Automatic mixing control device and control method applied to heat-sensitive paint processing

Abstract

The present application relates to the technical field of material processing, and in particular to an automatic mixing control device and control method applied to heat-sensitive paint processing, the method comprising: performing difference analysis on reaction information of the n-1th operation in the current batch and reaction information of the n-1th operation in each historical batch to determine similar batches; determining a cumulative target raw material quantity difference between each similar batch and the current batch, a target raw material quantity difference of the n-1th operation, and a cumulative influence coefficient of the target raw material; and determining a target raw material quantity of the nth operation in the current batch according to a target raw material quantity of the nth operation in each similar batch, a calculation weight of each similar batch, and a similarity coefficient of each similar batch. The present application can dynamically adjust the target raw material quantity according to real-time raw material reaction conditions, thereby improving the yield of heat-sensitive paint.

Description

Technical Field

[0001] This invention relates to the technical field of materials processing, and specifically to an automatic mixing control device and control method for processing heat-sensitive coatings. Background Technology

[0002] A thermosensitive coating can be prepared by uniformly mixing colorless dyes, color developers, sensitizers, fillers, and adhesives in a certain proportion. During the mixing process, it is necessary to strictly control the proportions and mixing quality of each raw material to ensure that the performance of the prepared thermosensitive coating meets expectations. After mixing, the raw materials need to be dispersed by high-speed stirring or the use of dispersants to break up agglomerates and form a uniform dispersion.

[0003] In the process of preparing thermosensitive coatings based on raw materials, the raw materials need to be added to a mixing device in a certain proportion for stirring. Since the mixing device has a large capacity, it can accommodate a large amount of raw materials for reaction. However, in application, it has been found that adding too much raw material at once will cause the machine to stir unevenly for a long time, resulting in the problem of local temperature accumulation being too high, ultimately leading to a lower-than-expected yield of thermosensitive coatings. Therefore, the existing technology will choose to add raw materials in small amounts multiple times to avoid the above-mentioned problem of uneven stirring to a certain extent. However, each time the material is added, the specific amount of raw material cannot be well adapted to the current reaction conditions, which also makes the yield of thermosensitive coatings lower than expected.

[0004] In other words, the yield of thermosensitive coatings prepared using existing technologies is relatively low. Summary of the Invention

[0005] To address the low yield problem in the preparation of thermosensitive coatings using existing technologies, the present invention aims to provide an automatic mixing control device and control method for thermosensitive coating processing. The specific technical solution adopted is as follows:

[0006] In a first aspect, one embodiment of the present invention provides an automatic mixing control method for processing heat-sensitive coatings, the method comprising:

[0007] Perform a difference analysis on the reaction information of the (n-1)th operation in the current batch and the reaction information of the (n-1)th operation in each historical batch to identify similar batches among multiple historical batches, where n is an integer greater than 1;

[0008] The calculation weight of each similar batch is determined based on the cumulative difference of each similar batch, the incremental difference of each similar batch, and the cumulative influence coefficient of the target raw material. The cumulative difference is used to indicate the difference in the amount of target raw material added in the previous n-1 operations between the corresponding similar batch and the current batch. The incremental difference is used to indicate the difference in the amount of target raw material added in the n-1 operation between the corresponding similar batch and the current batch. The target raw material is any one of the multiple raw materials used to prepare the thermosensitive coating.

[0009] The amount of target raw material added to the current batch in the nth operation is determined based on the amount of target raw material added to each similar batch in the nth operation, the calculated weight of each similar batch, and the similarity coefficient of each similar batch. The similarity coefficient is used to indicate the degree of similarity between the reaction curves of the corresponding similar batch and the current batch.

[0010] In one embodiment, the step of performing a difference analysis on the reaction information of the (n-1)th operation in the current batch and the reaction information of the (n-1)th operation in each historical batch to identify similar batches among multiple historical batches includes:

[0011] Obtain the reaction curve of the (n-1)th operation in the current batch and the reaction curve of the (n-1)th operation in each historical batch, wherein the reaction curve is used to represent the degree of disorder over time in the corresponding operation, and the degree of disorder is used to indicate the degree of reaction disorder of the multiple raw materials at the corresponding time.

[0012] A difference analysis is performed on the slope of the curve points between the reaction curve of the (n-1)th operation in the current batch and the reaction curve of the (n-1)th operation in each historical batch to obtain multiple slope difference indices for each historical batch.

[0013] A difference analysis of the disorder of the curve points between the reaction curve of the (n-1)th operation in the current batch and the reaction curve of the (n-1)th operation in each historical batch is performed to obtain multiple reaction degree difference indices for each historical batch.

[0014] Based on the multiple slope difference indices and multiple disorder difference indices corresponding to each historical batch, the batch difference value corresponding to each historical batch is determined.

[0015] Historical batches whose batch difference value is less than or equal to a preset first threshold are identified as similar batches.

[0016] In one embodiment, the step of obtaining the disorder degree of the target curve point includes:

[0017] The difference between the sampled temperature value at each sampling location at the target time and the average temperature at the target time is calculated to obtain the temperature difference value at each sampling location at the target time. The average temperature is the average of the sampled temperature values ​​at multiple sampling locations at the target time. The target time is the time corresponding to the target curve point. The target curve point is any curve point in the reaction curve of the (n-1)th operation in the current batch, or the target curve point is any curve point in the reaction curve of the (n-1)th operation in the historical batch.

