Dynamic monitoring and control method and system for the preparation process of ultra-high performance concrete

Abstract

This invention discloses a dynamic monitoring and adjustment method and system for the preparation process of ultra-high performance concrete, relating to the field of concrete preparation technology. The method includes the following steps: an image acquisition device and a laser particle size analyzer work together to capture images of the area where the laser beam illuminates the aggregate particles in real time. This invention, by introducing a combination of image acquisition and morphological analysis, accurately extracts the geometric shape features of the aggregate particles and quantifies their irregularity, thereby achieving adaptive adjustment of the beam density. This allows the laser particle size analyzer to adjust the beam density in real time according to the morphological complexity of the particles, ensuring accurate capture of the scattering signals from irregular particles. This significantly improves the particle size measurement accuracy of the laser particle size analyzer for aggregates with complex morphologies, enhancing the monitoring capability and reliability of particle size distribution. Especially when dealing with highly irregular particles, it effectively improves the accuracy and stability of the measurement.

Description

Technical Field

[0001] This invention relates to the field of concrete preparation technology, specifically to a method and system for dynamic monitoring and regulation of the preparation process of ultra-high performance concrete. Background Technology

[0002] Monitoring the preparation process of ultra-high performance concrete (UHPC) refers to the real-time collection and analysis of various key parameter data during the production of UHPC to ensure that the quality and performance of the concrete meet the expected requirements. This process typically involves precise control of the proportions of raw materials (such as cement, admixtures, and aggregates), 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 each stage of production, allowing for the timely detection and correction of potential problems, thereby ensuring that the final UHPC possesses excellent mechanical properties, durability, and workability.

[0003] In the preparation of ultra-high performance concrete, the particle size distribution of aggregates directly affects the flowability, density, and final mechanical properties of the concrete. Laser particle size analyzers, based on the principle of laser scattering, measure the particle size distribution of aggregates, and are particularly suitable for the analysis of fine particles, widely used in aggregate monitoring during concrete production. A proper blend of fine and coarse particles can effectively fill the voids between aggregates, increase the contact surface, improve the density of concrete, reduce porosity, and thus enhance its strength and durability. Precise control of aggregate particle size distribution can optimize the water-cement ratio, reduce the use of cement and water, and improve the workability and constructability of concrete. Furthermore, a good particle size distribution helps reduce shrinkage deformation and cracking in concrete, improving its long-term weather resistance. Therefore, accurate monitoring of particle size distribution not only ensures the stability of concrete performance but also effectively reduces costs, increases production efficiency, and optimizes the preparation process.

[0004] The existing technology has the following shortcomings:

[0005] In laser particle size analyzers, which measure the particle size distribution of aggregates using the principle of laser scattering, a fixed beam density is typically used to illuminate the aggregate sample. However, when the aggregate particles exhibit high irregularity in shape, the way they scatter the laser beam changes significantly. This is especially true for angular or flaky particles, whose larger surface areas cause variations in the angle and intensity of the scattered light, thus affecting the measurement results. With irregular particle shapes, the changes in scattering angle and intensity become more complex, rendering the traditional fixed beam density insufficient to ensure measurement accuracy.

[0006] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this invention is to provide a dynamic monitoring and adjustment method and system for the preparation process of ultra-high performance concrete. 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 achieving adaptive adjustment of the beam density. This allows the laser particle size analyzer to adjust the beam density in real time according to the morphological complexity of the particles, ensuring accurate capture of the scattering signals of irregular particles. This significantly improves the particle size measurement accuracy of the laser particle size analyzer for aggregate particles with complex morphologies, enhances the monitoring capability and reliability of particle size distribution, and effectively improves the accuracy and stability of measurements, especially when dealing with highly irregular particles, thus solving the problems mentioned in the background technology.

[0008] To achieve the above objectives, 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 works 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] The acquired images of the aggregate particle area irradiated by laser are preprocessed.

[0011] After image preprocessing, morphological analysis methods are used to extract the geometry of aggregate particles;

[0012] After obtaining the geometric shape characteristics of aggregate particles, the irregularity characteristics of aggregate particles reflecting their morphological complexity are extracted, and the extracted characteristics are analyzed in depth. Based on the analysis results, a quantifiable irregularity index is constructed to quantitatively evaluate the overall irregularity of aggregate particles in the laser particle size analyzer irradiation area.

