Method, device, equipment, medium and program product for monitoring sand and gravel particle size distribution

Abstract

This invention relates to the field of sand and gravel processing simulation technology, and discloses a method, device, equipment, medium, and program product for monitoring sand and gravel particle size distribution. The method for monitoring sand and gravel particle size distribution includes: obtaining the initial particle size distribution curve of the sand and gravel to be processed; dividing the particle size of the sand and gravel to be processed according to the monitoring of the initial particle size distribution curve and the discharge port size information to obtain multiple particle size regions; performing sand and gravel crushing simulation on the sand and gravel to be processed in each monitoring particle size region to obtain the target particle size distribution curve; performing screening simulation on the monitoring target sand and gravel according to the monitoring target particle size distribution curve and the sieve aperture information to obtain the screening particle size distribution; and constructing a standardized log based on the monitoring of the initial particle size distribution curve, the monitoring target particle size distribution curve, and the monitoring screening particle size distribution to monitor the sand and gravel particle size distribution. This invention achieves accurate monitoring of sand and gravel particle size distribution by analyzing the particle size distribution at different stages of sand and gravel processing simulation.

Description

Technical Field

[0001] This invention relates to the field of sand and gravel processing simulation technology, specifically to methods, devices, equipment, media, and program products for monitoring the particle size distribution of sand and gravel. Background Technology

[0002] The particle size distribution of sand and gravel aggregates is a core indicator for evaluating the quality of sand and gravel products. In sand and gravel processing lines, the particle size distribution of raw materials continuously changes after crushing and screening, ultimately forming finished aggregates that meet the requirements of different applications. Accurate modeling and full-process monitoring of particle size distribution are the core of production line simulation technology, and monitoring its evolution throughout the entire process is crucial for the quality control of sand and gravel products.

[0003] The production-level modeling method based on empirical formulas in related technologies does not track the details of particle size distribution. It only calculates the processing capacity of each sand and gravel processing equipment and uses empirical crushing ratio coefficients to estimate the total output distribution. It cannot track the details of particle size distribution and is difficult to accurately reflect the changing law of sand and gravel particle size distribution during the production process. Summary of the Invention

[0004] This invention provides a method, device, equipment, medium, and program product for monitoring the particle size distribution of sand and gravel, in order to solve the problem that production-level modeling methods based on empirical formulas in related technologies are difficult to accurately reflect the changing patterns of sand and gravel particle size distribution during the production process.

[0005] In a first aspect, the present invention provides a method for monitoring the particle size distribution of sand and gravel, comprising: acquiring an initial particle size distribution curve of the sand and gravel to be processed; dividing the particle size of the sand and gravel to be processed into multiple particle size regions based on the initial particle size distribution curve and the discharge port size information; performing sand and gravel crushing simulation on the sand and gravel to be processed in each particle size region to obtain a target particle size distribution curve corresponding to the target sand and gravel; performing sieving simulation on the target sand and gravel based on the target particle size distribution curve and the sieve aperture information to obtain the sieved particle size distribution; and constructing a standardized log based on the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution to monitor the particle size distribution of sand and gravel.

[0006] The sand and gravel particle size distribution monitoring method of the present invention obtains the initial particle size distribution curve of the sand and gravel to be processed and completes particle size classification by combining it with the discharge port size information of the crushing equipment. This enables precise matching between the initial particle size characteristics of the sand and gravel raw materials and the equipment discharge conditions, providing standardized and refined basic particle size units for subsequent crushing and screening simulation stages. The present invention performs sand and gravel crushing simulation on the sand and gravel to be processed in each particle size region to obtain the target particle size distribution curve corresponding to the target sand and gravel. This accurately reconstructs the particle size change law of sand and gravel with different initial particle sizes after crushing and accurately predicts the particle size distribution of the crushed sand and gravel. This invention simulates the screening of target sand and gravel based on the target particle size distribution curve and sieve aperture information to obtain the screened particle size distribution. It accurately simulates the actual particle size distribution of sand and gravel after screening, allowing for early prediction of the particle size state after screening. Based on the initial particle size distribution curve, the target particle size distribution curve, and the screened particle size distribution, this invention constructs a standardized log for monitoring the particle size distribution of sand and gravel. By integrating particle size distribution data from the initial raw material stage, after crushing, and after screening, the standardized log can completely retain particle size change data throughout the entire sand and gravel processing process, achieving traceable and quantifiable recording of particle size distribution changes. Compared with related technologies, this invention, based on a standardized log, enables long-term and accurate monitoring of sand and gravel particle size distribution, improving the precision of particle size control in sand and gravel processing.

[0007] In one optional implementation, an initial particle size distribution curve of the sand to be processed is obtained. Based on the initial particle size distribution curve and the discharge port size information, the particle size of the sand to be processed is divided to obtain multiple particle size regions, including: setting a standard sieve aperture sequence; determining the initial particle size distribution curve based on the mass proportion of the sand to be processed in different particle size intervals in the standard sieve aperture sequence; the standard sieve aperture sequence is a sequence of sieve apertures generated according to different particle size intervals in order of particle size; comparing the particle size of the sand to be processed corresponding to the initial particle size distribution curve with the discharge port size information; when the particle size of the sand to be processed is greater than the discharge port size information, the sand to be processed is divided into a first particle size region; when the particle size of the sand to be processed is less than or equal to the discharge port size information, the sand to be processed is divided into a second particle size region; the sand particle size in the first particle size region is greater than the sand particle size in the second particle size region.

[0008] In one optional implementation, a sand and gravel crushing simulation is performed on the sand and gravel to be processed in each particle size region to obtain the target particle size distribution curve corresponding to the target sand and gravel. This includes: performing a sand and gravel crushing simulation on the sand and gravel to be processed in the first particle size region, and obtaining a first particle size distribution curve based on the mass proportion of the target sand and gravel after the sand and gravel crushing simulation in different particle size intervals in the standard sieve sequence; obtaining a second particle size distribution curve based on the mass proportion of the sand and gravel to be processed in the second particle size region in different particle size intervals in the standard sieve sequence; and performing a weighted summation of the first particle size distribution curve and the second particle size distribution curve to obtain the target particle size distribution curve.