[0018] The difference between the sampled acid-base value at each sampling location at the target time and the mean acid-base value at the target time is calculated to obtain the acid-base difference value at each sampling location at the target time. The mean acid-base value is the average of the sampled acid-base values ​​at multiple sampling locations at the target time.

[0019] The disorder of the target curve point is determined based on the temperature difference, acid-base difference, and current fluctuation value at each sampling location at the target time. The current fluctuation value at the target time is used to indicate the degree of fluctuation of the current data at the target time.

[0020] In one embodiment, determining the batch difference value corresponding to each historical batch based on multiple slope difference indices and multiple disorder difference indices corresponding to each historical batch includes:

[0021] Calculate the product of each slope difference index and the corresponding disorder difference index for each historical batch to obtain multiple batch difference parameters for each historical batch. Among them, the multiple batch difference parameters for each historical batch correspond one-to-one with the multiple slope difference indices for each historical batch.

[0022] Calculate the sum of multiple batch difference parameters corresponding to each historical batch to obtain the batch difference value corresponding to each historical batch.

[0023] In one embodiment, the step of obtaining the cumulative influence coefficient of the target raw material includes:

[0024] Based on the multiple historical batches, multiple first data and multiple second data associated with the target raw material are obtained, wherein the multiple first data and the multiple second data correspond one-to-one, the multiple first data correspond one-to-one with multiple operations, the change in the amount of target raw material added in any two different operations in the multiple operations is the same, and the cumulative amount of target raw material added in any two different operations in the multiple operations is different. The first data is used to indicate the cumulative amount of target raw material added at the corresponding operation, and the second data is used to indicate the degree of influence of the target raw material added at the corresponding operation on the reaction process.

[0025] Correlation analysis is performed on the plurality of first data and the plurality of second data to obtain the cumulative influence coefficient of the target raw material.

[0026] In one embodiment, the step of obtaining the target second data includes:

[0027] Obtain the target change amount and target curve difference value corresponding to the target operation, wherein the target operation is any one of the multiple operations, the target change amount is used to indicate the change in the amount of target raw material added during the target operation, the target curve difference value is used to indicate the degree of difference in the reaction curve between the target operation and the previous operation corresponding to the target operation, the reaction curve is used to represent the degree of disorder in the corresponding operation over time, and the degree of disorder is used to indicate the degree of reaction disorder of the multiple raw materials at the corresponding time.

[0028] Calculate the ratio of the target change amount corresponding to the target operation to the target curve difference value to obtain the target second data corresponding to the target operation, wherein the plurality of second data includes the target second data.

[0029] In one embodiment, the step of performing correlation analysis on the plurality of first data and the plurality of second data to obtain the cumulative influence coefficient of the target raw material includes:

[0030] A target straight line is obtained by performing linear fitting on the plurality of first data and the plurality of second data;

[0031] The cumulative influence coefficient of the target raw material is determined based on the slope of the target straight line.

[0032] In one embodiment, after determining the amount of target raw material added to the current batch in the nth operation based on the amount of target raw material added to each similar batch in the nth operation, the calculated weight of each similar batch, and the similarity coefficient of each similar batch, the method further includes:

[0033] The reaction information of the target time period is analyzed to obtain the analysis results. The target time period is the time period from the start time of the (n-1)th operation of the current batch to the set start time of the nth operation of the current batch. The analysis results are used to indicate the stability of the mixed reaction of the multiple raw materials in the target time period.

[0034] When the analysis results indicate that the stability of the mixed reaction of the multiple raw materials in the target time period matches the preset stability conditions, the nth operation of the current batch is performed based on the amount of the target raw material added in the nth operation.

[0035] In one embodiment, after analyzing the response information for the target time period and obtaining the analysis results, the method further includes:

[0036] When the analysis results indicate that the stability of the mixed reaction of the plurality of raw materials during the target time period does not match the stability conditions, the execution of the nth operation for the current batch is delayed.

[0037] Secondly, another embodiment of the present invention provides an automatic mixing control device for processing heat-sensitive coatings, the device comprising:

[0038] The batch determination module is used to perform difference analysis on the reaction information of the (n-1)th operation in the current batch and the reaction information of the (n-1)th operation in each historical batch, so as to identify similar batches among multiple historical batches, where n is an integer greater than 1.

[0039] The weight calculation module is used to determine the calculation weight of each similar batch based on the cumulative difference of each similar batch, the incremental difference of each similar batch, and the cumulative influence coefficient of the target raw material. The cumulative difference is used to indicate the difference in the amount of target raw material added in the previous n-1 operations between the corresponding similar batch and the current batch. The incremental difference is used to indicate the difference in the amount of target raw material added in the n-1 operation between the corresponding similar batch and the current batch. The target raw material is any one of a plurality of raw materials used to prepare the thermosensitive coating.

[0040] The quantity calculation module is used to determine the quantity of the target raw material added to the current batch in the nth operation based on the quantity of the target raw material added to each similar batch in the nth operation, the calculation weight of each similar batch, and the similarity coefficient of each similar batch. The similarity coefficient is used to indicate the degree of similarity between the reaction curves of the corresponding similar batch and the current batch.

[0041] Thirdly, in another embodiment of the present invention, an electronic device is provided, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method described in the first aspect.