[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, the geometric shape extraction of aggregate particles is typically achieved through the following morphological analysis steps:

[0015] Binarization is applied to convert grayscale images into black and white images in order to distinguish granular regions from background regions;

[0016] Perform an etching operation to separate the boundaries of the adhered particles, making the particle outline clearer;

[0017] An expansion treatment is performed to restore the area where the particle edges have excessively shrunk after corrosion, ensuring the integrity of the particles.

[0018] By using opening or closing operations, the particle outline is further smoothed, small holes or broken edges are filled, and a geometric shape with a complete structure and clear boundaries is extracted.

[0019] Preferably, the irregularity features of aggregate particles are extracted. The extracted features are the deviation of the actual fractal dimension of the aggregate particle outline from the theoretical smooth outline dimension. After in-depth analysis of the extracted features, a fractal dimension deviation reference value is generated. Based on the fractal dimension deviation reference value, a quantifiable irregularity index is constructed to quantitatively assess the overall irregularity of aggregate particles in the laser particle size analyzer irradiation area.

[0020] Preferably, the specific steps for generating a fractal dimension deviation reference value after performing 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 aggregate particle profiles is calculated using fractal dimension analysis methods. This process obtains the complexity of particle profiles through image analysis and uses advanced fractal analysis techniques such as the box-counting method or differential box-counting to measure the self-similarity and complexity of particle boundaries. The calculation formula is as follows: ,in: It uses a size of The number of boxes required to cover the particle boundary. It's the size of the box. It is the actual fractal dimension of the aggregate particle boundary;

[0022] Calculate the fractal dimension of a theoretically smooth contour (such as an ideal geometric shape like a circle or ellipse). For ideally smooth contours, such as a perfect circle or a regular ellipse, the fractal dimension is typically close to 2 (i.e., the maximum value). Theoretically, these contours have a low fractal dimension, indicating that their boundaries are simple and smooth. 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 generated fractal dimension deviation reference value is defined as: ,in: The fractal dimension corresponding to an ideal smooth contour (such as a circle) is typically 2. The fractal dimension deviates from the reference value, used to quantify the degree of irregularity in particle geometry. This is an adjustment coefficient used to control the magnitude of the deviation's impact on the fractal dimension's deviation from the reference value.

[0023] Preferably, the fractal dimension analysis method is either box counting or difference box counting.

[0024] Preferably, as can be seen from the fractal dimension deviation reference value, the larger the fractal dimension deviation reference value generated after in-depth analysis of the deviation of the actual fractal dimension of the aggregate particle outline from the theoretical smooth outline 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 scattering signals of irregularly shaped particles. The specific steps are as follows:

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

[0027] Based on the calculated regulatory factors In a laser particle size analyzer, the beam density is adaptively adjusted using the following formula: ,in: This is the adjusted beam density. It is the basic beam density. It is the adjustment coefficient, used to control the sensitivity of beam density adjustment.

[0028] The dynamic monitoring and adjustment system for the preparation process of ultra-high performance concrete 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 laser particle size analyzer to capture images of the area where the laser irradiates the aggregate particles in real time.

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

[0031] The morphological analysis module extracts the geometry of aggregate particles using morphological analysis methods after image preprocessing.

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

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

[0034] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0035] This invention introduces a technology combining image acquisition and morphological analysis to accurately extract the geometric shape features of aggregate particles and quantify their irregularity. This enables adaptive adjustment of the beam density, allowing the laser particle size analyzer to adjust the beam density in real time according to the morphological complexity of the particles. This ensures accurate capture of the scattering signals from irregular particles, significantly improving the particle size measurement accuracy of the laser particle size analyzer for complex-shaped aggregate particles. It also enhances the monitoring capability and reliability of particle size distribution, especially when dealing with highly irregular particles, effectively improving the accuracy and stability of the measurement. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0037] Figure 1 This is a flowchart of the method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process according to the present invention.

[0038] Figure 2 This is a schematic diagram of the module of the dynamic monitoring and adjustment system for the preparation process of ultra-high performance concrete of the present invention. Detailed Implementation

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

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

[0041] The image acquisition device (such as a high-resolution camera or microscope camera) works in conjunction with the laser particle size analyzer to capture images of the area where the laser shines on 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. These images provide crucial visual data for subsequent analysis. The image acquisition device must possess sufficient resolution and sharpness to capture detailed particle surface morphology information, ensuring the accuracy of subsequent feature extraction. Furthermore, synchronization between image acquisition and laser analysis is critical; it ensures precise alignment between the laser-illuminated area and the acquired image area, thereby providing consistent data support for particle size analysis.

