Dynamic monitoring and adjusting method and system for ultra-high performance concrete preparation process

Abstract

The invention discloses an ultra-high performance concrete preparation process dynamic monitoring and adjusting method and system, and relates to the technical field of concrete preparation, and the method comprises the following steps: enabling an image acquisition device and a laser particle size analyzer to cooperatively work, and capturing an image of an aggregate particle area irradiated by laser in real time; by introducing the technology of combining image acquisition and morphological analysis, the geometrical shape characteristics of aggregate particles are accurately extracted, and the irregularity of the particles is quantified, so that the self-adaptive adjustment of the light beam density is realized, the laser particle size analyzer can adjust the light beam density in real time according to the morphological complexity of the particles, and the detection accuracy is improved. The scattering signal of irregular particles can be accurately captured, the particle size measurement precision of the laser particle size analyzer on aggregate particles with complex forms is remarkably improved, the monitoring capability and reliability of particle size distribution are enhanced, and particularly, the measurement accuracy and stability can be effectively improved when particles with high irregularity are processed.

Description

Technical Field

[0001] The present invention relates to the technical field of concrete preparation, and in particular to a method and system for dynamically monitoring and regulating an ultra-high performance concrete preparation process. Background Art

[0002] Ultra-high-performance concrete (UHPC) production process monitoring involves the real-time collection and analysis of key parameter data during the production of ultra-high-performance concrete (UHPC) to ensure that the concrete's quality and performance meet expected requirements. This process typically involves precise control of the proportions of raw materials (cement, admixtures, aggregates, etc.), monitoring of physical environmental factors such as mixing, water addition, temperature, and humidity, and tracking performance indicators such as strength and durability during the hardening process. Through sensors, data acquisition systems, and intelligent analysis algorithms, precise control can be implemented at every stage of production, allowing potential problems to be identified and corrected promptly, thereby ensuring that the final UHPC possesses excellent mechanical properties, durability, and workability.

[0003] In the preparation of ultra-high-performance concrete (UHPC), the particle size distribution of aggregates directly impacts the concrete's fluidity, compactness, and ultimate mechanical properties. Laser particle size analyzers, using the principle of laser scattering, measure the particle size distribution of aggregate particles. They are particularly suitable for analyzing fine particles and are widely used for aggregate monitoring in concrete production. A balanced combination of fine and coarse particles effectively fills the gaps between aggregates, increasing the contact surface, improving the density of concrete, and reducing porosity, thereby enhancing its strength and durability. Precisely controlling the aggregate size distribution optimizes the water-cement ratio, reduces cement and water usage, and improves the workability and construction properties of concrete. Furthermore, a good particle size distribution helps reduce shrinkage deformation and cracking in concrete, enhancing its long-term weathering resistance. Therefore, precise monitoring of particle size distribution not only ensures the stability of concrete performance but also effectively reduces costs, improves production efficiency, and optimizes the preparation process.

[0004] The existing technology has the following deficiencies:

[0005] When laser particle size analyzers measure aggregate particle size distribution using the laser scattering principle, they typically illuminate the aggregate sample with a fixed beam density. However, when aggregate particles exhibit a high degree of irregularity, the way they scatter the laser beam can change significantly. This is especially true for angular or flaky particles, whose larger surface areas cause variations in the angle and intensity of scattered light, affecting measurement results. The variations in scattering angle and intensity become more complex in the case of irregular particle shapes, making the traditional fixed beam density insufficient for ensuring accurate measurements.

[0006] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0007] The purpose of the present invention is to provide a dynamic monitoring and adjustment method and system for the ultra-high performance concrete preparation process. By introducing a technology that combines image acquisition and morphological analysis, the geometric shape characteristics of aggregate particles are accurately extracted and the irregularity of the particles is quantified, thereby realizing adaptive adjustment of the light beam density, enabling the laser particle size analyzer to adjust the light beam density in real time according to the morphological complexity of the particles, ensuring that the scattering signals of irregular particles can be accurately captured, significantly improving the particle size measurement accuracy of the laser particle size analyzer for aggregate particles with complex morphology, enhancing the monitoring capability and reliability of the particle size distribution, especially when processing highly irregular particles, and effectively improving the accuracy and stability of the measurement to solve the problems in the above-mentioned background technology.