[0042] Fourthly, in another embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0043] The present invention has the following beneficial effects:

[0044] This invention, in the process of preparing a thermosensitive coating by adding raw materials in small quantities and multiple times for mixing and reaction, analyzes the difference between the reaction information of the (n-1)th operation in the current batch and the reaction information of the (n-1)th operation in each historical batch. This allows for the identification of similar batches with similar reaction conditions among multiple historical batches. Furthermore, it analyzes the cumulative amount of raw materials added and the difference between the current batch and each similar batch. Combined with the cumulative influence coefficient used to quantify the impact of cumulative raw material addition on the degree of reaction, the calculation weight of each similar batch is determined from multiple perspectives, i.e., the guiding weight of each similar batch for the current batch. Based on this, and combined with the amount of raw materials added in the nth operation of each similar batch, the amount of target raw material to be added in the nth operation of the current batch is calculated. This method allows for dynamic adjustment of the amount of target raw material added based on the real-time reaction status of each raw material, achieving precise control of the amount of target raw material added, suppressing incomplete reaction of raw materials, and improving the yield of the thermosensitive coating. Attached Figure Description

[0045] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a schematic flowchart illustrating an automatic mixing control method for processing heat-sensitive coatings, provided as an embodiment of the present invention.

[0047] Figure 2 This is a schematic diagram of an automatic mixing control device for processing heat-sensitive coatings, provided in one embodiment of the present invention.

[0048] Figure 3 This is a schematic diagram of the structure of an electronic device provided in one embodiment of the present invention. Detailed Implementation

[0049] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an automatic mixing control device and control method for heat-sensitive coating processing proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0051] The following description, in conjunction with the accompanying drawings, details the specific scheme of an automatic mixing control device and control method for heat-sensitive coating processing provided by the present invention.

[0052] This invention proposes an automatic mixing control method for the processing of heat-sensitive coatings. Please refer to [link / reference]. Figure 1 The diagram illustrates an automatic mixing control method for heat-sensitive coating processing according to an embodiment of the present invention, which includes the following steps:

[0053] Step S1: Perform a difference analysis on the reaction information of the (n-1)th operation in the current batch and the reaction information of the (n-1)th operation in each historical batch to identify similar batches among multiple historical batches.

[0054] Where n is an integer greater than 1.

[0055] The above reaction information is collected based on multiple sensors pre-installed in the mixing device (also known as the stirring device). The mixing device is used to receive multiple raw materials fed in by the feeding device and to stir them at high speed to break up the agglomerates in the raw materials and form a uniform dispersion. The dispersion can be used as a heat-sensitive coating.

[0056] The reaction information may include current data, temperature data, and pH data. Current data can be understood as the current value of the motor driving the stirring rod of the mixing device (collected by a current sensor). Temperature data can be understood as the temperature value of the mixture formed by mixing the raw materials in the mixing device (collected by a temperature sensor). pH data can be understood as the pH value of the mixture formed by mixing the raw materials in the mixing device (collected by a pH sensor). It should be noted that, to avoid data acquisition errors, multiple temperature sensors and multiple pH sensors can be set in the array of the mixing device. That is, multiple temperature and pH data exist simultaneously. Multiple temperature data at the same time correspond to different temperature sampling positions within the mixing device, and similarly, multiple pH data at the same time correspond to different pH sampling positions within the mixing device.

[0057] In this invention, the process of adding raw materials to the mixing device in small quantities multiple times and reacting them to finally output a dispersion can be considered as one production process. Batch division is based on this production process; the current batch corresponds to the current production process of the mixing device, while historical batches correspond to completed production processes of the mixing device. Specifically, the (n-1)th operation of a certain batch refers to the (n-1)th feeding operation performed during the production process corresponding to that batch (referring to the operation of controlling the feeding device to add a set amount of raw material to the mixing device).

[0058] Based on the above settings, by performing difference analysis on the reaction information, the difference analysis of the reaction status between the current batch and multiple historical batches can be realized. In order to find historical batches (i.e., similar batches) with reaction status that are similar to the current batch, the reaction information of the (n-1)th operation is selected for difference analysis, since the amount of raw materials added in the nth operation is to be measured. This ensures the accuracy of the identified similar batches while reducing the size of the data to be analyzed, thereby improving the overall data processing efficiency.

[0059] Further, the step of performing a difference analysis on the reaction information of the (n-1)th operation in the current batch and the reaction information of the (n-1)th operation in each historical batch to identify similar batches among multiple historical batches includes:

[0060] Obtain the reaction curve of the (n-1)th operation in the current batch and the reaction curve of the (n-1)th operation in each historical batch, wherein the reaction curve is used to represent the degree of disorder over time in the corresponding operation, and the degree of disorder is used to indicate the degree of reaction disorder of the multiple raw materials at the corresponding time.

[0061] A difference analysis is performed on the slope of the curve points between the reaction curve of the (n-1)th operation in the current batch and the reaction curve of the (n-1)th operation in each historical batch to obtain multiple slope difference indices for each historical batch.

[0062] A difference analysis of the disorder of the curve points between the reaction curve of the (n-1)th operation in the current batch and the reaction curve of the (n-1)th operation in each historical batch is performed to obtain multiple reaction degree difference indices for each historical batch.

[0063] Based on the multiple slope difference indices and multiple disorder difference indices corresponding to each historical batch, the batch difference value corresponding to each historical batch is determined.

[0064] Historical batches whose batch difference value is less than or equal to a preset first threshold are identified as similar batches.

[0065] Specifically, the time period indicated by the reaction curve of the (n-1)th operation in the current batch is the period from the start of the (n-1)th feeding operation in the current batch to the first duration threshold (e.g., 5 minutes). By analyzing the current, pH, and temperature data at each moment (data sampling is performed at a set frequency, such as once per second) within the time period indicated by the reaction curve of the (n-1)th operation in the current batch, the degree of disorder at each moment can be obtained, thus forming the reaction curve of the (n-1)th operation in the current batch. The process of obtaining the reaction curve of the (n-1)th operation in historical batches is similar and will not be described further to avoid repetition.

