A method for optimizing construction process of diamond wear-resistant floor

Abstract

The application provides a diamond wear-resistant floor construction process optimization method, and belongs to the technical field of wind tunnel construction.The application analyzes stress distribution by establishing a three-dimensional finite element model, removes base layer floating slurry by using a vacuum water suction device, sprays a penetrating interface agent to improve interface bonding, monitors interface bonding quality by using an ultrasonic detection device, realizes quantitative diamond scattering by using a variable frequency scattering device equipped with machine vision and proportional-integral-derivative closed-loop control, generates a distribution density three-dimensional cloud map and identifies abnormal areas by using a laser radar scanning device, carries out supplementary scattering correction and screeding treatment on the abnormal areas, and realizes quality determination by constructing a Voronoi diagram to calculate uniformity evaluation index, thereby solving the technical problem that local area wear-resistant performance is not up to standard due to the difficulty in accurately controlling diamond wear-resistant floor scattering uniformity.

Description

Technical Field

[0001] This invention belongs to the field of wind tunnel construction technology, and more specifically, relates to an optimized method for the construction process of corundum wear-resistant flooring. Background Technology

[0002] Emery aggregate wear-resistant flooring is a commonly used flooring material in heavy-duty environments such as industrial plants and warehousing logistics facilities. Traditional construction methods involve manually or using simple machinery to evenly spread emery aggregate onto the concrete base surface, followed by mechanical smoothing and finishing to form a wear-resistant surface layer. However, in current industrial flooring construction practices, the lack of real-time monitoring and feedback mechanisms for the spreading equipment means operators rely on experience to judge the spreading density, making precise quantitative control of the spreading process difficult. When constructing large areas using traditional methods, significant differences in emery aggregate distribution density exist in different areas of the floor, leading to over- or under-spreading in some areas, affecting the overall uniformity of the floor's wear resistance. In other words, existing technologies suffer from the technical problem of difficulty in precisely controlling the uniformity of emery aggregate spreading, resulting in substandard wear resistance in some areas. Summary of the Invention

[0003] In view of this, the present invention provides an optimized construction process method for corundum wear-resistant flooring, which can solve the technical problem in the prior art where the uniformity of corundum wear-resistant flooring application is difficult to control precisely, resulting in substandard wear resistance in some areas.

[0004] This invention is implemented as follows: This invention provides an optimized construction process method for diamond abrasion-resistant flooring, comprising: establishing a three-dimensional finite element model including a base concrete layer, an interface bonding layer, and a diamond abrasion-resistant layer, and calculating stress distribution cloud maps and displacement distribution cloud maps; using a vacuum water suction device to remove laitance from the base concrete surface and spraying a penetrating interface agent; using an ultrasonic testing device to monitor the bonding quality of the interface bonding layer and calculate the interface bonding strength evaluation index; when the interface bonding strength evaluation index is greater than a preset threshold for interface bonding strength, using a frequency conversion spreading device to perform diamond abrasion spreading operations, the frequency conversion spreading device being equipped with a machine... The system includes a vision acquisition module and a proportional-integral-derivative (PID) closed-loop control module. The machine vision acquisition module acquires images of the floor surface in real time and calculates the spreading density deviation value. The PID closed-loop control module dynamically adjusts the discharge frequency based on the spreading density deviation value. A lidar scanning device is used to perform a three-dimensional scan of the floor surface after the diamond abrasive is spread and generate a three-dimensional cloud map of the diamond abrasive distribution density. Areas with insufficient density are supplemented with additional spreading to correct the density, while areas with excessive density are leveled. A high-resolution camera is used to acquire images of the processed floor surface, construct a Voronoi diagram to analyze the spatial distribution pattern, and calculate the uniformity evaluation index.

[0005] The vacuum water suction device includes a vacuum pump, a water suction pipe, and a water suction head. The bottom of the water suction head is equipped with a porous water suction plate, which removes free water and laitance from the surface of the base concrete through vacuum negative pressure.

[0006] The vacuum water absorption device is set to a negative pressure of 30 to 60 kPa and a water absorption time of 5 to 15 minutes, so that the moisture content of the base concrete surface is reduced to 4 to 8%.

[0007] The penetrating interface agent is a silane or epoxy interface treatment agent. The penetrating interface agent improves the interface microstructure by filling the pores and microcracks in the interface transition zone.

[0008] The interface bonding strength evaluation index is calculated through the interface bonding strength evaluation equation set, which includes the ultrasonic time-normalized equation, the amplitude attenuation normalized equation, and the interface bonding strength comprehensive equation.

[0009] The inputs to the ultrasonic time standardization equation include the ultrasonic transmission time at the measuring point and the standard ultrasonic transmission time. The output is a standardized ultrasonic time parameter, which is equal to the ultrasonic transmission time at the measuring point divided by the standard ultrasonic transmission time.

[0010] The inputs to the comprehensive equation for interface bonding strength include standardized ultrasonic time parameters, standardized amplitude attenuation parameters, ultrasonic time weighting coefficients, and amplitude attenuation weighting coefficients. The interface bonding strength evaluation index is equal to the ultrasonic time weighting coefficient divided by the sum of the standardized ultrasonic time parameters and the amplitude attenuation weighting coefficient divided by the standardized amplitude attenuation parameters.

[0011] The preset threshold for the interface bonding strength is 0.75 to 0.95. When the interface bonding strength evaluation index is less than the preset threshold for interface bonding strength, the laitance removal treatment step and the interface bonding quality monitoring step are repeated.

[0012] The proportional-integral-derivative closed-loop control module calculates the discharge frequency adjustment amount based on the spreading density deviation value through a set of discharge frequency adjustment equations. The set of discharge frequency adjustment equations includes proportional adjustment equations, integral adjustment equations, derivative adjustment equations, and comprehensive frequency adjustment equations.

[0013] The inputs to the proportional adjustment equation include the spreading density deviation value, the target spreading density, and the proportional coefficient. The proportional adjustment component is equal to the spreading density deviation value divided by the target spreading density and then multiplied by the proportional coefficient, which is set to 0.4 to 0.8.

[0014] The inputs to the integral adjustment equation include the cumulative sum of historical spreading density deviations, the target spreading density, the number of samplings, and the integral coefficient. The integral adjustment component is equal to the cumulative sum of historical spreading density deviations divided by the product of the target spreading density and the number of samplings, and then multiplied by the integral coefficient.

[0015] The three-dimensional cloud map of the diamond abrasive distribution density is generated by acquiring three-dimensional point cloud data through a lidar scanning device, and the diamond abrasive distribution density is obtained by calculating the number of scanning points per unit area and the average reflection intensity.

[0016] The insufficient density area is the area where the distribution density of corundum is less than 90% of the target distribution density, and the excessive density area is the area where the distribution density of corundum is greater than 110% of the target distribution density.

[0017] The supplementary spreading and correction operation uses a handheld precision spreader, with the discharge accuracy of the handheld precision spreader set to 10 to 30. The leveling process uses a laser-guided leveling device.

[0018] The Voronoi diagram is a spatial partitioning diagram constructed based on the centroid coordinates of the diamond particles. The Voronoi diagram is constructed using the Fortune scanline algorithm or the Bowyer-Watson incremental insertion algorithm.

[0019] The uniformity evaluation index is calculated using the uniformity evaluation equation. The uniformity evaluation index is equal to the standard coefficient of variation divided by the ratio of the standard deviation of the Voronoi polygon area to the average area of ​​the Voronoi polygon. When the uniformity evaluation index is less than the uniformity standard threshold, the respreading correction operation and the leveling treatment operation are repeated.

[0020] This invention employs a variable frequency spreading device equipped with a machine vision acquisition module and a proportional-integral-derivative closed-loop control module to acquire real-time images of the floor surface and calculate the spreading density deviation. Based on the deviation, the discharge frequency is dynamically adjusted to achieve precise quantitative control of the diamond abrasive spreading process. By introducing a lidar scanning device to generate a three-dimensional cloud map of the diamond abrasive distribution density, areas of insufficient and excessive density are identified. Targeted supplementary spreading or leveling treatment is applied to abnormal areas, eliminating local performance defects caused by spreading density fluctuations in traditional processes. By constructing a spatial distribution analysis method based on Voronoi diagrams, the distribution characteristics of diamond abrasive particles are transformed into a quantifiable uniformity evaluation index, establishing an objective standard for quality judgment. When the uniformity evaluation index meets a preset threshold, the consistency of diamond abrasive distribution in all areas of the floor is ensured, thereby guaranteeing the uniformity of overall wear resistance performance. In summary, this invention solves the technical problem mentioned in the background art where the difficulty in precisely controlling the uniformity of diamond abrasive spreading in wear-resistant flooring leads to substandard wear resistance performance in some areas. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the overall structure of the vacuum water suction device in the embodiment.

[0022] Figure 2 This is a schematic diagram of the ultrasonic testing device in the embodiment.

[0023] Figure 3 This is a schematic diagram of the structure and control of the frequency conversion spreading device in the embodiment.

[0024] Figure 4 This is a stress distribution cloud diagram of the three-dimensional finite element model in the embodiment.

[0025] Figure 5 This is a Voronoi diagram uniformity analysis and polygon area distribution diagram in the embodiment. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below.