[0008] In order to achieve the above object, the present invention provides the following technical solution: a method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process, comprising the following steps:

[0009] The image acquisition device is used in conjunction with the laser particle size analyzer to capture images of the area where the laser irradiates the aggregate particles in real time;

[0010] Preprocessing the acquired image of the aggregate particle area irradiated by the laser;

[0011] After image preprocessing, the geometric shape of aggregate particles is extracted using morphological analysis methods;

[0012] After obtaining the geometric shape characteristics of the aggregate particles, the irregularity characteristics of the aggregate particles that reflect their morphological complexity are extracted. The extracted characteristics are then deeply analyzed. Based on the analysis results, a quantifiable irregularity index is constructed to quantitatively evaluate the overall irregularity of the aggregate particles within the irradiation area of ​​the laser particle size analyzer.

[0013] The beam density of the laser particle size analysis is adaptively adjusted according to the overall irregularity of the aggregate particles in the laser irradiation area.

[0014] Preferably, after image preprocessing is completed, the geometric shape extraction of aggregate particles is usually achieved through the following morphological analysis steps:

[0015] Apply binarization processing to convert the grayscale image into a black and white image in order to distinguish the particle area from the background area;

[0016] Perform an erosion operation to separate the stuck grain boundaries and make the grain outlines clearer;

[0017] Perform expansion treatment to restore the excessively shrunk areas of the particle edges after corrosion and ensure the integrity of the particles;

[0018] Through opening or closing operations, the particle contours are further smoothed, small holes or broken edges are filled, and geometric shapes with complete structures and clear boundaries are extracted.

[0019] Preferably, the irregularity characteristics of the aggregate particles are extracted, wherein the extracted characteristics are the deviations of the actual fractal dimensions of the aggregate particle contours relative to the theoretical smooth contour dimensions, and after an in-depth analysis of the extracted characteristics, a fractal dimension deviation reference value is generated. Based on the fractal dimension deviation reference value, a quantifiable irregularity index is constructed to quantitatively evaluate the overall irregularity of the aggregate particles in the irradiation area of ​​the laser particle size analyzer.

[0020] Preferably, the specific steps of generating a fractal dimension deviation reference value after performing an in-depth analysis on the deviation of the actual fractal dimension of the aggregate particle profile from the theoretical smooth profile dimension are as follows:

[0021] The actual fractal dimension of the aggregate particle outline is calculated using the fractal dimension analysis method. This process obtains the complexity of the particle outline through image analysis and uses advanced fractal analysis techniques such as the box-counting method or the differential box-counting method to measure the self-similarity and complexity of the particle boundaries. The calculation formula is: ,in: Use size The number of boxes required to cover the particle boundaries, is the size of the box, is the actual fractal dimension of the aggregate particle boundary;

[0022] Calculate the fractal dimension of a theoretical smooth contour (e.g., ideal geometric shapes like circles and ellipses). Ideal smooth contours, such as perfect circles or regular ellipses, typically have a fractal dimension close to 2 (the highest value). Theoretically, these contours have a low fractal dimension, indicating a simple and smooth boundary. The fractal dimension of this ideal shape is obtained through theoretical analysis, and the deviation between the actual fractal dimension and the theoretical smooth contour dimension is calculated. The resulting fractal dimension deviation from the reference value is defined as: ,in: is the fractal dimension corresponding to an ideal smooth contour (such as a circle), usually 2, is the deviation of the fractal dimension from the reference value, which is used to quantify the degree of irregularity of the particle geometry. is the adjustment coefficient, which is used to control the influence of the deviation on the fractal dimension deviation from the reference value.

[0023] Preferably, the fractal dimension analysis method is selected from one of the box counting method and the differential box counting method.

[0024] Preferably, it can be seen from the fractal dimension deviation reference value that the greater the performance value of the fractal dimension deviation from the reference value generated after in-depth analysis of the deviation of the actual fractal dimension of the aggregate particle contour relative to the theoretical smooth contour dimension, the higher the degree of geometric irregularity of the aggregate particle, and vice versa.