[0066] In the above settings, after obtaining the reaction curve of the (n-1)th operation in the current batch and the reaction curve of the (n-1)th operation in each historical batch, the differences between different curves are comprehensively evaluated from the aspects of curve slope and disorder. This avoids the error caused by single-dimensional evaluation and makes the determined batch difference value more accurate and reliable.

[0067] In application, the batch difference value corresponding to each historical batch can be normalized (e.g., using the max-min normalization method), and then the normalized batch difference value is compared with the first threshold to eliminate numerical differences and make the identified similar batches more accurate. In this case, the first threshold can be set to 0.3.

[0068] Furthermore, the steps for obtaining the disorder degree of the target curve points include:

[0069] The difference between the sampled temperature value at each sampling location at the target time and the average temperature at the target time is calculated to obtain the temperature difference value at each sampling location at the target time. The average temperature is the average of the sampled temperature values ​​at multiple sampling locations at the target time. The target time is the time corresponding to the target curve point. The target curve point is any curve point in the reaction curve of the (n-1)th operation in the current batch, or the target curve point is any curve point in the reaction curve of the (n-1)th operation in the historical batch.

[0070] The difference between the sampled acid-base value at each sampling location at the target time and the mean acid-base value at the target time is calculated to obtain the acid-base difference value at each sampling location at the target time. The mean acid-base value is the average of the sampled acid-base values ​​at multiple sampling locations at the target time.

[0071] The disorder of the target curve point is determined based on the temperature difference, acid-base difference, and current fluctuation value at each sampling location at the target time. The current fluctuation value at the target time is used to indicate the degree of fluctuation of the current data at the target time.

[0072] In one example, the disorder of the target curve point can be determined based on the absolute value of the temperature difference at each sampling location at the target time, the absolute value of the acid-base difference at each sampling location at the target time, and the current fluctuation value at the target time.

[0073] For example, the disorder of the target curve points It can be represented as:

[0074]

[0075] in, This represents the current fluctuation value at the target time, where M represents the total number of sampling locations. This represents the sampled temperature value at the a-th sampling location at the target time (i.e., the aforementioned temperature data). This represents the average temperature at the target time. Let represent the sampled acid-base value at the a-th sampling position at the target time (i.e., the aforementioned acid-base data). This represents the average pH value at the target time, and exp(.) represents the exponential operation with the natural constant e as the base.

[0076] It should be noted that the greater the temperature difference between sampling locations, the greater the temperature difference between different sampling locations at the target time, which reflects the less complete the raw material mixing reaction at the target time and the greater the corresponding disorder. Similarly, the greater the pH difference between sampling locations, the greater the pH difference between different sampling locations at the target time, which also reflects the less complete the raw material mixing reaction at the target time and the greater the corresponding disorder. Furthermore, the greater the current fluctuation value at the target time, the greater the degree of change in the motor output power at the target time, which also reflects the less complete the raw material mixing reaction at the target time and the greater the corresponding disorder.

[0077] The above settings aggregate temperature and pH data from multiple sampling locations to avoid sampling errors caused by single-dimensional evaluation and single sampling location settings. This allows for a comprehensive assessment of the degree of disorder in the raw material mixing reaction at the corresponding sampling time, making the determined degree of disorder more accurate.

[0078] In one example, the current fluctuation value at the target time can be the absolute value of the difference between the current value at the target time (i.e., the aforementioned current data) and the current value at the time preceding the target time.

[0079] Furthermore, determining the batch difference value corresponding to each historical batch based on multiple slope difference indices and multiple disorder difference indices corresponding to each historical batch includes:

[0080] Calculate the product of each slope difference index and the corresponding disorder difference index for each historical batch to obtain multiple batch difference parameters for each historical batch. Among them, the multiple batch difference parameters for each historical batch correspond one-to-one with the multiple slope difference indices for each historical batch.

[0081] Calculate the sum of multiple batch difference parameters corresponding to each historical batch to obtain the batch difference value corresponding to each historical batch.

[0082] For example, the batch difference value corresponding to the j-th historical batch among multiple historical batches. It can be represented as:

[0083]

[0084] Wherein, DM represents the total number of curve points included in the reaction curve of the (n-1)th operation in the current batch. This represents the slope of the z-th curve point in the reaction curve of the (n-1)-th operation in the j-th historical batch. This represents the slope of the z-th point on the reaction curve for the (n-1)th operation in the current batch. This represents the disorder at the z-th curve point in the reaction curve of the (n-1)-th operation in the j-th historical batch. This represents the disorder of the z-th curve point in the reaction curve of the (n-1)th operation of the current batch. This represents the z-th slope difference index corresponding to the j-th historical batch. This represents the z-th disorder difference index corresponding to the j-th historical batch.

[0085] Step S2: Determine the calculation weight of each similar batch based on the cumulative difference of each similar batch, the incremental difference of each similar batch, and the cumulative influence coefficient of the target raw material.

[0086] The cumulative difference is used to indicate the difference in the amount of target raw material added in the previous n-1 operations between the corresponding similar batch and the current batch, and the incremental difference is used to indicate the difference in the amount of target raw material added in the n-1 operation between the corresponding similar batch and the current batch. The target raw material is any one of a plurality of raw materials used to prepare the thermosensitive coating.

[0087] For example, the cumulative difference can be the absolute value of the difference between the amount of target raw material added in the previous n-1 operations and the amount added in the current batch of the corresponding similar batch.

