A method of measuring the size of a spheroid

Abstract

The present application relates to the technical field of measurement, and especially relates to a kind of pelletizing diameter measurement method.The method comprises the following steps: pelletizing diameter data acquisition and ball quantity acquisition are carried out by the pelletizing diameter detection device preset on pelletizing disc, and pelletizing diameter data and ball quantity data are obtained; qualified ball mass is calculated according to the pelletizing diameter data, and qualified ball mass data is obtained; real-time feed flow data and real-time water supply amount data are obtained, and pelletizing rate is calculated according to the real-time feed flow data, real-time water supply amount data and the qualified ball mass data, and pelletizing rate data is obtained; system pelletizing rate is calculated according to the ball quantity data and the pelletizing rate data, and system pelletizing rate data is obtained, to carry out pelletizing disc adjustment operation.The present application calculates the pelletizing rate of each pelletizing disc in real time, and when the pelletizing rate of a certain pelletizing disc becomes low, it is convenient to feedback and adjust the pelletizing disc in time.

Description

Technical Field

[0001] This invention relates to the field of measurement technology, and in particular to a method for measuring the size of spherical particles. Background Technology

[0002] In the steel industry, pelletizing is a commonly used iron ore refining technology. The pelletizing process is a crucial step in the iron ore pelletizing production line, and the stability and improvement of green pellet quality largely depend on it. The pelletizing machine, as the core equipment in the pelletizing process, mainly includes disc pelletizers and cylindrical pelletizers. Large-scale, high-volume production lines generally use cylindrical pelletizers; however, due to the dominance of small- and medium-sized pelletizing production lines, disc pelletizers are more prevalent.

[0003] When the pelletizing machine is working, the materials move along their respective tracks within the machine, forming green pellets of varying diameters. Once the green pellets reach a certain strength, they are discharged from the pelletizing machine and fall into a subsequent green pellet receiving device. The pellet quality of the pelletizing machine is a key parameter in the pelletizing process; the higher the pass rate of the green pellets, the higher the pellet quality of the pelletizing machine.

[0004] Factors affecting pellet quality include the motor speed, water supply, weight of each component in the mixture, moisture content of each component, and proportion of binder in the mixture. Technicians pre-set appropriate motor speed, water supply, weight of each component in the mixture, moisture content of each component, and proportion of binder in the mixture to achieve a predetermined pellet yield, thereby ensuring the pellet quality of the pelletizing machine.

[0005] The pelletizing rate is a crucial indicator of pelletizing efficiency. High pelletizing efficiency typically requires a high pelletizing rate, which is calculated by statistically analyzing data such as pellet quantity, return pellet quantity, and input material quantity. Return pellet quantity refers to the amount of pellets with unacceptable particle size within the total pellet quantity, separated through multi-stage screening. Because the pelletizing rate is related to the return pellet quantity, it cannot be calculated in a timely manner, leading to delayed feedback and impacting subsequent chain grate processes. Furthermore, current methods cannot calculate the pelletizing rate for each individual pelletizing machine, making it impossible to quantitatively adjust the parameters of a single machine to improve its pelletizing rate. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention proposes a method for measuring the particle size of granules, thereby resolving at least one of the aforementioned technical issues.

[0007] This application provides a method for measuring the particle size of granules, the method comprising:

[0008] The ball size data and the number of balls are collected by a ball size detection device pre-installed on the ball forming plate.

[0009] The qualified ball mass is calculated based on the ball size data to obtain the qualified ball mass data;

[0010] Acquire real-time feed flow rate data and real-time water supply data, and calculate the ball formation rate based on the real-time feed flow rate data, real-time water supply data and qualified ball mass data to obtain ball formation rate data;

[0011] The system ball formation rate is calculated based on the ball quantity data and the ball formation rate data to obtain the system ball formation rate data, which is then used to adjust the ball-forming tray.

[0012] This invention uses a pellet size detection device installed in each pelletizing pan to calculate the real-time pelletizing rate of each pan by detecting the real-time pellet size and quantity. The system's pelletizing rate is then calculated in real-time. This method provides results earlier than traditional methods, allowing for timely feedback on the current pelletizing rate. The method is simple and reliable; has low maintenance costs; requires fewer supporting devices; and is stable and reliable.

[0013] Optionally, the pellet size data includes first pellet size data and second pellet size data, and the pellet quantity data includes first pellet quantity data and second pellet quantity data. The step of collecting pellet size data and pellet quantity data using a pellet size detection device pre-installed on the pelletizing plate includes:

[0014] The first ball size data and the first ball number data are obtained by collecting ball size data and collecting ball number data by using a first ball size detection device that is preset on the side of the ball forming plate.

[0015] The second ball size detection device, positioned above the pelletizing plate, collects ball size data and ball quantity data to obtain the second ball size data and the second ball quantity data. The detection rate parameter data of the first ball size detection device is less than or equal to the detection rate parameter data of the second ball size detection device.

[0016] This invention utilizes two particle size detection devices positioned at different locations—a side position and an overhead position—to acquire more information about particle size, increasing the diversity of perspectives on the pelletizing process, improving the quality of initial data, and reducing the error rate of data detection. The first particle size detection device has a lower detection rate parameter, while the second has a higher one. These different rate parameters allow for flexible acquisition of particle size data under different conditions. The second particle size detection device can be used when more detailed data is needed, while the first device can be used under normal circumstances, thereby improving efficiency.

[0017] Optionally, the step of calculating the qualified ball mass based on the ball size data to obtain qualified ball mass data includes:

[0018] The qualified ball mass is calculated based on the ball size data using the qualified ball mass calculation formula; the qualified ball mass calculation formula is as follows:

[0019]

[0020] M i Let d be the qualified ball quality data corresponding to the i-th ball-making plate. 16 Here are the diameter data for a 16mm sphere, k is the sphere diameter data, d8 is the sphere diameter data for an 8mm sphere, π is the value of pi, and d... k For the diameter data of a sphere in kmm, n k ρ represents the number of spheres with a diameter of km, ρ represents the sphere density, and i represents the sphere-forming disk sequence.

[0021] This invention utilizes a formula for calculating the mass of qualified balls, enabling automated calculation without manual measurement or calculation, thus improving efficiency and reducing human error. Based on ball diameter and density information, the formula provides relatively accurate qualified ball mass data, ensuring product quality meets specified standards. By using this formula, different ball diameter data (d...) can be used to calculate the mass of qualified balls. k This invention calculates the mass of qualified balls within different diameter ranges and produces qualified balls of varying diameters during the ball-making process. Compared to traditional techniques, this invention allows for the calculation of qualified balls upon exiting the ball tray, thereby increasing measurement efficiency.

