Method and device for preparing homogeneous slurry

Abstract

The invention discloses a method and a device for preparing homogeneous slurry, which are applied to the field of batteries, and the method comprises the following steps: adaptively acquiring an optimal grinding parameter set matched with an expected particle size index from a plurality of alternative grinding parameter sets to ensure that the particle size of the obtained target slurry meets the expected particle size index; as a result, the flexibility of the determined grinding parameters is improved. The difference value between the expected maximum particle size range and the expected minimum particle size range is smaller than the preset value, so that the particle size distribution range of the target slurry is narrowed, namely the difference value between the maximum particle size and the minimum particle size of the target slurry is ensured to be small, the difference between particles of the target slurry is reduced, and the uniformity of particle size distribution of the target slurry is ensured; and thus, the quality of the obtained target slurry is improved. In addition, the target material flow and the target total grinding frequency matched with the required capacity can be determined. And the alternative material flow and the alternative grinding total frequency matched with each required capacity are recommended and displayed to an operator, so that the operator flexibly selects the required capacity. Under the condition that the actual particle size of the zirconium ball is abnormal, it is determined that the zirconium ball is seriously abraded, and alarm information is sent out, so that an operator can replace the zirconium ball in time.

Description

Technical Field

[0001] This application relates to the field of batteries, specifically to a method and apparatus for preparing a homogeneous slurry. Background Technology

[0002] Lithium-ion battery cathode materials have advantages such as good cycle stability, high energy density, and stable electrochemical platform, making them widely used in new energy electric vehicles and large and small energy storage fields.

[0003] In related technologies, during the production of cathode materials, grinding mills typically use fixed grinding parameters to grind the pre-dispersion liquid to obtain a slurry, which is then processed to obtain the cathode material.

[0004] However, because the pre-dispersion liquid was ground using fixed grinding parameters, the quality of the obtained slurry was low. Summary of the Invention

[0005] This application provides a method and apparatus for preparing a homogeneous slurry, which can solve the problems in related technologies. The technical solution includes: On the one hand, a method for preparing a homogeneous slurry is provided, the method comprising: Obtain the desired particle size index for the target slurry. The desired particle size index includes the desired maximum particle size range, the desired minimum particle size range, and the desired median particle size range. The difference between the desired maximum particle size range and the desired minimum particle size range is less than a preset value. From multiple alternative grinding parameter sets, obtain the optimal grinding parameter set that matches the desired particle size index; The optimal set of grinding parameters is used to grind the pre-dispersed liquid to obtain the target slurry.

[0006] Optionally, from a set of multiple alternative grinding parameters, the optimal set of grinding parameters that matches the desired particle size index is obtained, including: For each set of alternative grinding parameters, the alternative particle size index of the target slurry is obtained when the pre-dispersion is ground using the alternative grinding parameter set. The alternative particle size index includes the alternative maximum particle size range, the alternative minimum particle size range, and the alternative median particle size range. From multiple alternative particle size indices, select the target alternative particle size index that is closest to the desired particle size index. The set of alternative grinding parameters corresponding to the target particle size index is taken as the optimal set of grinding parameters that matches the desired particle size index.

[0007] Optionally, when the pre-dispersion is milled using an alternative set of milling parameters, alternative particle size parameters for the target slurry can be obtained, including: Input the candidate key grinding parameters from the candidate grinding parameter set into the particle size index prediction model to obtain the candidate particle size index of the target slurry when the pre-dispersion liquid is ground using the candidate grinding parameter set. Among them, the influence of the alternative key grinding parameters on the particle size distribution of the target slurry is greater than the degree threshold.

[0008] Optional key grinding parameters include: alternative grinding speed, alternative pump speed of diaphragm pump, and alternative ideal particle size of zirconium balls.

[0009] Optionally, the candidate key grinding parameters from the candidate grinding parameter set are input into the particle size index prediction model to obtain the candidate particle size index of the target slurry when the pre-dispersion liquid is ground using the candidate grinding parameter set, including: By inputting the target material flow rate, the target total number of grinding cycles, and the candidate key grinding parameters from the set of candidate grinding parameters into the particle size index prediction model, the candidate particle size index of the target slurry is obtained when the pre-dispersion liquid is ground using the set of candidate grinding parameters.

[0010] Optionally, each set of alternative grinding parameters includes: the target material flow rate and the target total number of grinding passes; the method also includes: The required production capacity to obtain the target slurry; The target material flow rate is determined by using the alternative material flow rate that matches the required production capacity, and the target total number of grinding cycles is determined by using the alternative grinding cycles that match the required production capacity. This allows for the achievement of both the target material flow rate and the target total number of grinding cycles that match the required production capacity.