[0088] Similarly, the incremental difference can be the absolute value of the difference between the amount of the target raw material added in the (n-1)th operation of the corresponding similar batch and the current batch.

[0089] In the above setup, after identifying multiple similar batches, before estimating the amount of target raw material added to the current batch in the nth operation based on the amount of target raw material added to each similar batch in the nth operation, the weight of the amount of target raw material added to each similar batch in the nth operation is determined by analyzing the single-time addition difference and cumulative addition difference between the similar batches and the current batch. Furthermore, a cumulative influence coefficient of the target raw material is introduced to correct the influence of the aforementioned cumulative addition difference in the weight calculation, improve the accuracy of the determined calculation weight, and thus improve the accuracy of the subsequently determined amount of target raw material added to the current batch in the nth operation.

[0090] It should be noted that when the target raw material is added to the mixing device and reacts with other raw materials, in addition to the amount of the target raw material added in the (n-1)th operation affecting the overall reaction, the cumulative amount of the target raw material added in the previous (n-1)th operations also affects the degree of multi-raw material mixing reaction. Based on this, in addition to analyzing the single addition difference between similar batches and the current batch, this invention further analyzes the cumulative addition difference between similar batches and the current batch to comprehensively evaluate the calculation weight of different similar batches from dimensions such as the cumulative addition amount and instantaneous addition amount of the target raw material, thereby accurately assessing the addition amount of different similar batches in the nth operation and the importance of the current batch in estimating the addition amount of the current batch in the nth operation.

[0091] It should be understood that the larger the cumulative difference and the larger the incremental difference, the greater the difference in the feeding situation between the corresponding similar batch and the current batch. In this case, the corresponding similar batch has less guiding significance for the current batch, and the smaller the calculation weight of the corresponding similar batch.

[0092] The cumulative influence coefficient of the target raw material is used to represent the degree of influence of the cumulative amount of the target raw material added in multiple operations in the corresponding batch on the degree of reaction of multiple raw materials.

[0093] For example, the calculated weight of the c-th similar batch among multiple similar batches. It can be represented as:

[0094]

[0095] in, This represents the incremental difference of the c-th similar batch among multiple similar batches. This represents the cumulative difference between the c-th similar batch and the c-th similar batch. This represents the cumulative influence coefficient of the target raw material, and exp(.) represents the exponential operation with the natural constant e as the base.

[0096] Furthermore, the step of obtaining the cumulative influence coefficient of the target raw material includes:

[0097] Based on the multiple historical batches, multiple first data and multiple second data associated with the target raw material are obtained, wherein the multiple first data and the multiple second data correspond one-to-one, the multiple first data correspond one-to-one with multiple operations, the change in the amount of target raw material added in any two different operations in the multiple operations is the same, and the cumulative amount of target raw material added in any two different operations in the multiple operations is different. The first data is used to indicate the cumulative amount of target raw material added at the corresponding operation, and the second data is used to indicate the degree of influence of the target raw material added at the corresponding operation on the reaction process.

[0098] Correlation analysis is performed on the plurality of first data and the plurality of second data to obtain the cumulative influence coefficient of the target raw material.

[0099] In the above settings, multiple operations with the same change in the amount of added target raw material but different cumulative amounts of added target raw material are found in multiple historical batches. By analyzing the correlation between the cumulative amount of added target raw material and the degree of impact on the reaction process after adding the same amount of target raw material in the above multiple operations, the cumulative influence coefficient of the target raw material can be determined.

[0100] Specifically, the step of performing correlation analysis on the plurality of first data and the plurality of second data to obtain the cumulative influence coefficient of the target raw material includes:

[0101] A target straight line is obtained by performing linear fitting on the plurality of first data and the plurality of second data;

[0102] The cumulative influence coefficient of the target raw material is determined based on the slope of the target straight line.

[0103] For example, a target rectangular coordinate system can be defined, with the horizontal axis representing the cumulative amount of the target raw material added during the corresponding operation, and the vertical axis representing the degree of influence of the target raw material added during the corresponding operation on the reaction process. Multiple first data points are mapped onto the target rectangular coordinate system to form multiple mapping points. By performing straight-line fitting on the multiple mapping points, a target straight line is obtained, and the cumulative influence coefficient of the target raw material is determined based on the slope of the target straight line.

[0104] The slope of the target line can be directly determined as the cumulative influence coefficient of the target raw material. The closer the slope of the target line is to 0, the weaker the correlation between the cumulative amount of the target raw material added and the degree of influence on the reaction process after adding the same amount of the target raw material, and vice versa.

[0105] Furthermore, the steps for obtaining the target second data include:

[0106] Obtain the target change amount and target curve difference value corresponding to the target operation, wherein the target operation is any one of the multiple operations, the target change amount is used to indicate the change in the amount of target raw material added during the target operation, the target curve difference value is used to indicate the degree of difference in the reaction curve between the target operation and the previous operation corresponding to the target operation, the reaction curve is used to represent the degree of disorder in the corresponding operation over time, and the degree of disorder is used to indicate the degree of reaction disorder of the multiple raw materials at the corresponding time.

[0107] Calculate the ratio of the target change amount corresponding to the target operation to the target curve difference value to obtain the target second data corresponding to the target operation, wherein the plurality of second data includes the target second data.

[0108] Specifically, the preceding operation corresponding to the target operation is the operation that is adjacent to and precedes the target operation in the batch containing the target operation.

