A real-time dynamic simulation method for sand mill based on clustering algorithm

Abstract

The present invention relates to the field of sanding simulation technology, and discloses a real-time dynamic simulation method for a sand mill based on a clustering algorithm, including: fitting a sand mill database based on a dynamic simulation environment, obtaining sand mill material parameters, wherein the sand mill material parameters include: reference material type, reference material particles, reference material temperature, reference particle diameter and comprehensive fitting ratio, retrieving a target sand mill parameter group in the sand mill database based on the sand mill material parameters, setting a target sand mill using the target sand mill parameter group, using the target sand mill to perform sand milling operations on the sand mill material, and using a dynamic monitoring unit to obtain the sand milling temperature and sand milling vibration of the sand milling material in real time, and after confirming that the sand milling temperature and sand milling vibration are respectively less than or equal to the reference material temperature and a preset vibration threshold, the sand milling of the sand mill material is realized. The main purpose of the present invention is to solve the problem of inaccurate sand mill parameter setting and energy waste when using the sand mill.

Description

Technical Field

[0001] The invention relates to a real-time dynamic simulation method for a sand mill based on a clustering algorithm, and belongs to the technical field of sand mill simulation. Background Art

[0002] Sand mill is a key equipment for the preparation of ultrafine powders. The performance of sand mill will directly affect the refinement degree and production efficiency of ultrafine powders. With the increasing frequency of use of sand mills, more and more sand mills are wasted due to inaccurate parameter settings during use. Therefore, how to use sand mills to sand materials and save energy during sand grinding has become an urgent problem to be solved.

[0003] The existing method for setting the parameters of a sand mill during sand grinding is mainly as follows: the sand mill operator sets the parameters of the sand mill based on his / her own operating experience and the parameters recommended by the sand mill manufacturer.

[0004] Although the above method can realize the setting of the sand mill parameters, it is difficult to set the parameters that meet the needs of each material when setting the parameters of the sand mill. In addition, due to the difference in experience of the sand mill operators, the parameters of the sand mill are inaccurately set, and there is a problem of energy waste when using the sand mill. Summary of the invention

[0005] The present invention provides a real-time dynamic simulation method and device for a sand mill based on a clustering algorithm, and a computer-readable storage medium, the main purpose of which is to solve the problems of inaccurate parameter setting of the sand mill and energy waste when using the sand mill.

[0006] To achieve the above object, the present invention provides a real-time dynamic simulation method for a sand mill based on a clustering algorithm, comprising:

[0007] Receiving a dynamic simulation instruction, and confirming a dynamic simulation environment based on the dynamic simulation instruction, wherein the dynamic simulation environment includes: one or more sand mills and a dynamic simulation system, wherein the dynamic simulation system includes: a dynamic fitting unit, a dynamic monitoring unit and a dynamic feedback unit;

[0008] Fit the sand grinding database based on the dynamic simulation environment;

[0009] Confirming receipt of a dynamic fitting instruction from a dynamic fitting unit, parsing the dynamic fitting instruction, and obtaining sanding material parameters of the material to be sanded, wherein the sanding material parameters include: reference material type, reference material particles, reference material temperature, reference particle diameter, and comprehensive fitting ratio, wherein the comprehensive fitting ratio refers to the ratio of the size of the material to be sanded after the sanding operation is performed on the material to be sanded to be less than or equal to a certain reference particle diameter;

[0010] Based on the sanding material parameters, an initial sanding parameter set is retrieved from a sanding database, and a target sanding parameter set is confirmed using the initial sanding parameter set;

[0011] A target sanding machine is set by using the target sanding parameter group, wherein the parameters of the target sanding machine when performing the sanding operation are set as the target sanding parameter group;

[0012] The target sand mill is used to perform a sanding operation on the material to be sanded, and the sanding temperature and sanding vibration of the material to be sanded are obtained in real time by using a dynamic monitoring unit. After confirming that the sanding temperature and the sanding vibration are respectively less than or equal to the reference material temperature and a preset vibration threshold, the dynamic feedback unit is used to send the sanding temperature and the sanding vibration to the initiator of the dynamic simulation instruction, so as to realize the sanding of the material to be sanded;

[0013] The step of fitting a sand grinding database based on a dynamic simulation environment includes:

[0014] For each of the one or more sand mills, perform the following operations:

[0015] Obtaining a manufacturing parameter set of a sand mill, wherein the manufacturing parameter set includes: a size parameter set, a material parameter set and an execution standard;

[0016] Performing a labeling operation on the sand mill using the manufacturing parameter set to obtain a labeled sand mill;

[0017] Summarize the identified sand mills to obtain one or more identified sand mills, and fit a sand mill database based on the one or more identified sand mills;

[0018] Wherein, fitting a sand mill database based on the one or more identified sand mills comprises:

[0019] The following operations are performed for each of the one or more marking sand mills:

[0020] Obtain a sanding parameter range set of an identified sanding mill, wherein the sanding parameter range set includes multiple sanding parameter ranges, wherein the multiple sanding parameter ranges are: one or more material reference ranges, a rotation speed range, one or more sanding medium ranges, a sanding time range, a material feed speed range, and a cooling water temperature range, wherein the sanding medium range includes a sanding medium type and a sanding medium particle range, and the material reference range includes a material particle type and a material particle range;

[0021] Extract sanding parameter ranges from the multiple sanding parameter ranges in sequence, and perform the following operations on the extracted sanding parameter ranges:

[0022] Acquire a first dividing threshold for dividing the extracted sanding parameter range, and perform a dividing operation on the sanding parameter range using the first dividing threshold to obtain a first sanding value set, wherein the first sanding value set includes a plurality of first sanding values;

[0023] Summarizing the first sanding value sets to obtain a plurality of first sanding value sets, wherein the first sanding value sets correspond to the sanding parameter ranges one by one;

[0024] A plurality of first sanding value sets and a pre-constructed control variable method are used to obtain a plurality of sanding parameter groups, and the following operations are performed on each of the plurality of sanding parameter groups:

[0025] The fitting sand mill and target sanding particles are obtained by using the sanding parameter group and the identification sand mill, and the fitting sand mill is used to perform a sanding operation on the target sanding particles, and the fitting sanding time is recorded in real time with the time of performing the sanding operation as the time starting point, and the sanding temperature set and the sanding vibration set of the fitting sand mill are monitored by using a pre-constructed monitoring site set and a preset monitoring frequency, until the fitting sanding time reaches the first sanding value corresponding to the sanding time range in the sanding parameter group, and the first sanding material is obtained, wherein the monitoring site set includes a plurality of monitoring sites, the sanding temperature set includes a plurality of sanding temperature time series groups, and the sanding temperature time series group includes a plurality of sanding temperature values, the sanding vibration set includes a plurality of sanding vibration time series groups, and the sanding vibration time series group includes a plurality of sanding vibration values, and the sanding temperature values ​​and the sanding vibration values ​​correspond to the monitoring sites one by one;

[0026] After confirming that the fitting sand mill is a preset standard sand mill by using the sand milling temperature set, the first sand milling material and the sand milling vibration set, retaining the sand milling parameter group corresponding to the standard sand mill, and summarizing the retained sand milling parameter group to obtain an initial sand milling parameter set;

[0027] The sanding parameter groups in the initial sanding parameter set are summarized according to the variables corresponding to the control variable method to obtain multiple analysis parameter group sets, and a sanding database is constructed using the multiple analysis parameter group sets, wherein the analysis parameter group set includes multiple analysis parameter groups.

[0028] Optionally, the step of using the sanding temperature set, the first sanding material, and the sanding vibration set to confirm that the fitting sanding mill is a preset standard sanding mill comprises:

[0029] Using a pre-built mixer to perform a stirring operation on the first sand-milled material to obtain a stirred sand-milled material, and obtaining a plurality of test material samples based on the stirred sand-milled material;

[0030] A detection unit set for detecting a material diameter range is obtained, wherein the detection unit set includes a plurality of detection units, detection units are sequentially extracted from the detection unit set, and the following operations are performed on the extracted detection units:

[0031] Using the extracted detection units and the multiple detection material samples, a plurality of standard material ratios are obtained, wherein the standard material ratios correspond to the detection material samples one by one, and a material particle threshold for dividing the standard material ratios is preset, and the diameters of the material particles in the standard material ratios are all less than or equal to the material particle threshold;

[0032] The standard material proportions are summarized respectively using the detected material samples to obtain multiple analysis diameter ratio groups, wherein the analysis diameter ratio groups correspond one-to-one to the detected material samples, and the comprehensive standard proportions are calculated based on the multiple analysis diameter ratio groups and the pre-constructed comprehensive material proportion relationship formula, and the fitting sand mill is confirmed as the preset standard sand mill using the comprehensive standard proportions, sand milling temperature set and sand milling vibration set.

[0033] Optionally, the comprehensive material ratio relationship is as follows:

[0034] ;

[0035] in, represents the comprehensive standard ratio, Indicates that the detection unit has a total of A detection unit, Indicates the preset coefficients, Indicates the first Standard material ratio, Indicates shared Analyze the diameter ratio group, Indicates the first of multiple analysis diameter ratio groups Reference ratio value for each analyzed diameter ratio group.