[0022] Optionally, the step of acquiring real-time feed flow rate data and real-time water supply data, and calculating the pelleting rate based on the real-time feed flow rate data, real-time water supply data, and the qualified ball quality data to obtain pelleting rate data, includes:

[0023] Real-time feed flow rate data is acquired, and the feed quantity is calculated based on the real-time feed flow rate data to obtain feed quantity data. The feed quantity data is calculated using a feed quantity calculation formula; specifically, the feed quantity calculation formula is as follows:

[0024]

[0025] W i Here, t2 represents the feed rate data corresponding to the i-th pelletizing disc, t1 represents the upper limit of the feed rate time, and w represents the lower limit of the feed rate time. i (t) represents the real-time feed flow rate data, t represents the feed rate time data, and i represents the pelletizing disc sequence item;

[0026] Real-time water supply data is acquired, and water supply is calculated based on the real-time water supply data to obtain water supply data. The water supply data is calculated using a water supply calculation formula; specifically, the water supply calculation formula is as follows:

[0027]

[0028] F i For the water supply data corresponding to the i-th pelletizing plate, f i (t) represents the real-time water supply data, t2 represents the upper limit of the feed rate time, t1 represents the lower limit of the feed rate time, t represents the feed rate time data, and i represents the pelleting disc sequence item.

[0029] The pelleting rate is calculated based on the feed rate data, the water supply data, and the qualified pellet mass data to obtain pelleting rate data; wherein the pelleting rate is calculated using a pelleting rate calculation formula, and the specific pelleting rate calculation formula is as follows:

[0030]

[0031] η i M represents the ball formation rate data corresponding to the i-th ball-forming plate. i W represents the qualified ball quality data corresponding to the i-th ball-making plate. i For the feed rate data of the i-th pelletizing disc, F i The water supply data is denoted as i, and the pelletizing disc sequence number is denoted as i.

[0032] This invention utilizes real-time data on feed flow rate, water supply, and qualified pellet quality to calculate the real-time pelleting rate. This facilitates timely monitoring of changes in the pelleting rate during the pelleting process, enabling prompt adjustments and control. The invention employs formulas for calculating feed and water supply, which accurately calculate real-time data, thus improving the accuracy of pelleting rate calculation. By combining qualified pellet quality, feed rate, and water supply data to calculate the pelleting rate, the influence of various factors on the pelleting rate can be considered, leading to a better understanding of the overall performance of the pelleting process. Real-time monitoring of the pelleting rate helps the production process operate more efficiently, ensures product quality meets specified standards, reduces scrap rates, and improves product consistency.

[0033] Optionally, the step of calculating the system ball formation rate based on the ball quantity data and the ball formation rate data to obtain the system ball formation rate data includes:

[0034] The system ball formation rate is calculated based on the ball quantity data and the ball formation rate data to obtain the system ball formation rate data; wherein the system ball formation rate is calculated using the system ball formation rate calculation formula, and the specific system ball formation rate calculation formula is as follows:

[0035]

[0036] Here, 'a' represents the system's pelleting rate data, 'i' represents the pelleting tray sequence, 'n' represents the number of pelleting trays, and 'W' represents the number of pelleting trays. 1i Let η be the total amount of raw materials in the i-th pelletizing disc over a certain period of time. i This represents the ball formation rate data corresponding to the i-th ball-forming plate;

[0037]

[0038] W 1i This refers to the total amount of raw materials generated by the i-th pelletizing disc over a given period of time. Let i be the ball release time data for the i-th ball-making board. For the goal-scoring time data of the i-th ball-creating plate, T 1k This represents the time required from the moment a ball is produced from the k-th ball-producing tray to the moment a ball is produced from the next ball-producing tray, where i is the ball-producing tray order, k is the ball-producing tray order, and w is the time required. 1i (t) represents the inflow rate data of the i-th pelleting plate, f 1i (t) represents the water flow rate data for the i-th pelletizing plate.

[0039] In this invention, the pelleting rate is calculated by combining the output and pelleting rate data of each pellet-making unit to determine the overall pelleting rate of the system. This calculation method is independent of the number of returned pellets, so the result is obtained earlier than traditional methods. The calculated pelleting rate is earlier than traditional calculations, providing timely feedback on the real-time pelleting rate. When the pelleting rate decreases, adjustments can be made promptly, and the results provide a clear indication of how much the pelleting rate of that particular pellet-making unit has improved, ensuring the overall pelleting rate. This method uses real-time data for calculation, including real-time pellet quantity and pelleting rate data, allowing for continuous updating and monitoring of the system's pelleting rate data to understand changes in the pellet-making process.

[0040] Optionally, the step of generating the proportional coefficient data includes the following steps:

[0041]

[0042]

[0043]

[0044]

[0045] 'a' represents the proportionality coefficient data. i represents the order of the pelletizing trays, n represents the number of pelletizing trays, and W... 1i Let η be the total amount of raw materials in the i-th pelletizing disc over a certain period of time. i W represents the ball formation rate data corresponding to the i-th ball-forming plate. 21 For total ball output data, W 22 For total return volume data, w 21 (t) represents the real-time ball output data. For real-time ball return data, This refers to the upper time limit data corresponding to the real-time ball output data. T represents the lower limit of the time period corresponding to the real-time ball output data. 21 This data represents the running time of the same batch of pellets from the total measuring belt scale to the return measuring belt scale.

[0046] This invention obtains a proportional system based on traditional calculation methods, providing accurate data support. The system's ball-forming rate, calculated using traditional formulas and the method employed in this invention, is theoretically equal and is obtained through conversion. The step of generating the proportional coefficient data is automated, requiring no manual intervention or calculation, thus improving efficiency and reducing human error. Furthermore, the data is pre-calculated.

[0047] Optionally, the pelleting disc adjustment operation includes the following steps:

[0048] The change rate of the ball formation rate of the system is calculated to obtain the change rate data of the ball formation rate of the system.

[0049] When the system pelleting rate data is determined to be less than or equal to a preset first system pelleting rate threshold data and the system pelleting rate data is greater than a preset second system pelleting rate threshold data, pelleting disc adjustment data is generated based on the system pelleting rate change rate data, the real-time feed flow rate data, and the real-time water supply data to perform pelleting disc parameter control and adjustment operations, wherein the first system pelleting rate threshold data is greater than the second system pelleting rate threshold data;

[0050] If the ball formation rate data of the system is determined to be less than or equal to the preset second system ball formation rate threshold data, then a ball forming disc detection operation is performed.

[0051] This invention enables real-time pelletizing process control by monitoring the system's pelletizing rate and its rate of change, as well as real-time feed flow and water supply data. This facilitates timely detection of problems and the implementation of corrective measures during pelletizing. The calculation of the system's pelletizing rate change rate takes into account the dynamic changes in the pelletizing rate, thus providing more accurate guidance to determine when adjustments to the pelletizing disc parameters are needed. Based on the system's pelletizing rate data and thresholds, the efficiency and quality of the pelletizing process can be monitored and controlled. If the system's pelletizing rate falls below the threshold, corrective measures can be taken to improve the pelletizing process. By dynamically adjusting the pelletizing disc parameters, raw materials and resources can be better utilized, thereby improving production efficiency and reducing costs.