[0009] In one optional implementation, the target sand and gravel are screened using a sieving simulation based on the target particle size distribution curve and the sieve aperture information to obtain the sieved particle size distribution. This includes: comparing the particle size of the target sand and gravel corresponding to the target particle size distribution curve with the sieve aperture information; performing multi-level sieving simulation on the target sand and gravel based on the comparison results to obtain sieving results; determining the oversize particle size distribution and the oversize particle size distribution corresponding to each sieve level based on the target sand and gravel mass proportion in each sieve level in the sieving results; and obtaining the sieved particle size distribution based on the oversize particle size distribution and the oversize particle size distribution.

[0010] In one optional implementation, a standardized log is constructed based on the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution, including: assigning a corresponding batch number to the sand and gravel to be processed; associating the batch number with the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution to obtain the association result; and storing the association result, the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution to obtain the standardized log.

[0011] In one optional embodiment, the method for monitoring the particle size distribution of sand and gravel further includes: mapping the finished sand and gravel products according to the particle size distribution and the finished product quality corresponding to the particle size interval labels to obtain a mapping table; performing node-level material balance analysis, overall quality balance analysis, particle size change trajectory analysis, time distribution analysis of each particle size product, and post-event quantitative analysis of cyclic load on the sand and gravel processing simulation process based on the standardized log and the mapping table to obtain analysis results, so as to evaluate the sand and gravel processing simulation process based on the analysis results.

[0012] This invention maps the finished sand and gravel products to particle size distribution according to particle size range labels and the corresponding finished product quality, resulting in a mapping table. This enables precise correlation between products and quality indicators for different particle size ranges of sand and gravel, clearly defining the quality standards corresponding to each particle size range. Based on standardized logs and the mapping table, this invention performs node-level material balance analysis, overall quality balance analysis, particle size change trajectory analysis, time distribution analysis of products at each particle size range, and post-processing quantitative analysis of cyclic loads during the sand and gravel processing simulation. The resulting analysis provides an objective and scientific evaluation of the rationality of the entire sand and gravel crushing and screening process, the adaptability of equipment operation, and the stability of production quality.

[0013] Secondly, the present invention provides a monitoring device for sand and gravel particle size distribution, comprising: a particle size division module, used to acquire the initial particle size distribution curve of the sand and gravel to be processed, and to divide the particle size of the sand and gravel to be processed into multiple particle size regions based on the initial particle size distribution curve and the discharge port size information; a sand and gravel crushing simulation module, used to perform sand and gravel crushing simulation on the sand and gravel to be processed in each particle size region to obtain the target particle size distribution curve corresponding to the target sand and gravel; a sand and gravel screening simulation module, used to perform screening simulation on the target sand and gravel based on the target particle size distribution curve and the screen aperture information to obtain the screening particle size distribution; and a particle size monitoring module, used to construct a standardized log based on the initial particle size distribution curve, the target particle size distribution curve, and the screening particle size distribution to monitor the sand and gravel particle size distribution.

[0014] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the sand and gravel particle size distribution monitoring method of the first aspect or any corresponding embodiment described above.

[0015] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the method for monitoring the particle size distribution of sand and gravel described in the first aspect or any corresponding embodiment thereof.

[0016] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the method for monitoring the particle size distribution of sand and gravel described in the first aspect or any corresponding embodiment. Attached Figure Description

[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the first process of a method for monitoring the particle size distribution of sand and gravel according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the second process of a method for monitoring the particle size distribution of sand and gravel according to an embodiment of the present invention; Figure 4This is a schematic diagram of the third process of the method for monitoring the particle size distribution of sand and gravel according to an embodiment of the present invention; Figure 5 This is a structural block diagram of a sand and gravel particle size distribution monitoring device according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0021] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0022] As an optional application scenario of this invention, such as Figure 1 As shown, the sand and gravel particle size distribution monitoring system may include at least one terminal device and at least one server. Figure 1 The system is illustrated in the example, which includes a computer 101, a mobile terminal 102, and a server 103, and the terminal devices such as the computer 101 and the mobile terminal 102 are connected to the server 103 through a network 110.

[0023] The terminal device can specifically be a smartphone, tablet, laptop, PDA, desktop computer, game console, smart TV, smart wearable device, in-vehicle terminal, VR (Virtual Reality) device, AR (Augmented Reality) device, etc. Server 103 can be a standalone physical server, a server cluster, a distributed system, or a cloud server providing cloud services. Network 110 can be a wired or wireless network, examples of which include, but are not limited to, the Internet, corporate intranet, local area network, wide area network, mobile communication network, and combinations thereof.

[0024] This invention provides a method for monitoring the particle size distribution of sand and gravel. By analyzing the particle size distribution at different stages of sand and gravel processing simulation, the method achieves accurate monitoring of the particle size distribution of sand and gravel.

[0025] According to an embodiment of the present invention, a method for monitoring the particle size distribution of sand and gravel is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0026] This embodiment provides a method for monitoring the particle size distribution of sand and gravel, which can be used with computer equipment. Figure 2 This is a first flowchart of a method for monitoring the particle size distribution of sand and gravel according to an embodiment of the present invention, as shown below. Figure 2 As shown, the process includes the following steps: Step S201: Obtain the initial particle size distribution curve of the sand and gravel to be processed. Based on the initial particle size distribution curve and the discharge port size information, divide the particle size of the sand and gravel to be processed to obtain multiple particle size regions.

[0027] Among them, the sand and gravel to be processed is the raw sand and gravel raw material that has not yet undergone crushing and screening; the initial particle size distribution curve represents the continuous change curve of the proportion of different particle sizes of the sand and gravel to be processed; the discharge port size information is the specification parameter of the opening width of the discharge port of the sand and gravel crushing equipment; multiple particle size regions can include coarse particle size region and fine particle size region. The coarse particle size region is the particle size region of the sand and gravel to be processed that is larger than the discharge port size information, and the fine particle size region is the particle size region of the sand and gravel to be processed that is smaller than or equal to the discharge port size information.