[0025] Preferably, the beam density of the laser particle size analyzer is adaptively adjusted according to the overall irregularity of the aggregate particles in the laser irradiation area, so that the laser particle size analyzer can more accurately capture the scattered signals of irregularly shaped particles. The specific steps are as follows:

[0026] The control factor is calculated by analyzing the deviation of the fractal dimension of the aggregate particles in the laser irradiation area from the reference value. The deviation of the fractal dimension from the reference value reflects the complexity of the particle boundary, that is, the deviation between the actual fractal dimension and the theoretical smooth contour dimension. The control factor related to the particle irregularity is calculated based on this fractal dimension deviation from the reference value. The calculation expression is: ,in: is a control factor used to control the adjustment range of the beam density. and is a constant coefficient, constant Used to control the scale of the regulatory factors, Used to adjust the influence of fractal dimension on regulatory factors;

[0027] According to the calculated regulatory factors , in the laser particle size analyzer, the beam density is adaptively adjusted. The formula for adaptive adjustment is as follows: ,in: is the adjusted beam density, is the base beam density, is the adjustment coefficient, which is used to control the adjustment sensitivity of the beam density.

[0028] The dynamic monitoring and adjustment system for the ultra-high performance concrete preparation process includes an image acquisition module, an image preprocessing module, a morphological analysis module, an irregularity feature extraction module, and a beam density adjustment module;

[0029] The image acquisition module works in conjunction with the image acquisition device and the laser particle size analyzer to capture the image of the area where the laser irradiates the aggregate particles in real time;

[0030] An image preprocessing module preprocesses the acquired image of the aggregate particle area irradiated by the laser;

[0031] The morphological analysis module extracts the geometric shape of aggregate particles using morphological analysis methods after image preprocessing is completed;

[0032] The irregularity feature extraction module, after obtaining the geometric shape characteristics of aggregate particles, extracts the irregularity features of aggregate particles that reflect their morphological complexity, conducts in-depth analysis of the extracted features, and constructs a quantifiable irregularity index based on the analysis results to quantitatively evaluate the overall irregularity of aggregate particles within the area irradiated by the laser particle size analyzer.

[0033] The beam density adjustment module adaptively adjusts the beam density of laser particle size analysis according to the overall irregularity of the aggregate particles in the laser irradiation area.

[0034] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0035] The present invention introduces a technology that combines image acquisition with morphological analysis to accurately extract the geometric shape characteristics of aggregate particles and quantify the irregularity of the particles, thereby achieving adaptive adjustment of the beam density. The laser particle size analyzer can adjust the beam density in real time according to the morphological complexity of the particles, ensuring that the scattering signals of irregular particles can be accurately captured. This significantly improves the particle size measurement accuracy of the laser particle size analyzer for aggregate particles with complex morphology, enhances the monitoring capability and reliability of particle size distribution, and can effectively improve the accuracy and stability of measurement, especially when processing highly irregular particles. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction to the drawings required for use in the embodiments will be given below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0037] Figure 1 The present invention is a flow chart of the method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process.

[0038] Figure 2 Schematic diagram of the modules of the dynamic monitoring and adjustment system for the ultra-high performance concrete preparation process of the present invention. DETAILED DESCRIPTION

[0039] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art.

[0040] The present invention provides Figure 1 The method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process shown includes the following steps:

[0041] An image acquisition device (such as a high-resolution camera or microscope camera) is used in conjunction with the laser particle size analyzer to capture images of the area where the laser irradiates the aggregate particles in real time;

[0042] A laser particle size analyzer illuminates an aggregate sample with a laser beam, while an image acquisition device simultaneously captures real-time images of the aggregate particles. This image provides critical visual data for subsequent analysis. The image acquisition device must have sufficient resolution and clarity to capture detailed particle surface morphology to ensure accurate feature extraction. Furthermore, synchronization between image acquisition and laser analysis is crucial, ensuring precise alignment between the laser irradiation area and the captured image area, thereby providing consistent data support for particle size analysis.