[0109] The change in the amount of target raw material added during the target operation is specifically the absolute value of the difference between the target operation and its corresponding previous operation in terms of the amount of target raw material added.

[0110] The target curve difference value can be obtained based on the aforementioned batch difference value calculation method. The only difference between the target curve difference value and the batch difference value is that the two curves calculated by the batch difference value are the two reaction curves corresponding to the different (n-1)th operations in two batches, while the two curves calculated by the target curve difference value are the two reaction curves corresponding to the target operation and its corresponding previous operation. To avoid repetition, this will not be elaborated further.

[0111] For example, the target second data corresponding to the target operation It can be represented as:

[0112]

[0113] in, This represents the change in the target corresponding to the target operation. This represents the difference value of the target curve corresponding to the target operation.

[0114] Step S3: Based on the amount of target raw material added to each similar batch in the nth operation, the calculated weight of each similar batch, and the similarity coefficient of each similar batch, determine the amount of target raw material added to the current batch in the nth operation.

[0115] The similarity coefficient is used to indicate the degree of similarity between the reaction curves of the corresponding similar batches and the current batch.

[0116] The similarity coefficient can be obtained by subtracting the batch difference value of the corresponding similar batches from 1.

[0117] For example, the amount of the target raw material added in the current batch during the nth operation. It can mean "to think":

[0118]

[0119] Where N represents the total number of similar batches. This represents the batch difference value of the c-th similar batch among multiple similar batches. Let represent the similarity coefficient of the c-th similar batch among multiple similar batches. This represents the amount of the target raw material added to the c-th similar batch in the nth operation. This represents the calculated weight of the c-th similar batch among multiple similar batches.

[0120] In one embodiment, after determining the amount of target raw material added to the current batch in the nth operation based on the amount of target raw material added to each similar batch in the nth operation, the calculated weight of each similar batch, and the similarity coefficient of each similar batch, the method further includes:

[0121] The reaction information of the target time period is analyzed to obtain the analysis results. The target time period is the time period from the start time of the (n-1)th operation of the current batch to the set start time of the nth operation of the current batch. The analysis results are used to indicate the stability of the mixed reaction of the multiple raw materials in the target time period.

[0122] When the analysis results indicate that the stability of the mixed reaction of the multiple raw materials in the target time period matches the preset stability conditions, the nth operation of the current batch is performed based on the amount of the target raw material added in the nth operation.

[0123] In applications, the proportions of the various raw materials used to prepare the thermosensitive coating are fixed. Therefore, after determining the amount of any one raw material to be added, the amounts of the other raw materials to be added can be determined according to the aforementioned proportions. In other words, after determining the amount of the target raw material to be added in the nth operation of the current batch, the amounts of other raw materials (raw materials other than the target raw material) to be added in the nth operation of the current batch can be determined.

[0124] Specifically, after the start time of the (n-1)th operation in the current batch, the time after the cumulative set period (e.g., 4 minutes) of that start time can be determined as the set start time of the nth operation in the current batch.

[0125] For example, the process of analyzing response information for a target time period to obtain analysis results can be as follows:

[0126] Based on the reaction information of the target time period, obtain the disorder level at the end of the target time period;

[0127] If the disorder level at the end of the target time period is less than or equal to the disorder level threshold (e.g., 0.35), an analytical result is generated indicating that the stability of the mixed reaction of the multiple raw materials during the target time period matches the preset stability conditions.

[0128] If the disorder level at the end of the target time period is greater than the disorder level threshold, an analytical result is generated indicating that the stability of the mixed reaction of the multiple raw materials during the target time period does not match the stability conditions.

[0129] Specifically, after analyzing the response information for the target time period and obtaining the analysis results, the method further includes:

[0130] When the analysis results indicate that the stability of the mixed reaction of the plurality of raw materials during the target time period does not match the stability conditions, the execution of the nth operation for the current batch is delayed.

[0131] Specifically, delaying the execution of the nth operation in the current batch means:

[0132] Starting from the set start time of the nth operation of the current batch, wait for the target interval (e.g., one minute) and then obtain the disorder level at the current time. Compare the disorder level at the current time with the disorder level threshold. If the disorder level at the current time is less than or equal to the disorder level threshold, then execute the nth operation of the current batch based on the amount of target raw material added in the nth operation of the current batch.

[0133] If the disorder level at the current moment is greater than the disorder level threshold, wait for the target interval again and repeat the above disorder level acquisition and comparison process until the disorder level is less than or equal to the disorder level threshold. Then, based on the amount of target raw material added to the current batch in the nth operation, execute the nth operation of the current batch.

[0134] In summary, this invention, in the process of preparing a thermosensitive coating by adding raw materials in small quantities and multiple times for mixing and reaction, analyzes the difference between the reaction information of the (n-1)th operation in the current batch and the reaction information of the (n-1)th operation in each historical batch. This allows for the identification of similar batches with similar reaction conditions among multiple historical batches. Furthermore, it analyzes the cumulative amount of raw materials added and the difference between the current batch and each similar batch. Combined with the cumulative influence coefficient used to quantify the impact of cumulative raw material addition on the degree of reaction, the calculation weight of each similar batch is determined from multiple perspectives, i.e., the guiding weight of each similar batch for the current batch. Based on this, and combined with the amount of raw materials added in the nth operation of each similar batch, the amount of target raw material added in the nth operation of the current batch is calculated. These measures can dynamically adjust the amount of target raw material added in conjunction with the real-time reaction status of each raw material, achieving precise control over the amount of target raw material added, suppressing incomplete reaction of raw materials, and improving the yield of the thermosensitive coating.