[0028] In some alternative implementations, the particle size data of the sand and gravel to be processed can be collected by a laser particle size analyzer and fitted to generate an initial particle size distribution curve. Alternatively, the initial particle size distribution curve of the sand and gravel to be processed can be obtained by a sand and gravel processing system. Or, the material can be passed through a series of standard sieves with decreasing apertures in sequence, and the mass of the material retained on each sieve can be weighed to obtain the initial particle size distribution curve.

[0029] Step S202: Perform sand and gravel crushing simulation for the sand and gravel to be processed in each particle size region to obtain the target particle size distribution curve corresponding to the target sand and gravel.

[0030] Among them, the target sand and gravel are the sand and gravel obtained after crushing simulation; the target particle size distribution curve represents the distribution curve of the proportion of different particle sizes of the crushed sand and gravel.

[0031] In some optional implementations, the crushing simulation of the sand and gravel to be processed in each particle size region is performed based on simulation software or a pre-trained sand and gravel processing simulation model. The crushing size of the sand and gravel to be processed in each particle size region is different. Therefore, the crushing simulation of the sand and gravel to be processed in each particle size region is performed separately to obtain the target particle size distribution curve corresponding to the target sand and gravel.

[0032] Step S203: Based on the target particle size distribution curve and sieve aperture information, perform a sieve simulation on the target sand and gravel to obtain the sieve particle size distribution.

[0033] Among them, the sieve aperture information is the diameter specification parameter of the sieve mesh; the sieve particle size distribution is the percentage data of each particle size after sand and gravel are screened by the sieve.

[0034] In some alternative implementations, the target sand and gravel are screened using simulation software or a pre-trained sand and gravel processing simulation model. The screening can be performed using a single-layer screen or multiple-layer screens.

[0035] Step S204: Based on the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution, a standardized log is constructed to monitor the particle size distribution of sand and gravel.

[0036] Among them, the standardized log is a log of particle size data for the entire sand and gravel process, recorded in a unified format and in a standardized manner.

[0037] In some optional implementations, the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution are entered into a database in a unified format according to timestamps, particle size, and the mass percentage of each particle size, generating a standardized electronic log. By retrieving the log data, the particle size distribution changes of sand and gravel throughout the entire process from raw materials to finished products can be monitored in real time.

[0038] The sand and gravel particle size distribution monitoring method provided in this embodiment obtains the initial particle size distribution curve of the sand and gravel to be processed and completes particle size classification by combining it with the discharge port size information of the crushing equipment. This enables precise matching between the initial particle size characteristics of the sand and gravel raw materials and the equipment discharge conditions, providing standardized and refined basic particle size units for subsequent crushing and screening simulation stages. This embodiment of the invention performs sand and gravel crushing simulation on the sand and gravel to be processed in each particle size region to obtain the target particle size distribution curve corresponding to the target sand and gravel. This accurately reconstructs the particle size change law of sand and gravel with different initial particle sizes after crushing and accurately predicts the particle size distribution of the crushed sand and gravel. This invention simulates the screening of target sand and gravel based on the target particle size distribution curve and sieve aperture information to obtain the screened particle size distribution. This accurately simulates the actual particle size distribution of the sand and gravel after screening, allowing for early prediction of the particle size state after screening. Based on the initial particle size distribution curve, the target particle size distribution curve, and the screened particle size distribution, this invention constructs a standardized log for monitoring the particle size distribution of sand and gravel. By integrating particle size distribution data from the initial raw material stage, after crushing, and after screening, this standardized log can completely retain particle size change data throughout the entire sand and gravel processing process, enabling traceable and quantifiable recording of particle size distribution changes. Compared with related technologies, this invention, based on a standardized log, enables long-term and accurate monitoring of sand and gravel particle size distribution, improving the particle size control accuracy in sand and gravel processing.

[0039] This embodiment provides a method for monitoring the particle size distribution of sand and gravel, which can be used with computer equipment. Figure 3 This is a second flowchart of a method for monitoring the particle size distribution of sand and gravel according to an embodiment of the present invention, as shown below. Figure 2 As shown, the process includes the following steps: Step S301: Obtain the initial particle size distribution curve of the sand and gravel to be processed. Based on the initial particle size distribution curve and the discharge port size information, divide the particle size of the sand and gravel to be processed to obtain multiple particle size regions.

[0040] Specifically, step S301 includes: Step S3011: Set a standard sieve aperture sequence. Determine the initial particle size distribution curve based on the mass proportion of the sand and gravel to be processed in different particle size ranges in the standard sieve aperture sequence. The standard sieve aperture sequence is a sequence of sieve apertures generated according to the particle size order of different particle size ranges.

[0041] The standard sieve aperture sequence is a series of standard sieve meshes with decreasing aperture sizes, which are a set of fixed size values ​​that decrease in a specific ratio, such as 150mm, 120mm, 100mm, 80mm, 60mm, 40mm, 20mm, 10mm, 5mm, 2.36mm, etc. In this embodiment of the invention, a discretized representation of the particle size distribution curve is established based on the standard sieve aperture size sequence as a mathematical representation of the particle size distribution. The advantage is that any two particle size distribution curves are established on the same particle size scale, and element-wise weighted calculations can be performed directly, such as weighted averages by mass ratio. There is no need to interpolate and align between different sieve aperture systems, eliminating the alignment error introduced by interpolation during the calculation of material mixing, crushing, screening and other processes.

[0042] In some alternative implementations, the standard sieve aperture sequence can be represented as:

[0043] in, For standard sieve aperture sequence, For the first The aperture of the sieve. This represents the total number of sieve holes.

[0044] In some alternative implementations, a particle size range is formed between two adjacent sieve apertures, for example, This represents a particle size range, with the upper and lower boundaries determined by the sizes of two adjacent sieve openings. The standard sieve opening sequence is divided into [number] ranges. A range of particle sizes.