[0011] Optionally, there can be multiple required production capacities; the methods also include: Displays the alternative material flow rate and the total number of alternative grinding cycles to match each required capacity. The alternative material flow rate matching the required capacity is used as the target material flow rate, and the total number of alternative grinding cycles matching the required capacity is used as the target total number of grinding cycles, including: In response to the selection command, the selected alternative material flow rate from the multiple alternative material flow rates displayed will be used as the target material flow rate, and the selected alternative total number of grinding times from the multiple alternative total number of grinding times displayed will be used as the target total number of grinding times.

[0012] By displaying alternative material flow rates and alternative total grinding times that match each required capacity, the system automatically recommends target material flow rates and target total grinding times to operators, allowing them to flexibly select the required capacity.

[0013] Optionally, the required production capacity of the target slurry can be obtained, including: Based on the standard production capacity of the target slurry, obtain multiple alternative material flow rates and multiple alternative grinding totals; Obtain the flow rate and total number of grinding cycles for each candidate material, and the corresponding candidate capacity. If the alternative capacity is greater than the standard capacity, and the difference between the alternative capacity and the standard capacity is less than the difference threshold, the alternative capacity will be used as the demand capacity.

[0014] Optionally, the method also includes: The actual grinding current was obtained during the grinding of the pre-dispersion liquid using the optimal set of grinding parameters. The actual particle size of the zirconium balls is obtained based on the actual grinding current and the optimal set of grinding parameters. An alarm will be issued if there is an anomaly in the actual particle size.

[0015] If the actual particle size is abnormal, the processing equipment can determine that the zirconium balls are severely worn and that grinding the pre-dispersion liquid with these zirconium balls cannot achieve the required production capacity. Therefore, it can issue an alarm message so that the operator can replace the zirconium balls in time.

[0016] Optionally, the method also includes: The actual particle size, the alternative grinding speed in the optimal grinding parameters, and the alternative pump speed of the diaphragm pump are input into the particle size index prediction model to obtain the predicted particle size index. If the difference between the predicted particle size index and the expected particle size index is greater than the preset difference, it is determined that there is an anomaly in the actual particle size.

[0017] On the other hand, a computer-readable storage medium is provided that stores a computer program thereon, which, when executed by a processor, implements the method for preparing a homogeneous slurry as described above.

[0018] In another aspect, a processing apparatus is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the method for preparing a homogeneous slurry as described above.

[0019] On another front, an apparatus for preparing a homogeneous slurry is provided, the apparatus comprising: The first acquisition module is used to acquire the expected particle size index of the target slurry. The expected particle size index includes the expected maximum particle size range, the expected minimum particle size range, and the expected median particle size range. The difference between the expected maximum particle size range and the expected minimum particle size range is less than a preset value. The second acquisition module is used to acquire the optimal set of grinding parameters that matches the desired particle size index from multiple alternative grinding parameter sets. The optimal set of grinding parameters is used to grind the pre-dispersed liquid to obtain the target slurry.

[0020] In summary, the embodiments of this application provide a method and apparatus for preparing homogeneous slurry. After obtaining the desired particle size index of the target slurry, the method adaptively obtains the optimal set of grinding parameters that matches the desired particle size index from multiple alternative grinding parameter sets, thereby ensuring that the particle size of the obtained target slurry meets the desired particle size index, thereby improving the flexibility of the determined grinding parameters.

[0021] Furthermore, since the difference between the expected maximum particle size range and the expected minimum particle size range is less than the preset value, the particle size distribution range of the target slurry can be narrowed, that is, the difference between the maximum and minimum particle size of the target slurry is small, thereby reducing the differences between particles in the target slurry, ensuring the uniformity of the particle size distribution of the target slurry, and thus improving the quality of the obtained target slurry.

[0022] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0023] Figure 1 This is a flowchart of a method for preparing a homogeneous slurry provided in an embodiment of this application; Figure 2 This is a flowchart of another method for preparing a homogeneous slurry provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of a processing device provided in an embodiment of this application; Figure 4 This is a block diagram of an apparatus for preparing a homogeneous slurry according to an embodiment of this application. Detailed Implementation

[0024] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0025] Figure 1 This is a flowchart illustrating a method for preparing a homogeneous slurry according to an embodiment of this application, applied to a processing device. For example... Figure 1 As shown, the method includes: Step 101: Obtain the desired particle size index for the target slurry.

[0026] The processing equipment can acquire pre-stored expected particle size indices for the target slurry, wherein the expected particle size indices include the expected maximum particle size range, the expected minimum particle size range, and the expected median particle size range, and the difference between the expected maximum particle size range and the expected minimum particle size range is less than a preset value.

[0027] For example, the expected maximum particle size range is characterized as Dmax = 0.6 μm - 1.1 μm, the expected minimum particle size range is characterized as D0 = 0.10 μm - 0.20 μm, and the expected median particle size range is characterized as D50 = 0.35 μm - 0.45 μm. The desired particle size distribution range of the target slurry can be a preset numerical range, characterized as 0.14μm-0.7μm; preferably 0.14μm-0.2μm.