[0043] After obtaining the image of the aggregate particle area irradiated by the laser, the image is preprocessed to improve the image quality;

[0044] The acquired raw images are often affected by noise, uneven lighting, and other interfering factors, necessitating image preprocessing. This includes operations such as denoising, contrast enhancement, adjusting lighting conditions, and edge detection. Common image processing methods include median filtering, Gaussian blurring, and histogram equalization. Image preprocessing improves image quality and prepares for subsequent particle shape recognition and irregularity feature extraction. Removing noise and irrelevant background information helps accurately identify the edges and shapes of aggregate particles, improving the accuracy of particle morphology analysis. By enhancing image contrast and light-dark balance, the outlines and details of aggregate particles can be more clearly seen, ensuring the reliability of feature extraction.

[0045] After image preprocessing is completed, the geometric shape of aggregate particles is extracted using morphological analysis methods (such as dilation, erosion, opening operation, closing operation, etc.);

[0046] After image preprocessing is completed, the geometric shape extraction of aggregate particles is usually achieved through the following four morphological analysis steps: first, binarization processing is applied to convert the grayscale image into a black and white image to distinguish the particle area from the background area; second, an erosion operation is performed to separate the adhered particle boundaries and make the particle contours clearer; then, dilation processing is performed to restore the areas where the particle edges may have over-shrunk after corrosion to ensure the integrity of the particles; finally, an opening operation (erosion followed by dilation) or a closing operation (dilation followed by erosion) is used to further smooth the particle contours and fill small holes or broken edges, thereby extracting geometric shapes with complete structures and clear boundaries, providing an accurate morphological basis for subsequent irregularity analysis.

[0047] These morphological operations effectively identify particle edges and outlines, allowing for further analysis of their shape characteristics (such as aspect ratio, surface area, and edge complexity). Morphological analysis extracts geometric features of aggregate particles from images, providing a crucial basis for subsequent irregularity analysis and particle size measurement. This step provides basic information on particle shape, such as whether the particles are spherical, irregular, angular, or flake-like. This step provides clear geometric data for further analysis of particle irregularity.

[0048] After obtaining the geometric shape characteristics of the aggregate particles, the irregularity characteristics of the aggregate particles that reflect their morphological complexity are extracted. The extracted characteristics are then deeply analyzed. Based on the analysis results, a quantifiable irregularity index is constructed to quantitatively evaluate the overall irregularity of the aggregate particles within the irradiation area of ​​the laser particle size analyzer.

[0049] Aggregate particle irregularity characteristics are extracted, where the extracted characteristics are the deviations of the actual fractal dimensions of the aggregate particle contours relative to the theoretical smooth contour dimensions. After in-depth analysis of the extracted characteristics, a fractal dimension deviation reference value is generated. Based on the fractal dimension deviation reference value, a quantifiable irregularity index is constructed to quantitatively evaluate the overall irregularity of the aggregate particles within the irradiation area of ​​the laser particle size analyzer.

[0050] The deviation of the actual fractal dimension of a particle's outline from the theoretical smooth outline's dimension refers to the difference between the complexity of the particle boundary as calculated using fractal geometry methods in an actual image and the fractal dimension of an ideal, smooth, regular outline. Theoretical smooth outlines (such as perfect circles) typically have a lower fractal dimension, indicating a simple structure and flat boundaries. Actual aggregate particles, however, due to natural crushing or processing, often have numerous bumps, angles, and multi-level nested structures on their boundaries, resulting in a higher fractal dimension. By comparing the difference in these two dimensions, the geometric complexity of the particle boundary can be quantified. A greater deviation indicates a more irregular and complex particle boundary, making it a sensitive indicator of the degree of irregularity in particle morphology.

[0051] The greater the deviation of the actual fractal dimension of an aggregate particle's outline from the theoretical smooth outline dimension, the more irregular the aggregate particle's geometry. This is because fractal dimension is a measure of boundary complexity. Ideally smooth outlines (such as circles or ellipses) have lower fractal dimensions, indicating regular shapes and smooth boundaries. However, due to natural crushing, friction, or external forces, the boundaries of actual aggregate particles often exhibit numerous irregular broken lines, depressions, or protrusions, making the boundaries more complex and tortuous, and increasing the fractal dimension. Therefore, a greater deviation of the fractal dimension indicates a more irregular and complex aggregate particle shape, with greater detail and structural irregularities. This deviation accurately reflects the degree of geometric irregularity in a particle and is a very important indicator in particle morphology analysis.