[0045] In some alternative implementations, the continuous particle size distribution is discretized into a mass allocation over a finite number of intervals, defined as an array of the percentage of material mass retained in each particle size interval, which can be represented as:

[0046] in, Reserve an array of material mass percentages for each particle size range. For the first The percentage of material mass in each particle size range relative to the total mass.

[0047] In some optional implementations, the array of material mass percentages for each particle size range is curve-processed to obtain an initial particle size distribution curve.

[0048] Step S3012: Compare the particle size of the sand and gravel to be processed corresponding to the initial particle size distribution curve with the discharge port size information. When the particle size of the sand and gravel to be processed is greater than the discharge port size information, the sand and gravel to be processed is divided into the first particle size region. When the particle size of the sand and gravel to be processed is less than or equal to the discharge port size information, the sand and gravel to be processed is divided into the second particle size region.

[0049] In this design, the particle size of the sand and gravel in the first particle size distribution is larger than that in the second particle size distribution. The first particle size distribution is the coarse particle size distribution, and the second particle size distribution is the fine particle size distribution. The particle size in the first particle size distribution is larger than the width of the discharge port of the crushing equipment. These particles exceed the discharge port gap and are repeatedly crushed within the crushing chamber until their size is reduced to a size that can pass through the discharge port. Therefore, the particle size distribution of the material in the coarse particle size distribution undergoes a fundamental change after crushing, resulting in a new particle size distribution curve. This new distribution can be described, for example, using the Rosin-Rammler distribution model. The particle size in the second particle size distribution is smaller than the width of the discharge port of the crushing equipment. These particles are smaller than the discharge port gap and can pass directly through the discharge port without being crushed. Therefore, the percentage of retained material in the fine particle size distribution remains unchanged and is directly retained in the output gradation.

[0050] In some optional implementations, the array of retained material mass percentages for each particle size interval corresponding to the initial particle size distribution curve is traversed. If the minimum value of the particle size interval is greater than the discharge port size information, the retained material mass percentage of that particle size interval is added to the coarse particle region mass percentage. If the maximum value of the particle size range is less than or equal to the discharge port size, then the percentage of retained material in that particle size range is added to the percentage of fine particle size. For particle size ranges where the minimum particle size is less than the discharge port size and the maximum particle size is greater than or equal to the discharge port size, the mass of the retained material of that particle size is divided into two parts according to the proportion of the discharge port size within that range, and assigned to the first particle size region and the second particle size region respectively.

[0051] Step S302: Perform sand and gravel crushing simulation for the sand and gravel to be processed in each particle size region to obtain the target particle size distribution curve corresponding to the target sand and gravel.

[0052] Specifically, step S302 includes: Step S3021: Perform sand and gravel crushing simulation on the sand and gravel to be processed in the first particle size region. Based on the mass proportion of the target sand and gravel in different particle size ranges in the standard sieve sequence after the sand and gravel crushing simulation, obtain the first particle size distribution curve.

[0053] Crushing equipment is the core equipment in a sand and gravel processing production line, its function being to crush large rocks into smaller particles. Different types of crushing equipment, such as jaw crushers, cone crushers, impact crushers, and vertical shaft impact crushers, employ different crushing principles, resulting in varying particle size distribution characteristics. This invention simulates the changes in gradation before and after crushing. By applying an empirical distribution model only to the coarse particles where crushing actually occurs, it avoids distorted predictions of the fine particle range when the overall gradation is used as input to the crushing model, thus improving the rationality of particle size distribution prediction during the crushing process.

[0054] For example, the crushing transformation function is used to simulate the crushing of the sand and gravel to be processed in the first particle size region. The crushing transformation function can be expressed as:

[0055] in, This is the first particle size distribution curve of the output material after crushing simulation. This is the initial particle size distribution curve of the sand and gravel to be processed in the first particle size region. For the crushing simulation algorithm, These are the crushing parameters.

[0056] In some alternative implementations, crushing parameters are parameters describing the crushing process conditions, containing three core fields: crushing equipment type, current discharge port size, and material lithology. The crushing equipment type includes jaw crusher, cone crusher, impact crusher, or vertical shaft impact crusher, which affects the particle size distribution characteristics of the crushed product. The current discharge port size, in mm, affects the maximum particle size of the crushed product. The material lithology, such as granite, limestone, basalt, sandstone, etc., affects the crushing difficulty and particle size distribution of the material.

[0057] In some optional implementations, the new particle size distribution Rcrushed generated after crushing of the material in the first particle size region is used to describe the percentage distribution of retained material mass on a standard sieve aperture sequence after crushing of the coarse-grained region material, and is described using the Rosin-Rammler distribution model. The parameters of the Rosin-Rammler distribution model are determined by type, css, and rockType.

[0058] In some alternative implementations, the Rosin-Rammler distribution model controls the distribution shape with two parameters, and its expression is:

[0059] in, For particle size greater than The percentage of material mass to total mass, ranging from 0 to 100. It is an exponential function. The target particle size, in mm, represents the particle size currently being calculated. Characteristic particle size, in mm, represents the particle size corresponding to approximately 36.8% of the total mass of material accumulated on the screen. It reflects the overall fineness of the material particles. The value of characteristic particle size is generally obtained by looking up the crushing equipment model coefficient table. The shape parameter controls the width of the distribution. The larger the particle size, the more concentrated the particle size distribution, indicating a more uniform particle size. The smaller the particle size, the more dispersed the particle size distribution.

[0060] In some alternative implementations, the Rosin-Rammler distribution model is used to calculate the values ​​at the boundary points of each particle size on the standard sieve aperture sequence. Adjacent two levels The difference in values ​​represents the percentage of material mass retained at that particle size. This yields an array of percentages of material mass in each particle size range after crushing, which are then processed into curves to obtain the first particle size distribution curve.

[0061] Step S3022: Based on the mass proportion of the sand and gravel to be processed in the second particle size region in different particle size ranges in the standard sieve aperture sequence, the second particle size distribution curve is obtained.

[0062] In the second particle size region, the particle size of the material is smaller than the discharge port size, so it can pass directly through the crushing chamber without being affected by the crushing action, and its relative distribution on the standard sieve aperture sequence remains unchanged.