[0135] This invention proposes an automatic mixing control device for the processing of heat-sensitive coatings. Please refer to [link / reference]. Figure 2 The diagram illustrates a structural schematic of an automatic mixing control device 200 for heat-sensitive coating processing according to an embodiment of the present invention. The device includes:

[0136] The batch determination module 201 is used to perform difference analysis on the reaction information of the (n-1)th operation in the current batch and the reaction information of the (n-1)th operation in each historical batch, so as to determine similar batches among multiple historical batches, where n is an integer greater than 1.

[0137] The weight calculation module 202 is used to determine the calculation weight of each similar batch based on the cumulative difference of each similar batch, the incremental difference of each similar batch and the cumulative influence coefficient of the target raw material. The cumulative difference is used to indicate the difference in the amount of target raw material added in the first n-1 operations between the corresponding similar batch and the current batch. The incremental difference is used to indicate the difference in the amount of target raw material added in the n-1th operation between the corresponding similar batch and the current batch. The target raw material is any one of a plurality of raw materials used to prepare the thermosensitive coating.

[0138] The quantity calculation module 203 is used to determine the quantity of the target raw material added to the current batch in the nth operation based on the quantity of the target raw material added to each similar batch in the nth operation, the calculated weight of each similar batch, and the similarity coefficient of each similar batch. The similarity coefficient is used to indicate the degree of similarity between the reaction curves of the corresponding similar batch and the current batch.

[0139] It should be noted that the apparatus provided in the above embodiments is only illustrative of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device can be divided into different functional modules to complete all or part of the functions described above. In addition, the automatic mixing control device for processing heat-sensitive coatings provided in the above embodiments and the automatic mixing control method for processing heat-sensitive coatings belong to the same concept. The specific implementation process is detailed in the method embodiments and will not be repeated here.

[0140] This invention also provides an electronic device. Please refer to [link to relevant documentation]. Figure 3 The electronic device may include a processor 301, a memory 302, and a program 3021 stored in the memory 302 and capable of running on the processor 301.

[0141] When program 3021 is executed by processor 301, it can achieve the following: Figure 1 Any steps in the corresponding method embodiments and the achievement of the same beneficial effects will not be repeated here.

[0142] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by hardware related to program instructions, and the program can be stored in a readable medium.

[0143] This invention also provides a readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described functions. Figure 1 Any step in the corresponding method embodiment can achieve the same technical effect, and will not be repeated here to avoid repetition.

[0144] The computer-readable storage medium of this invention can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0145] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0146] The program code contained on the storage medium can be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0147] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or terminal. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0148] This invention also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned steps to achieve the automatic mixing control method for processing heat-sensitive coatings provided in the above embodiments.

[0149] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0150] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. An automatic mixing control method applied to the processing of heat-sensitive paints, characterized in that, The method comprises: differential analysis is performed on reaction information of the n-1th operation in the current batch and reaction information of the n-1th operation in each historical batch to determine similar batches in the plurality of historical batches, n being an integer greater than 1; a calculation weight of each similar batch is determined according to a cumulative difference value of each similar batch, an incremental difference value of each similar batch and a cumulative influence coefficient of the target raw material, wherein the cumulative difference value is used to indicate a difference in the amount of the target raw material added in the first n-1 operations between the corresponding similar batch and the current batch, and the incremental difference value is used to indicate a difference in the amount of the target raw material added in the n-1th operation between the corresponding similar batch and the current batch, and the target raw material is any one of the plurality of raw materials used to prepare the heat-sensitive paint; an amount of the target raw material added in the nth operation of the current batch is determined according to the amount of the target raw material added in the nth operation of each similar batch, the calculation weight of each similar batch and a similarity coefficient of each similar batch, wherein the similarity coefficient is used to indicate a similarity degree of the reaction curve between the corresponding similar batch and the current batch; the differential analysis performed on the reaction information of the n-1th operation in the current batch and the reaction information of the n-1th operation in each historical batch to determine the similar batches in the plurality of historical batches comprises: reaction curves of the n-1th operation in the current batch and reaction curves of the n-1th operation in each historical batch are obtained, wherein the reaction curve is used to represent a degree of disorder over time in the corresponding operation, and the degree of disorder is used to indicate a degree of reaction disorder of the plurality of raw materials at the corresponding time; differential analysis is performed on the slope of the curve point between the reaction curve of the n-1th operation in the current batch and the reaction curve of the n-1th operation in each historical batch to obtain a plurality of slope difference indexes corresponding to each historical batch; differential analysis is performed on the degree of disorder of the curve point between the reaction curve of the n-1th operation in the current batch and the reaction curve of the n-1th operation in each historical batch to obtain a plurality of reaction degree difference indexes corresponding to each historical batch; a batch difference value corresponding to each historical batch is determined according to the plurality of slope difference indexes corresponding to each historical batch and the plurality of degree of disorder difference indexes corresponding to each historical batch; the historical batch with a batch difference value less than or equal to a preset first threshold value is determined as the similar batch; the step of obtaining the degree of disorder of the target curve point comprises: a temperature difference value of each sampling position at a target time is obtained by calculating a difference between a sampling temperature value of each sampling position at the target time and a temperature mean value at the target time, wherein the temperature mean value is a mean value of a plurality of sampling temperature values of a plurality of sampling positions at the target time, the target time is a time corresponding to the target curve point, and the target curve point is any one curve point in the reaction curve of the n-1th operation in the current batch or any one curve point in the reaction curve of the n-1th operation in the historical batch. Differences between the sampling pH values at each sampling position at the target moment and an average pH value at the target moment are calculated to obtain pH difference values at each sampling position at the target moment, wherein the average pH value is an average of the plurality of sampling pH values at the plurality of sampling positions at the target moment. The turbulence degree of the target curve point is determined according to the temperature difference value at each sampling position at the target moment, the pH difference value at each sampling position at the target moment, and a current fluctuation value at the target moment, wherein the current fluctuation value is used to indicate a fluctuation degree of current data at the target moment.