[0027] The invention provides an optimized construction process method for corundum wear-resistant flooring, including:

[0028] S10. Establish a three-dimensional finite element model including the base concrete layer, the interface bonding layer, and the diamond abrasive wear-resistant layer. Define the constitutive relationship of each layer and the interface contact properties. Apply heavy load and temperature boundary conditions. Calculate the stress distribution cloud map and displacement distribution cloud map. Identify stress concentration areas and potential crack paths.

[0029] S20. Use a vacuum water suction device to remove laitance from the surface of the base concrete. Set the negative pressure of the vacuum water suction device to 30-60 kPa and the water suction time to 5-15 minutes to reduce the moisture content of the base concrete surface to 4-8%. Then spray a penetrating interface agent on the surface of the base concrete.

[0030] S30. Use an ultrasonic testing device to monitor the bonding quality of the interface bonding layer. The transmission frequency of the ultrasonic testing device is set to 40-60kHz, the distance between the receiving sensors is set to 100-200mm, the ultrasonic transmission time and amplitude attenuation coefficient are collected, and the interface bonding strength evaluation index is calculated based on the ultrasonic transmission time and amplitude attenuation coefficient.

[0031] S40. When the interface bonding strength evaluation index is greater than the preset threshold of interface bonding strength, a variable frequency spreading device is used to spread diamond abrasive. The variable frequency spreading device is equipped with a machine vision acquisition module and a proportional integral derivative closed-loop control module. The machine vision acquisition module acquires images of the floor surface in real time and calculates the spreading density deviation value. The proportional integral derivative closed-loop control module dynamically adjusts the discharge frequency according to the spreading density deviation value.

[0032] S50. Use a lidar scanning device to perform a three-dimensional scan on the floor surface after the diamond abrasive has been spread. The scanning accuracy of the lidar scanning device is set to 0.5-1.5mm, and the scanning range is set to 0-10m. Generate a three-dimensional cloud map of the diamond abrasive distribution density and identify areas with insufficient density and areas with excessive density.

[0033] S60. For areas with insufficient density, perform supplementary spreading and correction; for areas with excessive density, perform leveling. The supplementary spreading and correction operations will be performed using a handheld precision spreader, with the discharge accuracy set to 10–30. The leveling process uses a laser-guided leveling device, and the leveling thickness control accuracy of the laser-guided leveling device is set to 0.2-0.8mm.

[0034] S70. Use a high-resolution camera to acquire images of the processed floor surface, perform preprocessing through grayscale transformation and Gaussian filtering, extract the corundum particle area using threshold segmentation, calculate the particle distribution density and area ratio, construct a Voronoi diagram to analyze the spatial distribution pattern, calculate the uniformity evaluation index based on the area of ​​the Voronoi polygon, and repeat steps S60 to S70 when the uniformity evaluation index is less than the uniformity standard threshold.

[0035] The vacuum water suction device includes a vacuum pump, a suction pipe, and a suction head. The vacuum pump generates negative pressure. The suction pipe connects the vacuum pump and the suction head. The bottom of the suction head is equipped with a perforated suction plate. The perforation diameter of the perforated suction plate is set to 2-5 mm, and the perforation spacing is set to 10-20 mm. The vacuum water suction device moves at a speed of 0.5-1.5 m / min on the base concrete surface. It removes free water and laitance from the base concrete surface through vacuum negative pressure, preventing the laitance layer from hindering the bonding of the diamond abrasive particles to the base concrete.

[0036] The penetrating interface agent is a silane-based or epoxy-based interface treatment agent. The solid content of the penetrating interface agent is set to 15-35%, the viscosity to 50-150 mPa·s, and the coating amount to 0.15-0.35. The penetrating interface agent has a penetration depth of 3–8 mm. It improves the interface microstructure by filling the pores and microcracks in the interface transition zone, thereby enhancing the adhesion between the base concrete and the corundum wear-resistant layer. The interface transition zone is the bonding area between the base concrete and the corundum wear-resistant layer. The thickness of the interface transition zone is 5–15 mm. The interface transition zone contains pores, microcracks, and hydration products. The pore diameter is 10–100 μm, and the microcrack width is 5–50 μm.

[0037] The ultrasonic transmission time is the time required for the ultrasonic wave to propagate from the transmitting sensor to the receiving sensor. The amplitude attenuation coefficient is the degree of amplitude attenuation of the ultrasonic wave during its propagation in the interface bonding layer. The amplitude attenuation coefficient is calculated by the ratio of the received signal amplitude to the transmitted signal amplitude.

[0038] The interface bonding strength evaluation index is calculated using an interface bonding strength evaluation equation set, which includes an ultrasonic time-normalized equation, an amplitude attenuation-normalized equation, and a comprehensive interface bonding strength equation. The ultrasonic time-normalized equation converts ultrasonic transmission time into a standardized ultrasonic time parameter. The inputs include the ultrasonic transmission time at the measuring point and the standard ultrasonic transmission time; the output is the standardized ultrasonic time parameter. The ultrasonic transmission time at the measuring point is the ultrasonic transmission time collected by the ultrasonic testing device at the measuring point in the interface bonding layer. The standard ultrasonic transmission time is the theoretical transmission time of ultrasonic waves propagating in a dense, defect-free interface bonding layer. The standard ultrasonic transmission time is obtained through ultrasonic testing experiments on a standard specimen, which is a high-quality abrasive-resistant flooring specimen with excellent interface bonding. The standardized ultrasonic time parameter is equal to the ultrasonic transmission time at the measuring point divided by the standard ultrasonic transmission time. The amplitude attenuation standardization equation is used to convert the amplitude attenuation coefficient into a standardized amplitude attenuation parameter. The inputs include the measurement point amplitude attenuation coefficient and the standard amplitude attenuation coefficient, and the output is the standardized amplitude attenuation parameter. The measurement point amplitude attenuation coefficient is the amplitude attenuation coefficient collected by the ultrasonic testing device at the measurement point of the interface bonding layer. The standard amplitude attenuation coefficient is the amplitude attenuation coefficient of the ultrasonic wave propagating in the interface bonding layer of the standard specimen. The standard amplitude attenuation coefficient is obtained by performing ultrasonic testing experiments on the standard specimen. The standardized amplitude attenuation parameter is equal to the measurement point amplitude attenuation coefficient divided by the standard amplitude attenuation coefficient. The comprehensive equation for interfacial bonding strength is used to calculate the interfacial bonding strength evaluation index based on standardized ultrasonic time parameters and standardized amplitude attenuation parameters. The inputs include standardized ultrasonic time parameters, standardized amplitude attenuation parameters, ultrasonic time weighting coefficients, and amplitude attenuation weighting coefficients. The output is the interfacial bonding strength evaluation index, which is equal to the ultrasonic time weighting coefficient divided by the sum of the standardized ultrasonic time parameters and the amplitude attenuation weighting coefficient divided by the standardized amplitude attenuation parameters. The ultrasonic time weighting coefficient is set to 0.4 to 0.6, the amplitude attenuation weighting coefficient is set to 0.4 to 0.6, and the sum of the ultrasonic time weighting coefficient and the amplitude attenuation weighting coefficient is equal to 1.

[0039] The preset threshold for interface bonding strength is 0.75–0.95. When the interface bonding strength evaluation index is less than the preset threshold, it indicates that the bonding quality of the interface bonding layer does not meet the requirements, and steps S20 to S30 need to be repeated. When the interface bonding strength evaluation index is greater than the preset threshold, it indicates that the bonding quality of the interface bonding layer meets the requirements, and step S40 is performed. The preset threshold for interface bonding strength is determined through an interface bonding strength comparison experiment. The interface bonding strength comparison experiment includes preparing diamond abrasive wear-resistant flooring specimens with different interface treatment processes, testing the measured values ​​of the interface bonding strength of the specimens using the pull-out method, and simultaneously testing the interface bonding strength evaluation index of the specimens using an ultrasonic testing device. A correspondence between the measured values ​​of interface bonding strength and the interface bonding strength evaluation index is established. The minimum value of the interface bonding strength evaluation index corresponding to the specimen with the measured value of interface bonding strength greater than the design requirement value is selected as the preset threshold for interface bonding strength. The design requirement value is 1.5–2.5 MPa.

[0040] The spreading density deviation value is the difference between the actual spreading density and the target spreading density. The actual spreading density is calculated by analyzing the floor surface image through a machine vision acquisition module, and the target spreading density is set to 4-7. .