[0052] The specific steps for generating a fractal dimension deviation reference value after in-depth analysis of the deviation of the actual fractal dimension of the aggregate particle profile from the theoretical smooth profile dimension are as follows:

[0053] The actual fractal dimension of the aggregate particle outline is calculated using the fractal dimension analysis method. This process obtains the complexity of the particle outline through image analysis and uses advanced fractal analysis techniques such as the box-counting method or the differential box-counting method to measure the self-similarity and complexity of the particle boundaries. The calculation formula is: ,in: Use size The number of boxes required to cover the particle boundaries, is the size of the box, is the actual fractal dimension of the aggregate particle boundary;

[0054] The purpose of this step is to evaluate the complexity of the particle outline through the fractal dimension. Indicates complex particle boundaries and irregular shapes; lower actual fractal dimension It means that the particle outline is relatively smooth and the shape is regular.

[0055] Next, the fractal dimension of a theoretical smooth contour (such as an ideal geometric shape like a circle or ellipse) is calculated. For ideal smooth contours, such as a perfect circle or a regular ellipse, the fractal dimension is typically close to 2 (the highest value). Theoretically, these contours have a low fractal dimension, indicating a simple and smooth boundary. The fractal dimension of this ideal shape is obtained through theoretical analysis, and the deviation between the actual fractal dimension and the theoretical smooth contour dimension is calculated. The resulting fractal dimension deviation from the reference value is defined as: ,in: is the fractal dimension corresponding to an ideal smooth contour (such as a circle), usually 2, is the deviation of the fractal dimension from the reference value, which is used to quantify the degree of irregularity of the particle geometry. is the adjustment coefficient, which is used to control the influence of the deviation on the fractal dimension deviation from the reference value;

[0056] This step calculates the fractal dimension deviation from the reference value , quantifies the complexity of the aggregate particle boundaries. The fractal dimension deviates from the reference value The larger the value, the more irregular the particle shape; the fractal dimension deviates from the reference value. The smaller it is, the more regular the particle shape is.

[0057] The fractal dimension deviation from the reference value indicates that a larger value, generated by in-depth analysis of the deviation of the actual fractal dimension of the aggregate particle outline from the theoretical smooth contour dimension, indicates a more irregular geometry of the aggregate particle. Conversely, a smaller value indicates a less irregular geometry. This is because the fractal dimension is a measure of the complexity of particle boundaries. A larger fractal dimension of an actual particle indicates a more tortuous and irregular particle boundary. On the other hand, a lower fractal dimension of a theoretical smooth contour (such as a circle or ellipse) indicates a simpler, more regular boundary. By calculating the deviation between the actual fractal dimension and the theoretical fractal dimension, the larger the fractal dimension's deviation from the reference value, the greater the difference between the particle boundary and the ideal regular shape, indicating a more complex and irregular shape. Therefore, a higher fractal dimension deviation from the reference value indicates a more irregular geometry of the particle, while a lower value indicates a shape closer to a regular geometry.

[0058] Adaptively adjust the beam density of the laser particle size analyzer according to the overall irregularity of the aggregate particles in the laser irradiation area, so that the laser particle size analyzer can more accurately capture the scattered signals of irregularly shaped particles and improve the monitoring accuracy of particle size distribution;

[0059] The laser particle size analyzer’s beam density is adaptively adjusted based on the overall irregularity of the aggregate particles in the laser irradiation area, enabling the laser particle size analyzer to more accurately capture the scattered signals of irregularly shaped particles. The specific steps are as follows:

[0060] The control factor is calculated by analyzing the deviation of the fractal dimension of the aggregate particles in the laser irradiation area from the reference value. The deviation of the fractal dimension from the reference value reflects the complexity of the particle boundary, that is, the deviation between the actual fractal dimension and the theoretical smooth contour dimension. The control factor related to the particle irregularity is calculated based on this fractal dimension deviation from the reference value. The calculation expression is: ,in: is a control factor used to control the adjustment range of the beam density. and is a constant coefficient, constant Used to control the scale of the regulatory factors, It is used to adjust the influence of fractal dimension on the control factor. Specifically, as the fractal dimension deviates from the reference value Increase, regulatory factors will increase, indicating that the particle has higher irregularity and the beam density needs to be increased to capture the scattered signal more accurately;

[0061] The purpose of this step is to quantify the irregularity of the particles and convert it into a control parameter, the control factor This factor indicates the degree to which adaptive adjustment of the laser particle size analyzer's beam density is necessary. This control factor ensures that the instrument can increase laser intensity appropriately when dealing with complex, irregular particles, thereby improving the recognition of scattered signals.