[0052] Optionally, the pelletizing disc inspection operation includes the following steps:

[0053] The camera preset on one side of the pelletizing tray is activated to capture images and obtain image data of the pelletizing tray;

[0054] The image data of the ball-forming disk is preprocessed according to the preset standard ball-forming disk image data to obtain ball-forming disk image preprocessing data;

[0055] Feature extraction is performed on the standard ball-forming disk image data and the preprocessed ball-forming disk image data to obtain standard ball-forming disk image feature data and ball-forming disk image feature data, respectively.

[0056] Clustering calculations are performed on the standard ball-forming disk image feature data and the ball-forming disk image feature data to obtain standard ball-forming disk image clustering data and ball-forming disk image clustering data, respectively;

[0057] Gaussian distribution calculations are performed on the standard ball-forming disk image clustering data and the ball-forming disk image clustering data to obtain standard ball-forming disk image Gaussian distribution data and ball-forming disk image Gaussian distribution data;

[0058] Similarity data is obtained by performing similarity calculation on the Gaussian distribution data of the standard ball-forming disk image and the Gaussian distribution data of the ball-forming disk image.

[0059] When the similarity data is determined to be greater than or equal to the preset similarity threshold data, a functional check of the pelleting tray is performed based on the real-time feed flow rate data and the real-time water supply data.

[0060] If the similarity data is determined to be less than the preset similarity threshold, an early warning operation is performed on the ball-forming device.

[0061] This invention provides an accurate assessment of the pelletizing tray's condition through image feature extraction and similarity calculation, facilitating the accurate identification of problems or anomalies. By setting a similarity threshold, anomalies in the pelletizing tray can be detected early, before problems escalate, thus reducing losses. Based on the detection results, targeted maintenance or early warning operations can be performed to optimize resource utilization, reduce downtime, and improve production efficiency. Compared to traditional image comparison methods, this invention employs a depth-based algorithm, providing data accuracy. Compared to other depth-based algorithms, it reduces the load on computing equipment and improves practicality.

[0062] Optionally, the step of performing image preprocessing on the pelletizing disc image data according to preset standard pelletizing disc image data to obtain pelletizing disc image preprocessing data includes:

[0063] Based on the preset standard pelletizing plate image data, the hue and saturation of the pelletizing plate image data are processed to obtain the hue and saturation adjustment data of the pelletizing plate image.

[0064] Histogram equalization is performed on the hue and saturation adjustment data of the ball-forming disk image to obtain the brightness adjustment data of the ball-forming disk image;

[0065] Color correction processing is performed on the brightness adjustment data of the ball-forming disk image to obtain preprocessed data of the ball-forming disk image.

[0066] This invention enhances the color information of an image by adjusting its hue and saturation, making the image clearer and facilitating better identification of the characteristics and problems of the ball-making disc. Histogram equalization enhances image contrast and improves brightness distribution, making the image easier to analyze, especially when the original image is under uneven lighting or has low contrast, which could easily lead to errors without processing. Color correction ensures that the color information in the image accurately reflects the real situation, helping to more accurately identify and analyze the image features of the ball-making disc.

[0067] Optionally, this application also provides a system for measuring the particle size of granules, used to perform the particle size measurement method described above, the system comprising:

[0068] The data acquisition module is used to acquire ball size data and ball quantity data through a ball size detection device pre-installed on the ball forming plate, and obtain ball size data and ball quantity data.

[0069] The qualified ball mass calculation module is used to calculate the qualified ball mass based on the ball diameter data to obtain the qualified ball mass data.

[0070] The pelleting rate calculation module is used to acquire real-time feed flow rate data and real-time water supply data, and to calculate the pelleting rate based on the real-time feed flow rate data, real-time water supply data and qualified pellet mass data to obtain pelleting rate data;

[0071] The system ball formation rate calculation module is used to calculate the system ball formation rate based on the ball quantity data and the ball formation rate data, and obtain the system ball formation rate data for ball formation tray adjustment operations.

[0072] The purpose of this invention is to detect the particle size of pellets in the pelletizing area of ​​a pelletizing disc, calculate the mass of qualified pellets based on the particle size, and calculate the pelletizing rate of each pelletizing disc in conjunction with the feed rate. The pelletizing rates of all pelletizing discs are statistically analyzed, and the measured pelletizing rate is calculated and compared with the pelletizing rate calculated by traditional methods. The pelletizing rate is analyzed, and the pelletizing rate of each pelletizing disc is calculated in real time. When the pelletizing rate of a particular disc decreases, feedback is provided for timely adjustment of the pelletizing disc. By installing a pellet size detection device on each pelletizing disc, the real-time pellet size and quantity detected by this device are used to calculate the real-time pelletizing rate of each pelletizing disc; then, the system's pelletizing rate is calculated in real time. This method provides results earlier than traditional methods of calculating pelletizing rate and can provide timely feedback on the current pelletizing rate status. This method is simple and reliable; has low maintenance costs; requires fewer supporting equipment; and is stable and reliable. Attached Figure Description

[0073] Other features, objects, and advantages of this application will become more apparent from the following detailed description of the non-limiting embodiments, taken with reference to the accompanying drawings:

[0074] Figure 1 A flowchart illustrating the steps of a method for measuring the particle size of granules according to one embodiment is shown;

[0075] Figure 2 A flowchart illustrating the steps of a method for calculating the ball formation rate according to an embodiment is shown;

[0076] Figure 3 A flowchart illustrating the steps of adjusting the pelletizing disc according to one embodiment is shown;

[0077] Figure 4 A flowchart illustrating the steps of a pelletizing disc inspection operation according to an embodiment is shown;

[0078] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0079] The technical method of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this invention.

[0080] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0081] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0082] The traditional principle for calculating the ball formation rate is the ratio of the mass of qualified balls to the total number of balls produced. The mass of qualified balls can be obtained by subtracting the number of returned balls from the total number of balls produced. The total number of balls produced refers to the sum of the balls produced by all ball-forming discs, which can be measured by the belt scale on the main conveyor belt.

[0083]

[0084]

[0085]

[0086] Where: η 系1 The ball formation rate calculated using traditional methods; W 21 Total number of balls played; w 21 W represents the total real-time ball output flow. 22 For the amount of ball returned; w 22 Real-time return ball flow rate; t1 and t2 are a certain time period; T21 is the running time of the same batch of pellets from the total measuring belt scale to the return ball measuring belt scale, which is a fixed value.

[0087] Typically, each pelletizing production line has multiple pelletizing trays, and due to differences in various process parameters, the pellet output rate varies from tray to tray. Each pelletizing tray needs to be equipped with a pellet size detection device to monitor the pellet diameter (d) and its corresponding quantity in real time. The pellets produced by the pelletizing tray can be considered standard pellets, and their volume can be calculated using the pellet volume formula. Since the density of the pellets is a measurable fixed value, the mass of the pellets can be calculated based on their volume.

[0088] The feed rate W entering the i-th pelletizing pan i for:

[0089]

[0090] Among them, w i (t) represents the real-time feed flow rate of the i-th pelletizing disc; t1 and t2 represent a certain time period.