[0043] After acquiring 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 interference factors, thus requiring image preprocessing. This includes noise reduction, contrast enhancement, lighting adjustment, and edge detection. Common image processing methods include median filtering, Gaussian blurring, and histogram equalization. The purpose of image preprocessing is to improve image quality, preparing it for subsequent particle shape recognition and irregularity feature extraction. Removing noise and irrelevant background information helps to accurately identify the edges and shapes of aggregate particles, improving the accuracy of particle morphology analysis. By enhancing the image's contrast and brightness balance, the outlines and details of aggregate particles can be seen more clearly, ensuring the reliability of feature extraction.

[0045] After image preprocessing, morphological analysis methods (such as dilation, erosion, opening, closing, etc.) are used to extract the geometry of aggregate particles;

[0046] After image preprocessing, the geometric shape extraction of aggregate particles is typically achieved through the following four morphological analysis steps: First, binarization is applied to convert the grayscale image into a black and white image to distinguish the particle area from the background area; second, erosion is performed to separate the boundaries of adhered particles, making the particle outline clearer; next, dilation is performed to restore areas where the particle edges may have shrunk excessively after erosion, ensuring the integrity of the particles; finally, opening operations (dilation after erosion) or closing operations (erosion after dilation) are used to further smooth the particle outline, fill small holes or fracture edges, thereby extracting a geometric shape with a complete structure and clear boundaries, providing an accurate morphological basis for subsequent irregularity analysis.

[0047] These morphological operations effectively identify particle edges and contours, and further analyze their shape characteristics (such as aspect ratio, surface area, and edge complexity). The role of morphological analysis is to extract the geometric shape features of aggregate particles from images, which is crucial for subsequent irregularity analysis and particle size measurement. This step provides basic shape information about the particles, such as whether they are regular spheres or irregular angular or flaky particles. This step provides clear geometric data support for further analysis of particle irregularity.

[0048] After obtaining the geometric shape characteristics of aggregate particles, the irregularity characteristics of aggregate particles reflecting their morphological complexity are extracted, and the extracted characteristics are analyzed in depth. Based on the analysis results, a quantifiable irregularity index is constructed to quantitatively evaluate the overall irregularity of aggregate particles in the laser particle size analyzer irradiation area.

[0049] The irregularity features of aggregate particles are extracted. The extracted features are the deviation of the actual fractal dimension of the aggregate particle outline from the theoretical smooth outline dimension. After in-depth analysis of the extracted features, 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 aggregate particles in the laser particle size analyzer irradiation area.

[0050] The deviation of the actual fractal dimension of a particle profile from the theoretical smooth profile dimension refers to the difference between the complexity of the particle boundary calculated using fractal geometry methods in the actual image and the fractal dimension of an ideal, smooth, and regular profile. Theoretically smooth profiles (such as perfect circles) typically have a low fractal dimension, representing simple structures and flat boundaries; however, actual aggregate particles, formed through natural crushing or processing, often have numerous bumps, protrusions, and multi-level nested structures at their boundaries, resulting in a higher fractal dimension. By comparing the difference in dimensions, the geometric complexity of the particle boundary can be quantified. A larger deviation indicates a more irregular and complex particle boundary, making it one of the sensitive indicators for measuring the degree of irregularity in particle morphology.

[0051] The greater the deviation of the actual fractal dimension of aggregate particle profile from the theoretical smooth profile dimension, the higher the degree of geometric irregularity of the aggregate particle. This is because fractal dimension is a measure of boundary complexity. An ideal smooth profile (such as a circle or ellipse) has a low fractal dimension, indicating a regular shape and smooth boundaries. However, due to natural breakage, friction, or external forces, the boundaries of actual aggregate particles often exhibit many irregular broken lines, depressions, or protrusions, making the boundaries more complex and tortuous, thus increasing the fractal dimension. Therefore, the greater the deviation of the fractal dimension, the more irregular and complex the shape of the aggregate particle, with more details and structural irregularities. This deviation accurately reflects the degree of irregularity in particle geometry and is a very important indicator in particle morphology analysis.

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

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

[0054] This step assesses the complexity of the particle profile using fractal dimensions. A higher actual fractal dimension... This indicates complex particle boundaries and irregular shapes; and a low actual fractal dimension. This indicates that the particle outline is relatively smooth and the shape is regular.