[0036] Optionally, the step of confirming that the fitting sand mill is a preset standard sand mill by using the comprehensive standard ratio, the sand milling temperature set and the sand milling vibration set comprises:

[0037] Extracting sanding vibration time sequence groups from the plurality of sanding vibration time sequence groups in sequence, and performing the following operations on the extracted sanding vibration time sequence groups:

[0038] Extracting the maximum sanding vibration value from the extracted sanding vibration time series group to obtain an analysis vibration value, summarizing the analysis vibration values ​​to obtain a plurality of analysis vibration values, and summarizing the analysis vibration values ​​using the monitoring sites corresponding to each of the plurality of analysis vibration values ​​to obtain one or more analysis vibration value groups;

[0039] The following operations are performed for each of the one or more analysis vibration value groups:

[0040] For each analysis vibration value in the analysis vibration value group, perform the following operations:

[0041] Comparing the analyzed vibration value with a preset analyzed vibration threshold, if the analyzed vibration value is greater than the analyzed vibration threshold, marking the analyzed vibration value as a target vibration value, and summarizing the target vibration values ​​according to the monitoring sites corresponding to the target vibration values ​​to obtain a plurality of target vibration value groups;

[0042] The following operations are performed for each of the multiple target vibration value groups:

[0043] Based on the monitoring sites and sanding vibration set corresponding to the target vibration value group, a monitoring vibration time series group is obtained, and the target vibration time series group is extracted from the monitoring vibration time series group using the target vibration value group;

[0044] The target vibration duration is determined according to the target vibration time sequence group, one or more analysis temperature value groups are obtained using the multiple sanding temperature time sequence groups, and the following operations are performed on each of the one or more analysis temperature value groups:

[0045] For each sanding temperature value in the analysis temperature value group, perform the following operations:

[0046] Calculating the monitoring temperature using the sanding temperature value and a pre-constructed monitoring temperature relationship;

[0047] Acquire a target temperature duration based on the monitored temperature;

[0048] respectively comparing the target vibration duration with a preset vibration duration threshold, the target temperature duration with a preset temperature duration threshold, and the comprehensive standard ratio with a preset comprehensive ratio threshold;

[0049] If the target vibration duration is less than or equal to the vibration duration threshold and the target temperature duration is less than or equal to the preset temperature duration threshold and the comprehensive standard ratio is greater than or equal to the comprehensive ratio threshold;

[0050] It is then confirmed that the fitted sand mill is a standard sand mill.

[0051] Optionally, the monitoring temperature relationship is as follows:

[0052] ;

[0053] in, represents the monitoring temperature of the fitted sand mill, represents the temperature of the fitted sand mill surface, represents the thermal conductivity of the fitted sand mill, represents the contact area between the fitted sand mill and the air, Indicates the thickness of the wall corresponding to the sand mill, It represents the difference between the temperature of cooling water in the fitting sand mill and the temperature of the environment. represents the convective heat transfer coefficient, Indicates the temperature of cooling water. Indicates the temperature of the environment, represents the surface emissivity, represents the Boltzmann constant.

[0054] Optionally, determining the target vibration duration according to the target vibration timing group includes:

[0055] The monitoring time interval is obtained by using the monitoring frequency, and one or more reference vibration time sequence groups are obtained according to the target vibration time sequence group, wherein the reference vibration time sequence group includes multiple target vibration values, and the absolute difference between the times corresponding to two adjacent target vibration values ​​is the monitoring time interval;

[0056] Acquire one or more reference durations using the one or more reference vibration timing groups, wherein the reference durations correspond to the reference vibration timing groups one by one;

[0057] A target vibration duration is determined based on the one or more reference durations, wherein the target vibration duration is a maximum reference duration among the one or more reference durations.

[0058] Optionally, constructing a sanding database using the plurality of analysis parameter sets comprises:

[0059] The following operations are performed for each of the multiple analysis parameter sets:

[0060] Mapping the analysis parameter group in the analysis parameter group set to the pre-constructed reference coordinate system to obtain the target fitting point set, wherein the horizontal axis of the reference coordinate system is the variable corresponding to the analysis parameter group, and the vertical axis of the reference coordinate system is the comprehensive standard ratio;

[0061] A fitting model set for fitting a curve is obtained, wherein the fitting model set includes a plurality of fitting models, fitting models are sequentially extracted from the fitting model set, and the following operations are performed on the extracted fitting models:

[0062] A fitting curve is obtained based on the extracted fitting model and the target fitting point set, and a target parameter set is retrieved from the fitting curve using the analysis parameter set, wherein the target parameter set includes a plurality of target parameter groups, and the target parameter groups correspond to the analysis parameter groups one by one, and the values ​​of the variables corresponding to the target parameter groups are the same as the values ​​of the variables corresponding to the analysis parameter groups;

[0063] The target parameter set, the analysis parameter set and the pre-constructed comprehensive fitting relationship are used to calculate the comprehensive fitting value, the comprehensive fitting value is summarized to obtain the comprehensive fitting value set, and the target curve is obtained by using the comprehensive fitting value set, wherein the target curve is the fitting curve corresponding to the minimum comprehensive fitting value in the comprehensive fitting value set, the target curve is summarized to obtain multiple target curves, and the sanding database is obtained based on the multiple target curves, wherein the comprehensive fitting relationship is as follows:

[0064] ;

[0065] in, represents the comprehensive fitting value, Indicates that the analysis parameter group has analysis parameter groups, Indicates the target parameter set. The comprehensive standard ratio corresponding to each target parameter group, Indicates the first The comprehensive standard ratio corresponding to each analysis parameter group.

[0066] Optionally, the using the initial sanding parameter set to determine a target sanding parameter set includes:

[0067] Extracting initial sanding parameter groups from the initial sanding parameter group set in sequence, and performing the following operations on the extracted initial sanding parameter groups:

[0068] The energy consumption prediction value is calculated based on the extracted initial sanding parameters and the pre-constructed energy consumption evaluation relationship, wherein the energy consumption evaluation relationship is as follows:

[0069] ;

[0070] in, represents the predicted value of energy consumption, represents the sanding time in the initial sanding parameter group, It represents the unit energy consumption of the sand mill in the initial sand mill parameter group. represents the unit loss of sanding medium in the initial sanding parameter group, Indicates the unit energy consumption to maintain the cooling water temperature, represents the fixed energy consumption of the sanding medium in the initial sanding parameter group, All are preset coefficients;

[0071] The energy consumption prediction values ​​are summarized to obtain an energy consumption prediction value set, and a target sanding parameter group is confirmed using the energy consumption prediction value set, wherein the target sanding parameter group is an initial sanding parameter group corresponding to the minimum energy consumption prediction value in the energy consumption prediction value set.

[0072] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0073] at least one processor; and,

[0074] a memory communicatively connected to the at least one processor; wherein,

[0075] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to implement the above-mentioned real-time dynamic simulation method of a sand mill based on a clustering algorithm.

[0076] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned sand mill real-time dynamic simulation method based on clustering algorithm.

[0077] Compared with the problems described in the background technology, the present invention first receives a dynamic simulation instruction, and confirms a dynamic simulation environment based on the dynamic simulation instruction, wherein the dynamic simulation environment includes: one or more sand mills and a dynamic simulation system. It can be seen that the present invention considers the existence of one or more sand mills in the dynamic simulation environment when confirming the dynamic simulation environment, thereby laying a foundation for the embodiment of the present invention to be more widely adapted to different materials to be sanded. In addition, the present invention fits a sanding database based on the dynamic simulation environment, thereby retrieving one or more sanding machines and their parameters for sanding corresponding to different sanding materials and different sanding requirements through the sanding database, and when constructing the sanding database, it is considered that temperature and vibration may cause inaccuracy in the data used to construct the sanding database, therefore, after confirming that the fitted sanding machine is the standard sanding machine through the target vibration duration, the target temperature duration and the comprehensive standard ratio, the sanding parameter group corresponding to the standard sanding machine is obtained, and the relationship between the variables corresponding to the sanding parameter group and the comprehensive standard ratio used to evaluate the sanding effect can be characterized through the sanding parameter group, thereby improving the accuracy of the construction of the sanding database. The embodiment of the present invention confirms receiving a dynamic fitting instruction from a dynamic fitting unit, parses the dynamic fitting instruction, obtains sanding material parameters of the material to be sanded, retrieves an initial sanding parameter set from a sanding database based on the sanding material parameters, uses the initial sanding parameter set to confirm a target sanding parameter set, and uses the target sanding parameter set to set a target sanding machine, wherein the parameters of the target sanding machine when performing the sanding operation are set as the target sanding parameter group, uses the target sanding machine to perform the sanding operation on the material to be sanded, and uses the dynamic monitoring unit to obtain the sanding temperature and sanding vibration of the material to be sanded during the sanding in real time, and after confirming that the sanding temperature and the sanding vibration are respectively less than or equal to the reference material temperature and the preset vibration threshold, uses the dynamic feedback unit to send the sanding temperature and the sanding vibration to the initiator of the dynamic simulation instruction, so as to realize the sanding of the material to be sanded. It can be seen that the embodiment of the present invention also takes into account the specific parameters of the material to be sanded, that is, the sanding material parameters, and uses the sanding material parameters to retrieve the target sanding parameter group with the lowest energy consumption in the sanding database, thereby reducing the energy consumption required when performing the sanding operation on the material to be sanded. Therefore, the real-time dynamic simulation method, device, electronic device and computer-readable storage medium of a sand mill based on a clustering algorithm proposed in the present invention mainly aim to solve the problems of inaccurate parameter setting of the sand mill and energy waste when using the sand mill. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 A schematic flow chart of a real-time dynamic simulation method for a sand mill based on a clustering algorithm provided by an embodiment of the present invention;

[0079] Figure 2A schematic structural diagram of an electronic device for implementing the sand mill real-time dynamic simulation method based on clustering algorithm provided by an embodiment of the present invention.