[0028] Step 102: Obtain the optimal set of grinding parameters that matches the desired particle size index from multiple alternative grinding parameter sets.

[0029] After obtaining the desired particle size index of the target slurry, the processing equipment can select the optimal grinding parameter set that matches the desired particle size index from multiple alternative grinding parameter sets.

[0030] The optimal set of grinding parameters is used to grind the pre-dispersed liquid to obtain the target slurry.

[0031] For example, the pre-dispersion can be obtained by mixing an iron source, a lithium source, a phosphorus source, an optional carbon source, and optional additives.

[0032] In summary, the embodiments of this application provide a method for preparing homogeneous slurry. After obtaining the desired particle size index of the target slurry, the method adaptively obtains the optimal set of grinding parameters that matches the desired particle size index from multiple alternative grinding parameter sets, ensuring that the particle size of the obtained target slurry meets the desired particle size index, thereby improving the flexibility of the determined grinding parameters.

[0033] Furthermore, since the difference between the expected maximum particle size range and the expected minimum particle size range is less than the preset value, the particle size distribution range of the target slurry can be narrowed, that is, the difference between the maximum and minimum particle size of the target slurry is small, thereby reducing the differences between particles in the target slurry, ensuring the uniformity of the particle size distribution of the target slurry, and thus improving the quality of the obtained target slurry.

[0034] Figure 2 This is a flowchart of another method for preparing a homogeneous slurry provided in an embodiment of this application, applied to a processing device. For example... Figure 2 As shown, the method includes: Step 201: Obtain the required production capacity of the target slurry.

[0035] The required production capacity refers to the total amount of the target slurry expected to be obtained from grinding the pre-dispersion liquid.

[0036] Optionally, the processing equipment can respond to a production rush command by acquiring the required capacity of the target slurry, which is greater than the standard capacity of the target slurry. The standard capacity of the target slurry refers to the fixed capacity pre-stored in the processing equipment. When no production rush is required, the capacity of the target slurry is set to the standard capacity. When a production rush is required, the capacity used is the required capacity.

[0037] The processing equipment can obtain multiple alternative material flow rates and multiple alternative grinding totals based on the standard capacity of the target slurry, and obtain the alternative capacity corresponding to each alternative material flow rate, alternative grinding totals, and the corresponding alternative grinding capacity.

[0038] The processing equipment can store multiple alternative material flow rates corresponding to the standard production capacity, as well as multiple alternative total grinding cycles. The equipment can also store a production capacity calculation algorithm. The processing equipment can input the alternative material flow rates and the total number of alternative grinding cycles into the algorithm to obtain the corresponding alternative production capacity. Material flow rate refers to the flow rate of the pre-dispersed liquid input into the grinder.

[0039] Optionally, the processing equipment can obtain multiple alternative material flow rates and multiple alternative grinding totals based on the standard capacity and standard testing time of the target slurry.

[0040] The standard testing time indicates the time required to test the quality of the target slurry, given that the target slurry has been obtained. This quality can refer to the particle size distribution of the target slurry.

[0041] In one implementation of this application, the processing equipment can obtain the required capacity of the target slurry and determine the required capacity as the alternative capacity among multiple alternative capacities that is greater than the standard capacity and has the smallest difference from the standard capacity.

[0042] Optionally, the alternative production capacity corresponding to the alternative material grinding flow rate and the total number of alternative grinding cycles is greater than the standard production capacity.

[0043] In another implementation of this application, there are multiple required capacities, and the processing equipment can use multiple target candidate capacities from these multiple alternative capacities as multiple required capacities. Each target candidate capacity is greater than the standard capacity, and the difference between the target candidate capacity and the standard capacity is less than a difference threshold. That is, the processing equipment selects a portion of the candidate capacity that is close to the standard capacity from the multiple alternative capacities as the required capacity.

[0044] Step 202: Take the alternative material flow rate that matches the required capacity as the target material flow rate, and take the alternative total number of grinding cycles that matches the required capacity as the target total number of grinding cycles.

[0045] When the required capacity is one, the processing equipment can use the alternative material flow rate that matches the required capacity as the target material flow rate, and use the total number of alternative grinding cycles that matches the required capacity as the target total number of grinding cycles.

[0046] When there are multiple required production capacities, the processing equipment can display alternative material flow rates and alternative total grinding times that match each required production capacity. In response to a selection command, the alternative material flow rate selected from the multiple displayed alternative material flow rates is used as the target material flow rate, and the alternative total grinding times selected from the multiple displayed alternative total grinding times is used as the target total grinding times.

[0047] By displaying alternative material flow rates and alternative total grinding times that match each required capacity, the system automatically recommends target material flow rates and target total grinding times to operators, allowing them to flexibly select the required capacity.

[0048] In this embodiment of the application, when there is no need to rush production, the processing equipment can use the standard material flow rate corresponding to the standard production capacity as the target material flow rate, and the standard total number of grinding cycles corresponding to the standard production capacity as the target total number of grinding cycles.