[0055] Next, the fractal dimension of the theoretically smooth contour (such as an ideal geometric shape like a circle or ellipse) is calculated. For ideally smooth contours, such as a perfect circle or a regular ellipse, the fractal dimension is typically close to 2 (i.e., the maximum value). Theoretically, these contours have a low fractal dimension, indicating that their boundaries are simple and smooth. 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 generated fractal dimension deviation reference value is defined as: ,in: The fractal dimension corresponding to an ideal smooth contour (such as a circle) is typically 2. The fractal dimension deviates from the reference value, used to quantify the degree of irregularity in particle geometry. This is an adjustment coefficient used to control the magnitude of the deviation's impact on the fractal dimension's deviation from the reference value;

[0056] This step involves calculating the fractal dimension deviation from the reference value. This quantifies the complexity of 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 the value, the more regular the particle shape.

[0057] As can be seen from the fractal dimension deviation from the reference value, the larger the deviation of the actual fractal dimension of the aggregate particle profile from the theoretical smooth profile dimension, the higher the degree of geometric irregularity of the aggregate particle, and vice versa. This is because the fractal dimension is an indicator used to measure the complexity of particle boundaries. The larger the actual fractal dimension of the particle, the stronger the tortuosity and irregularity of the particle boundary. The theoretical smooth profile (such as a circle or ellipse) has a lower fractal dimension, indicating a simpler and more regular boundary. By calculating the deviation between the actual and theoretical fractal dimensions, the larger the deviation from the reference value, the greater the difference between the particle boundary and the ideal regular shape, and the more complex and irregular the shape. Therefore, a high deviation from the reference value indicates a more irregular particle geometry, while a low deviation indicates that the shape is closer to a regular geometry.

[0058] The laser particle size analyzer adaptively adjusts the beam density of the laser particle size analyzer according to the overall irregularity of the aggregate particles in the laser irradiation area, enabling the laser particle size analyzer to more accurately capture the scattering signals of irregularly shaped particles and improve the monitoring accuracy of particle size distribution.

[0059] The laser particle size analyzer adaptively adjusts the beam density based on the overall irregularity of the aggregate particles in the laser irradiation area, enabling it 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 fractal dimension deviation of aggregate particles within the laser irradiation area from the reference value. This fractal dimension deviation reflects the complexity of the particle boundary, i.e., the deviation between the actual fractal dimension and the theoretical smooth contour dimension. Based on this fractal dimension deviation reference value, the control factor related to particle irregularity is calculated. The expression for the calculation is as follows: ,in: It is a control factor used to control the adjustment range of beam density. and It is a constant coefficient, a constant. Used to control the scale of regulatory factors This is used to adjust the degree of influence of fractal dimension on the control factor. Specifically, as the fractal dimension deviates from the reference value... Increase, regulatory factors The increase indicates a higher degree of particle irregularity, requiring an increase in beam density to more accurately capture the scattered signal;

[0061] The purpose of this step is to quantify the irregularity of the particles and convert it into adjustment parameters, or regulatory factors. This indicates the degree of necessity for adaptively adjusting the beam density of the laser particle size analyzer. This control factor ensures that the instrument can appropriately increase the laser intensity when dealing with complex and irregular particles, thereby improving the recognition accuracy of the scattered signal.

[0062] Based on the calculated regulatory factors In a laser particle size analyzer, the beam density is adaptively adjusted using the following formula: ,in: This is the adjusted beam density. It is the basic beam density. This is the adjustment coefficient, used to control the sensitivity of beam density adjustment. Optimization is typically performed based on experimental data to ensure that the beam density adjustment does not deviate excessively from the original value. (Regulation factor) A larger beam size indicates a more irregular particle shape. The system will increase the beam density to ensure that enough scattered light is captured, thereby improving the accuracy of particle size distribution measurement.

[0063] This step automatically adjusts the beam density of the laser particle size analyzer based on the irregularity of the particles. By adjusting the beam density, the instrument can more accurately capture the scattered signals from irregularly shaped particles, thereby improving the monitoring accuracy of particle size distribution. Adjusting the beam density allows the measurement process to adapt to different particle shapes, especially when the particles have complex shapes, enhancing the accuracy and robustness of the measurement.

[0064] By adaptively adjusting the beam density of the laser particle size analyzer according to the irregularity of aggregate particles, the analyzer can accurately capture the scattering signals of particles with different shapes, thereby improving the monitoring accuracy of particle size distribution. In actual measurement, aggregate particles may exhibit varying degrees of complexity. More regular particles (such as spheres and rounds) have simple, smooth boundaries, resulting in more uniform scattered light when the laser beam illuminates them, making it easier for the laser particle size analyzer to measure their particle size distribution. However, for irregularly shaped particles with complex boundaries (such as angular, flaky, or fragmented particles), the intensity and angle of the scattered light change significantly due to their complex edges and irregular morphology. This means that the conventional beam density of the laser particle size analyzer may be insufficient to capture all the information from the scattered light, thus affecting the accuracy and precision of particle size measurement.