[0063] Step S3023: The first particle size distribution curve and the second particle size distribution curve are weighted and summed to obtain the target particle size distribution curve.

[0064] The target particle size distribution curve can be represented as:

[0065] in, The first particle size distribution curve in the target particle size distribution curve The target retention material quality for each particle size range The first particle size distribution curve is the first... The retained material mass within each particle size range The second particle size distribution curve is the first one. The retained material mass within each particle size range Set a weight for the first one. Set a weight for the second one.

[0066] Step S303: Based on the target particle size distribution curve and sieve aperture information, perform a sieving simulation on the target sand and gravel to obtain the sieving particle size distribution.

[0067] Specifically, step S303 includes: Step S3031: Compare the particle size of the target sand and gravel corresponding to the target particle size distribution curve with the sieve aperture information, and perform multi-level sieving simulation on the target sand and gravel based on the comparison results to obtain the sieving results.

[0068] Specifically, when the minimum value of the target sand and gravel particle size range corresponding to the target particle size distribution curve is greater than the sieve aperture information, all materials within the particle size range are included in the oversize material, and the percentage of retained material mass in this particle size range is directly added to the cumulative oversize mass. When the maximum value of the target sand and gravel particle size range corresponding to the target particle size distribution curve is less than the sieve aperture information, the materials within the particle size range are allocated according to the screening ratio. The portion that is screened according to the screening ratio actually passes through the sieve and is included in the undersize material, while the remaining portion fails to pass through the sieve due to incomplete screening and is included in the oversize material. The sieving ratio ranges from [0,1], meaning the proportion of material with a particle size smaller than the sieve aperture that actually passes through the sieve aperture. When the minimum value of the particle size range corresponding to the target particle size distribution curve is less than or equal to the sieve aperture information, and the maximum value of the particle size range is greater than or equal to the sieve aperture information, assuming that the particle size is uniformly distributed within the particle size range, the percentage of retained material within the particle size range is divided according to the position ratio of the sieve aperture information within the particle size range. The portion with a particle size larger than the sieve aperture information is assigned to the upper part of the sieve, and the portion with a particle size smaller than the sieve aperture information is assigned to the lower part of the sieve. For example, the position ratio of the sieve aperture information within the particle size range can be expressed as:

[0069] in, This represents the proportion of the sieve pore size information within the particle size range. For sieve aperture information, This represents the minimum value of the particle size range of the target sand and gravel corresponding to the target particle size distribution curve. This represents the maximum value of the target sand and gravel particle size range corresponding to the target particle size distribution curve.

[0070] In some alternative implementations, the percentage of retained material mass within the particle size range ( The percentage of material retained within the particle size range is 1.5 times the amount that passes through the sieve. The portion that is doubled is sieved out.

[0071] In some alternative implementations, in an ideal screening process, 100% of the material with a particle size larger than the screen aperture is classified as oversize product, and 100% of the material with a particle size smaller than the screen aperture is classified as undersize product. In actual screening, due to limited screening time, a large feed layer thickness, and high moisture content, some fine particles are carried away and mixed into the oversize product before they can pass through the screen aperture, resulting in an actual screening efficiency of less than 1. A single-layer screening transformation function can be defined, and multi-layer screening transformation functions can be obtained by recursively applying the single-layer screening transformation function layer by layer, thereby simulating multi-stage screening of the target sand and gravel.

[0072] The single-layer sieving transformation function is defined as follows:

[0073] in, For the screening results, For screening simulation algorithm, To obtain the particle size distribution curve of the material entering the screening process, These are the screening parameters.

[0074] In some optional implementations, the screening parameters include two core fields: screen aperture and screening efficiency. The screening results include: oversize particle size distribution and undersize particle size distribution.

[0075] In some alternative implementations, vibrating screens in actual production typically include multiple screens to separate the feed into multiple particle size fractions. Furthermore, the multi-layer screening is modeled as a layer-by-layer recursion of the single-layer screening function. The inputs are the particle size distribution and mass of the material, and the outputs are multiple sub-materials divided according to the screen openings.

[0076] In some alternative implementations, the multi-layer sieving transformation function can be expressed as:

[0077] in, For the first The undersize product from the first sieve is the product with the smallest particle size, smaller than that of the second sieve. sieve holes, For the first The product passing through the first sieve is the product with the largest particle size, which is larger than the opening size of the first sieve layer. This is a multi-layer screening simulation algorithm. To obtain the particle size distribution curve of the material entering the screening process, These are multi-layer screening parameters, arranged in descending order of sieve aperture size, with each element corresponding to a single layer of sieve parameters.

[0078] In some alternative implementations, step 1 is... The single-layer sieving function is called with input and params3[0] as parameters to obtain the sieving results. Its upper sieve distribution This is the first product. sieved gradation As input to the next layer. Step k (k=2,...,K) uses the sieve distribution from the previous layer. For input, params3[k 1] Call the single-layer sieving function for the parameters to obtain Its upper sieve distribution That is, the first Product After the Kth layer is completed, the gradation of the last layer is screened out. As the K+1th product .

[0079] In some alternative implementations, each product relative quality percentage The mass percentage of each screening layer is obtained by multiplying the mass percentages of each screening layer. The mass percentage of the first screening layer is: = The mass percentage on the k-th sieve is: = ,all The sum of them equals 1.

[0080] In some optional implementations, in the sand and gravel processing production simulation, the screening agent constructs params3 based on its own number of screen layers and the array of screen aperture sizes in each layer during the material handling process, and calls the multi-layer screening transformation function to obtain the K+1 product gradation and corresponding mass percentage.

[0081] Step S3032: Based on the target sand and gravel mass ratio of each screening layer in the screening results, determine the particle size distribution of the material on the screen corresponding to each screening layer.

[0082] In some optional implementations, the target sand and gravel mass percentage includes the oversize mass percentage and the undersize mass percentage, where the oversize mass percentage can be expressed as:

[0083] in, The percentage of the mass remaining on the screen. This represents the percentage of material retained on the sieve.