[0062] According to the calculated regulatory factors , in the laser particle size analyzer, the beam density is adaptively adjusted. The formula for adaptive adjustment is as follows: ,in: is the adjusted beam density, is the base beam density, Is the adjustment coefficient, which is used to control the adjustment sensitivity of the beam density. Usually, optimization is performed based on experimental data to ensure that the beam density adjustment does not deviate too much from the original value. Larger, indicating that the particle shape is more irregular, the system will increase the beam density to ensure that enough scattered light is captured, improving the accuracy of particle size distribution measurement;

[0063] This step automatically adjusts the laser particle size analyzer's beam density based on the particle irregularity. By adjusting the beam density, the instrument can more accurately capture the scattered signal from irregularly shaped particles, thereby improving the accuracy of particle size distribution monitoring. Adjusting the beam density adapts the measurement process to particles of varying morphologies, enhancing measurement accuracy and robustness, especially for complex particle shapes.

[0064] By adaptively adjusting the laser particle size analyzer's beam density based on the irregularity of the aggregate particles, the analyzer can accurately capture the scattered signals of the particles when faced with particles of different shapes, thereby improving the monitoring accuracy of the particle size distribution. In actual measurement, the shapes of aggregate particles may exhibit varying degrees of complexity. Relatively regular particles (such as spheres and circles) have simple, smooth boundaries. When the light beam illuminates these particles, the scattered light is relatively uniform, and the laser particle size analyzer can more easily measure their particle size distribution. However, for particles with irregular shapes and complex boundaries (such as angular, flaky, or fragmented particles), the intensity and angle of the scattered light will vary significantly due to their more complex edges and irregular shapes. As a result, the conventional beam density of the laser particle size analyzer may not be sufficient to capture all the information of the scattered light, which in turn affects the accuracy and precision of the particle size measurement.

[0065] To overcome this problem, laser particle size analyzers incorporate an adaptive beam density adjustment mechanism based on particle irregularity, enabling dynamic adjustment of beam density. First, the system calculates the overall irregularity of the aggregate particles based on their geometrical characteristics. For example, if the particles have complex shapes and exhibit significant edge irregularities (such as depressions or protrusions), the system will identify this as a sign of high irregularity and automatically increase the beam density. This increased beam density enhances the instrument's sensitivity to scattered light from complex particles, ensuring that more scattered signals are captured and improving the accuracy of monitoring the particle size distribution of complex particles.

[0066] Conversely, when particles are more regular in shape, the system detects a lower degree of irregularity and appropriately reduces the beam density. This reduction avoids excessively strong scattered light signals from regular particles, which could lead to oversaturation and affect measurement accuracy. This adjustment allows the laser particle size analyzer to maintain optimal sensitivity and avoid unnecessary measurement errors.

[0067] The role of this step is reflected in several key aspects: First, it can adjust the beam density of the laser particle size analyzer in real time according to the different shapes of the particles, so that both regular and irregular particles can obtain appropriate light intensity, ensuring accurate measurement of the particle size distribution. Secondly, by increasing or decreasing the beam density, the system can dynamically adapt to the scattering characteristics of different particles, thereby reducing the measurement error caused by beam intensity mismatch. In addition, this adaptive adjustment can effectively improve the analyzer's response ability when dealing with particles with complex morphologies, especially in the measurement of highly irregular particles (such as gravel and crushed materials), significantly improving the accuracy and stability of particle size measurement. Finally, through fine control of the beam density, this step effectively avoids the problem of excessive reflection or oversaturation measurement, reduces the errors and deviations that may occur during the measurement process, and thus improves the applicability and reliability of the laser particle size analyzer in practical applications.