[0091] The water flow rate F entering the i-th pelletizing machine i for:

[0092]

[0093] Where, f i (t) represents the real-time water flow rate to the pelletizing tray.

[0094] The mass of qualified green pellets produced by the i-th pelletizing machine after a time T is M. i for:

[0095]

[0096] Where, d k This represents a ball with a diameter of km; n k The number of balls with a diameter of km; these two parameters are obtained in real time by the particle size measuring device; ρ is the pellet density, which can be obtained by analysis, and is a fixed value when the pelletizing raw materials remain unchanged.

[0097] The ball-forming rate η of the i-th ball-forming machine i for:

[0098]

[0099] Formulas (4)-(7) can be used to calculate the real-time ball formation rate of each ball-forming plate, providing data support for the subsequent calculation of the overall ball formation rate.

[0100] The pelletizing rate is calculated by combining the output and pelletizing rate data of each pellet production to determine the pelletizing rate of the entire system. This calculation method is independent of the return volume, so the result is obtained earlier than the traditional calculation method (1).

[0101] Typically, each pelletizing production line has multiple pelletizing trays. If there are n pelletizing trays, the total pelletizing rate η is... 系2 for:

[0102]

[0103]

[0104] Where: a is the proportionality coefficient; W 1i η represents the total amount of raw materials in the i-th pelletizing disc over a given period of time; i w represents the ball formation rate of the i-th ball-forming plate. 1i (t) represents the feed flow rate of the i-th pelletizing disc; f i (t) represents the water flow rate of the i-th pelletizing plate; T1k represents the time required from the start of pellet production from the k-th pelletizing plate to the start of production from the next pelletizing plate.

[0105] The theoretical ball-forming rate of the system calculated by the two methods is equal, that is:

[0106] η 系1 =η 系2 (10)

[0107] The proportional coefficient a can be calculated using formula (10). Once the proportional coefficient is calculated, the ball formation rate of the system can be calculated using formula (8). The ball formation rate calculated by this method is earlier than that calculated by the traditional method, and can provide timely feedback on the real-time ball formation rate. When the ball formation rate decreases, adjustments can be made in time. After the adjustment, the ball formation rate of the ball-making plate can be intuitively fed back, ensuring the overall ball formation rate.

[0108] Please see Figures 1 to 4 This application provides a method for measuring the particle size of granules, the method comprising:

[0109] S1. Collect ball size data and ball quantity data by using a ball size detection device pre-set on the ball forming plate;

[0110] Specifically, the pellet size detection device is installed in a preset location, such as on the side of the pelletizing tray. The device is then activated to begin collecting pellet size data. The device collects pellet size data over a specific time period, recording the diameter and number of each pellet. The collected pellet size data and pellet count data are stored in a computer or data recording device for later use.

[0111] S2. Calculate the mass of qualified balls based on the ball size data to obtain the mass data of qualified balls;

[0112] Specifically, using the collected ball size data, the qualified ball mass calculation formula is applied to calculate the qualified ball mass of each ball.

[0113] S3. Obtain real-time feed flow rate data and real-time water supply data, and calculate the ball formation rate based on the real-time feed flow rate data, real-time water supply data and qualified ball quality data to obtain ball formation rate data;

[0114] Specifically, sensors or flow meters are installed to acquire real-time feed flow rate data and real-time water supply data. Using the real-time feed flow rate data, real-time water supply data, and qualified ball quality data, the ball formation rate is calculated for each time period using the ball formation rate calculation formula.

[0115] S4. Calculate the system ball formation rate based on the ball quantity data and the ball formation rate data to obtain the system ball formation rate data, and then adjust the ball-forming plate.

[0116] Specifically, using the ball quantity data and the calculated pelleting rate data, the system pelleting rate calculation formula is applied to calculate the system pelleting rate to reflect the performance of the entire pelleting process. Based on the system pelleting rate data, adjustments are made to the pelleting disc, such as modifying the operating parameters of the pelleting disc, such as rotation speed, wet material ratio, or additives, to improve the pelleting rate and quality.

[0117] This invention uses a pellet size detection device installed in each pelletizing pan to calculate the real-time pelletizing rate of each pan by detecting the real-time pellet size and quantity. The system's pelletizing rate is then calculated in real-time. This method provides results earlier than traditional methods, allowing for timely feedback on the current pelletizing rate. The method is simple and reliable; has low maintenance costs; requires fewer supporting devices; and is stable and reliable.

[0118] Optionally, the pellet size data includes first pellet size data and second pellet size data, and the pellet quantity data includes first pellet quantity data and second pellet quantity data. The step of collecting pellet size data and pellet quantity data using a pellet size detection device pre-installed on the pelletizing plate includes:

[0119] The first ball size and the number of balls are collected by a first ball size detection device that is preset on the side of the ball forming plate, so as to obtain the first ball size data and the first ball number data.

[0120] Specifically, a first pellet size detection device is installed on the side of the pelletizing disc. The first pellet size detection device is activated to begin collecting pellet size data. The device collects pellet size data over a specific time period and records the diameter and number of each pellet.

[0121] The second ball size detection device, positioned above the pelletizing plate, collects ball size data and ball quantity data to obtain the second ball size data and the second ball quantity data. The detection rate parameter data of the first ball size detection device is less than or equal to the detection rate parameter data of the second ball size detection device.

[0122] Specifically, a second pellet size detection device is installed above the pelletizing disc. The second pellet size detection device is then activated to begin collecting pellet size data. The device collects pellet size data over a specific time period and records the diameter and number of each pellet.

[0123] This invention utilizes two particle size detection devices positioned at different locations—a side position and an overhead position—to acquire more information about particle size, increasing the diversity of perspectives on the pelletizing process, improving the quality of initial data, and reducing the error rate of data detection. The first particle size detection device has a lower detection rate parameter, while the second has a higher one. These different rate parameters allow for flexible acquisition of particle size data under different conditions. The second particle size detection device can be used when more detailed data is needed, while the first device can be used under normal circumstances, thereby improving efficiency.

[0124] Optionally, the step of calculating the qualified ball mass based on the ball size data to obtain qualified ball mass data includes:

[0125] The qualified ball mass is calculated based on the ball size data using the qualified ball mass calculation formula; the qualified ball mass calculation formula is as follows:

[0126]

[0127] M i Let d be the qualified ball quality data corresponding to the i-th ball-making plate. 16 Here are the diameter data for a 16mm sphere, k is the sphere diameter data, d8 is the sphere diameter data for an 8mm sphere, π is the value of pi, and d... k For the diameter data of a sphere in kmm, n k ρ represents the number of spheres with a diameter of km, ρ represents the sphere density, and i represents the sphere-forming disk sequence.