[0041] The proportional-integral-derivative closed-loop control module calculates the discharge frequency adjustment amount based on the spreading density deviation value using a set of discharge frequency adjustment equations. This set of equations includes a proportional adjustment equation, an integral adjustment equation, a derivative adjustment equation, and a comprehensive frequency adjustment equation. The proportional adjustment equation is used to calculate the proportional adjustment component based on the current spreading density deviation value. The inputs include the spreading density deviation value, the target spreading density, and a proportional coefficient. The output is the proportional adjustment component, which is equal to the spreading density deviation value divided by the target spreading density and then multiplied by the proportional coefficient, which is set to 0.4–0.8. The integral adjustment equation is used to calculate the integral adjustment component based on the cumulative historical spreading density deviation values. The inputs include the cumulative sum of historical spreading density deviation values, the target spreading density, the number of samplings, and the integral coefficient. The output is the integral adjustment component, which is equal to the cumulative sum of historical spreading density deviation values ​​divided by the product of the target spreading density and the number of samplings, and then multiplied by the integral coefficient. The cumulative sum of historical spreading density deviation values ​​is the sum of all spreading density deviation values ​​from the start of the spreading operation to the current moment. The number of samplings is the number of times the machine vision acquisition module acquires images from the start of the spreading operation to the current moment. The integral coefficient is set to 0.1 to 0.3. The differential adjustment equation is used to calculate the differential adjustment component based on the rate of change of the spreading density deviation value. The inputs include the current spreading density deviation value, the previous spreading density deviation value, the target spreading density, and the differential coefficient. The output is the differential adjustment component, which is equal to the difference between the current and previous spreading density deviation values, divided by the target spreading density, and multiplied by the differential coefficient. The previous spreading density deviation value is the spreading density deviation value collected and calculated by the machine vision acquisition module in the previous sampling period at the current moment. The differential coefficient is set to 0.05–0.15. The frequency comprehensive adjustment equation is used to calculate the discharge frequency adjustment amount based on the proportional adjustment component, integral adjustment component, and differential adjustment component. The inputs include the proportional adjustment component, integral adjustment component, and differential adjustment component. The output is the discharge frequency adjustment amount, which is equal to the sum of the proportional adjustment component, integral adjustment component, and differential adjustment component. The proportional coefficient, integral coefficient, and differential coefficient are determined through proportional-integral-differential parameter optimization experiments. These experiments involve conducting multiple spreading operations on an experimental floor, with each spreading operation using a different combination of proportional coefficient, integral coefficient, and differential coefficient. The uniformity of the diamond abrasive distribution after each spreading operation is measured, and the proportional coefficient, integral coefficient, and differential coefficient corresponding to the combination with the optimal diamond abrasive distribution uniformity are selected as set values.

[0042] The three-dimensional cloud map of the diamond abrasive distribution density is generated from three-dimensional point cloud data acquired by a lidar scanning device. The three-dimensional point cloud data includes the spatial coordinates and reflection intensity of each scanned point on the ground surface. The spatial coordinates include the x-coordinate, y-coordinate, and height coordinates of the scanned point. The diamond abrasive distribution density is obtained by calculating the number of scanned points per unit area and the average reflection intensity, with the unit area set to 0.01–0.1. .

[0043] The insufficient density area refers to the region where the distribution density of the corundum is less than 90% of the target distribution density, and the excessive density area refers to the region where the distribution density of the corundum is greater than 110% of the target distribution density. The target distribution density is calculated based on the target spreading density and the density of the corundum material, and the density of the corundum material is 3.5–4.0. .

[0044] The Voronoi diagram is a spatial partitioning map constructed based on the centroid coordinates of the diamond particles. The Voronoi diagram divides the floor surface into multiple Voronoi polygons, each containing a diamond particle centroid. All points within a Voronoi polygon are less distant from the centroid of the diamond particle than from any other diamond particle centroid. The coordinates of the diamond particle centroids are extracted from the floor surface image using an image processing algorithm. The Voronoi diagram is constructed using either the Fortune scanline algorithm or the Bowyer-Watson incremental insertion algorithm. The Fortune scanline algorithm is a Voronoi diagram generation algorithm in computational geometry, while the Bowyer-Watson incremental insertion algorithm is a Voronoi diagram generation algorithm based on Delaunay triangulation.

[0045] The uniformity evaluation index is calculated using a uniformity evaluation equation. This equation is used to calculate the uniformity evaluation index based on the area distribution characteristics of Voronoi polygons. The inputs include the standard deviation of the Voronoi polygon area, the average Voronoi polygon area, and the standard coefficient of variation. The output is the uniformity evaluation index, which is equal to the standard coefficient of variation divided by the ratio of the standard deviation of the Voronoi polygon area to the average Voronoi polygon area. The standard deviation of the Voronoi polygon area is the standard deviation of the areas of all Voronoi polygons. The average Voronoi polygon area is the arithmetic mean of the areas of all Voronoi polygons. The standard coefficient of variation is the coefficient of variation of the Voronoi polygon area under an ideal uniform distribution. The standard coefficient of variation is set to 0.15–0.25 and is determined through an ideal distribution simulation experiment. This simulation experiment includes generating a uniformly distributed ideal point set in a computer, constructing a Voronoi diagram of the ideal point set, and calculating the coefficient of variation of the Voronoi polygon area of ​​the ideal point set Voronoi diagram as the standard coefficient of variation.

[0046] The uniformity standard threshold is set to 0.80–0.95. When the uniformity evaluation index is greater than the uniformity standard threshold, it indicates that the uniformity of the corundum distribution meets the requirements; when the uniformity evaluation index is less than the uniformity standard threshold, it indicates that the uniformity of the corundum distribution does not meet the requirements. The uniformity standard threshold is determined through a uniformity comparison experiment. This experiment includes preparing corundum wear-resistant flooring specimens with different spreading processes, testing the measured wear resistance of the specimens using a wear test, and simultaneously calculating the uniformity evaluation index of the specimens. A correspondence between the measured wear resistance values ​​and the uniformity evaluation index is established. The minimum uniformity evaluation index value corresponding to the specimen whose measured wear resistance values ​​meet the design requirements is selected as the uniformity standard threshold. The measured wear resistance values ​​are characterized by measuring the wear amount of the specimens under specified wear conditions, namely, a wear speed of 1000 revolutions and a load of 9.8 N.

[0047] The specific implementation methods of the above steps are described in detail below.

[0048] The specific implementation of step S10 includes: Step 101, establishing a three-dimensional geometric model including a base concrete layer, an interface bonding layer, and a diamond abrasive wear-resistant layer, and setting the thickness parameters and spatial relationship of each layer, wherein the thickness of the base concrete layer is 100-150mm, the thickness of the interface bonding layer is 5-15mm, and the thickness of the diamond abrasive wear-resistant layer is 3-8mm; Step 102, defining the elastic modulus of the base concrete layer as 25-35GPa, the Poisson's ratio as 0.15-0.25, and the bond stiffness of the interface bonding layer as 5-15. The elastic modulus of the corundum wear-resistant layer is 40–60 GPa, and the Poisson's ratio is 0.18–0.28. Step 103: Set the contact properties between the interface bonding layer and the base concrete layer, and between the interface bonding layer and the corundum wear-resistant layer. Use a friction contact model, setting the friction coefficient to 0.4–0.7 and the normal stiffness coefficient to... ~ m 3 Step 104: Apply a uniformly distributed load of 10–30 kN / m to the surface of the diamond abrasive wear-resistant layer. 2 In step S10, a temperature boundary condition is applied to the side of the model, with a temperature difference set to 20–40°C to simulate the effect of diurnal temperature variation. Step S105 involves using finite element analysis software to calculate the stress and displacement fields, generating stress and displacement distribution cloud maps, and identifying stress concentration areas with stress values ​​greater than 15 MPa and potential crack path areas with displacement gradients greater than 0.5 mm / m. This step S10 utilizes finite element numerical simulation to establish a multi-layered composite structure model and apply actual working condition loads, pre-identifying potentially weak areas after construction. This provides a theoretical basis for subsequent optimization of process parameters and achieves the technical effect of predicting the location of structural defects in advance.

[0049] The specific implementation of step S20 includes: Step 201, starting the vacuum pump and adjusting it to a set negative pressure value of 30-60 kPa, transmitting the negative pressure to the suction head through the suction pipe, setting the hole diameter of the porous suction plate at the bottom of the suction head to 2-5 mm and the hole spacing to 10-20 mm to ensure uniform distribution of negative pressure; Step 202, the operator pushes the vacuum suction device to move back and forth on the surface of the base concrete at a moving speed of 0.5-1.5 m / min, the vacuum negative pressure causing the free water on the surface of the base concrete to be absorbed and dissolved. The laitance is sucked into the suction pipe through the porous suction plate; Step 203: The moisture content of the treated base concrete surface is measured using a moisture content meter. The measurement point spacing is set to 1-3m, and the measurement depth is set to 5-10mm to ensure that the moisture content is reduced to 4-8%; Step 204: A penetrating interface agent is evenly sprayed onto the base concrete surface using a spraying device. The nozzle diameter of the spraying device is set to 1.5-3.0mm, the spraying pressure is set to 0.3-0.6MPa, and the spraying amount is controlled at 0.15-0.35. The penetrating interface agent is a silane or epoxy material with a solid content of 15-35% and a viscosity of 50-150. Through capillary action and concentration diffusion, the agent penetrates to a depth of 3–8 mm into the base concrete. In this step S20, a combination of vacuum negative pressure water absorption and penetrating interface agent treatment is used. By removing the laitance layer and free water on the surface of the base concrete, and then filling the pores and microcracks in the interface transition zone, the technical effect of improving the bonding strength between the base concrete and the diamond abrasive wear-resistant layer is achieved.