[0068] The above solution can effectively solve the problem of inaccurate measurement caused by fixed beam density when the laser particle size analyzer is faced with irregularly shaped aggregate particles. Specifically, the solution introduces a technology that combines image acquisition and morphological analysis to accurately extract the geometric shape characteristics of aggregate particles and quantify the irregularity of the particles, thereby achieving adaptive adjustment of the beam density. This method of dynamically adjusting the beam density enables the laser particle size analyzer to adjust the beam density in real time according to the morphological complexity of the particles, ensuring that the scattered signals of irregular particles can be accurately captured. This solution significantly improves the particle size measurement accuracy of the laser particle size analyzer for aggregate particles with complex morphology, enhances the monitoring capability and reliability of particle size distribution, and can effectively improve the accuracy and stability of measurement, especially when dealing with highly irregular particles.

[0069] The present invention provides Figure 2 The dynamic monitoring and adjustment system for the ultra-high performance concrete preparation process shown includes an image acquisition module, an image preprocessing module, a morphological analysis module, an irregularity feature extraction module, and a beam density adjustment module;

[0070] The image acquisition module works in conjunction with the image acquisition device and the laser particle size analyzer to capture images of the area where the laser irradiates the aggregate particles in real time;

[0071] Image preprocessing module, which preprocesses the acquired images of the aggregate particle area irradiated by the laser to improve the image quality and ensure the accuracy of subsequent analysis;

[0072] The morphological analysis module extracts the geometric shape of aggregate particles using morphological analysis methods after image preprocessing is completed;

[0073] The irregularity feature extraction module, after obtaining the geometric shape characteristics of aggregate particles, extracts the irregularity features of aggregate particles that reflect their morphological complexity, conducts in-depth analysis of the extracted features, and constructs a quantifiable irregularity index based on the analysis results to quantitatively evaluate the overall irregularity of aggregate particles within the area irradiated by the laser particle size analyzer.

[0074] The beam density adjustment module adaptively adjusts the beam density of laser particle size analysis according to the overall irregularity of the aggregate particles in the laser irradiation area.

[0075] The method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process provided in an embodiment of the present invention is implemented by the above-mentioned dynamic monitoring and adjustment system for the ultra-high performance concrete preparation process. The specific methods and processes of the dynamic monitoring and adjustment system for the ultra-high performance concrete preparation process are detailed in the embodiment of the method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process, which will not be repeated here.

[0076] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0077] The above description is merely illustrative of certain exemplary embodiments of the present invention. It goes without saying that those skilled in the art will be able to modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and description are illustrative in nature and should not be construed as limiting the scope of protection of the claims.

[0078] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0079] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0080] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection of some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0081] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0082] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0083] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0084] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for dynamic monitoring and adjustment of ultra-high performance concrete preparation process, characterized in that: The following steps are involved: The image acquisition device is used in conjunction with the laser particle size analyzer to capture images of the area where the laser irradiates the aggregate particles in real time; Preprocessing the acquired image of the aggregate particle area irradiated by the laser; After image preprocessing, the geometric shape of aggregate particles is extracted using morphological analysis methods; After obtaining the geometric shape characteristics of the aggregate particles, the irregularity characteristics of the aggregate particles that reflect their morphological complexity are extracted. The extracted characteristics are then deeply analyzed. Based on the analysis results, a quantifiable irregularity index is constructed to quantitatively evaluate the overall irregularity of the aggregate particles within the irradiation area of ​​the laser particle size analyzer. The beam density of the laser particle size analysis is adaptively adjusted according to the overall irregularity of the aggregate particles in the laser irradiation area.

2. The method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process according to claim 1, characterized in that: After image preprocessing is completed, the geometric shape extraction of aggregate particles is usually achieved through the following morphological analysis steps: Apply binarization processing to convert the grayscale image into a black and white image in order to distinguish the particle area from the background area; Perform an erosion operation to separate the stuck grain boundaries and make the grain outlines clearer; Perform expansion treatment to restore the excessively shrunk areas of the particle edges after corrosion and ensure the integrity of the particles; Through opening or closing operations, the particle contours are further smoothed, small holes or broken edges are filled, and geometric shapes with complete structures and clear boundaries are extracted.