[0065] To overcome this problem, the laser particle size analyzer introduces an adaptive beam density adjustment mechanism based on particle irregularity, enabling dynamic adjustment of the beam density. First, the system calculates the overall irregularity of the aggregate particles based on their geometric characteristics. For example, if the particle shape is complex and the edges exhibit high irregularity (such as depressions or protrusions), the system identifies the high irregularity and automatically increases the beam density. By increasing the beam density, the instrument enhances its sensitivity to the scattered light from complex particles, ensuring the capture of more scattered signals and improving the monitoring accuracy of particle size distribution for complex shapes.

[0066] Conversely, when the particle shape is relatively regular, the system detects lower particle irregularity and appropriately reduces the beam density. Reducing the beam density aims to avoid generating excessively strong scattered light signals on regular particles, as this excessive light intensity could lead to measurement oversaturation and affect accuracy. Through this adjustment, the laser particle size analyzer can maintain optimal sensitivity and avoid unnecessary measurement errors.

[0067] This step serves several key purposes: First, it adjusts the laser particle size analyzer's beam density in real time based on particle shape, ensuring appropriate light intensity for both regular and irregular particles, thus guaranteeing accurate particle size distribution measurement. Second, by increasing or decreasing the beam density, the system dynamically adapts to the scattering characteristics of different particles, reducing measurement errors caused by beam intensity mismatch. Furthermore, this adaptive adjustment effectively improves the analyzer's response to complex particle shapes, particularly in measuring highly irregular particles (such as crushed stone and broken materials), significantly enhancing the accuracy and stability of particle size measurements. Finally, through precise beam density control, this step effectively avoids excessive reflection or oversaturation measurements, reducing potential errors and deviations during measurement, thereby improving the applicability and reliability of the laser particle size analyzer in practical applications.

[0068] The above solution effectively addresses the problem of inaccurate measurements caused by fixed beam density in laser particle size analyzers when dealing with irregularly shaped aggregate particles. Specifically, the solution combines image acquisition with morphological analysis to accurately extract the geometric features of aggregate particles and quantify their irregularity, thereby enabling adaptive adjustment of the beam density. This dynamic beam density adjustment allows the laser particle size analyzer to adjust the beam density in real time according to the morphological complexity of the particles, ensuring accurate capture of the scattering signals from irregular particles. This solution significantly improves the particle size measurement accuracy of laser particle size analyzers for complex-shaped aggregate particles, enhances the monitoring capability and reliability of particle size distribution, and effectively improves measurement accuracy and stability, especially when dealing with highly irregular particles.

[0069] This invention provides, for example Figure 2 The ultra-high performance concrete preparation process dynamic monitoring and adjustment system 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 laser particle size analyzer to capture images of the area where the laser irradiates the aggregate particles in real time.

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

[0072] The morphological analysis module extracts the geometry of aggregate particles using morphological analysis methods after image preprocessing.

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

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

[0075] The method for dynamic monitoring and regulation of the ultra-high performance concrete preparation process provided in this embodiment of the invention is implemented through the above-mentioned dynamic monitoring and regulation system for the ultra-high performance concrete preparation process. For details of the specific methods and procedures of the dynamic monitoring and regulation system for the ultra-high performance concrete preparation process, please refer to the embodiment of the method for dynamic monitoring and regulation of the ultra-high performance concrete preparation process, which will not be repeated here.

[0076] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0077] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0078] Those skilled in the art will recognize that the units and algorithm steps of the various examples 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 implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art 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 understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing 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 illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0081] The units described as separate components may or may not be physically separate. 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 the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0082] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0083] If the aforementioned functions are implemented as 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 this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

