the ground particles was measured using a laser particle size analyzer to obtain several diameter values. If the largest diameter value among the plurality of diameter values ​​is greater than the preset diameter value, grinding is performed again. Grinding is stopped after grinding at the second speed for a second time period. The diameter value of the ground particles is detected again. Grinding is stopped when the total maximum diameter value of the plurality of diameter values ​​is less than or equal to the preset diameter value. The second speed is greater than the first speed, and the second time period is equal to the first time period.

4. The image processing-based eco-cement preparation process according to claim 3, characterized in that, Drying and mixing the milled raw materials includes: The ground clinker, limestone, slag, fly ash, and phosphogypsum are dried using a drying device. The actual moisture content of the clinker, limestone, slag, fly ash, and phosphogypsum is detected and compared with a preset moisture content. If the actual moisture content is less than or equal to the preset moisture content, the drying process is stopped. The dried clinker, limestone, slag, fly ash, and phosphogypsum are placed in a mixing device and stirred until they are evenly mixed. After the first stirring time period, stirring is stopped to obtain the original cement.

5. The image processing-based eco-cement preparation process according to claim 4, characterized in that, The detection of the initial setting time and final setting time of the original cement includes: Several resistivity values ​​of the original cement were measured in real time using a resistivity meter. Establish a rectangular coordinate system with time as the horizontal axis and resistivity as the vertical axis; Several resistivity values ​​are plotted as points in the rectangular coordinate system, and adjacent points are connected to obtain a resistivity image. The resistivity difference between two adjacent points is calculated sequentially from left to right to obtain several resistivity difference values. The resistivity differences are compared sequentially with a preset resistivity difference. When the resistivity difference is greater than or equal to the preset resistivity difference, two points corresponding to the resistivity difference are extracted. The maximum time corresponding to the two points is the initial setting time of the original cement. Analyzing the resistivity image, when the resistivity image reaches an inflection point, the latter half of the image shows a stable trend, and the time corresponding to the inflection point is the final setting time of the original cement.

6. The image processing-based eco-cement preparation process according to claim 5, characterized in that, Adjustments were made to the specific gravity of certain raw materials in the original cement based on the test results, including: When the initial setting time is less than the preset initial setting time, let the initial setting time be t1 and the preset initial setting time be t2, then the second correction coefficient is: ; When the final setting time is less than the preset final setting time, let the final setting time be t3 and the preset final setting time be t4, then the third correction coefficient k3 is... ; The initial specific gravity of phosphogypsum in the original cement is adjusted to e2 according to the second correction coefficient k2, where e2 = e1 + k2 × e1; The initial specific gravity of phosphogypsum in the original cement is adjusted to e3 according to the third correction coefficient k3, where e3 = e1 + k3 × e1; The initial specific gravity of clinker in the original cement is adjusted to d2 according to the second correction coefficient k2, where d2 = d1 - k2 × d1; The initial specific gravity of clinker in the original cement is adjusted to d3 according to the third correction coefficient k3, where d3 = d1 - k3 × d1.

7. The image processing-based eco-cement preparation process according to claim 6, characterized in that, The volume expansion rate of the model cured in water at various ages was tested, and the specific gravity of some raw materials in the original cement was adjusted based on the test results, including: Measure the initial length, initial width, and initial height of the model, and calculate the initial volume of the model based on the initial length, initial width, and initial height. The model was placed in water for maintenance, with constant water temperature and humidity conditions. On the 7th day, the model is taken out, and the first length, first width and first height of the model are measured. The first volume of the model is calculated based on the first length, first width and first height. Let the initial volume be V1 and the first volume be V2, then the first volume expansion rate α1 of the model on day 7 is: ; On the 28th day, the model was removed, and the second length, second width, and second height of the model were measured. The second volume of the model was then calculated based on the second length, second width, and second height. Let the initial volume be V1 and the second volume be V3, then the expansion rate α2 of the second volume of the model on day 28 is: ; When the first volume expansion rate is less than the preset volume expansion rate, let the preset volume expansion rate be α3, then the fourth correction coefficient k4 is... ; The initial specific gravity of limestone in the original cement is adjusted to a4 according to the fourth correction coefficient k4, where a4 = a3 + k4 × a3; When the second volume expansion rate is less than the preset volume expansion rate, let the preset volume expansion rate be α3, then the fifth correction coefficient k5 is: ; The initial specific gravity of limestone in the original cement is adjusted to a5 according to the fifth correction coefficient k5, where a5 = a3 + k5 × a3.

8. A system applying the image processing-based eco-cement preparation process as described in any one of claims 1-7, characterized in that, include: The image acquisition module acquires surface images of the road surface to be paved through an image acquisition device, obtains road surface images, analyzes the road surface images, and obtains the depressions on the road surface to be paved. The material analysis module is connected to the image acquisition module to collect and analyze the material around the recessed portion and obtain the analysis results of the material. The first adjustment module is connected to the material analysis module and adjusts the preset proportions of several cement raw materials based on the analysis results of the material. The cement acquisition module is connected to the first adjustment module. It grinds several raw materials separately, detects the particle diameter of the several raw materials after grinding, obtains several diameter values, and compares the largest diameter value among the several diameter values ​​with a preset diameter value. When the largest diameter value is less than or equal to the preset diameter value, grinding is stopped. The several raw materials after grinding are dried and mixed to obtain raw cement. The time detection module detects the initial setting time and final setting time of the original cement, and adjusts the proportion of some raw materials in the original cement according to the detection results to obtain a second proportion. The volume expansion rate detection module pours the original cement into a mold to prepare a model, detects the volume expansion rate of the model after curing it in water to various ages, and adjusts the specific gravity of some raw materials in the original cement according to the detection results to obtain a third specific gravity. The second adjustment module determines the final specific gravity based on the preset specific gravity, the second specific gravity, and the third specific gravity. It then re-processes cement based on the final specific gravity of several raw materials to obtain the final cement. The module also re-detects the initial setting time, final setting time, and volume expansion rate of the final cement. If the detection results differ from the preset results, the module readjusts the final specific gravity of several raw materials for the final cement, processes the cement, and conducts further detection until the detection results match the preset results.

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