[0080] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0081] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0082] The embodiment of the present application provides a real-time dynamic simulation method for a sand mill based on a clustering algorithm. The execution subject of the real-time dynamic simulation method for a sand mill based on a clustering algorithm includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the real-time dynamic simulation method for a sand mill based on a clustering algorithm can be executed by software or hardware installed on a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0083] Embodiment 1:

[0084] Reference Figure 1 FIG. 1 is a flow chart of a real-time dynamic simulation method for a sand mill based on a clustering algorithm provided by an embodiment of the present invention. In this embodiment, the real-time dynamic simulation method for a sand mill based on a clustering algorithm includes:

[0085] S1. Receive a dynamic simulation instruction, and confirm a dynamic simulation environment based on the dynamic simulation instruction, wherein the dynamic simulation environment includes: one or more sand mills and a dynamic simulation system, wherein the dynamic simulation system includes: a dynamic fitting unit, a dynamic monitoring unit and a dynamic feedback unit.

[0086] It should be understood that the dynamic simulation instruction refers to the instruction issued by the sand mill researchers, and the dynamic simulation environment refers to the environment used to realize the dynamic simulation of the sand mill. The difference between one or more sand mills is that the size parameters, materials used and preparation processes of different sand mills may be different. Therefore, one or more sand mills that can realize the sand grinding of materials can be retrieved from one or more sand mills in combination with the materials actually required to be sanded. The dynamic simulation system is a software or APP used to realize real-time dynamic simulation of the sand mill, and the dynamic simulation system includes: a dynamic fitting unit, a dynamic monitoring unit and a dynamic feedback unit. For the application of the specific units, please refer to the subsequent embodiments.

[0087] For example, Xiao Zhang, as a researcher of sand mills, in order to study the sanding performance of sand mills, issues the dynamic simulation instruction and confirms the dynamic simulation environment for realizing dynamic simulation of sand mills.

[0088] S2. Fit the sand grinding database based on the dynamic simulation environment.

[0089] It is understandable that the sanding database is fitted based on the dynamic simulation environment, including:

[0090] For each of the one or more sand mills, perform the following operations:

[0091] Obtaining a manufacturing parameter set of a sand mill, wherein the manufacturing parameter set includes: a size parameter set, a material parameter set and an execution standard;

[0092] Performing a labeling operation on the sand mill using the manufacturing parameter set to obtain a labeled sand mill;

[0093] The identified sand mills are summarized to obtain one or more identified sand mills, and a sand mill database is fitted based on the one or more identified sand mills.

[0094] It should be explained that the size parameter set refers to the set of sizes of the sand mill when the sand mill is manufactured. The size parameter set includes but is not limited to: grinding chamber diameter, grinding chamber length, rotor diameter and rotor width. The material parameter set refers to the set of materials used in the manufacture of the sand mill, and the materials in the material parameter set correspond to the sizes in the size parameter set. The material parameter set includes but is not limited to: stainless steel, carbon steel, plastic and rubber. The implementation standard refers to: the implementation standard adopted when manufacturing the sand mill. For example: using different national standards to produce sand mills.

[0095] Furthermore, using the manufacturing parameter set to perform a labeling operation on a sand mill can achieve differentiation of the sand mills and improve the accuracy of analyzing different sand mills.

[0096] Exemplarily, there are five types of sand mills with the same implementation standards, and the implementation standards are all: HG / T 2469-2011. Here, only the first sand mill and the second sand mill are taken as examples: the material used in the grinding chamber of the first sand mill is stainless steel, and the material used in the rotor is silicon carbide, the material used in the grinding chamber of the second sand mill is carbon steel, and the material used in the rotor is zirconium oxide, and the size parameter set corresponding to the first sand mill is the first size parameter set, and the size parameter set corresponding to the second sand mill is the second size parameter set, wherein the difference between the first size parameter set and the second size parameter set is that: there is at least one size parameter different between the first size parameter set and the second size parameter set, the material parameter set corresponding to the first sand mill is the first material parameter set, and the material parameter set corresponding to the second sand mill is the second material parameter set, and the first sand mill is marked by using the manufacturing parameter set, and the marked sand mill obtained is: HG / T 2469-2011-first size parameter set-first material parameter set, other technologies can achieve the same effect, which will not be repeated here. Therefore, using the manufacturing parameter set to perform the identification operation on the sand mill, the identification sand mill can improve the accuracy of the analysis of the identification sand mill on the basis of distinguishing the identification sand mill.

[0097] It should be understood that the step of fitting a sanding database based on the one or more identified sanding machines includes:

[0098] The following operations are performed for each of the one or more marking sand mills:

[0099] Obtain a sanding parameter range set of an identified sanding mill, wherein the sanding parameter range set includes multiple sanding parameter ranges, wherein the multiple sanding parameter ranges are: one or more material reference ranges, a rotation speed range, one or more sanding medium ranges, a sanding time range, a material feed speed range, and a cooling water temperature range, wherein the sanding medium range includes a sanding medium type and a sanding medium particle range, and the material reference range includes a material particle type and a material particle range;

[0100] Extract sanding parameter ranges from the multiple sanding parameter ranges in sequence, and perform the following operations on the extracted sanding parameter ranges:

[0101] Acquire a first dividing threshold for dividing the extracted sanding parameter range, and perform a dividing operation on the sanding parameter range using the first dividing threshold to obtain a first sanding value set, wherein the first sanding value set includes a plurality of first sanding values;

[0102] Summarizing the first sanding value sets to obtain a plurality of first sanding value sets, wherein the first sanding value sets correspond to the sanding parameter ranges one by one;

[0103] A plurality of first sanding value sets and a pre-constructed control variable method are used to obtain a plurality of sanding parameter groups, and the following operations are performed on each of the plurality of sanding parameter groups:

[0104] The fitting sand mill and target sanding particles are obtained by using the sanding parameter group and the identification sand mill, and the fitting sand mill is used to perform a sanding operation on the target sanding particles, and the fitting sanding time is recorded in real time with the time of performing the sanding operation as the time starting point, and the sanding temperature set and the sanding vibration set of the fitting sand mill are monitored by using a pre-constructed monitoring site set and a preset monitoring frequency, until the fitting sanding time reaches the first sanding value corresponding to the sanding time range in the sanding parameter group, and the first sanding material is obtained, wherein the monitoring site set includes a plurality of monitoring sites, the sanding temperature set includes a plurality of sanding temperature time series groups, and the sanding temperature time series group includes a plurality of sanding temperature values, the sanding vibration set includes a plurality of sanding vibration time series groups, and the sanding vibration time series group includes a plurality of sanding vibration values, and the sanding temperature values ​​and the sanding vibration values ​​correspond to the monitoring sites one by one;

[0105] After confirming that the fitting sand mill is a preset standard sand mill by using the sand milling temperature set, the first sand milling material and the sand milling vibration set, retaining the sand milling parameter group corresponding to the standard sand mill, and summarizing the retained sand milling parameter group to obtain an initial sand milling parameter set;

[0106] The sanding parameter groups in the initial sanding parameter set are summarized according to the variables corresponding to the control variable method to obtain multiple analysis parameter group sets, and a sanding database is constructed using the multiple analysis parameter group sets, wherein the analysis parameter group set includes multiple analysis parameter groups.

[0107] Further, the material particle range refers to the diameter range of the material that needs to be sand-milled. Optionally, after the material is screened, the aperture range for screening the material is used as the material particle range. For example: after a certain material is screened through a 70mm sieve, the screened material is screened through a 50mm sieve, and the material particle range corresponding to the material retained on the 50mm sieve is 50mm to 70mm. The same effect can be achieved by using other technologies, which will not be repeated here. The speed range refers to the speed range of the sand mill used for sand milling. Optionally, the speed range is provided by the user manual of the sand mill. The sand milling medium range refers to the range of the medium used for sand milling the material, and the diameter range of the medium. Optionally, the sand milling medium range is the range provided by the medium manufacturer. For example: when using a certain zirconia ball, the sand milling medium range extracted by the manufacturer is: 0.4mm to 0.6mm, then 0.4mm to 0.6mm is the sand milling medium range, and when it comes to the medium range of a certain size, it can be obtained by screening. The sanding time range refers to the time period used to perform the sanding operation. For example: the sanding time range is: 1 to 2 hours, which means that the time period for sanding under normal circumstances is 1 to 2 hours. The type of sanding media refers to the type of media used when sanding. For example: the types of sanding media include but are not limited to: glass beads and zirconium oxide. The types of material particles include but are not limited to: titanium dioxide and paint. The cooling water temperature range refers to the temperature range of the cooling water used to cool the sand mill when the sand mill is in use. For example: when using a certain model of sand mill, the recommended cooling water temperature range is 15 to 30 degrees Celsius. The material feed rate range refers to the rate at which the material is fed into the grinding chamber of the sand mill.

[0108] It is understandable that the first division threshold is a numerical value used to divide the extracted sanding parameter range. Optionally, the first division threshold is set manually. For example: the sanding time range is 1 to 2 hours, and the preset first division threshold is 3, then 3 can be used to divide 1 to 2 hours into: 1 hour, one and a half hours and 2 hours, and 1 hour, one and a half hours and 2 hours constitute the first sanding value set. The remaining sanding parameter ranges are consistent with the division of the sanding time range and can achieve the same effect. Optionally, the division of the sanding parameter range is achieved using the equal division method and the first division threshold, and the same effect can be achieved using other technologies, which will not be repeated here.

[0109] Furthermore, the sanding parameter group includes the first sanding value corresponding to each sanding parameter range in the sanding parameter range set, and the first sanding values ​​included in different sanding parameter groups are not exactly the same, that is, a first sanding value in the sanding parameter group is changed by the control variable method, so that all forms of the sanding parameter group can be exhaustively enumerated. The technology of obtaining multiple sanding parameter groups in multiple first sanding value sets using the control variable method is prior art and will not be repeated here. A fitting sand mill refers to a sand mill after the sanding parameters of the identification sand mill are set to the first sanding values ​​corresponding to the rotation speed range, one or more sanding medium ranges, material feed speed range, cooling water temperature range and sanding time range. The target sanding particles refer to the material particle types corresponding to one or more material reference ranges and the first sanding values ​​corresponding to the material particle ranges.