[0128] This invention utilizes a formula for calculating the mass of qualified balls, enabling automated calculation without manual measurement or calculation, thus improving efficiency and reducing human error. Based on ball diameter and density information, the formula provides relatively accurate qualified ball mass data, ensuring product quality meets specified standards. By using this formula, different ball diameter data (d...) can be used to calculate the mass of qualified balls. kThis invention calculates the mass of qualified balls within different diameter ranges and produces qualified balls of varying diameters during the ball-making process. Compared to traditional techniques, this invention allows for the calculation of qualified balls upon exiting the ball tray, thereby increasing measurement efficiency.

[0129] Optionally, the step of acquiring real-time feed flow rate data and real-time water supply data, and calculating the pelleting rate based on the real-time feed flow rate data, real-time water supply data, and the qualified ball quality data to obtain pelleting rate data, includes:

[0130] S31. Obtain real-time feed flow rate data, and calculate the feed amount based on the real-time feed flow rate data to obtain feed amount data, wherein the feed amount data is calculated using a feed amount calculation formula; wherein the feed amount calculation formula is specifically:

[0131]

[0132] W i Here, t2 represents the feed rate data corresponding to the i-th pelletizing disc, t1 represents the upper limit of the feed rate time, and w represents the lower limit of the feed rate time. i (t) represents the real-time feed flow rate data, t represents the feed rate time data, and i represents the pelletizing disc sequence item;

[0133] S32. Obtain real-time water supply data, and calculate the water supply based on the real-time water supply data to obtain water supply data, wherein the water supply data is calculated using a water supply calculation formula; wherein the water supply calculation formula is specifically:

[0134]

[0135] F i For the water supply data corresponding to the i-th pelletizing plate, f i (t) represents the real-time water supply data, t2 represents the upper limit of the feed rate time, t1 represents the lower limit of the feed rate time, t represents the feed rate time data, and i represents the pelleting disc sequence item.

[0136] S33. The pelleting rate is calculated based on the feed rate data, the water supply data, and the qualified ball quality data to obtain pelleting rate data; wherein the pelleting rate is calculated using a pelleting rate calculation formula, and the specific pelleting rate calculation formula is as follows:

[0137]

[0138] η i M represents the ball formation rate data corresponding to the i-th ball-forming plate. i W represents the qualified ball quality data corresponding to the i-th ball-making plate. iFor the feed rate data of the i-th pelletizing disc, F i The water supply data is denoted as i, and the pelletizing disc sequence number is denoted as i.

[0139] This invention utilizes real-time data on feed flow rate, water supply, and qualified pellet quality to calculate the real-time pelleting rate. This facilitates timely monitoring of changes in the pelleting rate during the pelleting process, enabling prompt adjustments and control. The invention employs formulas for calculating feed and water supply, which accurately calculate real-time data, thus improving the accuracy of pelleting rate calculation. By combining qualified pellet quality, feed rate, and water supply data to calculate the pelleting rate, the influence of various factors on the pelleting rate can be considered, leading to a better understanding of the overall performance of the pelleting process. Real-time monitoring of the pelleting rate helps the production process operate more efficiently, ensures product quality meets specified standards, reduces scrap rates, and improves product consistency.

[0140] Optionally, the step of calculating the system ball formation rate based on the ball quantity data and the ball formation rate data to obtain the system ball formation rate data includes:

[0141] The system ball formation rate is calculated based on the ball quantity data and the ball formation rate data to obtain the system ball formation rate data; wherein the system ball formation rate is calculated using the system ball formation rate calculation formula, and the specific system ball formation rate calculation formula is as follows:

[0142]

[0143] Here, 'a' represents the system's pelleting rate data, 'i' represents the pelleting tray sequence, 'n' represents the number of pelleting trays, and 'W' represents the number of pelleting trays. 1i Let η be the total amount of raw materials in the i-th pelletizing disc over a certain period of time. i This represents the ball formation rate data corresponding to the i-th ball-forming plate;

[0144]

[0145] W 1i This refers to the total amount of raw materials generated by the i-th pelletizing disc over a given period of time. Let i be the ball release time data for the i-th ball-making board. For the goal-scoring time data of the i-th ball-creating plate, T 1k This represents the time required from the moment a ball is produced from the k-th ball-producing tray to the moment a ball is produced from the next ball-producing tray, where i is the ball-producing tray order, k is the ball-producing tray order, and w is the time required. 1i (t) represents the inflow rate data of the i-th pelleting plate, f 1i (t) represents the water flow rate data for the i-th pelletizing plate.

[0146] In this invention, the pelleting rate is calculated by combining the output and pelleting rate data of each pellet-making unit to determine the overall pelleting rate of the system. This calculation method is independent of the number of returned pellets, so the result is obtained earlier than traditional methods. The calculated pelleting rate is earlier than traditional calculations, providing timely feedback on the real-time pelleting rate. When the pelleting rate decreases, adjustments can be made promptly, and the results provide a clear indication of how much the pelleting rate of that particular pellet-making unit has improved, ensuring the overall pelleting rate. This method uses real-time data for calculation, including real-time pellet quantity and pelleting rate data, allowing for continuous updating and monitoring of the system's pelleting rate data to understand changes in the pellet-making process.

[0147] Optionally, the step of generating the proportional coefficient data includes the following steps:

[0148]

[0149]

[0150]

[0151]

[0152] 'a' represents the proportionality coefficient data. i represents the order of the pelletizing trays, n represents the number of pelletizing trays, and W... 1i Let η be the total amount of raw materials in the i-th pelletizing disc over a certain period of time. i W represents the ball formation rate data corresponding to the i-th ball-forming plate. 21 For total ball output data, W 22 For total return volume data, w 21 (t) represents the real-time ball output data. For real-time ball return data, This refers to the upper time limit data corresponding to the real-time ball output data. T represents the lower limit of the time period corresponding to the real-time ball output data. 21 This data represents the running time of the same batch of pellets from the total measuring belt scale to the return measuring belt scale.

[0153] This invention obtains a proportional system based on traditional calculation methods, providing accurate data support. The system's ball-forming rate, calculated using traditional formulas and the method employed in this invention, is theoretically equal and is obtained through conversion. The step of generating the proportional coefficient data is automated, requiring no manual intervention or calculation, thus improving efficiency and reducing human error. Furthermore, the data is pre-calculated.

[0154] Optionally, the pelleting disc adjustment operation includes the following steps:

[0155] S401. Calculate the rate of change of the ball formation rate data of the system to obtain the rate of change of the ball formation rate data of the system.

[0156] Specifically, the rate of change of the system's ball formation rate = (current system ball formation rate - previous system ball formation rate) time interval.