[0049] Step 203: Obtain the desired particle size index for the target slurry.

[0050] The processing equipment can acquire pre-stored expected particle size indices for the target slurry, wherein the expected particle size indices include the expected maximum particle size range, the expected minimum particle size range, and the expected median particle size range, and the difference between the expected maximum particle size range and the expected minimum particle size range is less than a preset value.

[0051] For example, the expected maximum particle size range is characterized as Dmax = 0.6 μm - 1.1 μm, the expected minimum particle size range is characterized as D0 = 0.10 μm - 0.20 μm, and the expected median particle size range is characterized as D50 = 0.35 μm - 0.45 μm; the expected particle size distribution range of the target slurry can be a preset numerical range, characterized as 0.14 μm - 0.7 μm; preferably 0.14 μm - 0.2 μm.

[0052] Since the difference between the expected maximum particle size range and the expected minimum particle size range is less than the preset value, the particle size distribution range of the target slurry can be narrowed, that is, the difference between the maximum and minimum particle size of the target slurry is small, thereby reducing the difference between particles in the target slurry and ensuring the uniformity of the particle size distribution of the target slurry.

[0053] Step 204: Obtain a set of multiple alternative grinding parameters.

[0054] Each set of alternative grinding parameters may include the target material flow rate, the target total number of grinding cycles, alternative key grinding parameters, the target grinding current, and the target pressure of the diaphragm pump in the grinder.

[0055] The alternative key grinding parameters may include: alternative grinding speed, alternative pump speed of the diaphragm pump, and alternative ideal particle size of the zirconium balls in the grinder. The values ​​of the alternative key grinding parameters are different in different sets of alternative grinding parameters, while the values ​​of other grinding parameters in the sets of alternative grinding parameters are the same.

[0056] In this embodiment of the application, the processing device can randomly generate multiple alternative key grinding parameters, and use each alternative key grinding parameter, target material flow rate, target total number of grinding cycles, target grinding current and target pressure of diaphragm pump as a set of alternative grinding parameters.

[0057] It should be noted that the influence of the candidate key grinding parameter on the particle size distribution of the target slurry is greater than the threshold value; that is, the candidate key grinding parameter significantly affects the particle size distribution of the target slurry. The influence of this candidate key grinding parameter on the particle size distribution of the target slurry is greater than the influence of other grinding parameters in the candidate grinding parameter set on the particle size distribution of the target slurry.

[0058] In this embodiment of the application, the processing device can acquire multiple sets of reference grinding parameters and reference particle size indices corresponding to the multiple sets of reference grinding parameters. Grinding parameters of the same type in the multiple sets of reference grinding parameters are taken as a parameter sequence, and multiple reference particle size indices are taken as a particle size index sequence. A target parameter sequence with a correlation greater than a preset threshold with the particle size index sequence is obtained from the multiple parameter sequences, and the parameter to which the target parameter sequence belongs is taken as the key grinding parameter.

[0059] Each set of reference grinding parameters may include reference material flow rate, total number of reference grinding cycles, reference grinding speed, reference pump speed of the diaphragm pump, reference ideal particle size of the zirconium balls, reference grinding current, and reference pressure of the diaphragm pump. The reference particle size index includes the reference maximum particle size range, the reference minimum particle size range, and the reference median particle size range. This reference particle size index is obtained when the pre-dispersion liquid is ground using the corresponding set of reference grinding parameters.

[0060] Taking an example where each set of reference grinding parameters includes reference material flow rate, reference grinding speed, reference pump speed of the diaphragm pump, and reference ideal particle size of the zirconium balls, the processing equipment can use the reference material flow rate from multiple sets of reference grinding parameters as the first parameter sequence, the reference grinding speed from multiple sets of reference grinding parameters as the second parameter sequence, the reference pump speed from multiple sets of reference grinding parameters as the third parameter sequence, and the reference ideal particle size from multiple sets of reference grinding parameters as the fourth parameter sequence. If the correlation between the second to fourth parameter sequences and the particle size index sequence is greater than a preset threshold, the processing equipment can determine the second to fourth parameter sequences as the target parameter sequences, and then use the grinding speed, the pump speed of the diaphragm pump, and the ideal particle size of the zirconium balls as key parameters.

[0061] This key parameter significantly affects the particle size distribution of the grinding slurry. Therefore, by optimizing this key parameter, a slurry with a uniform particle size distribution can be obtained. Furthermore, by collecting a "reference grinding parameter set and reference particle size index" for each grinding process, the key grinding parameters that have the greatest impact on the particle size distribution width can be identified.

[0062] In this embodiment of the application, before obtaining the correlation between each parameter sequence and the particle size index sequence, the processing device can perform cluster analysis on multiple reference grinding parameter sets, and remove reference grinding parameter sets with abnormal parameters, as well as the reference particle size index corresponding to the reference grinding parameter set, so as to improve the accuracy of the determined key parameters.