[0110] It should be explained that the sanding temperature timing group is obtained by measuring the temperature at each of the multiple monitoring sites at the monitoring frequency, and then sorting the measured temperatures in order from early to late, and obtaining a sequence of sanding temperature values, and the time for monitoring the sanding temperature value is less than or equal to the first sanding value corresponding to the sanding time range. The sanding vibration timing group is obtained in the same way as the sanding temperature timing group, and can achieve the same effect, which will not be repeated here.

[0111] It should be understood that the monitoring site set refers to a set of sites for monitoring a sand mill. For ease of understanding, the shape of the sand mill is approximated as a cylinder, and multiple sites can be obtained at certain intervals on the height of the sand mill. The set of these sites is the monitoring site set. For example: the height of the cylinder corresponding to the sand mill is 5 decimeters, and 10 sites are obtained every one decimeter, then 60 sites can be obtained at the sand mill, and the monitoring site set is composed of 60 sites. Optionally, the monitoring site set is artificially set, and the same effect can be achieved by using other technologies, which will not be repeated here.

[0112] It is understandable that the step of confirming that the fitting sand mill is a preset standard sand mill by using the sand milling temperature set, the first sand milling material and the sand milling vibration set includes:

[0113] Using a pre-built mixer to perform a stirring operation on the first sand-milled material to obtain a stirred sand-milled material, and obtaining a plurality of test material samples based on the stirred sand-milled material;

[0114] A detection unit set for detecting a material diameter range is obtained, wherein the detection unit set includes a plurality of detection units, detection units are sequentially extracted from the detection unit set, and the following operations are performed on the extracted detection units:

[0115] Using the extracted detection units and the multiple detection material samples, a plurality of standard material ratios are obtained, wherein the standard material ratios correspond to the detection material samples one by one, and a material particle threshold for dividing the standard material ratios is preset, and the diameters of the material particles in the standard material ratios are all less than or equal to the material particle threshold;

[0116] The standard material proportions are summarized respectively using the detected material samples to obtain multiple analysis diameter ratio groups, wherein the analysis diameter ratio groups correspond one-to-one to the detected material samples, and the comprehensive standard proportions are calculated based on the multiple analysis diameter ratio groups and the pre-constructed comprehensive material proportion relationship formula, and the fitting sand mill is confirmed as the preset standard sand mill using the comprehensive standard proportions, sand milling temperature set and sand milling vibration set.

[0117] It is understandable that the purpose of performing the stirring operation on the first sanding material is to improve the randomness of sampling the first sanding material so that the detected material samples after use can better characterize the distribution of particles of different diameters in the first sanding material, thereby improving the accuracy of the particle diameter analysis in the first sanding material. The stirred sanding material refers to the first sanding material that is performing the stirring operation or has just completed the stirring operation.

[0118] It should be understood that the detection unit refers to a unit that can detect the diameter range of the material in the detection material sample. Optionally, a laser is used as the detection unit, and other technologies can achieve the same effect, which will not be repeated here. The standard material ratio refers to the proportion of the material when the material diameter is less than the material particle threshold after the detection unit detects the detection material sample. For example: the detection material sample is detected by a laser, and the preset material particle threshold is 38 microns, and the standard material ratio is 60%, wherein the standard material ratio is that the material in the detection material sample with a diameter less than 38 microns accounts for 60% of the detection material sample.

[0119] Exemplarily, the detection unit set includes a total of 5 detection units and the detection material sample includes a total of 6 detection material samples. Then, 6 standard material ratios can be obtained using each of the 5 detection units and the 6 detection material samples. Summarizing the standard material ratios using the detection material samples means: summarizing the standard material ratios after detecting a certain detection material sample using 5 detection units. Therefore, the standard material ratios are summarized separately using the detection material samples to obtain 6 analysis diameter ratio groups.

[0120] Furthermore, the comprehensive material ratio relationship is as follows:

[0121] ;

[0122] in, represents the comprehensive standard ratio, Indicates that the detection unit has a total of A detection unit, Indicates the preset coefficients, Indicates the first Standard material ratio, Indicates shared Analyze the diameter ratio group, Indicates the first of multiple analysis diameter ratio groups Reference ratio value for each analyzed diameter ratio group.

[0123] It should be explained that by presetting coefficients in the comprehensive material ratio relationship formula, the problem of inaccurate acquisition of standard material ratios due to randomness in detection can be reduced, thereby improving the accuracy of standard material ratio analysis.

[0124] It is understandable that the use of the comprehensive standard ratio, sanding temperature set and sanding vibration set to confirm that the fitted sanding mill is a preset standard sanding mill includes:

[0125] Extracting sanding vibration time sequence groups from the plurality of sanding vibration time sequence groups in sequence, and performing the following operations on the extracted sanding vibration time sequence groups:

[0126] Extracting the maximum sanding vibration value from the extracted sanding vibration time series group to obtain an analysis vibration value, summarizing the analysis vibration values ​​to obtain a plurality of analysis vibration values, and summarizing the analysis vibration values ​​using the monitoring sites corresponding to each of the plurality of analysis vibration values ​​to obtain one or more analysis vibration value groups;

[0127] The following operations are performed for each of the one or more analysis vibration value groups:

[0128] For each analysis vibration value in the analysis vibration value group, perform the following operations:

[0129] Comparing the analyzed vibration value with a preset analyzed vibration threshold, if the analyzed vibration value is greater than the analyzed vibration threshold, marking the analyzed vibration value as a target vibration value, and summarizing the target vibration values ​​according to the monitoring sites corresponding to the target vibration values ​​to obtain a plurality of target vibration value groups;

[0130] The following operations are performed for each of the multiple target vibration value groups:

[0131] Based on the monitoring sites and sanding vibration set corresponding to the target vibration value group, a monitoring vibration time series group is obtained, and the target vibration time series group is extracted from the monitoring vibration time series group using the target vibration value group;

[0132] The target vibration duration is determined according to the target vibration time sequence group, one or more analysis temperature value groups are obtained using the multiple sanding temperature time sequence groups, and the following operations are performed on each of the one or more analysis temperature value groups:

[0133] For each sanding temperature value in the analysis temperature value group, perform the following operations:

[0134] Calculating the monitoring temperature using the sanding temperature value and a pre-constructed monitoring temperature relationship;

[0135] Acquire a target temperature duration based on the monitored temperature;

[0136] respectively comparing the target vibration duration with a preset vibration duration threshold, the target temperature duration with a preset temperature duration threshold, and the comprehensive standard ratio with a preset comprehensive ratio threshold;

[0137] If the target vibration duration is less than or equal to the vibration duration threshold and the target temperature duration is less than or equal to the preset temperature duration threshold and the comprehensive standard ratio is greater than or equal to the comprehensive ratio threshold;

[0138] It is then confirmed that the fitted sand mill is a standard sand mill.

[0139] It should be understood that the monitoring sites corresponding to each of the multiple analysis vibration value groups are the same monitoring sites. There are two situations that can satisfy the analysis vibration value being greater than the analysis vibration threshold. The first situation: the sand mill will produce excessive vibration due to unreasonable setting parameters of the sand mill. The second situation: due to a fault in the vibration monitoring unit, the measured sand mill vibration value is inconsistent with the actual vibration value of the sand mill, resulting in the analysis vibration value being greater than the analysis vibration threshold. In order to avoid the misjudgment of unreasonable sand mill parameters due to the second situation, therefore, by confirming that the target vibration duration is less than or equal to the vibration duration threshold, it is ensured that the unreasonable vibration of the sand mill is due to unreasonable parameter settings.

[0140] Furthermore, the monitoring vibration timing group refers to the sanding vibration value at each monitoring site, and the sanding vibration values ​​at the monitoring sites are sorted in order from early to late according to the time when the sanding vibration values ​​are monitored, thereby obtaining a sequence of sanding vibration values. The target vibration timing group refers to: a sequence composed of target vibration values ​​and analysis vibration values ​​at the monitoring site, and the interval between the time corresponding to two adjacent target vibration values ​​or analysis vibration values ​​in the target vibration timing group is the monitoring time interval. The method for obtaining the analysis temperature value group is the same as the method for obtaining the analysis vibration value group, and can achieve the same effect, which will not be repeated here.

[0141] It should be explained that the step of determining the target vibration duration according to the target vibration timing group includes:

[0142] The monitoring time interval is obtained by using the monitoring frequency, and one or more reference vibration time sequence groups are obtained according to the target vibration time sequence group, wherein the reference vibration time sequence group includes multiple target vibration values, and the absolute difference between the times corresponding to two adjacent target vibration values ​​is the monitoring time interval;

[0143] Acquire one or more reference durations using the one or more reference vibration timing groups, wherein the reference durations correspond to the reference vibration timing groups one by one;

[0144] A target vibration duration is determined based on the one or more reference durations, wherein the target vibration duration is a maximum reference duration among the one or more reference durations.

[0145] Exemplarily, if the monitoring frequency is once per second, the monitoring time interval is 1 second. The reference duration refers to the absolute difference between the time corresponding to the first reference vibration value and the time corresponding to the last reference vibration value in the target vibration timing group. Here, the time corresponding to the first reference vibration value is the time when the first reference vibration value is monitored. For example: the time corresponding to the first reference vibration value in a target vibration timing group is ten o'clock, and the time corresponding to the last reference vibration value is half past ten, then the reference duration is half an hour.