[0084] In some alternative implementations, the percentage of undersize material can be expressed as:

[0085] in, The percentage of the mass passing through the screen. This represents the percentage of material retained after screening.

[0086] In some optional implementations, the oversize and undersize mass percentages are then normalized (divided by their respective cumulative percentages and multiplied by 100) to obtain the oversize particle size distribution and the oversize particle size distribution.

[0087] Step S3033: Based on the particle size distribution of the material on the screen, obtain the sieve particle size distribution.

[0088] Among them, the sieve particle size distribution is composed of the particle size distribution of the material on the sieve and the particle size distribution of the material on the sieve.

[0089] Step S304: Based on the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution, construct a standardized log to monitor the particle size distribution of sand and gravel.

[0090] Specifically, step S304 includes: Step S3041: Assign corresponding batch numbers to the sand and gravel to be processed, and associate the batch numbers with the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution to obtain the association results.

[0091] Step S3042: Store the correlation results, initial particle size distribution curve, target particle size distribution curve, and sieved particle size distribution to obtain a standardized log.

[0092] To achieve full-process tracking of materials from input to finished product, a standardized log recording mechanism for material batches throughout the entire flow process is established. Each material batch is given a globally unique batch number when it is created. The batch number runs through the entire flow process of materials from the receiving station, through various levels of crushing and screening, until it enters the finished product warehouse.

[0093] In some optional implementations, each log entry in the standardized log includes the following fields: simulation time (simTime, the simulation clock value that records the occurrence of the event, in hours), batch number (batchId, associated with the specific material batch), node name (the name of the device where the event occurred), event type (event), batch quality (the quality value of the batch at the time of the event, in tons), and characteristic particle size (the median particle size value of the current gradation curve of the batch, in millimeters).

[0094] The event types use a fixed set of values, mainly including two categories. The first category is batch-related events, such as `batch_in` indicating that a batch of materials has arrived at a certain node, and `batch_out` indicating that a batch of materials has been output from a certain node. The second category is state transition events, such as equipment start-up events, equipment stop-down events, equipment start / stop events, fault occurrence events, maintenance start events, and maintenance end events, recording the state transitions of equipment faults and maintenance. Material events are associated with specific material batches and record their current quality and median particle size, while state events record the time of equipment state changes.

[0095] In some alternative implementations, the flow record data is generated from the key actions of the state machines of each device's intelligent agents and the material handling process, and is centrally written into a unified process data storage.

[0096] In some alternative implementations, this data can be used to reconstruct the complete flow trajectory of any batch of materials from the receiving station to the finished product warehouse by filtering by batch number after the simulation. The trajectory includes the arrival time, residence time, mass, and characteristic particle size changes of the batch of materials at each node, thus intuitively showing the gradual change process of material particle size in each process stage of the entire line.

[0097] In some optional implementations, the monitoring method for sand and gravel particle size distribution further includes: mapping the finished sand and gravel products according to particle size interval labels and the finished product quality corresponding to the particle size interval labels, based on the sieved particle size distribution, to obtain a mapping table; performing node-level material balance analysis, overall quality balance analysis, particle size change trajectory analysis, time distribution analysis of each particle size product, and post-event quantitative analysis of cyclic load on the sand and gravel processing simulation process based on the standardized logs and mapping table, to obtain analysis results, and to evaluate the sand and gravel processing simulation process based on the analysis results.

[0098] To support finished product quality analysis, cumulative inbound statistics by particle size range are established in the finished product warehouse. A particle size range boundary point array `grade=[b0,b1,...,bL]` (unit: mm) is defined. L+1 boundary points divide the particle size range into L consecutive particle size ranges, where the i-th range is [b...b1...bL]. i-1 ,b i (i=1,2,…,L). The finished product warehouse maintains a mapping table with particle size labels as keys and cumulative incoming mass as values. Whenever a batch of material enters the finished product warehouse, the warehouse sequentially queries the mass percentage of each particle size interval from the batch's gradation curve, multiplies the percentage by the total batch mass to obtain the incoming mass of that interval, and adds it to the corresponding label item in the mapping table. After the entire simulation runs, the mapping table accumulates the total output of each particle size product, which can be directly used to calculate the output ratio of each particle size in the finished product warehouse, product qualification rate, and other quality indicators.

[0099] In some optional implementations, node-level material balance analysis involves, for any node n within any time window [ta, tb], calculating the total mass of batch_in events (min), i.e., the total amount of material entering the node within the time window, and the total mass of batch_out events (mout), i.e., the total amount of material output from the node within the time window, from the flow records. When the node processing latency is short and the silo temporary storage is stable, |min| should be satisfied. mout| / min≤δ1, where δ1 is the set quality conservation tolerance threshold for the node. When the difference exceeds this tolerance, it indicates that there is an anomaly in the material handling logic of the node, and the material handling process of the node needs to be investigated.

[0100] In some alternative implementations, the overall mass balance analysis involves calculating the total feed volume M of all feed hoppers over the entire simulation period. in The sum of the mass of graded materials in all finished product silos, M out After the simulation ends and all materials in transit are cleared, |M| should be satisfied. in M out M in2 | / M in ≤δ2, where δ2 is the threshold for the overall quality conservation tolerance, M in2 M represents the amount of material still in the conveyor belt and hopper at the end of the simulation. in2 The result is obtained by summing the current load of all conveyors and the current inventory of all non-finished material bins. When the difference exceeds the tolerance, the source of the difference is located one by one according to the node-level material balance.

[0101] In some optional implementations, particle size variation trajectory analysis involves selecting the batch number (batchId) and extracting all event sequences for that batch from the flow record in ascending order of simTime. This yields the arrival time, departure time, location at each node, and median particle size (d50) variation trajectory for that batch. By comparing the particle size variation trajectories under different lithologies and process schemes, the impact of process configuration on the quality of finished materials produced from sand and gravel processing can be evaluated.