[0063] For example, the processing device can use the K-Means algorithm to perform cluster analysis on multiple sets of reference grinding parameters.

[0064] In some embodiments, correlation analysis may involve obtaining Pearson correlation coefficient, Spearman rank correlation coefficient, distance correlation coefficient, mutual information (MI) coefficient, maximal information coefficient (MIC), and determining feature importance or Shapley additive exPlanations (SHAP) values ​​using correlation calculation algorithms. The correlation calculation algorithms may include random forest algorithms or gradient boosting decision tree (BDT) algorithms.

[0065] Among them, the Pearson correlation coefficient is used to measure the linearity, while the Spearman rank correlation coefficient is used to measure monotonicity.

[0066] Step 205: For each set of alternative grinding parameters, obtain the alternative particle size index of the target slurry when the pre-dispersion liquid is ground using the set of alternative grinding parameters.

[0067] The candidate particle size index may include the candidate maximum particle size range, the candidate minimum particle size range, and the candidate median particle size range.

[0068] For each set of alternative grinding parameters, the processing equipment can input the alternative key grinding parameters in the set into the particle size index prediction model to obtain the alternative particle size index of the target slurry when the pre-dispersion liquid is ground using the alternative grinding parameter set.

[0069] In this embodiment of the application, the processing device can acquire multiple sample data and train the multiple sample data to obtain a particle size index prediction model.

[0070] Each sample data point may include key grinding parameters and the corresponding particle size index. The particle size index prediction model may include a support vector machine model or a neural network model.

[0071] In this embodiment, the processing device can input the key grinding parameters of each sample into the initial model to obtain the predicted particle size label output by the initial model, and calculate the loss value between each predicted particle size label and the corresponding sample particle size index. If the loss value is greater than or equal to a preset loss value, the processing device can adjust the parameters of the initial model until the loss value is less than the preset loss value. After that, the processing device can use the trained model as the particle size index prediction model.

[0072] Optionally, the processing device can normalize the reference key parameters in the reference grinding parameter set used for correlation analysis in step 203 above, and use the normalized reference key parameters as a sample key grinding parameter. The reference particle size index corresponding to the reference grinding parameter set can be normalized, and the normalized reference particle size index can be used as the sample particle size index corresponding to the sample key grinding parameter.

[0073] In some embodiments of this application, the processing device can input the target material flow rate, the target total number of grinding cycles, and the candidate key grinding parameters from the set of candidate grinding parameters into the particle size index prediction model to obtain the candidate particle size index of the target slurry when the pre-dispersion liquid is ground using the set of candidate grinding parameters.

[0074] Optionally, each sample data may also include the sample material flow rate and the total number of sample grinding cycles.

[0075] The processing equipment can normalize the reference material flow rate and the total number of reference grinding times in the reference grinding parameter set used for correlation analysis in step 203 above, and use the normalized reference material flow rate as a sample material flow rate and the normalized total number of reference grinding times as a sample total number of grinding times.

[0076] Step 206: From multiple candidate particle size indices, obtain the target candidate particle size index that is closest to the desired particle size index.

[0077] After acquiring multiple candidate particle size indicators, the processing equipment can select the target candidate particle size indicator that is closest to the desired particle size indicator from among the multiple candidate particle size indicators.

[0078] The processing equipment can perform similarity analysis between each candidate particle size index and the desired particle size index, and select the candidate particle size index with the highest similarity to the desired particle size index as the target candidate particle size index.

[0079] For example, the processing device can perform a correlation analysis between each candidate particle size index and the desired particle size index, and select the candidate particle size index with the highest correlation to the desired particle size index as the target candidate particle size index.

[0080] Step 207: Select the set of alternative grinding parameters corresponding to the target alternative particle size index as the set of optimal grinding parameters that match the desired particle size index.

[0081] After obtaining the target candidate particle size index that is closest to the desired particle size index, the processing equipment can use the set of candidate grinding parameters corresponding to the target candidate particle size index as the optimal grinding parameter set that matches the desired particle size index.

[0082] The optimal set of grinding parameters is used to grind the pre-dispersed liquid to obtain the target slurry.

[0083] Step 208: During the grinding of the pre-dispersion liquid using the optimal set of grinding parameters, obtain the actual grinding current.

[0084] The processing equipment obtains the actual grinding current of the mill during the grinding process of the pre-dispersed liquid using the optimal set of grinding parameters.

[0085] Step 209: Based on the actual grinding current and the optimal grinding parameter set, obtain the actual particle size of the zirconium balls.

[0086] After obtaining the actual grinding current, the processing equipment can determine the actual particle size of the zirconium balls based on the actual grinding current and the optimal set of grinding parameters.