[0146] It should be understood that the target temperature duration is obtained in the same manner as the target vibration duration, and can achieve the same effect, which will not be described in detail here. When the target temperature duration is greater than the temperature duration threshold, the material in the sand mill may deteriorate due to temperature, and when the target vibration duration is greater than the vibration duration threshold, the sand mill may vibrate, thereby causing the sand mill to be unstable and possibly causing safety hazards.

[0147] It should be explained that the monitoring temperature relationship is as follows:

[0148] ;

[0149] in, represents the monitoring temperature of the fitted sand mill, represents the temperature of the fitted sand mill surface, represents the thermal conductivity of the fitted sand mill, represents the contact area between the fitted sand mill and the air, Indicates the thickness of the wall corresponding to the sand mill, It represents the difference between the temperature of cooling water in the fitting sand mill and the temperature of the environment. represents the convective heat transfer coefficient, Indicates the temperature of cooling water. Indicates the temperature of the environment, represents the surface emissivity, represents the Boltzmann constant.

[0150] It is understandable that the monitoring temperature relationship formula includes but is not limited to the thermal conductivity and the area of ​​contact between the fitted sand mill and the air, which are all related to the size parameter set, material parameter set and execution standard corresponding to the fitted sand mill. Optionally, the thermal conductivity is obtained by experiment.

[0151] Further, the constructing of the sand grinding database using the plurality of analysis parameter sets includes:

[0152] The following operations are performed for each of the multiple analysis parameter sets:

[0153] Mapping the analysis parameter group in the analysis parameter group set to the pre-constructed reference coordinate system to obtain the target fitting point set, wherein the horizontal axis of the reference coordinate system is the variable corresponding to the analysis parameter group, and the vertical axis of the reference coordinate system is the comprehensive standard ratio;

[0154] A fitting model set for fitting a curve is obtained, wherein the fitting model set includes a plurality of fitting models, fitting models are sequentially extracted from the fitting model set, and the following operations are performed on the extracted fitting models:

[0155] A fitting curve is obtained based on the extracted fitting model and the target fitting point set, and a target parameter set is retrieved from the fitting curve using the analysis parameter set, wherein the target parameter set includes a plurality of target parameter groups, and the target parameter groups correspond to the analysis parameter groups one by one, and the values ​​of the variables corresponding to the target parameter groups are the same as the values ​​of the variables corresponding to the analysis parameter groups;

[0156] The target parameter set, the analysis parameter set and the pre-constructed comprehensive fitting relationship are used to calculate the comprehensive fitting value, the comprehensive fitting value is summarized to obtain the comprehensive fitting value set, and the target curve is obtained by using the comprehensive fitting value set, wherein the target curve is the fitting curve corresponding to the minimum comprehensive fitting value in the comprehensive fitting value set, the target curve is summarized to obtain multiple target curves, and the sanding database is obtained based on the multiple target curves, wherein the comprehensive fitting relationship is as follows:

[0157] ;

[0158] in, represents the comprehensive fitting value, Indicates that the analysis parameter group has analysis parameter groups, Indicates the target parameter set. The comprehensive standard ratio corresponding to each target parameter group, Indicates the first The comprehensive standard ratio corresponding to each analysis parameter group.

[0159] It is understandable that the fitting model refers to a model that can fit multiple points into a curve. Optionally, polynomial fitting is used as the fitting model. Optionally, a plane rectangular coordinate system is used as the reference coordinate system. The target fitting point set refers to the set of points obtained by mapping the values ​​of the variables corresponding to the analysis reference array in the analysis reference array set and the comprehensive standard ratio corresponding to the analysis reference array to the reference coordinate system.

[0160] It should be understood that the fitting curve refers to the curve obtained by fitting the target fitting point set using the fitting model. Retrieving the target parameter set from the fitting curve means using the values ​​of the variables corresponding to the analysis parameter set in the analysis parameter set to confirm the same comprehensive standard ratio as the values ​​of the variables corresponding to the analysis parameter set in the fitting curve, and the smaller the comprehensive fitting value, the better the fitting effect of using the fitting curve to fit the target fitting point set.

[0161] Furthermore, the sanding database refers to a database composed of a plurality of target curves.

[0162] S3, confirming receipt of the dynamic fitting instruction from the dynamic fitting unit, parsing the dynamic fitting instruction, and obtaining the sanding material parameters of the material to be sanded, wherein the sanding material parameters include: reference material type, reference material particles, reference material temperature, reference particle diameter and comprehensive fitting ratio.

[0163] It should be explained that the dynamic fitting instruction refers to an instruction issued by a sanding operator, and the instruction includes the effect that the sanding operator wants to achieve. The reference material type refers to the type of material to be sanded, and the reference material particles refer to the size of the particles in the material to be sanded. Optionally, the diameter of the particles in the material to be sanded is used as the reference material particles. The reference material temperature refers to the temperature at which the material to be sanded will not cause the material to be sanded to deteriorate during sanding. The reference particle diameter refers to the diameter of the particles in the material to be sanded that is desired to be achieved after the sanding operation is performed on the material to be sanded. The comprehensive fitting ratio refers to the ratio of the size of the material to be sanded after the sanding operation is performed on the material to be sanded that is less than or equal to a certain reference particle diameter.

[0164] Exemplarily, the comprehensive fitting ratio is 80 percent, and the reference particle diameter is 38 microns, which means that after the sanding operation is performed on the material to be sanded, the diameter of the material to be sanded after sanding is less than or equal to 38 microns, and the material with a diameter less than or equal to 38 microns is not less than 80 percent of the material to be sanded after sanding.

[0165] S4. Based on the sanding material parameters, an initial sanding parameter set is retrieved from a sanding database, and a target sanding parameter set is confirmed using the initial sanding parameter set.

[0166] It is understandable that the initial sanding parameter set is retrieved from the sanding database based on the sanding material parameters, including:

[0167] Extract target curves from the sanding database in sequence, and perform the following operations on the extracted target curves:

[0168] Using the comprehensive fitting ratio corresponding to the sanding material parameters, a proportional straight line is constructed in the reference coordinate system corresponding to the target curve, wherein the ordinate corresponding to the proportional straight line is the comprehensive fitting ratio;

[0169] If there is at least one intersection point between the proportional straight line and the target curve, a reference sanding parameter set is obtained using the at least one intersection point, wherein the reference sanding parameter set includes one or more reference sanding parameter sets, and the reference sanding parameter sets correspond to the intersection points one by one;

[0170] The reference sanding parameter sets are summarized to obtain a first sanding parameter set, and an initial sanding parameter set is obtained using a pre-constructed k-means clustering algorithm and the first sanding parameter set.

[0171] It should be understood that the purpose of constructing a proportional straight line in the reference coordinate system corresponding to the target curve is to determine whether there is an intersection between the proportional straight line and the target curve. When there is an intersection between the proportional straight line and the target curve, it indicates that after the sanding operation is performed on the material to be sanded using the parameter group corresponding to the target curve at the intersection, the comprehensive standard ratio corresponding to the material to be sanded after the sanding operation can reach the comprehensive fitting ratio.

[0172] It is understandable that the k-means clustering algorithm can be used to cluster multidimensional data to obtain multiple clusters, where the multidimensional data refers to the first sanding value and the comprehensive standard ratio corresponding to the intersection points corresponding to the sanding material parameters including: reference material type, reference material particles, reference material temperature, reference particle diameter and comprehensive fitting ratio, and the initial sanding parameter set refers to the set of reference sanding parameter sets in the cluster where the sanding material parameters are located.

[0173] Further, the using the initial sanding parameter set to determine the target sanding parameter set includes:

[0174] Extracting initial sanding parameter groups from the initial sanding parameter group set in sequence, and performing the following operations on the extracted initial sanding parameter groups:

[0175] The energy consumption prediction value is calculated based on the extracted initial sanding parameters and the pre-constructed energy consumption evaluation relationship, wherein the energy consumption evaluation relationship is as follows:

[0176] ;

[0177] in, represents the predicted value of energy consumption, represents the sanding time in the initial sanding parameter group, It represents the unit energy consumption of the sand mill in the initial sand mill parameter group. represents the unit loss of sanding medium in the initial sanding parameter group, Indicates the unit energy consumption to maintain the cooling water temperature, represents the fixed energy consumption of the sanding medium in the initial sanding parameter group, All are preset coefficients;

[0178] The energy consumption prediction values ​​are summarized to obtain an energy consumption prediction value set, and a target sanding parameter group is confirmed using the energy consumption prediction value set, wherein the target sanding parameter group is an initial sanding parameter group corresponding to the minimum energy consumption prediction value in the energy consumption prediction value set.

[0179] It should be understood that the use of different initial sanding parameters may correspond to different energy consumption prediction values. Therefore, it is necessary to fit the energy consumption value corresponding to each initial sanding parameter according to the different initial sanding parameters, and then, identify the target sanding parameter group in the initial sanding parameter group, so that the sanding of the material to be sanded can be achieved with lower energy consumption. Optionally, the unit loss of the sanding medium is obtained by experimental means. For example: obtain the time during which the sanding medium corresponding to the initial sanding parameter group can be used normally and the production energy consumption of the sanding medium, and use the production energy consumption ratio time to obtain the unit loss. Fixed energy consumption refers to the energy consumption required to produce the sanding medium.

[0180] S5. Setting a target sanding machine using the target sanding parameter group, wherein the parameters of the target sanding machine when performing the sanding operation are set as the target sanding parameter group.

[0181] It should be understood that setting a target sanding mill using the target sanding parameter set means setting the parameters of the sanding mill corresponding to the target sanding parameter set as the parameters in the target sanding parameter set.