[0157] S402. When it is determined that the system pelletizing rate data is less than or equal to a preset first system pelletizing rate threshold data and the system pelletizing rate data is greater than a preset second system pelletizing rate threshold data, pelletizing disc adjustment data is generated based on the system pelletizing rate change rate data, the real-time feed flow rate data, and the real-time water supply data, so as to perform pelletizing disc parameter control and adjustment operations, wherein the first system pelletizing rate threshold data is greater than the second system pelletizing rate threshold data;

[0158] Specifically, historical system pelleting rate data was analyzed, revealing a significant decrease in pelleting rate under certain time periods or operating conditions. By comparing the system pelleting rate with real-time feed flow rate and water supply data, the data trends were identified. Trend 1: Under certain high feed flow rates, the system pelleting rate decreased. Trend 2: Under lower water supply conditions, the system pelleting rate also decreased. Adjustment strategies were developed: Based on the data analysis results, adjustments were made according to preset instructions: For Trend 1: During high feed flow rates, the rotation speed of the pelletizing disc was reduced to lessen the mechanical load on the pelletizing process and prevent the pellets from becoming too large or uneven. For Trend 2: The planned increase in water supply was to increase the wet material ratio, thereby improving the pellet size distribution.

[0159] Specifically, assuming the system pelleting rate is 85%, the first system pelleting rate threshold is 90%, and the second system pelleting rate threshold is 80%, the system pelleting rate change rate data indicates a recent decrease in pelleting rate. Real-time feed flow data shows a high current feed flow rate, while real-time water supply data shows a low current water supply rate. Based on the above data and conditions: the system pelleting rate is less than or equal to the first system pelleting rate threshold (85% <= 90%), and the system pelleting rate is greater than the second system pelleting rate threshold (85% > 80%). Therefore, the following conditions are met: the system pelleting rate is less than or equal to the first system pelleting rate threshold and the system pelleting rate is greater than the second system pelleting rate threshold. In this case, according to preset instructions and strategies, the pelleting disc parameters can be adjusted to improve the system pelleting rate. Specific adjustment strategies include reducing the rotation speed of the pelleting disc to reduce mechanical load.

[0160] Increase the water supply to improve the proportion of wet material and improve the particle size distribution.

[0161] Specifically, let's assume the system's ball formation rate is 85%. Let's assume the first system's ball formation rate threshold is 90%. Let's assume the second system's ball formation rate threshold is 80%. Let's assume the system's ball formation rate change rate is -2%. Based on the above data: the system's ball formation rate is less than or equal to the first system's ball formation rate threshold (85% ≤ 90%). Simultaneously, the system's ball formation rate is greater than the second system's ball formation rate threshold (85% > 80%).

[0162] S403. When it is determined that the ball formation rate data of the system is less than or equal to the preset second system ball formation rate threshold data, a ball forming disc detection operation is performed.

[0163] Specifically, stop the pelletizing tray operation. Activate the camera located on one side of the pelletizing tray to acquire image data. Perform image processing and analysis on the acquired image data, including preset image preprocessing, feature extraction, clustering calculation, Gaussian distribution calculation, and similarity calculation. Based on the image analysis results, determine if there are any problems or anomalies in the pelletizing tray, such as uneven pellet size distribution or substandard pellet shape. If an anomaly is detected, the system will trigger an alarm or notify the operator for further inspection and maintenance.

[0164] Specifically, vibration sensors are used to monitor the vibration of the ball-making machinery. If the ball-making disc malfunctions or produces balls unevenly, it will cause changes in the vibration pattern. By analyzing the vibration data, abnormalities can be detected.

[0165] This invention enables real-time pelletizing process control by monitoring the system's pelletizing rate and its rate of change, as well as real-time feed flow and water supply data. This facilitates timely detection of problems and the implementation of corrective measures during pelletizing. The calculation of the system's pelletizing rate change rate takes into account the dynamic changes in the pelletizing rate, thus providing more accurate guidance to determine when adjustments to the pelletizing disc parameters are needed. Based on the system's pelletizing rate data and thresholds, the efficiency and quality of the pelletizing process can be monitored and controlled. If the system's pelletizing rate falls below the threshold, corrective measures can be taken to improve the pelletizing process. By dynamically adjusting the pelletizing disc parameters, raw materials and resources can be better utilized, thereby improving production efficiency and reducing costs.

[0166] Optionally, the pelletizing disc inspection operation includes the following steps:

[0167] S4031. Activate the camera preset on one side of the pelletizing tray to acquire images and obtain pelletizing tray image data;

[0168] Specifically, a camera is installed on one side of the pelletizing tray and activated to capture image data from the tray. The camera's position and angle should be pre-set to ensure that image data from the pelletizing tray can be captured.

[0169] S4032. Perform image preprocessing on the ball-forming disk image data according to the preset standard ball-forming disk image data to obtain ball-forming disk image preprocessing data.

[0170] Specifically, the acquired pelleting disc image data is preprocessed using preset standard pelleting disc image data to better extract pellet size information. Preprocessing includes color correction, brightness adjustment, and noise reduction to make the image clearer and reduce interference.

[0171] S4033. Perform feature extraction on the standard ball-forming disk image data and the preprocessed ball-forming disk image data to obtain standard ball-forming disk image feature data and ball-forming disk image feature data, respectively.

[0172] Specifically, features are extracted from standard pelleting disc image data and preprocessed pelleting disc image data, including color distribution, texture features, size, and location of the pelleting disc. Feature extraction methods can utilize computer vision techniques such as feature detectors and descriptors.

[0173] Specifically, color features in an image are described using color histograms or statistical information about color channels, such as color histograms, color mean, and color standard deviation to describe color distribution. Texture features are used to describe texture information in an image, such as the surface texture of a sphere-forming disk, using methods including Gray-Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP), and Histogram of Oriented Gradients (HOG). Shape and contour information of objects in an image are detected, including edge detection, shape fitting, and contour extraction.

[0174] S4034. Perform clustering calculations on the standard ball-forming disk image feature data and the ball-forming disk image feature data to obtain standard ball-forming disk image clustering data and ball-forming disk image clustering data, respectively.

[0175] Specifically, using the extracted feature data, clustering calculations are performed on the feature data of the standard ball-forming disk image and the feature data of the ball-forming disk image to classify similar images into the same category, including K-means clustering, hierarchical clustering, etc.

[0176] S4035. Perform Gaussian distribution calculation on the standard ball-forming disk image clustering data and the ball-forming disk image clustering data to obtain standard ball-forming disk image Gaussian distribution data and ball-forming disk image Gaussian distribution data.

[0177] Specifically, Gaussian distribution calculations were performed on the standard ball-forming disk image clustering data and the ball-forming disk image clustering data to establish a Gaussian model for each category. The Gaussian distribution model is used to describe the image feature distribution of each category for subsequent similarity calculations.

[0178] S4036. Calculate the similarity between the Gaussian distribution data of the standard ball-forming disk image and the Gaussian distribution data of the ball-forming disk image to obtain similarity data;

[0179] Specifically, Gaussian distribution data was used to calculate the similarity between standard ball-forming disk images and ball-forming disk images. The similarity was measured using statistical methods, such as Kullback-Leibler divergence or Jensen-Shannon distance.

[0180] S4037. When it is determined that the similarity data is greater than or equal to the preset similarity threshold data, then a functional check of the pelleting tray is performed based on the real-time feed flow data and the real-time water supply data.