[0050] The specific implementation of step S30 includes: Step 301, arranging the transmitting and receiving sensors of the ultrasonic testing device at a spacing of 100-200 mm on the surface of the interface bonding layer; the transmitting sensor generates an ultrasonic signal with a frequency of 40-60 kHz, and the ultrasonic wave propagates in the interface bonding layer in the form of a longitudinal wave; Step 302, the receiving sensor collects the ultrasonic transmission signal, records the time required for the ultrasonic wave to propagate from the transmitting sensor to the receiving sensor as the ultrasonic transmission time at the measuring point, and simultaneously records the ratio of the received signal amplitude to the transmitted signal amplitude as the amplitude attenuation coefficient at the measuring point; Step 303, dividing the ultrasonic transmission time at the measuring point by the standard ultrasonic transmission time to obtain the standardized ultrasonic time parameter. Transmission time is obtained through ultrasonic testing on standard specimens with excellent interface bonding quality, with a reference value of 20–40 microseconds. Step 304 involves dividing the measured amplitude attenuation coefficient by the standard amplitude attenuation coefficient to obtain a standardized amplitude attenuation parameter. The standard amplitude attenuation coefficient is obtained through ultrasonic testing on standard specimens, with a reference value of 0.6–0.8. Step 305 involves adding the result of dividing the ultrasonic time weighting coefficient by the standardized ultrasonic time parameter and the result of dividing the amplitude attenuation weighting coefficient by the standardized amplitude attenuation parameter to calculate the interface bonding strength evaluation index. The ultrasonic time weighting coefficient is set to 0.4–0.6, and the amplitude attenuation weighting coefficient is set to 0.4–0.6; their sum equals 1. In this step S30, ultrasonic non-destructive testing technology and a multi-parameter fusion evaluation method are adopted. By measuring the propagation time and amplitude attenuation characteristics of ultrasonic waves in the interface bonding layer, the interface bonding quality is comprehensively evaluated, resulting in the technical effect of real-time monitoring of interface bonding strength and determining whether it meets construction requirements.

[0051] The specific implementation of step S40 includes: Step 401, determining whether the interface bonding strength evaluation index is greater than the preset threshold of interface bonding strength (0.75-0.95). If it is less than the preset threshold, repeat steps S20 to S30; if it is greater than the preset threshold, continue with subsequent steps. Step 402, starting the frequency conversion spreading device, the machine vision acquisition module acquires real-time images of the ground surface through a high-resolution camera, the acquisition frame rate is set to 5-15 frames / second, and the image resolution is set to 1920×1080 pixels. Step 403, performing grayscale processing and edge detection on the acquired images, extracting the contour features of the diamond particles, counting the number of diamond particles and the coverage area per unit area, and calculating the actual spreading density. Step 404, comparing the actual spreading density with the target spreading density (4-7). The following steps are performed: Step 405: The proportional-integral-derivative (PID) closed-loop control module calculates the proportional adjustment component based on the current spread density deviation value, the integral adjustment component based on the cumulative sum of historical spread density deviation values, and the derivative adjustment component based on the difference between the current and previous spread density deviation values. These three adjustment components are then added together to obtain the discharge frequency adjustment amount. Step 406: The motor speed of the variable frequency spreader is dynamically adjusted according to the discharge frequency adjustment amount. When the spread density deviation value is negative, the discharge frequency is increased; when the spread density deviation value is positive, the discharge frequency is decreased, achieving real-time closed-loop control of the diamond abrasive spread density. In this step S40, a combination of machine vision feedback and PID control algorithm is used. By acquiring real-time images of the floor surface and dynamically adjusting the discharge frequency of the spreader, the technical effect of accurately controlling the diamond abrasive spread density and reducing spread uniformity deviation is achieved.

[0052] The specific implementation of step S50 includes: Step 501: Activating the lidar scanning device. The lidar transmitter emits a laser beam with a wavelength of 905nm. The laser beam scans the ground surface in a scanning line manner, with a scanning accuracy set to 0.5–1.5mm and a scanning range set to 0–10m; Step 502: The lidar receiver receives the laser signal reflected from the ground surface and calculates the spatial coordinates of the scanning point, including the horizontal, vertical, and height coordinates, based on the laser round-trip time, while simultaneously recording the reflection intensity value; Step 503: After acquiring the three-dimensional point cloud data of the complete area, the ground surface is divided into sections with a side length of 0.01–0.1m. The grid cells are divided, and the number of scanning points and average reflection intensity within each grid cell are counted; Step 504: Calculate the diamond abrasive distribution density based on the number of scanning points and average reflection intensity per unit area. The diamond abrasive distribution density is positively correlated with the number of scanning points and reflection intensity, generating a three-dimensional cloud map of the diamond abrasive distribution density; Step 505: Set the target distribution density as the target spreading density divided by the diamond abrasive material density, 3.5–4.0. After multiplying by a unit conversion factor, areas where the density of the corundum distribution is less than 90% of the target density are identified as areas with insufficient density, and areas where the density of the corundum distribution is greater than 110% of the target density are identified as areas with excessive density. In this step S50, LiDAR 3D scanning technology is used to acquire high-precision 3D point cloud data of the floor surface and analyze the spatial distribution characteristics of the corundum, resulting in the technical effect of comprehensively identifying areas with abnormal density after the spreading operation.

[0053] The specific implementation of step S60 includes: Step 601, the operator uses a handheld precision spreader to perform supplementary spreading and correction work on areas with insufficient density. The handheld precision spreader is equipped with an electronic weighing module and a flow control valve, and the discharge accuracy is set to 10-30. Step 602: During the re-spreading process, the operator calculates the required amount of corundum to be re-spread based on the area of ​​the insufficient density region and the amount of density loss. The required amount of corundum to be re-spread is equal to the amount of density loss multiplied by the area area, and the amount of density loss is equal to the target distribution density minus the actual distribution density. Step 603: The operator uses a laser-guided leveling device to level the areas with excessive density. The laser-guided leveling device is equipped with a laser range sensor and a servo-controlled scraper. The laser range sensor measures the height of the ground surface in real time, and the servo-controlled scraper automatically adjusts the scraper height according to the height deviation. The leveling thickness control accuracy is set to 0.2-0.8 mm. Step 604: During the leveling process, the laser-guided leveling device moves back and forth in the areas with excessive density at a speed of 0.3-0.8 m / min, scraping the excess corundum into the recycling container. In this step S60, a combination of precision application and laser-guided leveling is used. By implementing targeted correction operations for areas with insufficient density and areas with excessive density, the technical effect of further improving the uniformity of diamond abrasive application is achieved.

[0054] The specific implementation of step S70 includes: Step 701: Using a high-resolution camera to acquire images of the processed floor surface, the camera resolution is set to 3840×2160 pixels, and the acquisition height is set to 1.5-2.5m to ensure image clarity and coverage; Step 702: Performing grayscale transformation on the acquired image, converting the color image to a grayscale image with a grayscale value range of 0-255, followed by Gaussian filtering, with the filter kernel size set to 5×5 pixels and the standard deviation set to 1.0-2.0 to remove image noise; Step 703: Using a threshold segmentation method to extract the diamond particle region, the threshold is set to the valley grayscale value between the two peaks of the grayscale histogram, and the image is binarized into foreground and background regions, with the foreground region corresponding to the diamond particles; Step 704: Performing connected component analysis on the binarized image to identify the contour boundary of each diamond particle, calculating the particle distribution density and area ratio, where the particle distribution density is equal to the number of particles divided by the image size. The total area, and the area percentage, is equal to the total area of ​​the particles divided by the total area of ​​the image; Step 705: Extract the centroid coordinates of each carborundum particle, and construct a Voronoi diagram using the Fröchen scanline algorithm or the Boyer-Watson incremental interpolation algorithm to divide the ground surface into multiple Voronoi polygons, each polygon containing the centroid of a carborundum particle; Step 706: Calculate the standard deviation and arithmetic mean of the areas of all Voronoi polygons. The standard deviation represents the dispersion of the area distribution, and the arithmetic mean represents the central tendency of the area distribution; Step 707: Divide the standard coefficient of variation (0.15-0.25) by the ratio of the standard deviation of the Voronoi polygon area to the average of the Voronoi polygon area to calculate the uniformity evaluation index; Step 708: Determine whether the uniformity evaluation index is greater than the uniformity standard threshold (0.80-0.95). If it is less than the uniformity standard threshold, repeat steps S60 to S70. If it is greater than the uniformity standard threshold, it indicates that the uniformity of the carborundum distribution meets the requirements. In this step S70, a combination of image processing and Voronoi diagram spatial analysis is used to quantitatively evaluate the spatial distribution pattern of the diamond particles and calculate the uniformity evaluation index, which brings about the technical effect of objectively determining whether the spreading quality meets the standards and guiding iterative correction operations.