[0182] Exemplarily, the target sanding parameter group includes: a rotation speed of 300 revolutions per minute, a sanding medium type of zirconium oxide, a first sanding value corresponding to the sanding medium particle range of 30 microns, a sanding time range of 30 minutes, and a cooling water temperature of 15 degrees Celsius. After setting the sand mill corresponding to the initial sanding parameters as the target sanding parameter group, the target sand mill is obtained.

[0183] S6. Utilize the target sand mill to perform sanding operation on the material to be sanded, and utilize the dynamic monitoring unit to obtain the sanding temperature and sanding vibration of the material to be sanded in real time during the sanding process. After confirming that the sanding temperature and the sanding vibration are respectively less than or equal to the reference material temperature and the preset vibration threshold, utilize the dynamic feedback unit to send the sanding temperature and the sanding vibration to the initiator of the dynamic simulation instruction to realize the sanding of the material to be sanded.

[0184] It should be understood that the sanding temperature and the sanding vibration are the temperature and vibration values ​​of the target sanding mill when the target sanding mill is used to sand the material to be sanded, and the acquisition methods of the sanding temperature and the sanding vibration are the same as the acquisition methods of the sanding temperature value and the sanding vibration value, respectively, and can achieve the same effect, which will not be repeated here. The purpose of confirming that the sanding temperature and the sanding vibration are respectively less than or equal to the reference material temperature and the preset vibration threshold is to be able to use the target sanding mill to achieve sanding of the material to be sanded under the premise of safety and reliability.

[0185] Compared with the problems described in the background technology, the present invention first receives a dynamic simulation instruction, and confirms a dynamic simulation environment based on the dynamic simulation instruction, wherein the dynamic simulation environment includes: one or more sand mills and a dynamic simulation system. It can be seen that the present invention considers the existence of one or more sand mills in the dynamic simulation environment when confirming the dynamic simulation environment, thereby laying a foundation for the embodiment of the present invention to be more widely adapted to different materials to be sanded. In addition, the present invention fits a sanding database based on the dynamic simulation environment, thereby retrieving one or more sanding machines and their parameters for sanding corresponding to different sanding materials and different sanding requirements through the sanding database, and when constructing the sanding database, it is considered that temperature and vibration may cause inaccuracy in the data used to construct the sanding database, therefore, after confirming that the fitted sanding machine is the standard sanding machine through the target vibration duration, the target temperature duration and the comprehensive standard ratio, the sanding parameter group corresponding to the standard sanding machine is obtained, and the relationship between the variables corresponding to the sanding parameter group and the comprehensive standard ratio used to evaluate the sanding effect can be characterized through the sanding parameter group, thereby improving the accuracy of the construction of the sanding database. The embodiment of the present invention confirms receiving a dynamic fitting instruction from a dynamic fitting unit, parses the dynamic fitting instruction, obtains sanding material parameters of the material to be sanded, retrieves an initial sanding parameter set from a sanding database based on the sanding material parameters, uses the initial sanding parameter set to confirm a target sanding parameter set, and uses the target sanding parameter set to set a target sanding machine, wherein the parameters of the target sanding machine when performing the sanding operation are set as the target sanding parameter group, uses the target sanding machine to perform the sanding operation on the material to be sanded, and uses the dynamic monitoring unit to obtain the sanding temperature and sanding vibration of the material to be sanded during the sanding in real time, and after confirming that the sanding temperature and the sanding vibration are respectively less than or equal to the reference material temperature and the preset vibration threshold, uses the dynamic feedback unit to send the sanding temperature and the sanding vibration to the initiator of the dynamic simulation instruction, so as to realize the sanding of the material to be sanded. It can be seen that the embodiment of the present invention also takes into account the specific parameters of the material to be sanded, that is, the sanding material parameters, and uses the sanding material parameters to retrieve the target sanding parameter group with the lowest energy consumption in the sanding database, thereby reducing the energy consumption required when performing the sanding operation on the material to be sanded. Therefore, the real-time dynamic simulation method, device, electronic device and computer-readable storage medium of a sand mill based on a clustering algorithm proposed in the present invention mainly aim to solve the problems of inaccurate parameter setting of the sand mill and energy waste when using the sand mill.

[0186] Embodiment 2:

[0187] like Figure 2 , which is a schematic diagram of the structure of an electronic device for implementing a real-time dynamic simulation method for a sand mill based on a clustering algorithm provided by an embodiment of the present invention.

[0188] The electronic device 1 may include a processor 10, a memory 11, a bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a real-time dynamic simulation program for a sand mill based on a clustering algorithm.

[0189] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. The memory 11 may be an internal storage unit of the electronic device 1 in some embodiments, such as a mobile hard disk of the electronic device 1. The memory 11 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), etc. equipped on the electronic device 1. Further, the memory 11 may also include both an internal storage unit of the electronic device 1 and an external storage device. The memory 11 may not only be used to store application software and various types of data installed in the electronic device 1, such as the code of a real-time dynamic simulation program of a sand mill based on a clustering algorithm, but may also be used to temporarily store data that has been output or is to be output.

[0190] The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes various functions and processes data of the electronic device 1 by running or executing programs or modules stored in the memory 11 (for example, a real-time dynamic simulation program for a sand mill based on a clustering algorithm, etc.), and calling data stored in the memory 11.

[0191] The bus may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0192] Figure 2 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 2 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0193] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to various components. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0194] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0195] Optionally, the electronic device 1 may further include a user interface, which may be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device, etc. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0196] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0197] The real-time dynamic simulation program of the sand mill based on the clustering algorithm stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve:

[0198] Receiving a dynamic simulation instruction, and confirming a dynamic simulation environment based on the dynamic simulation instruction, wherein the dynamic simulation environment includes: one or more sand mills and a dynamic simulation system, wherein the dynamic simulation system includes: a dynamic fitting unit, a dynamic monitoring unit and a dynamic feedback unit;

[0199] Fit the sand grinding database based on the dynamic simulation environment;

[0200] Confirming receipt of a dynamic fitting instruction from a dynamic fitting unit, parsing the dynamic fitting instruction, and obtaining sanding material parameters of the material to be sanded, wherein the sanding material parameters include: reference material type, reference material particles, reference material temperature, reference particle diameter, and comprehensive fitting ratio, wherein the comprehensive fitting ratio refers to the ratio of the size of the material to be sanded after the sanding operation is performed on the material to be sanded to be less than or equal to a certain reference particle diameter;

[0201] Based on the sanding material parameters, an initial sanding parameter set is retrieved from a sanding database, and a target sanding parameter set is confirmed using the initial sanding parameter set;

[0202] A target sanding machine is set by using the target sanding parameter group, wherein the parameters of the target sanding machine when performing the sanding operation are set as the target sanding parameter group;

[0203] The target sand mill is used to perform a sanding operation on the material to be sanded, and the sanding temperature and sanding vibration of the material to be sanded are obtained in real time by using a dynamic monitoring unit. After confirming that the sanding temperature and the sanding vibration are respectively less than or equal to the reference material temperature and a preset vibration threshold, the dynamic feedback unit is used to send the sanding temperature and the sanding vibration to the initiator of the dynamic simulation instruction, so as to realize the sanding of the material to be sanded;

[0204] The step of fitting a sand grinding database based on a dynamic simulation environment includes:

[0205] For each of the one or more sand mills, perform the following operations:

[0206] Obtaining a manufacturing parameter set of a sand mill, wherein the manufacturing parameter set includes: a size parameter set, a material parameter set and an execution standard;

[0207] Performing a labeling operation on the sand mill using the manufacturing parameter set to obtain a labeled sand mill;

[0208] Summarize the identified sand mills to obtain one or more identified sand mills, and fit a sand mill database based on the one or more identified sand mills;

[0209] Wherein, fitting a sand mill database based on the one or more identified sand mills comprises:

[0210] The following operations are performed for each of the one or more marking sand mills:

[0211] Obtain a sanding parameter range set of an identified sanding mill, wherein the sanding parameter range set includes multiple sanding parameter ranges, wherein the multiple sanding parameter ranges are: one or more material reference ranges, a rotation speed range, one or more sanding medium ranges, a sanding time range, a material feed speed range, and a cooling water temperature range, wherein the sanding medium range includes a sanding medium type and a sanding medium particle range, and the material reference range includes a material particle type and a material particle range;

[0212] Extract sanding parameter ranges from the multiple sanding parameter ranges in sequence, and perform the following operations on the extracted sanding parameter ranges:

[0213] Acquire a first dividing threshold for dividing the extracted sanding parameter range, and perform a dividing operation on the sanding parameter range using the first dividing threshold to obtain a first sanding value set, wherein the first sanding value set includes a plurality of first sanding values;

[0214] Summarizing the first sanding value sets to obtain a plurality of first sanding value sets, wherein the first sanding value sets correspond to the sanding parameter ranges one by one;

[0215] A plurality of first sanding value sets and a pre-constructed control variable method are used to obtain a plurality of sanding parameter groups, and the following operations are performed on each of the plurality of sanding parameter groups:

[0216] The fitting sand mill and target sanding particles are obtained by using the sanding parameter group and the identification sand mill, and the fitting sand mill is used to perform a sanding operation on the target sanding particles, and the fitting sanding time is recorded in real time with the time of performing the sanding operation as the time starting point, and the sanding temperature set and the sanding vibration set of the fitting sand mill are monitored by using a pre-constructed monitoring site set and a preset monitoring frequency, until the fitting sanding time reaches the first sanding value corresponding to the sanding time range in the sanding parameter group, and the first sanding material is obtained, wherein the monitoring site set includes a plurality of monitoring sites, the sanding temperature set includes a plurality of sanding temperature time series groups, and the sanding temperature time series group includes a plurality of sanding temperature values, the sanding vibration set includes a plurality of sanding vibration time series groups, and the sanding vibration time series group includes a plurality of sanding vibration values, and the sanding temperature values ​​and the sanding vibration values ​​correspond to the monitoring sites one by one;

[0217] After confirming that the fitting sand mill is a preset standard sand mill by using the sand milling temperature set, the first sand milling material and the sand milling vibration set, retaining the sand milling parameter group corresponding to the standard sand mill, and summarizing the retained sand milling parameter group to obtain an initial sand milling parameter set;

[0218] The sanding parameter groups in the initial sanding parameter set are summarized according to the variables corresponding to the control variable method to obtain multiple analysis parameter group sets, and a sanding database is constructed using the multiple analysis parameter group sets, wherein the analysis parameter group set includes multiple analysis parameter groups.