[0102] In some optional implementations, time distribution analysis of finished product materials by particle size is performed. Curves showing the cumulative amount entering the silo as a function of simulation time are extracted from the cumulative data of finished product grading, categorized by particle size label. During steady-state operation, the cumulative entry rate of each particle size should tend to be constant, and their ratio represents the product gradation ratio under steady-state conditions. A step change in the slope of the curve at a certain moment typically corresponds to process changes such as route switching (e.g., switching from an open circuit to a closed circuit) or equipment parameter adjustments (e.g., reducing the discharge port size), and can be used to assess the impact of process changes on product grading.

[0103] The sand and gravel particle size distribution monitoring method provided in this embodiment uses a standard sieve aperture sequence as the gradation curve representation method with a unified scale for the entire system. This allows any two gradation curves to be directly weighted element-wise, eliminating interpolation alignment errors between different sieve aperture systems and ensuring the strict comparability of particle size data across the entire system. The partitioned superimposed crushing transformation model separates the fine particles that are physically unacceptable to crushing from the crushing calculation, applying the Rosin-Rammler model only to the coarse particles that undergo crushing behavior, thus improving the physical rationality of crushing product prediction. The standardized structure of flow record entries, combined with the cumulative particle size statistics of the finished product bin, supports seven types of multi-dimensional statistical analysis, including node-level material balance, overall quality balance, particle size change trajectory, product time distribution, equipment utilization bottlenecks, energy consumption distribution, and cyclic load convergence. This provides complete quantitative data support for process optimization and quality improvement.

[0104] This embodiment provides a method for monitoring the particle size distribution of sand and gravel, which can be used with computer equipment. Figure 4 This is a third flowchart of a method for monitoring the particle size distribution of sand and gravel according to an embodiment of the present invention, as shown below. Figure 4 As shown, the process includes the following steps: A unified representation of standard sieve aperture sequence and particle size distribution curve; a mathematical model definition for particle size distribution transformation during crushing; a layer-by-layer recursive algorithm for multi-layer sieving; and a record of particle size transfer throughout the entire process and multi-dimensional statistical analysis.

[0105] This embodiment also provides a monitoring device for sand and gravel particle size distribution, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0106] This embodiment provides a device for monitoring the particle size distribution of sand and gravel, such as... Figure 5 As shown, it includes: The particle size division module 501 is used to obtain the initial particle size distribution curve of the sand and gravel to be processed. Based on the initial particle size distribution curve and the discharge port size information, the particle size of the sand and gravel to be processed is divided to obtain multiple particle size regions.

[0107] The sand and gravel crushing simulation module 502 is used to simulate the crushing of sand and gravel to be processed in each particle size region to obtain the target particle size distribution curve corresponding to the target sand and gravel.

[0108] The sand and gravel screening simulation module 503 is used to simulate the screening of target sand and gravel based on the target particle size distribution curve and the sieve aperture information to obtain the screening particle size distribution.

[0109] The particle size monitoring module 504 is used to construct a standardized log based on the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution to monitor the particle size distribution of sand and gravel.

[0110] In some optional implementations, the granularity division module 501 includes: The initial particle size distribution curve determination unit is used to set the standard sieve aperture sequence and determine the initial particle size distribution curve based on the mass proportion of the sand and gravel to be processed in different particle size ranges in the standard sieve aperture sequence. The standard sieve aperture sequence is a sequence of sieve apertures generated according to the particle size order based on different particle size ranges.

[0111] The particle size division unit is used to compare the particle size of the sand and gravel to be processed corresponding to the initial particle size distribution curve with the discharge port size information. When the particle size of the sand and gravel to be processed is greater than the discharge port size information, the sand and gravel to be processed is divided into the first particle size region. When the particle size of the sand and gravel to be processed is less than or equal to the discharge port size information, the sand and gravel to be processed is divided into the second particle size region. The particle size of the sand and gravel in the first particle size region is greater than the particle size of the sand and gravel in the second particle size region.

[0112] In some alternative implementations, the sand and gravel crushing simulation module 502 includes: The first curve determination unit is used to simulate the crushing of sand and gravel in the first particle size region. Based on the mass proportion of the target sand and gravel in different particle size ranges in the standard sieve sequence after the crushing simulation, the first particle size distribution curve is obtained.

[0113] The second curve determination unit is used to obtain the second particle size distribution curve based on the mass proportion of the sand and gravel to be processed in the second particle size region in different particle size ranges in the standard sieve aperture sequence.

[0114] The target curve determination unit is used to perform a weighted summation of the first particle size distribution curve and the second particle size distribution curve to obtain the target particle size distribution curve.

[0115] In some alternative implementations, the sand and gravel screening simulation module 503 includes: The screening simulation unit is used to compare the particle size of the target sand and gravel corresponding to the target particle size distribution curve with the sieve aperture information, and to perform multi-level screening simulation on the target sand and gravel based on the comparison results to obtain the screening results.

[0116] The material distribution determination unit is used to determine the particle size distribution of the material on the screen for each screening layer based on the target sand and gravel mass ratio of each screening layer in the screening results.

[0117] The sieve particle size distribution determination unit is used to obtain the sieve particle size distribution based on the particle size distribution of the material on the sieve and the particle size distribution of the material on the sieve.

[0118] In some alternative implementations, the particle size monitoring module 504 includes: The data association unit is used to assign corresponding batch numbers to the sand and gravel to be processed, and associate the batch numbers with the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution to obtain the association results.

[0119] The standardized storage unit is used to store the correlation results, initial particle size distribution curve, target particle size distribution curve, and sieved particle size distribution to obtain a standardized log.

[0120] In some optional embodiments, the monitoring device for sand and gravel particle size distribution further includes: The data mapping module is used to map the finished sand and gravel products according to the particle size distribution and the corresponding finished product quality based on the particle size interval labels, thus obtaining a mapping table.

[0121] The simulation evaluation module is used to perform node-level material balance analysis, overall quality balance analysis, particle size change trajectory analysis, time distribution analysis of products of each particle size, and post-event quantitative analysis of cyclic load on the sand and gravel processing simulation process based on standardized logs and mapping tables. The analysis results are used to evaluate the sand and gravel processing simulation process.