[0055] It should be noted that the key technical ideas of this invention include the following aspects. First, finite element numerical simulation technology is used to pre-identify stress concentration areas and potential crack paths in multi-layer composite structures. Compared with traditional methods relying on experience, this allows for quantitative analysis of the structural mechanical response before construction, providing a theoretical basis for optimizing interface treatment and spreading process parameters. This avoids delamination and cracking problems caused by weak interfaces, improving the scientific nature and accuracy of construction plan formulation. Second, vacuum negative pressure water absorption is used to remove the laitance layer on the surface of the base concrete, combined with a penetrating interface agent to fill the pores in the interface transition zone. Compared with traditional mechanical grinding or acid washing methods, this effectively improves the interface microstructure without damaging the base concrete structure. Ultrasonic non-destructive testing technology is used to monitor the interface bonding strength in real time and quantitatively evaluate the bonding quality, ensuring that the interface bonding performance meets design requirements and improving the controllability and reliability of interface treatment. Third, machine vision feedback and proportional-integral-derivative closed-loop control algorithms are used to dynamically adjust the diamond abrasive spreading density. Compared with traditional manual spreading or open-loop mechanical spreading methods, this can detect spreading density deviations in real time and automatically correct the discharge frequency, significantly reducing density fluctuations during spreading and improving the accuracy and consistency of spreading operations. Fourth, using lidar 3D scanning to identify density anomaly areas and combining it with Voronoi diagram spatial analysis to quantitatively evaluate the uniformity of corundum distribution, compared to traditional visual inspection or random sampling methods, can comprehensively acquire 3D spatial information of the floor surface and objectively calculate the uniformity evaluation index. This provides precise guidance for iterative correction operations and improves the comprehensiveness and accuracy of quality inspection. The synergistic effect of the above technical approaches is reflected in: using finite element simulation to guide the optimization of interface processing parameters; using real-time monitoring of interface strength to ensure the basic conditions for spreading operations; using closed-loop control to improve the accuracy of spreading density; and using 3D scanning and spatial analysis to achieve comprehensive quality evaluation. This forms a complete technical chain from design optimization to process control to quality inspection. Compared to traditional experience-driven and discrete detection methods, it achieves digital monitoring and intelligent control of the entire construction process, significantly improving the interfacial bonding performance and spreading uniformity of corundum wear-resistant flooring, and reducing the risk of construction quality fluctuations and delamination and cracking during later use.

[0056] It should be noted that this invention also solves the following technical problems: First, the technical problem of insufficient interfacial bonding strength caused by the laitance layer on the surface of the base concrete hindering the bonding of the diamond abrasive particles to the base. This invention uses a vacuum water suction device to perform negative pressure suction on the base surface, precisely controlling the water suction negative pressure value within the range of 30 to 60 kPa, and setting the water suction time to 5 to 15 minutes, reducing the moisture content of the base surface to 4 to 8%, effectively removing the free water and laitance layer that hinder bonding. Subsequently, a penetrating interface agent is sprayed to fill the pores and microcracks in the interface transition zone, improving the interface microstructure and enhancing the bonding performance between the base and the wear-resistant layer. Second, the technical problem of difficulty in real-time monitoring of construction quality due to the lack of effective detection methods for interface bonding quality. This invention uses an ultrasonic testing device to obtain the ultrasonic transmission time and amplitude attenuation coefficient of the interface bonding layer, and calculates the interface bonding strength evaluation index by weighting the ultrasonic time standardization parameter and the amplitude attenuation standardization parameter. When the evaluation index is greater than a preset threshold, the interface bonding quality is determined to meet the requirements, realizing non-destructive testing and real-time monitoring of interface bonding quality, and avoiding later quality problems caused by interface defects.

[0057] Specifically, the principle of this invention is as follows: This invention uses a closed-loop feedback control principle to solve the problem of spreading uniformity control. The machine vision acquisition module obtains the actual value of the spreading density in real time through image analysis. The proportional-integral-derivative (PID) control module calculates the deviation between the actual value and the target value and decomposes it into proportional, integral, and derivative components. The proportional component responds to the current deviation to achieve rapid adjustment, the integral component eliminates accumulated errors to avoid system deviations, and the derivative component predicts the trend of deviation changes to suppress overshoot oscillations. The three components work together to drive the variable frequency spreading device to dynamically adjust the discharge frequency, so that the spreading density continuously approaches the target value. The lidar scanning device obtains the spatial coordinates and reflection intensity data of the floor surface through high-precision three-dimensional measurement, transforming the physical characteristics of the carborundum distribution into a visualized density cloud map, providing data support for the accurate location of abnormal areas. The Voronoi diagram divides the floor surface into polygonal units centered on carborundum particles. The standard deviation of the polygon area reflects the dispersion of particle distribution. A uniformity evaluation index is established through standard coefficient of variation normalization to achieve quantitative evaluation of spreading quality. When the evaluation index meets the threshold, it indicates that the spatial distribution of particles has reached an ideal uniform state, ensuring the consistency of the wear-resistant layer performance.

[0058] The following provides a specific embodiment 1 of the present invention, and the specific implementation of each step in this embodiment 1 is described in detail below.

[0059] The specific implementation of step S10 is to establish a three-dimensional finite element model including a base concrete layer, an interface bonding layer, and a diamond abrasive wear-resistant layer, define the constitutive relationship of each layer material and the interface contact properties, apply heavy load and temperature boundary conditions, calculate stress distribution cloud map and displacement distribution cloud map, and identify stress concentration areas and potential crack paths. This step uses finite element analysis software for numerical simulation, and the simulation results guide the subsequent optimization of construction parameters.

[0060] The specific implementation of step S20 involves using a vacuum suction device to remove laitance from the surface of the base concrete. The vacuum suction device includes a vacuum pump, a suction pipe, and a suction head. The vacuum pump generates negative pressure. The suction pipe connects the vacuum pump and the suction head. A perforated suction plate is installed at the bottom of the suction head. The perforation diameter of the perforated suction plate is set to 2–5 mm, and the perforation spacing is set to 10–20 mm. The vacuum suction negative pressure value is set to 30–60 kPa, and the suction time is set to 5–15 minutes. The vacuum suction device is used to remove laitance from the base concrete surface. The surface movement speed is set to 0.5–1.5 m / min. Free water and laitance on the base concrete surface are removed using vacuum negative pressure, reducing the surface moisture content to 4–8%. This prevents the laitance layer from hindering the bonding of the abrasive particles to the base concrete. Subsequently, a penetrating interface agent, either silane or epoxy-based, is sprayed onto the base concrete surface. The solid content of the penetrating interface agent is set to 15–35%, the viscosity to 50–150 mPa·s, and the spraying amount to 0.15–0.35 ml. The penetrating interface agent has a penetration depth of 3-8 mm. It improves the microstructure of the interface by filling the pores and microcracks in the interface transition zone, thereby enhancing the bonding performance between the base concrete and the diamond abrasive wear-resistant layer. The interface transition zone is the bonding area between the base concrete and the diamond abrasive wear-resistant layer. The thickness of the interface transition zone is 5-15 mm. The interface transition zone contains pores, microcracks, and hydration products. The pore diameter is 10-100 μm, and the microcrack width is 5-50 μm.

[0061] The specific implementation of step S30 involves using an ultrasonic testing device to monitor the bonding quality of the interface bonding layer. The transmission frequency of the ultrasonic testing device is set to 40–60 kHz, and the distance between the receiving sensors is set to 100–200 mm. The ultrasonic transmission time and amplitude attenuation coefficient are collected. The interface bonding strength evaluation index is calculated based on the ultrasonic transmission time and amplitude attenuation coefficient. The ultrasonic transmission time is the time required for the ultrasonic wave to travel from the transmitting sensor to the receiving sensor, and the amplitude attenuation coefficient is the degree of amplitude attenuation during the propagation of the ultrasonic wave in the interface bonding layer. The interface bonding strength evaluation index is obtained through a set of interface bonding strength evaluation equations, which includes the ultrasonic time-normalized equation, the amplitude attenuation normalized equation, and the comprehensive interface bonding strength equation. The formula for the ultrasonic time-normalized equation is as follows:

[0062] ;

[0063] In the formula, The ultrasonic time parameter is standardized and dimensionless. The ultrasonic transmission time at the measuring point is expressed in units of 1. ; Standard ultrasonic transmission time, in units of .in, This refers to the ultrasonic transmission time collected by the ultrasonic testing device at the measuring point of the interface bonding layer. This is the theoretical transmission time for ultrasonic waves to propagate through a dense, defect-free interface layer. The standard specimen, a corundum abrasion-resistant flooring specimen with excellent interfacial bonding quality, was obtained through ultrasonic testing on a standard specimen. The formula for the amplitude attenuation normalization equation is as follows:

[0064] ;

[0065] In the formula, The amplitude attenuation parameter is standardized and dimensionless. The amplitude attenuation coefficient at the measuring point is dimensionless. The amplitude attenuation coefficient is a dimensionless standard amplitude attenuation coefficient. The formula for calculating the amplitude attenuation coefficient is as follows:

[0066] ;

[0067] In the formula, The received signal amplitude is expressed in mV. This represents the amplitude of the transmitted signal, measured in mV. The amplitude attenuation coefficient of ultrasonic waves propagating in the interfacial bonding layer of a standard specimen is obtained through ultrasonic testing experiments on the standard specimen. Specifically, the experiments include: Step 1: Selecting a standard specimen with excellent interfacial bonding quality; Step 2: Placing ultrasonic transmitting and receiving sensors on the surface of the standard specimen; Step 3: Transmitting ultrasonic signals and recording the amplitude of the transmitted signals. and received signal amplitude Step 4: Calculate the amplitude attenuation coefficient using the formula. The formula for the comprehensive equation of interface strength is expressed as follows:

[0068] ;

[0069] In the formula, This is a dimensionless index for evaluating the strength of interface bonding. The time-weighted coefficient for ultrasound is dimensionless and set to 0.4–0.6. The amplitude attenuation weighting coefficient is dimensionless and set to 0.4–0.6. and The sum equals 1. Interface bonding strength preset threshold. The value ranges from 0.75 to 0.95, when the interface bonding strength evaluation index... Less than the preset threshold of interface bonding strength When the interface bonding strength evaluation index is reached, it indicates that the bonding quality of the interface bonding layer does not meet the requirements, and steps S20 to S30 need to be repeated. Greater than the preset threshold for interface bonding strength When the bonding quality of the interface bonding layer meets the requirements, proceed to step S40, where... A preset threshold for interface bonding strength is established. This threshold is dimensionless and determined through comparative experiments on interface bonding strength. These experiments include preparing diamond abrasive wear-resistant flooring specimens with different interface treatment processes, testing the measured interface bonding strength of the specimens using the pull-out method, and simultaneously testing the interface bonding strength evaluation index of the specimens using an ultrasonic testing device. A correspondence between the measured interface bonding strength and the interface bonding strength evaluation index is established. The minimum value of the interface bonding strength evaluation index corresponding to the specimen with the measured interface bonding strength greater than the design requirement value is selected as the preset threshold for interface bonding strength. The design requirement value is 1.5–2.5 MPa.

[0070] The specific implementation of step S40 involves using a variable frequency spreading device to spread corundum when the interface bonding strength evaluation index exceeds a preset threshold for interface bonding strength. The variable frequency spreading device is equipped with a machine vision acquisition module and a proportional-integral-derivative (PID) closed-loop control module. The machine vision acquisition module acquires real-time images of the floor surface and calculates the spreading density deviation value. The PID closed-loop control module dynamically adjusts the discharge frequency based on the spreading density deviation value. The formula for calculating the spreading density deviation value is as follows:

[0071] ;

[0072] In the formula, This is the spread density deviation value, in units of ; This represents the actual spreading density, in units of... ; Target spreading density, unit: Set to 4-7 .in, The data is obtained by analyzing images of the floor surface using a machine vision acquisition module. The proportional-integral-derivative (PID) closed-loop control module calculates the discharge frequency adjustment based on the spreading density deviation using a set of discharge frequency adjustment equations. This set of equations includes proportional, integral, derivative, and comprehensive frequency adjustment equations. The formula for the proportional adjustment equation is as follows:

[0073] ;

[0074] In the formula, The component used for proportional adjustment is dimensionless. The proportionality constant is dimensionless and set to 0.4–0.8. The integral adjustment equation is expressed as follows:

[0075] ;

[0076] In the formula, The integral adjustment component is dimensionless. This is the cumulative sum of historical spread density deviations, in units of ; The number of samples is dimensionless. The integral coefficient is dimensionless and is set to 0.1–0.3. For the first The spread density deviation value at the time of sampling, in units of ; This is the sampling sequence number, dimensionless, with a value range of 1 to... .in, This is the sum of all spreading density deviations from the start of the spreading operation to the current moment. Let be the number of times the machine vision acquisition module has acquired images from the start of the spreading operation to the current moment. The formula for the differential adjustment equation is as follows:

[0077] ;

[0078] In the formula, The differential adjustment component is dimensionless. This represents the current spreading density deviation value, in units of... ; This represents the density deviation value from the previous application, in units of... ; is the differential coefficient, dimensionless, and set to 0.05–0.15. Wherein, This represents the spread density deviation value acquired and calculated by the machine vision acquisition module in the previous sampling period at the current moment. The formula for the frequency comprehensive adjustment equation is as follows:

[0079] ;

[0080] In the formula, This is the quantity for adjusting the discharge frequency, dimensionless. Proportional coefficient. Integral coefficient Differential coefficients The proportional-integral-differential (PID) parameter optimization experiment was conducted. The experiment involved multiple spreading operations on the experimental floor, with each spreading operation using a different combination of proportional coefficients, integral coefficients, and differential coefficients. The uniformity of the diamond abrasive distribution after each spreading operation was measured, and the proportional coefficients, integral coefficients, and differential coefficients corresponding to the combination with the optimal diamond abrasive distribution uniformity were selected as the set values.

[0081] The specific implementation of step S50 involves using a lidar scanning device to perform a three-dimensional scan of the floor surface after the application of corundum. The scanning accuracy of the lidar scanning device is set to 0.5–1.5 mm, and the scanning range is set to 0–10 m. A three-dimensional cloud map of the corundum distribution density is generated to identify areas with insufficient density and areas with excessive density. The three-dimensional cloud map of the corundum distribution density is generated from the three-dimensional point cloud data acquired by the lidar scanning device. The three-dimensional point cloud data includes the spatial coordinates and reflection intensity of each scanned point on the floor surface. The spatial coordinates include the abscissa, ordinate, and height coordinates of the scanned point. The formula for calculating the corundum distribution density is as follows:

[0082] ;

[0083] In the formula, The distribution density of corundum is dimensionless. This represents the number of scan points per unit area, expressed in units. The average reflection intensity of the scanning points per unit area is dimensionless. For unit area, the unit is Set to 0.01~0.1 ; For reference reflection intensity, it is dimensionless and has an empirical value of 100. Among them, The density is obtained by calculating the arithmetic mean of the reflection intensity of all scanning points within a unit area. Areas with insufficient density are defined as those where the density of the corundum distribution is less than 90% of the target density, while areas with excessive density are defined as those where the density of the corundum distribution is greater than 110% of the target density. The formula for calculating the target density is as follows:

[0084] ;

[0085] In the formula, The target distribution density is dimensionless. This refers to the density of corundum material, in units of... The value is 3.5 to 4.0. ; For reference thickness, the unit is cm, and the empirical value is 0.5.

[0086] The specific implementation of step S60 involves supplementing and correcting areas with insufficient density by spreading the material, and leveling areas with excessive density by scraping the material. The supplementing and correcting operation uses a handheld precision spreader, and the discharge accuracy of the handheld precision spreader is set to 10-30. The leveling process uses a laser-guided leveling device, and the leveling thickness control accuracy of the laser-guided leveling device is set to 0.2-0.8mm.

[0087] The specific implementation of step S70 is as follows: a high-resolution camera is used to acquire images of the processed floor surface, grayscale transformation and Gaussian filtering are performed for preprocessing, threshold segmentation is used to extract the area of ​​diamond particles, particle distribution density and area ratio are calculated, a Voronoi diagram is constructed to analyze the spatial distribution pattern, and a uniformity evaluation index is calculated based on the area of ​​the Voronoi polygon. When the uniformity evaluation index is less than the uniformity standard threshold, steps S60 to S70 are repeated. The Voronoi diagram is a spatial partitioning map constructed based on the centroid coordinates of diamond particles. The Voronoi diagram divides the surface into multiple Voronoi polygons, each containing a diamond particle centroid. All points within a Voronoi polygon are less distant from their respective diamond particle centroids than from any other diamond particle centroid. The diamond particle centroid coordinates are extracted from the surface image using image processing algorithms. The Voronoi diagram is constructed using either the Fortune scanline algorithm or the Bowyer-Watson incremental interpolation algorithm. The Fortune scanline algorithm is a Voronoi diagram generation algorithm in computational geometry, while the Bowyer-Watson incremental interpolation algorithm is a Voronoi diagram generation algorithm based on Delaunay triangulation. The uniformity evaluation index is calculated using the uniformity evaluation equation, which is expressed as follows:

[0088] ;

[0089] In the formula, It is a dimensionless index for evaluating uniformity. The standard coefficient of variation is dimensionless and is set to 0.15–0.25. Here is the standard deviation of the area of ​​the Voronoi polygon, in units of ; This represents the average area of ​​a Voronoi polygon, in units of... The formula for calculating the standard deviation of the area of ​​a Voronoi polygon is as follows:

[0090] ;

[0091] In the formula, The total number of Voronoi polygons, dimensionless; For the first The area of ​​a Voronoi polygon, in units of ; The Voronoi polygon index is dimensionless and ranges from 1 to 1. The formula for calculating the average area of ​​a Voronoi polygon is as follows:

[0092] .

[0093] in, denoted as the coefficient of variation of the area of ​​a Voronoi polygon under an ideal uniform distribution. The ideal distribution simulation experiment was used to determine the optimal distribution. This simulation involved generating a uniformly distributed ideal point set in a computer, constructing a Voronoi diagram of the ideal point set, and calculating the coefficient of variation of the Voronoi polygon area as the standard coefficient of variation. A standard threshold for uniformity was also established. The uniformity evaluation index is set to 0.80–0.95. Greater than the uniformity standard threshold When the uniformity of the diamond grit distribution meets the requirements, it indicates that the uniformity evaluation index is within acceptable limits. Less than the uniformity standard threshold When the time is right, it indicates that the uniformity of the distribution of the diamond grit does not meet the requirements, among which The uniformity standard threshold is dimensionless and is determined through a uniformity comparison experiment. The uniformity comparison experiment includes preparing abrasive wear-resistant floor specimens with different spreading processes, testing the measured wear resistance of the specimens using a wear test, and simultaneously calculating the uniformity evaluation index of the specimens. A correspondence between the measured wear resistance values ​​and the uniformity evaluation index is established. The minimum uniformity evaluation index corresponding to the specimen whose measured wear resistance values ​​meet the design requirements is selected as the uniformity standard threshold. The measured wear resistance values ​​are characterized by measuring the wear amount of the specimens under specified wear conditions, which are a wear speed of 1000 revolutions and a load of 9.8 N.