[0219] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figure 1 to Figure 2 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0220] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0221] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0222] Receiving a dynamic simulation instruction, and confirming a dynamic simulation environment based on the dynamic simulation instruction, wherein the dynamic simulation environment includes: one or more sand mills and a dynamic simulation system, wherein the dynamic simulation system includes: a dynamic fitting unit, a dynamic monitoring unit and a dynamic feedback unit;

[0223] Fit the sand grinding database based on the dynamic simulation environment;

[0224] Confirming receipt of a dynamic fitting instruction from a dynamic fitting unit, parsing the dynamic fitting instruction, and obtaining sanding material parameters of the material to be sanded, wherein the sanding material parameters include: reference material type, reference material particles, reference material temperature, reference particle diameter, and comprehensive fitting ratio, wherein the comprehensive fitting ratio refers to the ratio of the size of the material to be sanded after the sanding operation is performed on the material to be sanded to be less than or equal to a certain reference particle diameter;

[0225] Based on the sanding material parameters, an initial sanding parameter set is retrieved from a sanding database, and a target sanding parameter set is confirmed using the initial sanding parameter set;

[0226] A target sanding machine is set by using the target sanding parameter group, wherein the parameters of the target sanding machine when performing the sanding operation are set as the target sanding parameter group;

[0227] The target sand mill is used to perform a sanding operation on the material to be sanded, and the sanding temperature and sanding vibration of the material to be sanded are obtained in real time by using a dynamic monitoring unit. After confirming that the sanding temperature and the sanding vibration are respectively less than or equal to the reference material temperature and a preset vibration threshold, the dynamic feedback unit is used to send the sanding temperature and the sanding vibration to the initiator of the dynamic simulation instruction, so as to realize the sanding of the material to be sanded;

[0228] The step of fitting a sand grinding database based on a dynamic simulation environment includes:

[0229] For each of the one or more sand mills, perform the following operations:

[0230] Obtaining a manufacturing parameter set of a sand mill, wherein the manufacturing parameter set includes: a size parameter set, a material parameter set and an execution standard;

[0231] Performing a labeling operation on the sand mill using the manufacturing parameter set to obtain a labeled sand mill;

[0232] Summarize the identified sand mills to obtain one or more identified sand mills, and fit a sand mill database based on the one or more identified sand mills;

[0233] Wherein, fitting a sand mill database based on the one or more identified sand mills comprises:

[0234] The following operations are performed for each of the one or more marking sand mills:

[0235] Obtain a sanding parameter range set of an identified sanding mill, wherein the sanding parameter range set includes multiple sanding parameter ranges, wherein the multiple sanding parameter ranges are: one or more material reference ranges, a rotation speed range, one or more sanding medium ranges, a sanding time range, a material feed speed range, and a cooling water temperature range, wherein the sanding medium range includes a sanding medium type and a sanding medium particle range, and the material reference range includes a material particle type and a material particle range;

[0236] Extract sanding parameter ranges from the multiple sanding parameter ranges in sequence, and perform the following operations on the extracted sanding parameter ranges:

[0237] Acquire a first dividing threshold for dividing the extracted sanding parameter range, and perform a dividing operation on the sanding parameter range using the first dividing threshold to obtain a first sanding value set, wherein the first sanding value set includes a plurality of first sanding values;

[0238] Summarizing the first sanding value sets to obtain a plurality of first sanding value sets, wherein the first sanding value sets correspond to the sanding parameter ranges one by one;

[0239] A plurality of first sanding value sets and a pre-constructed control variable method are used to obtain a plurality of sanding parameter groups, and the following operations are performed on each of the plurality of sanding parameter groups:

[0240] The fitting sand mill and target sanding particles are obtained by using the sanding parameter group and the identification sand mill, and the fitting sand mill is used to perform a sanding operation on the target sanding particles, and the fitting sanding time is recorded in real time with the time of performing the sanding operation as the time starting point, and the sanding temperature set and the sanding vibration set of the fitting sand mill are monitored by using a pre-constructed monitoring site set and a preset monitoring frequency, until the fitting sanding time reaches the first sanding value corresponding to the sanding time range in the sanding parameter group, and the first sanding material is obtained, wherein the monitoring site set includes a plurality of monitoring sites, the sanding temperature set includes a plurality of sanding temperature time series groups, and the sanding temperature time series group includes a plurality of sanding temperature values, the sanding vibration set includes a plurality of sanding vibration time series groups, and the sanding vibration time series group includes a plurality of sanding vibration values, and the sanding temperature values ​​and the sanding vibration values ​​correspond to the monitoring sites one by one;

[0241] After confirming that the fitting sand mill is a preset standard sand mill by using the sand milling temperature set, the first sand milling material and the sand milling vibration set, retaining the sand milling parameter group corresponding to the standard sand mill, and summarizing the retained sand milling parameter group to obtain an initial sand milling parameter set;

[0242] The sanding parameter groups in the initial sanding parameter set are summarized according to the variables corresponding to the control variable method to obtain multiple analysis parameter group sets, and a sanding database is constructed using the multiple analysis parameter group sets, wherein the analysis parameter group set includes multiple analysis parameter groups.

[0243] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0244] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0245] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0246] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A real-time dynamic simulation method for a sand mill based on a clustering algorithm, characterized in that: The method comprises: Receiving a dynamic simulation instruction, and confirming a dynamic simulation environment based on the dynamic simulation instruction, wherein the dynamic simulation environment includes: one or more sand mills and a dynamic simulation system, wherein the dynamic simulation system includes: a dynamic fitting unit, a dynamic monitoring unit and a dynamic feedback unit; Fit the sand grinding database based on the dynamic simulation environment; Confirming receipt of a dynamic fitting instruction from a dynamic fitting unit, parsing the dynamic fitting instruction, and obtaining sanding material parameters of the material to be sanded, wherein the sanding material parameters include: reference material type, reference material particles, reference material temperature, reference particle diameter, and comprehensive fitting ratio, wherein the comprehensive fitting ratio refers to the ratio of the size of the material to be sanded after the sanding operation is performed on the material to be sanded to be less than or equal to a certain reference particle diameter; Based on the sanding material parameters, an initial sanding parameter set is retrieved from a sanding database, and a target sanding parameter set is confirmed using the initial sanding parameter set; A target sanding machine is set by using the target sanding parameter group, wherein the parameters of the target sanding machine when performing the sanding operation are set as the target sanding parameter group; The target sand mill is used to perform a sanding operation on the material to be sanded, and the sanding temperature and sanding vibration of the material to be sanded are obtained in real time by using a dynamic monitoring unit. After confirming that the sanding temperature and the sanding vibration are respectively less than or equal to the reference material temperature and a preset vibration threshold, the dynamic feedback unit is used to send the sanding temperature and the sanding vibration to the initiator of the dynamic simulation instruction, so as to realize the sanding of the material to be sanded; The step of fitting a sand grinding database based on a dynamic simulation environment includes: For each of the one or more sand mills, perform the following operations: Obtaining a manufacturing parameter set of a sand mill, wherein the manufacturing parameter set includes: a size parameter set, a material parameter set and an execution standard; Performing a labeling operation on the sand mill using the manufacturing parameter set to obtain a labeled sand mill; Summarize the identified sand mills to obtain one or more identified sand mills, and fit a sand mill database based on the one or more identified sand mills; Wherein, fitting a sand mill database based on the one or more identified sand mills comprises: The following operations are performed for each of the one or more marking sand mills: Obtain a sanding parameter range set of an identified sanding mill, wherein the sanding parameter range set includes multiple sanding parameter ranges, wherein the multiple sanding parameter ranges are: one or more material reference ranges, a rotation speed range, one or more sanding medium ranges, a sanding time range, a material feed speed range, and a cooling water temperature range, wherein the sanding medium range includes a sanding medium type and a sanding medium particle range, and the material reference range includes a material particle type and a material particle range; Extract sanding parameter ranges from the multiple sanding parameter ranges in sequence, and perform the following operations on the extracted sanding parameter ranges: Acquire a first dividing threshold for dividing the extracted sanding parameter range, and perform a dividing operation on the sanding parameter range using the first dividing threshold to obtain a first sanding value set, wherein the first sanding value set includes a plurality of first sanding values; Summarizing the first sanding value sets to obtain a plurality of first sanding value sets, wherein the first sanding value sets correspond to the sanding parameter ranges one by one; A plurality of first sanding value sets and a pre-constructed control variable method are used to obtain a plurality of sanding parameter groups, and the following operations are performed on each of the plurality of sanding parameter groups: The fitting sand mill and target sanding particles are obtained by using the sanding parameter group and the identification sand mill, and the fitting sand mill is used to perform a sanding operation on the target sanding particles, and the fitting sanding time is recorded in real time with the time of performing the sanding operation as the time starting point, and the sanding temperature set and the sanding vibration set of the fitting sand mill are monitored by using a pre-constructed monitoring site set and a preset monitoring frequency, until the fitting sanding time reaches the first sanding value corresponding to the sanding time range in the sanding parameter group, and the first sanding material is obtained, wherein the monitoring site set includes a plurality of monitoring sites, the sanding temperature set includes a plurality of sanding temperature time series groups, and the sanding temperature time series group includes a plurality of sanding temperature values, the sanding vibration set includes a plurality of sanding vibration time series groups, and the sanding vibration time series group includes a plurality of sanding vibration values, and the sanding temperature values ​​and the sanding vibration values ​​correspond to the monitoring sites one by one; After confirming that the fitting sand mill is a preset standard sand mill by using the sand milling temperature set, the first sand milling material and the sand milling vibration set, retaining the sand milling parameter group corresponding to the standard sand mill, and summarizing the retained sand milling parameter group to obtain an initial sand milling parameter set; The sanding parameter groups in the initial sanding parameter set are summarized according to the variables corresponding to the control variable method to obtain multiple analysis parameter group sets, and a sanding database is constructed using the multiple analysis parameter group sets, wherein the analysis parameter group set includes multiple analysis parameter groups.