[0087] Optionally, the processing equipment can obtain the actual particle size of the zirconium balls based on the actual grinding current and multiple target optimal parameters from the optimal grinding parameter set, excluding the target grinding current, the target total number of grinding cycles, and the alternative ideal particle size of the zirconium balls.

[0088] The processing equipment can input the actual grinding current and multiple target optimal parameters into the objective function to obtain the actual particle size of the zirconium balls.

[0089] The objective function is a multivariate linear relationship between the optimal parameters and the grinding current. The optimal parameters may include material flow rate, grinding speed, diaphragm pump speed, ideal zircon ball size, and diaphragm pump pressure. The ideal zircon ball size refers to the size of the zircon ball before wear occurs, i.e., the initial size of the zircon ball.

[0090] The processing equipment can obtain multiple optimal parameters and the grinding current corresponding to each optimal parameter, and fit these multiple optimal parameters and multiple grinding currents to obtain the objective function.

[0091] Step 210: If there is an abnormality in the actual particle size, issue an alarm message.

[0092] After obtaining the actual particle size of the zirconium balls, the processing equipment can determine whether the actual particle size is abnormal. If the actual particle size is abnormal, it can be determined that the zirconium balls are severely worn, and using these zirconium balls to grind the pre-dispersion liquid cannot achieve the required production capacity. Therefore, an alarm message can be issued so that the operator can replace the zirconium balls in time. If the actual particle size is not abnormal, no alarm message needs to be issued.

[0093] In some embodiments of this application, the processing device can input the actual particle size, the alternative grinding speed and the alternative pump speed from the optimal grinding parameters into the particle size index prediction model to obtain the predicted particle size index. If the difference between the predicted particle size index and the expected particle size index is greater than a preset difference, it can be determined that the actual particle size is abnormal. If the difference between the predicted particle size index and the expected particle size index is less than or equal to a preset difference, it can be determined that the actual particle size is not abnormal.

[0094] The difference between the predicted particle size index and the expected particle size index can refer to the similarity between the two. If the similarity between the predicted and expected particle size indices is greater than a similarity threshold, then the difference between the predicted and expected particle size indices is greater than a preset difference. If the similarity between the predicted and expected particle size indices is less than or equal to the similarity threshold, then the difference between the predicted and expected particle size indices is less than or equal to a preset difference.

[0095] The solutions provided in this application are closely aligned with actual production and are characterized by automation, high efficiency, and precision.

[0096] In summary, the embodiments of this application provide a method for preparing homogeneous slurry. After obtaining the desired particle size index of the target slurry, the method adaptively obtains the optimal set of grinding parameters that matches the desired particle size index from multiple alternative grinding parameter sets, ensuring that the particle size of the obtained target slurry meets the desired particle size index, thereby improving the flexibility of the determined grinding parameters.

[0097] Furthermore, since the difference between the expected maximum particle size range and the expected minimum particle size range is less than the preset value, the particle size distribution range of the target slurry can be narrowed, that is, the difference between the maximum and minimum particle size of the target slurry is small, thereby reducing the differences between particles in the target slurry, ensuring the uniformity of the particle size distribution of the target slurry, and thus improving the quality of the obtained target slurry.

[0098] This application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method for preparing homogeneous slurry described in the above embodiments.

[0099] Figure 3 This is a schematic diagram of the structure of a processing device provided in an embodiment of this application, such as... Figure 3 As shown, the processing device 30 may include a memory 301, a processor 302, and a computer program stored in the memory 301 and executable on the processor 302. When the processor 302 executes the computer program, it implements the method for preparing homogeneous slurry as described in the above embodiments.

[0100] The processing equipment can be a grinder or a device connected to a grinder.

[0101] Figure 4 This is a block diagram of an apparatus for preparing a homogeneous slurry according to an embodiment of this application, as shown below. Figure 4 As shown, the device includes: The first acquisition module 401 is used to acquire the expected particle size index of the target slurry. The expected particle size index includes the expected maximum particle size range, the expected minimum particle size range, and the expected median particle size range in the target slurry. The difference between the expected maximum particle size range and the expected minimum particle size range is less than a preset value. The second acquisition module 402 is used to acquire the optimal set of grinding parameters that matches the desired particle size index from multiple alternative grinding parameter sets. The optimal set of grinding parameters is used to grind the pre-dispersed liquid to obtain the target slurry.

[0102] Optionally, the second acquisition module 402 is used for: For each set of alternative grinding parameters, the alternative particle size index of the target slurry is obtained when the pre-dispersion is ground using the alternative grinding parameter set. The alternative particle size index includes the alternative maximum particle size range, the alternative minimum particle size range, and the alternative median particle size range. From multiple alternative particle size indices, select the target alternative particle size index that is closest to the desired particle size index. The set of alternative grinding parameters corresponding to the target particle size index is taken as the optimal set of grinding parameters that matches the desired particle size index.