2. The automatic mixing control method for heat-sensitive paint processing according to claim 1, characterized by, The batch difference value corresponding to each historical batch is determined according to the plurality of slope difference indexes corresponding to each historical batch and the plurality of turbulence difference indexes corresponding to each historical batch, and includes: The product of each slope difference index corresponding to each historical batch and the corresponding turbulence difference index is calculated to obtain a plurality of batch difference parameters corresponding to each historical batch, wherein the plurality of batch difference parameters corresponding to each historical batch and the plurality of slope difference indexes corresponding to each historical batch are in one-to-one correspondence. The sum of the plurality of batch difference parameters corresponding to each historical batch is calculated to obtain the batch difference value corresponding to each historical batch.

3. The automatic mixing control method for heat sensitive paint processing according to claim 1, wherein, The cumulative influence coefficient of the target raw material is obtained by: Based on the plurality of historical batches, a plurality of first data and a plurality of second data associated with the target raw material are obtained, wherein the plurality of first data and the plurality of second data are in one-to-one correspondence, the plurality of first data and a plurality of operations are in one-to-one correspondence, the change amount of the amount of the target raw material added in any two different operations of the plurality of operations is the same, and the cumulative amount of the target raw material added in any two different operations of the plurality of operations is different, the first data is used to indicate the cumulative amount of the target raw material added in the corresponding operation, and the second data is used to indicate the influence degree of the added target raw material on the reaction progress in the corresponding operation; The cumulative influence coefficient of the target raw material is obtained by performing correlation analysis on the plurality of first data and the plurality of second data.

4. The automatic mixing control method for heat-sensitive paint processing according to claim 3, characterized by, The target second data is obtained by: The target change amount and the target curve difference value corresponding to the target operation are obtained, wherein the target operation is any one of the plurality of operations, the target change amount is used to indicate the change amount of the added amount of the target raw material in the target operation, the target curve difference value is used to indicate the difference degree of the reaction curve between the target operation and the previous operation corresponding to the target operation, the reaction curve is used to represent the turbulence degree with time in the corresponding operation, and the turbulence degree is used to indicate the reaction turbulence degree of the plurality of raw materials at the corresponding moment; The ratio of the target change amount and the target curve difference value corresponding to the target operation is calculated to obtain the target second data corresponding to the target operation, wherein the plurality of second data includes the target second data.

5. The automatic mixing control method for heat-sensitive paint processing according to claim 3, characterized by, The target second data is obtained by: The target straight line is obtained by performing linear fitting on the plurality of first data and the plurality of second data. determine a cumulative influence coefficient of the target raw material based on a slope of the target straight line.

6. The automatic mixing control method for heat sensitive paint processing according to claim 1, wherein, After determining the amount of the target raw material added in the nth operation of the current batch based on the amount of the target raw material added in the nth operation of each similar batch, the calculation weight of each similar batch, and the similarity coefficient of each similar batch, the method further comprises: analyzing reaction information of a target time period to obtain an analysis result, wherein the target time period is a time period from a start time of the (n-1)th operation of the current batch to a set start time of the nth operation of the current batch, and the analysis result is used to indicate a stability degree of a mixed reaction of the plurality of raw materials in the target time period; when the analysis result indicates that the stability degree of the mixed reaction of the plurality of raw materials in the target time period matches a preset stability condition, performing the nth operation of the current batch based on the amount of the target raw material added in the nth operation of the current batch.

7. The automatic mixing control method for heat-sensitive paint processing according to claim 6, characterized in that, After analyzing the reaction information of the target time period to obtain the analysis result, the method further comprises: when the analysis result indicates that the stability degree of the mixed reaction of the plurality of raw materials in the target time period does not match the stability condition, delaying the performance of the nth operation of the current batch.

8. An automatic mixing control device for use in the processing of heat sensitive coatings, characterized by, The device is used to implement the steps of the automatic mixing control method applied to the processing of heat-sensitive paint according to any one of claims 1-7, and the device comprises: a batch determination module configured to perform difference analysis on reaction information of the (n-1)th operation of the current batch and reaction information of the (n-1)th operation of each historical batch to determine similar batches from a plurality of historical batches, n being an integer greater than 1; a weight calculation module configured to determine a calculation weight of each similar batch based on a cumulative difference value of each similar batch, an incremental difference value of each similar batch, and a cumulative influence coefficient of the target raw material, wherein the cumulative difference value is used to indicate a difference in the amount of the target raw material added in the first n-1 operations between the corresponding similar batch and the current batch, the incremental difference value is used to indicate a difference in the amount of the target raw material added in the nth operation between the corresponding similar batch and the current batch, and the target raw material is any one of the plurality of raw materials used to prepare heat-sensitive paint; an amount measurement module configured to determine the amount of the target raw material added in the nth operation of the current batch based on the amount of the target raw material added in the nth operation of each similar batch, the calculation weight of each similar batch, and the similarity coefficient of each similar batch, wherein the similarity coefficient is used to indicate a similarity degree of a reaction curve between the corresponding similar batch and the current batch.

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