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

Claims

1. A method for dynamic monitoring and adjustment of the preparation process of ultra-high performance concrete, characterized in that, Includes the following steps: The image acquisition device works in conjunction with the laser particle size analyzer to capture images of the area where the laser irradiates the aggregate particles in real time. The acquired images of the aggregate particle area irradiated by laser are preprocessed. After image preprocessing, morphological analysis methods are used to extract the geometry of aggregate particles; After obtaining the geometric shape characteristics of aggregate particles, the irregularity characteristics of aggregate particles reflecting their morphological complexity are extracted, and the extracted characteristics are analyzed in depth. Based on the analysis results, a quantifiable irregularity index is constructed to quantitatively evaluate the overall irregularity of aggregate particles in the laser particle size analyzer irradiation area. 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. The irregularity features of aggregate particles are extracted. The extracted features are the deviation of the actual fractal dimension of the aggregate particle outline from the theoretical smooth outline dimension. After in-depth analysis of the extracted features, 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 aggregate particles in the laser particle size analyzer irradiation area. The specific steps for generating a fractal dimension deviation reference value after performing in-depth analysis on the deviation of the actual fractal dimension of aggregate particle profile from the theoretical smooth profile dimension are as follows: The actual fractal dimension of aggregate particle profiles is calculated using fractal dimension analysis. The calculation expression is as follows: ,in: It uses a size of The number of boxes required to cover the particle boundary. It's the size of the box. It is the actual fractal dimension of the aggregate particle boundary; The fractal dimension of the ideal shape is obtained through theoretical analysis. The deviation of the fractal dimension from the reference value is calculated by the deviation between the actual fractal dimension and the theoretical smooth contour dimension. The expression for the calculation is as follows: ,in: The fractal dimension corresponding to the ideal smooth contour is 2. The fractal dimension deviates from the reference value, used to quantify the degree of irregularity in particle geometry. This is an adjustment coefficient used to control the magnitude of the deviation's impact on the fractal dimension's deviation from the reference value.

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, the geometric shape of aggregate particles is extracted through the following morphological analysis steps: Binarization is applied to convert grayscale images into black and white images in order to distinguish granular regions from background regions; Perform an etching operation to separate the boundaries of the adhered particles, making the particle outline clearer; An expansion treatment is performed to restore the area where the particle edges have excessively shrunk after corrosion, ensuring the integrity of the particles. By using opening or closing operations, the particle outline is further smoothed, small holes or broken edges are filled, and a geometric shape with a complete structure and clear boundaries is extracted.

3. The method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process according to claim 1, characterized in that, The fractal dimension analysis method should be either box counting or difference box counting.

4. The method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process according to claim 1, characterized in that, As can be seen from the deviation of the fractal dimension from the reference value, the larger the deviation of the actual fractal dimension of the aggregate particle profile from the theoretical smooth profile dimension after in-depth analysis, the higher the degree of geometric irregularity of the aggregate particle, and vice versa.

5. The method for dynamic monitoring and adjustment of the ultra-high performance concrete preparation process according to claim 1, characterized in that, The laser particle size analyzer adaptively adjusts the beam density based on the overall irregularity of the aggregate particles in the laser irradiation area, enabling it 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 aggregate particles within the laser irradiation area from the reference value. The expression for the calculation is as follows: ,in: It is a control factor used to control the adjustment range of beam density. and It is a constant coefficient, a constant coefficient Used to control the scale of the regulatory factor, constant coefficient Used to adjust the degree of influence of fractal dimension on regulatory factors; Based on the calculated regulatory factors In a laser particle size analyzer, the beam density is adaptively adjusted using the following formula: ,in: This is the adjusted beam density. It is the basic beam density. It is the adjustment coefficient, used to control the sensitivity of beam density adjustment.

6. A dynamic monitoring and control system for the preparation process of ultra-high performance concrete, used to implement the dynamic monitoring and control method for the preparation process of ultra-high performance concrete as described in any one of claims 1-5, characterized in that, It includes an image acquisition module, an image preprocessing module, a morphological analysis module, an irregularity feature extraction module, and a beam density adjustment module; The image acquisition module works in conjunction with the laser particle size analyzer to capture images of the area where the laser irradiates the aggregate particles in real time. The image preprocessing module preprocesses the acquired image of the aggregate particle area irradiated by the laser. The morphological analysis module extracts the geometry of aggregate particles using morphological analysis methods after image preprocessing. The irregularity feature extraction module extracts irregularity features of aggregate particles that reflect their morphological complexity after obtaining the geometric shape features of the aggregate particles. It then performs in-depth analysis on the extracted features and constructs a quantifiable irregularity index based on the analysis results to quantitatively assess the overall irregularity of aggregate particles within the laser particle size analyzer irradiation area. The beam density adjustment module adaptively adjusts the beam density of the laser particle size analysis based on the overall irregularity of the aggregate particles in the laser irradiation area.

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