[0181] Specifically, if the similarity data is greater than or equal to a preset similarity threshold, it indicates that the current pelletizing disc image is similar to the standard image, and the process proceeds to the next step. Based on the similarity data, it is determined that the current pelletizing disc image is similar to the standard image. Then, functional checks are performed based on real-time feed flow rate data and real-time water supply data, including checking parameters such as the quality, quantity, and particle size of the pellets, to ensure that the pelletizing process operates normally.

[0182] S4038. When it is determined that the similarity data is less than the preset similarity threshold data, an early warning operation is performed on the ball-forming device.

[0183] Specifically, if the similarity data is less than a preset similarity threshold, it indicates that the current pelletizing disc image is not similar enough to the standard image, and there is a problem. In this case, the device is triggered to issue an early warning, notifying relevant personnel to conduct inspection and maintenance.

[0184] This invention provides an accurate assessment of the pelletizing tray's condition through image feature extraction and similarity calculation, facilitating the accurate identification of problems or anomalies. By setting a similarity threshold, anomalies in the pelletizing tray can be detected early, before problems escalate, thus reducing losses. Based on the detection results, targeted maintenance or early warning operations can be performed to optimize resource utilization, reduce downtime, and improve production efficiency. Compared to traditional image comparison methods, this invention employs a depth-based algorithm, providing data accuracy. Compared to other depth-based algorithms, it reduces the load on computing equipment and improves practicality.

[0185] Optionally, the step of performing image preprocessing on the pelletizing disc image data according to preset standard pelletizing disc image data to obtain pelletizing disc image preprocessing data includes:

[0186] Based on the preset standard pelletizing plate image data, the hue and saturation of the pelletizing plate image data are processed to obtain the hue and saturation adjustment data of the pelletizing plate image.

[0187] Specifically, for hue and saturation processing, standard image processing tools and algorithms can be used, such as converting to the HSV (Hue, Saturation, Lightness) color space. The hue and saturation values ​​are then adjusted to better match the standard image. Finally, the image is converted back to the RGB color space to obtain the adjusted image.

[0188] Histogram equalization is performed on the hue and saturation adjustment data of the ball-forming disk image to obtain the brightness adjustment data of the ball-forming disk image;

[0189] Specifically, histogram equalization is a method used to enhance image contrast. This step involves: converting the image to grayscale; calculating the histogram of the grayscale image to understand the distribution of different gray levels; applying a histogram equalization algorithm to balance the brightness distribution of the different gray levels; and finally, converting the equalized image back to a color image.

[0190] Color correction processing is performed on the brightness adjustment data of the ball-forming disk image to obtain preprocessed data of the ball-forming disk image.

[0191] Specifically, color correction aims to adjust the colors of an image to match a standard image. Implementation may include the following steps: determining the color channels that need correction (e.g., red, green, and blue channels); calculating the color offsets that need adjustment using the standard image as a reference; applying the offsets to the corresponding color channels of the image to correct the colors; and converting the image back to its original color space.

[0192] This invention enhances the color information of an image by adjusting its hue and saturation, making the image clearer and facilitating better identification of the characteristics and problems of the ball-making disc. Histogram equalization enhances image contrast and improves brightness distribution, making the image easier to analyze, especially when the original image is under uneven lighting or has low contrast, which could easily lead to errors without processing. Color correction ensures that the color information in the image accurately reflects the real situation, helping to more accurately identify and analyze the image features of the ball-making disc.

[0193] Optionally, this application also provides a system for measuring the particle size of granules, used to perform the particle size measurement method described above, the system comprising:

[0194] The data acquisition module is used to acquire ball size data and ball quantity data through a ball size detection device pre-installed on the ball forming plate, and obtain ball size data and ball quantity data.

[0195] The qualified ball mass calculation module is used to calculate the qualified ball mass based on the ball diameter data to obtain the qualified ball mass data.

[0196] The pelleting rate calculation module is used to acquire real-time feed flow rate data and real-time water supply data, and to calculate the pelleting rate based on the real-time feed flow rate data, real-time water supply data and qualified pellet mass data to obtain pelleting rate data;

[0197] The system ball formation rate calculation module is used to calculate the system ball formation rate based on the ball quantity data and the ball formation rate data, and obtain the system ball formation rate data for ball formation tray adjustment operations.

[0198] The purpose of this invention is to detect the particle size of pellets in the pelletizing area of ​​a pelletizing disc, calculate the mass of qualified pellets based on the particle size, and calculate the pelletizing rate of each pelletizing disc in conjunction with the feed rate. The pelletizing rates of all pelletizing discs are statistically analyzed, and the measured pelletizing rate is calculated and compared with the pelletizing rate calculated by traditional methods. The pelletizing rate is analyzed, and the pelletizing rate of each pelletizing disc is calculated in real time. When the pelletizing rate of a particular disc decreases, feedback is provided for timely adjustment of the pelletizing disc. By installing a pellet size detection device on each pelletizing disc, the real-time pellet size and quantity detected by this device are used to calculate the real-time pelletizing rate of each pelletizing disc; then, the system's pelletizing rate is calculated in real time. This method provides results earlier than traditional methods of calculating pelletizing rate and can provide timely feedback on the current pelletizing rate status. This method is simple and reliable; has low maintenance costs; requires fewer supporting equipment; and is stable and reliable.

[0199] Therefore, the embodiments should be regarded as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended application documents rather than the foregoing description. Thus, it is intended that all variations falling within the meaning and scope of the equivalents of the application documents be incorporated into the invention.

[0200] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method for measuring the particle size of granules, characterized in that, The method includes: The ball size data and the ball number data are collected by a ball size detection device pre-installed on the ball forming plate. The qualified ball mass is calculated based on the ball size data to obtain the qualified ball mass data; Acquire real-time feed flow rate data and real-time water supply data, and calculate the ball formation rate based on the real-time feed flow rate data, real-time water supply data and qualified ball mass data to obtain ball formation rate data; Based on the ball quantity data and the ball formation rate data, the system ball formation rate is calculated to obtain system ball formation rate data for ball formation tray adjustment. The system ball formation rate is calculated using a system ball formation rate calculation formula, which is as follows: ； For the system's ball formation rate data, For proportionality coefficient data, For the order of the ball-making plate, For the number of balls produced, For the first Data on the total amount of raw materials in a pelletizing pan over a period of time. For the first Data on the ball formation rate corresponding to each ball-forming tray; ； For the first Data on the total amount of raw materials in a pelletizing pan over a period of time. For the first Data on the ball release time of each ball-creating table. For the first The goal-scoring time data for each goal-creating line. This represents the time required from the moment a ball is produced from the k-th ball-making tray to the moment a ball is produced from the next ball-making tray. For the order of the ball-making plate, The order of ball production in the ball-making board. For the first Individual ball-making plate inflow data For the first Data on water flow rate for each pelletizing disc; The steps for generating the proportional coefficient data include the following: ； ； ； ； The aforementioned proportionality coefficient data, The ball formation rate calculated using traditional methods. For the order of the ball-making plate, For the number of balls produced, For the first Data on the total amount of raw materials in a pelletizing pan over a period of time. For the first Ball formation rate data corresponding to each ball-forming plate. For total number of balls played, This refers to the total number of returns. For real-time ball output data, For real-time ball return data, This refers to the upper time limit data corresponding to the real-time ball output data. This is the lower limit of the time corresponding to the real-time ball output data. This data represents the running time of the same batch of pellets from the total measuring belt scale to the return measuring belt scale.