[0103] Optionally, the second acquisition module 402 is used for: Input the candidate key grinding parameters from the candidate grinding parameter set into the particle size index prediction model to obtain the candidate particle size index of the target slurry when the pre-dispersion liquid is ground using the candidate grinding parameter set. Among them, the influence of the alternative key grinding parameters on the particle size distribution of the target slurry is greater than the degree threshold.

[0104] Optional key grinding parameters include: alternative grinding speed, alternative pump speed of diaphragm pump, and alternative ideal particle size of zirconium balls.

[0105] Optionally, the second acquisition module 402 is used for: By inputting the target material flow rate, the target total number of grinding cycles, and the candidate key grinding parameters from the set of candidate grinding parameters into the particle size index prediction model, the candidate particle size index of the target slurry is obtained when the pre-dispersion liquid is ground using the set of candidate grinding parameters.

[0106] Optionally, each set of alternative grinding parameters includes: the target material flow rate and the target total number of grinding cycles; the second acquisition module 402 is also used for: The required production capacity to obtain the target slurry; The alternative material flow rate that matches the required capacity is taken as the target material flow rate, and the total number of alternative grinding cycles that matches the required capacity is taken as the target total number of grinding cycles.

[0107] Optionally, the required capacity can be multiple; the second acquisition module 402 is also used for: Displays the alternative material flow rate and the total number of alternative grinding cycles to match each required capacity. The alternative material flow rate matching the required capacity is used as the target material flow rate, and the total number of alternative grinding cycles matching the required capacity is used as the target total number of grinding cycles, including: In response to the selection command, the selected alternative material flow rate from the multiple alternative material flow rates displayed will be used as the target material flow rate, and the selected alternative total number of grinding times from the multiple alternative total number of grinding times displayed will be used as the target total number of grinding times.

[0108] Optionally, the second acquisition module 402 is also used for: Based on the standard production capacity of the target slurry, obtain multiple alternative material flow rates and multiple alternative total grinding times; Obtain the flow rate and total number of grinding cycles for each candidate material, and the corresponding candidate capacity. If the alternative capacity is greater than the standard capacity, and the difference between the alternative capacity and the standard capacity is less than the difference threshold, the alternative capacity will be used as the demand capacity.

[0109] Optionally, the second acquisition module 402 is also used for: The actual grinding current was obtained during the grinding of the pre-dispersion liquid using the optimal set of grinding parameters. The actual particle size of the zirconium balls is obtained based on the actual grinding current and the optimal set of grinding parameters. An alarm will be issued if there is an anomaly in the actual particle size.

[0110] Optionally, the second acquisition module 402 is also used for: The actual particle size, the alternative grinding speed in the optimal grinding parameters, and the alternative pump speed of the diaphragm pump are input into the particle size index prediction model to obtain the predicted particle size index. If the difference between the predicted particle size index and the expected particle size index is greater than the preset difference, it is determined that there is an anomaly in the actual particle size.

[0111] In summary, the embodiments of this application provide an apparatus for preparing homogeneous slurry. After obtaining the desired particle size index of the target slurry, the apparatus adaptively obtains the optimal set of grinding parameters that matches the desired particle size index from multiple alternative grinding parameter sets, ensuring that the particle size of the obtained target slurry meets the desired particle size index, thereby improving the flexibility of the determined grinding parameters.

[0112] Furthermore, since the difference between the expected maximum particle size range and the expected minimum particle size range is less than the preset value, the particle size distribution range of the target slurry can be narrowed, that is, the difference between the maximum and minimum particle size of the target slurry is small, thereby reducing the differences between particles in the target slurry, ensuring the uniformity of the particle size distribution of the target slurry, and thus improving the quality of the obtained target slurry.

[0113] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0114] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0115] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0116] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0117] Furthermore, the terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying relative importance, or implicitly specifying the number of technical features indicated in this embodiment. Therefore, features defined with terms such as "first" and "second" in the embodiments of this invention can explicitly or implicitly indicate that the embodiment includes at least one of those features. In the description of this invention, the word "multiple" means at least two or more, such as two, three, four, etc., unless otherwise explicitly specified in the embodiments.

[0118] In this invention, unless otherwise explicitly specified or limited in the embodiments, the terms "installation," "connection," "joining," and "fixing" appearing in the embodiments should be interpreted broadly. For example, a connection can be a fixed connection, a detachable connection, or an integral part; it can also be a mechanical connection, an electrical connection, etc. Of course, it can also be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal communication of two components, or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific implementation.

[0119] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0120] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for preparing a homogeneous slurry, characterized in that, The method includes: Obtain the desired particle size index for the target slurry. The desired particle size index includes the desired maximum particle size range, the desired minimum particle size range, and the desired median particle size range. The difference between the desired maximum particle size range and the desired minimum particle size range is less than a preset value. From multiple alternative grinding parameter sets, obtain the optimal grinding parameter set that matches the desired particle size index; The optimal grinding parameter set is used to grind the pre-dispersion liquid to obtain the target slurry.