[0122] The sand and gravel particle size distribution monitoring device provided in this embodiment of the invention can execute the sand and gravel particle size distribution monitoring method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0123] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0124] The following is a detailed reference. Figure 6 This diagram illustrates a suitable structural design for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 601, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 602 or a program loaded from memory 608 into random access memory (RAM) 603. RAM 603 also stores various programs and data required for the operation of the electronic device. The processor 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0125] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0126] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a memory 608, or installed from a ROM 602. When the computer program is executed by the processor 601, it performs the functions defined in the sand and gravel particle size distribution monitoring method of the embodiments of the present invention.

[0127] Figure 6 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0128] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the method for monitoring sand and gravel particle size distribution shown in the above embodiments is implemented.

[0129] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0130] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method of monitoring the distribution of grit particle sizes, characterised by, The method includes: The initial particle size distribution curve of the sand and gravel to be processed is obtained. Based on the initial particle size distribution curve and the discharge port size information, the particle size of the sand and gravel to be processed is divided to obtain multiple particle size regions. For each of the aforementioned particle size regions, a sand and gravel crushing simulation is performed on the sand and gravel to be processed to obtain the target particle size distribution curve corresponding to the target sand and gravel. Based on the target particle size distribution curve and sieve aperture information, the target sand and gravel are screened in a simulation to obtain the screened particle size distribution. Based on the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution, a standardized log is constructed to monitor the particle size distribution of sand and gravel.

2. The method of claim 1, wherein, The initial particle size distribution curve of the sand and gravel to be processed is obtained. Based on the initial particle size distribution curve and the discharge port size information, the particle size of the sand and gravel to be processed is divided to obtain multiple particle size regions, including: A standard sieve aperture sequence is set, and the initial particle size distribution curve is determined based on the mass proportion of different particle size ranges in the standard sieve aperture sequence of the sand and gravel to be processed; the standard sieve aperture sequence is a sieve aperture sequence generated in order of particle size according to different particle size ranges. The particle size of the sand and gravel to be processed corresponding to the initial particle size distribution curve is compared with the discharge port size information. When the particle size of the sand and gravel to be processed is greater than the discharge port size information, the sand and gravel to be processed is divided into a first particle size region. When the particle size of the sand and gravel to be processed is less than or equal to the discharge port size information, the sand and gravel to be processed is divided into a second particle size region. The particle size of the sand and gravel in the first particle size region is greater than the particle size of the sand and gravel in the second particle size region.

3. The method of claim 2, wherein, The process of performing sand and gravel crushing simulation on the sand and gravel to be processed for each of the aforementioned particle size regions to obtain the target particle size distribution curve corresponding to the target sand and gravel includes: A sand and gravel crushing simulation is performed on the sand and gravel to be processed in the first particle size region. Based on the mass proportion of the target sand and gravel in different particle size ranges in the standard sieve sequence after the sand and gravel crushing simulation, a first particle size distribution curve is obtained. Based on the mass proportion of the sand and gravel to be processed in the second particle size region in different particle size ranges in the standard sieve sequence, a second particle size distribution curve is obtained; The target particle size distribution curve is obtained by weighted summation of the first particle size distribution curve and the second particle size distribution curve.

4. The method according to any one of claims 1 to 3, characterized in that, The step of performing a sieving simulation on the target sand and gravel based on the target particle size distribution curve and sieve aperture information to obtain the sieved particle size distribution includes: The particle size of the target sand and gravel corresponding to the target particle size distribution curve is compared with the sieve aperture information. Based on the comparison results, a multi-level sieve simulation is performed on the target sand and gravel to obtain the sieve results. Based on the target sand and gravel mass ratio of each screening layer in the screening results, determine the oversize particle size distribution and oversize particle size distribution of each screening layer. The sieve particle size distribution is obtained based on the particle size distribution of the material on the sieve and the particle size distribution of the material on the sieve.

5. The method according to any one of claims 1 to 3, characterized in that, The step of constructing a standardized log based on the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution includes: Assign a corresponding batch number to the sand and gravel to be processed, and associate the batch number with the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution to obtain the association result; The correlation results, the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution are stored to obtain the standardized log.

6. The method according to any one of claims 1 to 3, characterized in that, The method further includes: Based on the sieved particle size distribution, the finished sand and gravel products are mapped according to the particle size interval labels and the finished product quality corresponding to the particle size interval labels to obtain a mapping table; Based on the standardized logs and the mapping table, node-level material balance analysis, overall quality balance analysis, particle size change trajectory analysis, time distribution analysis of products of each particle size, and post-hoc quantitative analysis of cyclic load are performed on the sand and gravel processing simulation process to obtain analysis results, which are then used to evaluate the sand and gravel processing simulation process.

7. A device for monitoring the size distribution of sand and gravel, characterized in that The device includes: The particle size division module is used to obtain the initial particle size distribution curve of the sand and gravel to be processed, and to divide the particle size of the sand and gravel to be processed according to the initial particle size distribution curve and the discharge port size information to obtain multiple particle size regions. The sand and gravel crushing simulation module is used to simulate the crushing of the sand and gravel to be processed in each of the aforementioned particle size regions, and to obtain the target particle size distribution curve corresponding to the target sand and gravel. The sand and gravel screening simulation module is used to perform screening simulation on the target sand and gravel based on the target particle size distribution curve and the sieve aperture information to obtain the screening particle size distribution. The particle size monitoring module is used to construct a standardized log based on the initial particle size distribution curve, the target particle size distribution curve, and the sieved particle size distribution, in order to monitor the particle size distribution of sand and gravel.

8. An electronic device, comprising: include: A memory and a processor are interconnected, the memory storing computer instructions, and the processor executing the computer instructions to perform the method for monitoring the particle size distribution of sand and gravel as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the method for monitoring the particle size distribution of sand and gravel as described in any one of claims 1 to 6.

10. A computer program product, characterised in that, Includes computer instructions for causing a computer to execute the method for monitoring the particle size distribution of sand and gravel as described in any one of claims 1 to 6.

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