3. The method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process according to claim 1, characterized in that: Aggregate particle irregularity characteristics are extracted, where the extracted characteristics are the deviations of the actual fractal dimensions of the aggregate particle contours relative to the theoretical smooth contour dimensions. After in-depth analysis of the extracted characteristics, a fractal dimension deviation reference value is generated. Based on the fractal dimension deviation reference value, a quantifiable irregularity index is constructed to quantitatively evaluate the overall irregularity of the aggregate particles within the irradiation area of ​​the laser particle size analyzer.

4. The method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process according to claim 3, characterized in that: The specific steps for generating a fractal dimension deviation reference value after in-depth analysis of the deviation of the actual fractal dimension of the aggregate particle profile from the theoretical smooth profile dimension are as follows: The actual fractal dimension of the aggregate particle outline is calculated using the fractal dimension analysis method. The calculation expression is: ,in: The size is The number of boxes required to cover the particle boundaries, is the size of the box, is the actual fractal dimension of the aggregate particle boundary; The fractal dimension of the ideal shape is obtained through theoretical analysis. The deviation between the actual fractal dimension and the theoretical smooth contour dimension is used to calculate the fractal dimension deviation reference value. The calculation expression is: ,in: is the fractal dimension corresponding to the ideal smooth contour, which takes a value of 2. is the deviation of the fractal dimension from the reference value, which is used to quantify the degree of irregularity of the particle geometry. is the adjustment coefficient, which is used to control the influence of the deviation on the fractal dimension deviation from the reference value.

5. The method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process according to claim 4, characterized in that: The fractal dimension analysis method is selected from the box counting method or the differential box counting method.

6. The method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process according to claim 4, characterized in that: It can be seen from the fractal dimension deviation from the reference value that the greater the performance value of the fractal dimension deviation from the reference value generated after in-depth analysis of the deviation of the actual fractal dimension of the aggregate particle contour relative to the theoretical smooth contour dimension, the higher the degree of geometric irregularity of the aggregate particle, and vice versa.

7. The method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process according to claim 4, characterized in that: The laser particle size analyzer’s beam density is adaptively adjusted based on the overall irregularity of the aggregate particles in the laser irradiation area, enabling the laser particle size analyzer to more accurately capture the scattered signals of irregularly shaped particles. The specific steps are as follows: The control factor is calculated by analyzing the deviation of the fractal dimension of the aggregate particles in the laser irradiation area from the reference value. The calculation expression is: ,in: is a control factor used to control the adjustment range of the beam density. and is a constant coefficient, a constant coefficient Used to control the scale of the regulatory factor, constant coefficient Used to adjust the influence of fractal dimension on regulatory factors; According to the calculated regulatory factors , in the laser particle size analyzer, the beam density is adaptively adjusted. The formula for adaptive adjustment is as follows: ,in: is the adjusted beam density, is the base beam density, is the adjustment coefficient, which is used to control the adjustment sensitivity of the beam density.

8. A dynamic monitoring and adjustment system for ultra-high performance concrete preparation process, used to implement the dynamic monitoring and adjustment method for ultra-high performance concrete preparation process according to any one of claims 1 to 7, characterized in that: It includes image acquisition module, image preprocessing module, morphological analysis module, irregularity feature extraction module and beam density adjustment module; The image acquisition module works in conjunction with the image acquisition device and the laser particle size analyzer to capture the image of the area where the laser irradiates the aggregate particles in real time; An image preprocessing module preprocesses the acquired image of the aggregate particle area irradiated by the laser; The morphological analysis module extracts the geometric shape of aggregate particles using morphological analysis methods after image preprocessing is completed; The irregularity feature extraction module, after obtaining the geometric shape characteristics of aggregate particles, extracts the irregularity features of aggregate particles that reflect their morphological complexity, conducts in-depth analysis of the extracted features, and constructs a quantifiable irregularity index based on the analysis results to quantitatively evaluate the overall irregularity of aggregate particles within the area irradiated by the laser particle size analyzer. The beam density adjustment module adaptively adjusts the beam density of laser particle size analysis according to the overall irregularity of the aggregate particles in the laser irradiation area.

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