2. The method according to claim 1, characterized in that, The pellet size data includes first pellet size data and second pellet size data, and the pellet quantity data includes first pellet quantity data and second pellet quantity data. The process of collecting pellet size data and pellet quantity data using a pellet size detection device pre-installed on the pelletizing tray, to obtain pellet size data and pellet quantity data, includes: The first ball size and the number of balls are collected by a first ball size detection device that is preset on the side of the ball forming plate, so as to obtain the first ball size data and the first ball number data. The second ball size detection device, positioned above the pelletizing plate, collects ball size data and ball quantity data to obtain the second ball size data and the second ball quantity data. The detection rate parameter data of the first ball size detection device is less than or equal to the detection rate parameter data of the second ball size detection device.

3. The method according to claim 1, characterized in that, The step of calculating the qualified ball mass based on the ball size data to obtain qualified ball mass data includes: The qualified ball mass is calculated based on the ball size data using the qualified ball mass calculation formula; the qualified ball mass calculation formula is as follows: ； For the first The quality data of qualified balls corresponding to each ball-making tray. The data is for a ball with a diameter of 16mm. For sphere diameter data, For a ball with a diameter of 8mm, For pi data, For sphere diameter data in mm, This represents the number of spheres with a diameter of km. For spherical density data, This is the sequence number of the ball-making board.

4. The method according to claim 1, characterized in that, The process of acquiring real-time feed flow rate data and real-time water supply data, and calculating the pelleting rate based on the real-time feed flow rate data, real-time water supply data, and qualified pellet mass data to obtain pelleting rate data includes: Real-time feed flow rate data is acquired, and the feed quantity is calculated based on the real-time feed flow rate data to obtain feed quantity data. The feed quantity data is calculated using a feed quantity calculation formula; specifically, the feed quantity calculation formula is as follows: ； For the first The feed rate data corresponding to each pelletizing disc This refers to the upper limit of the feed rate over time. This is the lower limit data for the feed rate over time. The real-time feed flow rate data, This is the feed rate over time data. This refers to the order of the ball-making process. Real-time water supply data is acquired, and water supply is calculated based on the real-time water supply data to obtain water supply data. The water supply data is calculated using a water supply calculation formula; specifically, the water supply calculation formula is as follows: ； For the first The water supply data corresponding to each pelletizing plate. The real-time water supply data, This refers to the upper limit of the feed rate over time. This is the lower limit data for the feed rate over time. This is the feed rate over time data. The ball-forming disk sequence item; The pelleting rate is calculated based on the feed rate data, the water supply data, and the qualified pellet mass data to obtain pelleting rate data; wherein the pelleting rate is calculated using a pelleting rate calculation formula, and the specific pelleting rate calculation formula is as follows: ； For the first Ball formation rate data corresponding to each ball-forming plate. For the first The quality data of qualified balls corresponding to each ball-making tray. For the first The feed rate data for each pelletizing disc, The water supply data, This refers to the order of the ball-forming disk.

5. The method according to claim 1, characterized in that, The pelleting tray adjustment operation includes the following steps: The change rate of the ball formation rate of the system is calculated to obtain the change rate data of the ball formation rate of the system. When the system pelleting rate data is determined to be less than or equal to a preset first system pelleting rate threshold data and the system pelleting rate data is greater than a preset second system pelleting rate threshold data, pelleting disc adjustment data is generated based on the system pelleting rate change rate data, the real-time feed flow rate data, and the real-time water supply data to perform pelleting disc parameter control and adjustment operations, wherein the first system pelleting rate threshold data is greater than the second system pelleting rate threshold data; If the ball formation rate data of the system is determined to be less than or equal to the preset second system ball formation rate threshold data, then a ball forming disc detection operation is performed.

6. The method according to claim 5, characterized in that, The pelleting tray inspection operation includes the following steps: The camera preset on one side of the pelletizing tray is activated to capture images and obtain image data of the pelletizing tray; The image data of the ball-forming disk is preprocessed according to the preset standard ball-forming disk image data to obtain ball-forming disk image preprocessing data; Feature extraction is performed on the standard ball-forming disk image data and the preprocessed ball-forming disk image data to obtain standard ball-forming disk image feature data and ball-forming disk image feature data, respectively. Clustering calculations are performed on the standard ball-forming disk image feature data and the ball-forming disk image feature data to obtain standard ball-forming disk image clustering data and ball-forming disk image clustering data, respectively; Gaussian distribution calculations are performed on the standard ball-forming disk image clustering data and the ball-forming disk image clustering data to obtain standard ball-forming disk image Gaussian distribution data and ball-forming disk image Gaussian distribution data; Similarity data is obtained by performing similarity calculation on the Gaussian distribution data of the standard ball-forming disk image and the Gaussian distribution data of the ball-forming disk image. When the similarity data is determined to be greater than or equal to the preset similarity threshold data, a functional check of the pelleting tray is performed based on the real-time feed flow rate data and the real-time water supply data. If the similarity data is determined to be less than a preset similarity threshold, an early warning operation is performed on the ball-forming device.

7. The method according to claim 6, characterized in that, The step of performing image preprocessing on the pelletizing disc image data according to preset standard pelletizing disc image data to obtain pelletizing disc image preprocessing data includes: Based on the preset standard pelletizing plate image data, the hue and saturation of the pelletizing plate image data are processed to obtain the hue and saturation adjustment data of the pelletizing plate image. Histogram equalization is performed on the hue and saturation adjustment data of the ball-forming disk image to obtain the brightness adjustment data of the ball-forming disk image; Color correction processing is performed on the brightness adjustment data of the ball-forming disk image to obtain preprocessed data of the ball-forming disk image.

8. A system for measuring the particle size of spherical particles, characterized in that, For performing the method for measuring the spherical particle size as described in claim 1, the spherical particle size measuring system comprises: The data acquisition module is used to acquire ball size data and ball quantity data through a ball size detection device pre-installed on the ball forming plate, and obtain ball size data and ball quantity data. The qualified ball mass calculation module is used to calculate the qualified ball mass based on the ball diameter data to obtain the qualified ball mass data. The pelleting rate calculation module is used to acquire real-time feed flow rate data and real-time water supply data, and to calculate the pelleting rate based on the real-time feed flow rate data, real-time water supply data and qualified pellet mass data to obtain pelleting rate data. The system ball formation rate calculation module is used to calculate the system ball formation rate based on the ball quantity data and the ball formation rate data, and obtain the system ball formation rate data for ball formation tray adjustment operations.

Images