2. The real-time dynamic simulation method for a sand mill based on a clustering algorithm as claimed in claim 1, characterized in that: The step of using the sanding temperature set, the first sanding material, and the sanding vibration set to confirm that the fitting sanding mill is a preset standard sanding mill includes: Using a pre-built mixer to perform a stirring operation on the first sand-milled material to obtain a stirred sand-milled material, and obtaining a plurality of test material samples based on the stirred sand-milled material; A detection unit set for detecting a material diameter range is obtained, wherein the detection unit set includes a plurality of detection units, detection units are sequentially extracted from the detection unit set, and the following operations are performed on the extracted detection units: Using the extracted detection units and the multiple detection material samples, a plurality of standard material ratios are obtained, wherein the standard material ratios correspond to the detection material samples one by one, and a material particle threshold for dividing the standard material ratios is preset, and the diameters of the material particles in the standard material ratios are all less than or equal to the material particle threshold; The standard material proportions are summarized respectively using the detected material samples to obtain multiple analysis diameter ratio groups, wherein the analysis diameter ratio groups correspond one-to-one to the detected material samples, and the comprehensive standard proportions are calculated based on the multiple analysis diameter ratio groups and the pre-constructed comprehensive material proportion relationship formula, and the fitting sand mill is confirmed as the preset standard sand mill using the comprehensive standard proportions, sand milling temperature set and sand milling vibration set.

3. The real-time dynamic simulation method for a sand mill based on a clustering algorithm as claimed in claim 2, characterized in that: The comprehensive material ratio relationship is as follows: ； in, represents the comprehensive standard ratio, Indicates that the detection unit has a total of A detection unit, Indicates the preset coefficients, Indicates the first Standard material ratio, Indicates shared Analyze the diameter ratio group, Indicates the first of multiple analysis diameter ratio groups Reference ratio value for each analyzed diameter ratio group.

4. The real-time dynamic simulation method for a sand mill based on a clustering algorithm as claimed in claim 3, characterized in that: The method of confirming that the fitting sand mill is a preset standard sand mill by using the comprehensive standard ratio, the sand milling temperature set and the sand milling vibration set comprises: Extracting sanding vibration time sequence groups from the plurality of sanding vibration time sequence groups in sequence, and performing the following operations on the extracted sanding vibration time sequence groups: Extracting the maximum sanding vibration value from the extracted sanding vibration time series group to obtain an analysis vibration value, summarizing the analysis vibration values ​​to obtain a plurality of analysis vibration values, and summarizing the analysis vibration values ​​using the monitoring sites corresponding to each of the plurality of analysis vibration values ​​to obtain one or more analysis vibration value groups; The following operations are performed for each of the one or more analysis vibration value groups: For each analysis vibration value in the analysis vibration value group, perform the following operations: Comparing the analyzed vibration value with a preset analyzed vibration threshold, if the analyzed vibration value is greater than the analyzed vibration threshold, marking the analyzed vibration value as a target vibration value, and summarizing the target vibration values ​​according to the monitoring sites corresponding to the target vibration values ​​to obtain a plurality of target vibration value groups; The following operations are performed for each of the multiple target vibration value groups: Based on the monitoring sites and sanding vibration set corresponding to the target vibration value group, a monitoring vibration time series group is obtained, and the target vibration time series group is extracted from the monitoring vibration time series group using the target vibration value group; The target vibration duration is determined according to the target vibration time sequence group, one or more analysis temperature value groups are obtained using the multiple sanding temperature time sequence groups, and the following operations are performed on each of the one or more analysis temperature value groups: For each sanding temperature value in the analysis temperature value group, perform the following operations: Calculating the monitoring temperature using the sanding temperature value and a pre-constructed monitoring temperature relationship; Acquire a target temperature duration based on the monitored temperature; respectively comparing the target vibration duration with a preset vibration duration threshold, the target temperature duration with a preset temperature duration threshold, and the comprehensive standard ratio with a preset comprehensive ratio threshold; If the target vibration duration is less than or equal to the vibration duration threshold and the target temperature duration is less than or equal to the preset temperature duration threshold and the comprehensive standard ratio is greater than or equal to the comprehensive ratio threshold; It is then confirmed that the fitted sand mill is a standard sand mill.

5. The real-time dynamic simulation method for a sand mill based on a clustering algorithm as claimed in claim 4, characterized in that: The monitoring temperature relationship is as follows: ； in, represents the monitoring temperature of the fitted sand mill, represents the temperature of the fitted sand mill surface, represents the thermal conductivity of the fitted sand mill, represents the area of ​​the fitted sand mill in contact with the air, Indicates the thickness of the wall corresponding to the sand mill, It represents the difference between the temperature of cooling water in the fitting sand mill and the temperature of the environment. represents the convective heat transfer coefficient, Indicates the temperature of cooling water. Indicates the temperature of the environment, represents the surface emissivity, represents the Boltzmann constant.

6. The real-time dynamic simulation method for a sand mill based on a clustering algorithm as claimed in claim 5, characterized in that: Determining the target vibration duration according to the target vibration timing group includes: The monitoring time interval is obtained by using the monitoring frequency, and one or more reference vibration time sequence groups are obtained according to the target vibration time sequence group, wherein the reference vibration time sequence group includes multiple target vibration values, and the absolute difference between the times corresponding to two adjacent target vibration values ​​is the monitoring time interval; Acquire one or more reference durations using the one or more reference vibration timing groups, wherein the reference durations correspond to the reference vibration timing groups one by one; A target vibration duration is determined based on the one or more reference durations, wherein the target vibration duration is a maximum reference duration among the one or more reference durations.

7. The real-time dynamic simulation method for a sand mill based on a clustering algorithm as claimed in claim 6, characterized in that: The method of constructing a sand grinding database using the plurality of analysis parameter sets comprises: The following operations are performed for each of the multiple analysis parameter sets: Mapping the analysis parameter group in the analysis parameter group set to the pre-constructed reference coordinate system to obtain the target fitting point set, wherein the horizontal axis of the reference coordinate system is the variable corresponding to the analysis parameter group, and the vertical axis of the reference coordinate system is the comprehensive standard ratio; A fitting model set for fitting a curve is obtained, wherein the fitting model set includes a plurality of fitting models, fitting models are sequentially extracted from the fitting model set, and the following operations are performed on the extracted fitting models: A fitting curve is obtained based on the extracted fitting model and the target fitting point set, and a target parameter set is retrieved from the fitting curve using the analysis parameter set, wherein the target parameter set includes a plurality of target parameter groups, and the target parameter groups correspond to the analysis parameter groups one by one, and the values ​​of the variables corresponding to the target parameter groups are the same as the values ​​of the variables corresponding to the analysis parameter groups; The target parameter set, the analysis parameter set and the pre-constructed comprehensive fitting relationship are used to calculate the comprehensive fitting value, the comprehensive fitting value is summarized to obtain the comprehensive fitting value set, and the target curve is obtained by using the comprehensive fitting value set, wherein the target curve is the fitting curve corresponding to the minimum comprehensive fitting value in the comprehensive fitting value set, the target curve is summarized to obtain multiple target curves, and the sanding database is obtained based on the multiple target curves, wherein the comprehensive fitting relationship is as follows: ； in, represents the comprehensive fitting value, Indicates that the analysis parameter group has analysis parameter groups, Indicates the target parameter set. The comprehensive standard ratio corresponding to each target parameter group, Indicates the first The comprehensive standard ratio corresponding to each analysis parameter group.

8. The real-time dynamic simulation method for a sand mill based on a clustering algorithm as claimed in claim 7, characterized in that: The step of using the initial sanding parameter set to determine a target sanding parameter set includes: Extracting initial sanding parameter groups from the initial sanding parameter group set in sequence, and performing the following operations on the extracted initial sanding parameter groups: The energy consumption prediction value is calculated based on the extracted initial sanding parameters and the pre-constructed energy consumption evaluation relationship, wherein the energy consumption evaluation relationship is as follows: ； in, represents the predicted value of energy consumption, represents the sanding time in the initial sanding parameter group, It represents the unit energy consumption of the sand mill in the initial sand mill parameter group. represents the unit loss of sanding medium in the initial sanding parameter group, Indicates the unit energy consumption to maintain the cooling water temperature, represents the fixed energy consumption of the sanding medium in the initial sanding parameter group, All are preset coefficients; The energy consumption prediction values ​​are summarized to obtain an energy consumption prediction value set, and a target sanding parameter group is confirmed using the energy consumption prediction value set, wherein the target sanding parameter group is an initial sanding parameter group corresponding to the minimum energy consumption prediction value in the energy consumption prediction value set.

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