2. The method according to claim 1, characterized in that, From a set of multiple alternative grinding parameters, the optimal set of grinding parameters that matches the desired particle size index is obtained, including: For each set of alternative grinding parameters, when the pre-dispersion liquid is ground using the set of alternative grinding parameters, alternative particle size indices of the target slurry are obtained, including alternative maximum particle size range, alternative minimum particle size range, and alternative median particle size range. From the multiple candidate particle size indices, obtain the target candidate particle size index that is closest to the desired particle size index; The set of alternative grinding parameters corresponding to the target alternative particle size index is taken as the optimal grinding parameter set that matches the desired particle size index.

3. The method according to claim 2, characterized in that, Obtaining candidate particle size parameters for the target slurry when the pre-dispersion liquid is ground using the aforementioned set of candidate grinding parameters includes: The candidate key grinding parameters in the set of candidate grinding parameters are input into the particle size index prediction model to obtain the candidate particle size index of the target slurry when the pre-dispersion liquid is ground using the set of candidate grinding parameters. Among them, the degree of influence of the alternative key grinding parameters on the particle size distribution of the target slurry is greater than the degree threshold.

4. The method according to claim 3, characterized in that, The alternative key grinding parameters include: alternative grinding speed, alternative pump speed of diaphragm pump, and alternative ideal particle size of zirconium balls.

5. The method according to claim 3, characterized in that, The candidate key grinding parameters from the set of candidate grinding parameters are input into the particle size index prediction model to obtain the candidate particle size index of the target slurry when the pre-dispersion liquid is ground using the set of candidate grinding parameters, including: The target material flow rate, the target total number of grinding cycles, and the candidate key grinding parameters from the set of candidate grinding parameters are input into the particle size index prediction model to obtain the candidate particle size index of the target slurry when the pre-dispersion liquid is ground using the set of candidate grinding parameters.

6. The method according to any one of claims 1 to 5, characterized in that, Each set of candidate grinding parameters includes: a target material flow rate and a target total number of grinding cycles; the method further includes: Obtain the required production capacity of the target slurry; The alternative material flow rate that matches the required production capacity is taken as the target material flow rate, and the total number of alternative grinding cycles that matches the required production capacity is taken as the target total number of grinding cycles.

7. The method according to claim 6, characterized in that, The required production capacity is multiple; the method further includes: Displays the alternative material flow rate and the total number of alternative grinding cycles to match each of the stated required capacities; The alternative material flow rate matching the required production capacity is taken as the target material flow rate, and the total number of alternative grinding cycles matching the required production capacity is taken as the target total number of grinding cycles, including: In response to the selection command, the selected alternative material flow rate from the plurality of displayed alternative material flow rates is taken as the target material flow rate, and the selected alternative total number of grinding times from the plurality of displayed alternative total number of grinding times is taken as the target total number of grinding times.

8. The method according to claim 6, characterized in that, Obtaining the required production capacity of the target slurry includes: Based on the standard production capacity of the target slurry, obtain multiple alternative material flow rates and multiple alternative total grinding times; Obtain the flow rate of each candidate material and the total number of grinding cycles for each candidate material, and the corresponding candidate production capacity; If the alternative capacity is greater than the standard capacity, and the difference between the alternative capacity and the standard capacity is less than a difference threshold, the alternative capacity shall be used as the demand capacity.

9. The method according to any one of claims 1 to 5, characterized in that, The method further includes: During the grinding of the pre-dispersion liquid using the optimal grinding parameter set, the actual grinding current is obtained; Based on the actual grinding current and the optimal grinding parameter set, the actual particle size of the zirconium balls is obtained; An alarm will be issued if the actual particle size is abnormal.

10. The method according to claim 9, characterized in that, The method further includes: The actual particle size, the alternative grinding speed in the optimal grinding parameters, and the alternative pump speed of the diaphragm pump are input into the particle size index prediction model to obtain the predicted particle size index. If the difference between the predicted particle size index and the expected particle size index is greater than a preset difference, it is determined that the actual particle size is abnormal.

11. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the method for preparing a homogeneous slurry as described in any one of claims 1 to 10.

12. A processing apparatus, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the method for preparing a homogeneous slurry as described in any one of claims 1 to 10.

13. An apparatus for preparing a homogeneous slurry, characterized in that, The device includes: The first acquisition module is used to acquire the expected particle size index of the target slurry. The expected particle size index includes the expected maximum particle size range, the expected minimum particle size range, and the expected median particle size range. The difference between the expected maximum particle size range and the expected minimum particle size range is less than a preset value. The second acquisition module is used to acquire the optimal set of grinding parameters that matches the desired particle size index from multiple alternative grinding parameter sets. The optimal grinding parameter set is used to grind the pre-dispersion liquid to obtain the target slurry.

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