[0094] It should be noted that the variables involved in this embodiment are explained in detail in Table 1.

[0095] Table 1. Variable Explanation Table

[0096]

[0097] To better understand and implement this invention, the following is a specific application scenario example 2: The technical team first established a three-dimensional finite element model including a base concrete layer, an interface bonding layer, and a corundum wear-resistant layer. The thickness of the base concrete layer was set to 150mm, the thickness of the interface bonding layer to 10mm, and the thickness of the corundum wear-resistant layer to 5mm. In the finite element model, the elastic modulus of the base concrete was defined as 30GPa and Poisson's ratio as 0.2, the elastic modulus of the interface bonding layer as 15GPa and Poisson's ratio as 0.25, and the elastic modulus of the corundum wear-resistant layer as 45GPa and Poisson's ratio as 0.18. A heavy load of 50kN / m² was applied to the model. And temperature boundary conditions, with the temperature range set from -10℃ to 40℃, to simulate the actual usage environment of the wear-resistant flooring surrounding the wind tunnel. For example... Figure 4 As shown, the calculated stress distribution cloud map shows that there is an obvious stress concentration area in the interface bonding layer, with the maximum stress value reaching 8.2 MPa. In the interface bonding layer located in the area where forklifts frequently operate, three potential crack paths were identified, which are located near the heavy load application points.

[0098] Based on the finite element analysis results, the technical team focused on the interface treatment quality in stress concentration areas. A vacuum suction device was used to remove laitance from the surface of the base concrete. The vacuum pump was set to a negative pressure of 45 kPa and a suction time of 10 minutes. Figure 1 As shown, the porous suction plate of the vacuum water suction device has a pore diameter of 3mm, a pore spacing of 15mm, and a moving speed of 1.0m / min on the base concrete surface. After treatment, the moisture content of the base concrete surface decreased from the initial 12% to 6%, and the thickness of the surface laitance layer decreased from 2mm to less than 0.3mm. Subsequently, the technical team sprayed a silane-based penetrating interface agent onto the base concrete surface. The interface agent had a solid content of 25%, a viscosity of 100mPa·s, and a spraying amount of 0.25kg / s. The penetration depth reached 5mm, effectively filling the pores with a diameter of 50μm and the microcracks with a width of 25μm in the interface transition zone.

[0099] After the interface agent has cured for 12 hours, the technical team uses an ultrasonic testing device to monitor the bonding quality of the interface layer. Figure 2As shown, the ultrasonic testing device's transmission frequency was set to 50kHz, and the distance between the receiving sensors was set to 150mm. Eighty-five measuring points were deployed within the construction area for comprehensive testing. During the testing process, ultrasonic transmission time and amplitude attenuation coefficient were collected. The standard ultrasonic transmission time was 120μs, and the standard amplitude attenuation coefficient was 0.65. The technical team calculated the interface bonding strength evaluation index for each measuring point, with both the ultrasonic time weighting coefficient and the amplitude attenuation weighting coefficient set to 0.5. The calculations showed that the interface bonding strength evaluation index for 78 of the 85 measuring points was greater than the preset threshold of 0.85, indicating that the interface bonding quality in these areas met the requirements. For the seven unqualified measuring points, the technical team repeated vacuum dehydration and interface agent spraying treatments. After the second treatment, the interface bonding strength evaluation index for all measuring points reached above 0.87.

[0100] After the interface bonding layer passed quality acceptance, the technical team used a variable frequency spreading device to perform the diamond abrasive spreading operation. For example... Figure 3 As shown, the machine vision acquisition module of the frequency conversion spreading device acquires images of the floor surface in real time, with the target spreading density set at 5.5 kg / m³. The proportional-integral-derivative (PID) closed-loop control module has a proportional gain of 0.6, an integral gain of 0.2, and a derivative gain of 0.1. During the spreading process, the machine vision module acquires images every 5 seconds and calculates the actual spreading density. If a spreading density deviation exceeds 0.3 kg / m³, the module will stop the spread. At that time, the control module immediately adjusts the discharge frequency of the variable frequency motor to make corrections. The spreading operation lasts for 45 minutes to complete the initial spreading of all areas.

[0101] After the initial application, the technical team used a lidar scanning device to perform a 3D scan of the floor surface. The scanning accuracy was set to 1.0 mm, and the scanning range covered the entire construction area. The generated 3D cloud map of the diamond aggregate distribution density showed 12 areas with insufficient density, totaling approximately 180 mm. And 8 areas of excessive density, with a total area of ​​approximately 95 The density of corundum in the area of ​​insufficient density is 4.8 kg / m³. The density of corundum in the excess area is 6.2 kg / m³, which is less than 90% of the target distribution density. The density was 110% higher than the target distribution density. The technical team used a handheld precision spreader to supplement and correct areas with insufficient density, with the output accuracy set at 20g / L. Each application should be controlled at a rate of 0.5 kg / m³. For areas with excessive density, a laser-guided leveling device is used for leveling, with the leveling thickness control precision set to 0.5mm. The excess diamond abrasive is scraped off and transferred to areas with insufficient density.

[0102] After the correction process was completed, the technical team used a high-resolution camera (4096×3072 pixels) to capture images of the floor surface, obtaining 200 images covering the entire construction area. After grayscale transformation and Gaussian filtering preprocessing, a threshold segmentation method was used to extract the diamond abrasive particle area, identifying 65,000 diamond abrasive particles. Figure 5 As shown, the technical team constructed a Voronoi diagram to analyze the spatial distribution pattern of the diamond particles. They used the Fortune scanline algorithm to generate Voronoi polygons and calculated the average area of ​​the Voronoi polygons to be 0.131. The standard deviation of the area is 0.028. According to the uniformity evaluation equation, the standard coefficient of variation was set to 0.20, and the calculated uniformity evaluation index was 0.93, which is greater than the uniformity standard threshold of 0.90, indicating that the uniformity of the corundum distribution meets the design requirements.

[0103] The technical team conducted performance tests on the completed emery abrasion-resistant flooring. Abrasion resistance was tested using an abrasion test with conditions set at 1000 revolutions per minute and a load of 9.8 N. The measured abrasion amount was 0.28 g, meeting the design requirement of less than 0.35 g. The interfacial bond strength was tested using the pull-out method, and the measured interfacial bond strength was 2.1 MPa, meeting the design requirement of over 1.8 MPa. Three months after construction, the technical team conducted a follow-up inspection of the flooring and found no cracks, no sandblasting, and no delamination on the surface. Wear was uniform in areas frequently used by forklifts, and the surface flatness remained good.

[0104] It should be noted that, in this embodiment, the complete implementation steps of the machine vision acquisition module are described in detail below:

[0105] Step 4021: Initialize the image acquisition system and start the machine vision acquisition module. Configure the high-resolution industrial camera parameters: set the camera resolution to 1920×1080 pixels, the acquisition frame rate to 5–15 frames / second, the exposure time to 5–20 milliseconds, the gain coefficient to 1.0–3.0, and the white balance mode to automatic. Set the camera lens focal length to 8–16mm and the aperture to F2.8–F5.6 to ensure that the image depth and sharpness meet the recognition requirements.

[0106] Step 4022: Lighting System Configuration. Configure LED ring or strip light sources. Set the color temperature to 5000–6500K, the illuminance to 1000–3000 lux, the installation height to 0.8–1.5m, and the angle between the light source and the floor surface to 30–60 degrees to avoid high-reflection areas and shadows. Use diffuse lighting to ensure uniform illumination distribution on the floor surface, with illuminance non-uniformity less than 10%.

[0107] Step 4023: Real-time Image Acquisition. The machine vision acquisition module continuously acquires images of the floor surface at a set frame rate. The camera is mounted on the moving platform of the frequency conversion spreading device, and the acquisition field of view is set to 0.5–1.5m × 0.5–1.5m. It moves synchronously with the spreading device to achieve full area coverage. The image acquisition triggering method adopts time triggering or displacement triggering. The displacement triggering interval is set to 0.2–0.5m to ensure that there is a 20–40% overlap between adjacent images to facilitate subsequent stitching.

[0108] Step 4024: Image Preprocessing. Preprocessing is performed on the acquired raw images. First, distortion correction is performed using the camera intrinsic parameter matrix and distortion coefficient matrix obtained from the checkerboard calibration board to remove distortion and eliminate the effects of radial and tangential lens distortion. Then, image enhancement is performed using a histogram equalization algorithm to improve image contrast, with the contrast enhancement coefficient set to 1.2–1.8.

[0109] Step 4025: Color Space Conversion. Convert the RGB color image to HSV or LAB color space. In HSV space, the hue (H) component ranges from 0 to 360 degrees, the saturation (S) component ranges from 0 to 1, and the lightness (V) component ranges from 0 to 1. Carborundum particles have a characteristic hue range in HSV space. The carborundum region is extracted by setting a hue threshold range. The lower limit of the hue threshold is set to 0 to 30 degrees, and the upper limit is set to 330 to 360 degrees, corresponding to the gray-black characteristics of carborundum material.

[0110] Step 4026: Image Segmentation and Feature Extraction. An adaptive threshold segmentation algorithm is used to binarize the preprocessed image, dividing it into a foreground region of corundum particles and a background region of concrete. The adaptive threshold window size is set from 15×15 pixels to 31×31 pixels, and the offset is set from -10 to +10. Morphological operations are performed on the binarized image: opening operations are used to remove small noise points, with the opening operation structuring element size set to 3×3 pixels; closing operations are used to fill the internal pores of the particles, with the closing operation structuring element size set to 5×5 pixels.

[0111] Step 4027: Particle Counting and Density Calculation. Connected component labeling is performed on the processed binarized image to identify each independent diamond abrasive particle region, and the particle count is recorded. Geometric feature parameters such as area, perimeter, and roundness are calculated for each particle. Roundness is equal to 4π multiplied by the particle area divided by the square of the particle perimeter. The roundness range is 0–1, with a roundness close to 1 indicating a near-circular particle shape. The actual spreading density is calculated based on the average area of ​​the diamond abrasive particles and the number of particles per unit area. The actual spreading density is equal to the total area of ​​particles per unit area multiplied by the density of the diamond abrasive material, which is 3.5–4.0 g / cm³.

[0112] Step 4028: Calculate the spreading density deviation. Compare the calculated actual spreading density with the target spreading density of 4-7 kg / m² to calculate the spreading density deviation. The spreading density deviation is equal to the actual spreading density minus the target spreading density. A positive deviation indicates that the spreading density is too high, while a negative deviation indicates that the spreading density is insufficient. Simultaneously, calculate the spreading density deviation rate, which is equal to the spreading density deviation divided by the target spreading density, multiplied by 100%. The deviation rate is controlled within ±5%.

[0113] Step 4029: Data Storage and Transmission. The acquisition timestamp, spatial coordinates, actual spreading density, and spreading density deviation of each image frame are stored in a data buffer. The data buffer capacity is set to 100–500 frames of data. The spreading density deviation is transmitted in real-time to the proportional-integral-derivative (PID) closed-loop control module via industrial Ethernet or fieldbus. The data transmission period is set to 50–200 milliseconds, and the data transmission protocol uses Modbus TCP or EtherCAT to ensure the real-time response performance of the control system.

[0114] Step 40210: Quality Monitoring and Anomaly Alarm. The machine vision acquisition module continuously monitors the spreading quality status. When the spreading density deviation rate exceeds ±10% in 3-5 consecutive frames, an anomaly alarm signal is triggered. The alarm signal is simultaneously alerted to the operator via an audible and visual alarm and the human-machine interface. The time, location, and degree of deviation of the anomaly are recorded, generating quality traceability data to provide data support for subsequent process improvements.

[0115] The complete process of this machine vision acquisition module adopts a combination of real-time acquisition with industrial cameras, multi-scale image processing, feature extraction and density calculation. By accurately identifying the spatial distribution of diamond particles and providing real-time feedback on the spreading density deviation information, it achieves the technical effect of realizing visualized monitoring and precise closed-loop control of the entire spreading operation.

[0116] This invention represents a significant technological advancement over traditional methods for constructing abrasive-resistant flooring. Firstly, stress analysis using a three-dimensional finite element model allows for the identification of stress concentration areas and potential crack paths before construction. This enables the technical team to specifically strengthen the interface treatment in these areas, fundamentally preventing interface delamination and cracking caused by stress concentration—a predictive capability that traditional methods relying on experience cannot achieve. Secondly, the vacuum dewatering device directly removes free water and laitance from the surface of the base concrete through negative pressure, avoiding the micro-damage caused by traditional mechanical grinding methods. It also reduces surface moisture content, creating favorable conditions for the full penetration of the interface agent and enhancing the microstructural integrity of the interface bonding layer. Thirdly, the ultrasonic testing device, through quantitative analysis of transmission time and amplitude attenuation coefficients, enables non-destructive testing and quantitative evaluation of interface bonding quality. Traditional methods, limited to destructive sampling through pull-out tests, cannot comprehensively assess interface bonding quality. Finally, the intelligent spreading system, comprised of the machine vision acquisition module and the proportional-integral-derivative closed-loop control module of the frequency conversion spreading device, can monitor the spreading density in real time and dynamically adjust the discharge frequency, ensuring a high degree of uniformity in the distribution of corundum. Traditional manual spreading methods rely on the experience and skills of operators, making precise control difficult and prone to uneven distribution. Through spatial distribution analysis using Voronoi diagrams, this invention achieves a quantitative evaluation of the uniformity of corundum particle distribution, providing a scientific basis for construction quality control. Traditional methods can only rely on subjective judgment through visual inspection, lacking quantitative standards. These technological advancements collectively guarantee the construction quality and long-term performance of corundum wear-resistant flooring.

[0117] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. An optimized construction process for corundum wear-resistant flooring, characterized in that, include: A three-dimensional finite element model was established, comprising a base concrete layer, an interface bonding layer, and a corundum wear-resistant layer, and stress and displacement distribution cloud maps were calculated. A vacuum dewatering device was used to remove laitance from the base concrete surface, and a penetrating interface agent was sprayed onto it. An ultrasonic testing device was used to monitor the bonding quality of the interface bonding layer and calculate the interface bonding strength evaluation index. When the interface bonding strength evaluation index exceeded the preset threshold, a variable frequency spreading device was used to spread corundum. This device was equipped with a machine vision acquisition module and a proportional-integral-derivative (PID) closed-loop control module. The machine vision acquisition module acquired real-time images of the floor surface and calculated the spreading density deviation value, while the PID closed-loop control module dynamically adjusted the discharge frequency based on the spreading density deviation value. A lidar scanning device was used to perform a three-dimensional scan of the floor surface after corundum spreading and generate a three-dimensional cloud map of corundum distribution density. Areas with insufficient density were supplemented with additional spreading, while areas with excessive density were leveled. A high-resolution camera was used to acquire images of the processed floor surface, construct a Voronoi diagram to analyze the spatial distribution pattern, and calculate the uniformity evaluation index.

2. The method according to claim 1, characterized in that, The vacuum water suction device includes a vacuum pump, a water suction pipe and a water suction head. The bottom of the water suction head is provided with a porous water suction plate, which removes free water and laitance from the surface of the base concrete through vacuum negative pressure.

3. The method according to claim 2, characterized in that, The vacuum water absorption device is set to a negative pressure of 30 to 60 kPa and a water absorption time of 5 to 15 minutes, so that the moisture content of the base concrete surface is reduced to 4 to 8%.

4. The method according to claim 3, characterized in that, The penetrating interface agent is a silane or epoxy interface treatment agent. The penetrating interface agent improves the interface microstructure by filling the pores and microcracks in the interface transition zone.

5. The method according to claim 4, characterized in that, The interface bonding strength evaluation index is calculated through the interface bonding strength evaluation equation set, which includes the ultrasonic time-normalized equation, the amplitude attenuation normalized equation, and the interface bonding strength comprehensive equation.

6. The method according to claim 5, characterized in that, The inputs to the ultrasonic time normalization equation include the ultrasonic transmission time at the measuring point and the standard ultrasonic transmission time. The output is a normalized ultrasonic time parameter, which is equal to the ultrasonic transmission time at the measuring point divided by the standard ultrasonic transmission time.

7. The method according to claim 6, characterized in that, The inputs to the comprehensive equation for interface bonding strength include standardized ultrasonic time parameters, standardized amplitude attenuation parameters, ultrasonic time weighting coefficients, and amplitude attenuation weighting coefficients. The interface bonding strength evaluation index is equal to the ultrasonic time weighting coefficient divided by the sum of the standardized ultrasonic time parameters and the amplitude attenuation weighting coefficient divided by the standardized amplitude attenuation parameters.

8. The method according to claim 7, characterized in that, The preset threshold for the interface bonding strength is 0.75 to 0.

95. When the interface bonding strength evaluation index is less than the preset threshold for interface bonding strength, the laitance removal treatment step and the interface bonding quality monitoring step are repeated.

9. The method according to claim 8, characterized in that, The proportional-integral-derivative closed-loop control module calculates the discharge frequency adjustment amount based on the spreading density deviation value through the discharge frequency adjustment equation set, which includes proportional adjustment equation, integral adjustment equation, derivative adjustment equation, and frequency comprehensive adjustment equation.

10. The method according to claim 9, characterized in that, The inputs to the proportional adjustment equation include the spreading density deviation value, the target spreading density, and the proportional coefficient. The proportional adjustment component is equal to the spreading density deviation value divided by the target spreading density and then multiplied by the proportional coefficient, which is set to 0.4 to 0.8.

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