CN115685942A - Production control method and system for filter cloth - Google Patents
Production control method and system for filter cloth Download PDFInfo
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The embodiment of the specification provides a production control method and a production control system for filter cloth, and the method comprises the steps of obtaining parameters of a blank body to be processed and target production specifications; determining target post-processing parameters based on the parameters of the blank to be processed and the target production specification, and processing the blank to be processed based on the target post-processing parameters to obtain filter cloth meeting the target production specification; wherein the target post-processing parameters include the stretching forces of the stretching apparatus in different directions and the corresponding stretching times. The system comprises: the acquisition module is used for acquiring parameters of a blank body to be processed and target production specifications; and the determining module is used for determining target post-processing parameters based on the parameters of the blank to be processed and the target production specification, and processing the blank to be processed based on the target post-processing parameters to obtain the filter cloth meeting the target production specification.
Description
Technical Field
The specification relates to the technical field of filter membranes, in particular to a production control method and system of filter cloth.
Background
The Polytetrafluoroethylene (PTFE) filtering membrane is a microporous membrane prepared by taking polytetrafluoroethylene as a raw material and adopting a special process through the methods of calendering, extruding, biaxial stretching and the like, and has the characteristics of high peel strength, large air permeability, uniform pore size distribution and the like. The polytetrafluoroethylene filter membrane is combined with a base material (such as fiber woven cloth, which can be terylene, vinylon, polypropylene fiber, glass fiber and the like) to prepare the novel environment-friendly, anti-static, waterproof, oilproof and flame-retardant film-coated filter cloth. However, because of the membrane-covered filter cloth with different functions and different purposes, the required parameters of the polytetrafluoroethylene filter membrane are different (such as air permeability, porosity, pore size and the like).
Therefore, it is desirable to provide a method and a system for controlling the production of filter cloth, which can quickly and accurately determine reasonable processing parameters according to different user requirements, so as to realize the automatic production control of filter cloth with different functions and different purposes, and improve the production efficiency and the production quality.
Disclosure of Invention
One or more embodiments of the present specification provide a method of controlling production of a filter cloth, the method including: acquiring parameters and target production specifications of a blank body to be processed; determining target post-processing parameters based on the parameters of the blank to be processed and the target production specification, and processing the blank to be processed based on the target post-processing parameters to obtain filter cloth meeting the target production specification; wherein the target post-processing parameters include stretching forces of the stretching apparatus in different directions and corresponding stretching times.
One or more embodiments of the present specification provide a production control system of a filter cloth, the system including: the acquisition module is used for acquiring parameters of a blank body to be processed and target production specifications; the determining module is used for determining target post-processing parameters based on the parameters of the blank to be processed and the target production specification, and processing the blank to be processed based on the target post-processing parameters to obtain filter cloth meeting the target production specification; wherein the target post-processing parameters include stretching forces of the stretching apparatus in different directions and corresponding stretching times.
One or more embodiments of the present specification provide a production control apparatus for filter cloth, the apparatus including at least one processor and at least one memory; the at least one memory is for storing computer instructions; the at least one processor is used for executing at least part of the computer instructions to realize the production control method of the filter cloth.
One or more embodiments of the present specification provide a computer-readable storage medium storing computer instructions, and when the computer reads the computer instructions in the storage medium, the computer executes the aforementioned method for controlling production of filter cloth.
Drawings
The present description will be further explained by way of exemplary embodiments, which will be described in detail by way of the accompanying drawings. These embodiments are not intended to be limiting, and in these embodiments like numerals are used to indicate like structures, wherein:
FIG. 1 is a schematic diagram of an application scenario of a production control system for a filter cloth according to some embodiments of the present disclosure;
fig. 2 is an exemplary flow chart of a method of controlling production of a filter cloth according to some embodiments herein;
FIG. 3 is an exemplary diagram illustrating a method of determining target post-processing parameters according to some embodiments herein;
FIG. 4 is an exemplary diagram illustrating another method of determining target post-processing parameters according to some embodiments of the present description;
fig. 5 is an exemplary block diagram of a production control system for filter cloth according to some embodiments of the present disclosure.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only examples or embodiments of the present description, and that for a person skilled in the art, the present description can also be applied to other similar scenarios on the basis of these drawings without inventive effort. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.
It should be understood that "system", "apparatus", "unit" and/or "module" as used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.
As used in this specification and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.
Flowcharts are used in this specification to illustrate the operations performed by the system according to embodiments of the present specification. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to or removed from these processes.
Fig. 1 is a schematic diagram of an application scenario of a production control system for a filter cloth according to some embodiments of the present disclosure.
As shown in fig. 1, the application scenario 100 may include a server 110, a network 120, a production device 130 database 140.
In some embodiments, the application scenario 100 may obtain a filter cloth meeting target production specifications by implementing the production control method of filter cloth disclosed in the present specification. For example, in a typical application scenario, the production of the filter cloth may include a pretreatment process and a post-processing process, the raw material is pretreated to obtain a blank to be treated, and then the blank to be treated is post-processed to obtain the filter cloth, wherein the pretreatment process may include raw material mixing, blank making, extrusion and drying; post-processing may include stretch-film forming and heat-setting processes. When filter cloth meeting the target production specification is to be obtained, the server 110 may first obtain the parameters of the blank to be processed and the target production specification, and determine target post-processing parameters based on the parameters of the blank to be processed and the target production specification. The production equipment 130 processes the green body to be processed based on the target post-processing parameters, thereby obtaining filter cloth meeting the target production specification.
In some embodiments, the server 110 may be used to process information and/or data related to the application scenario 100. For example, the server 110 may determine target post-processing parameters based on the blank parameters to be processed and target production specifications, which may include the stretching forces of the stretching apparatus in different directions and corresponding stretching times. In some embodiments, the server 110 may be a single server or a group of servers. The set of servers can be centralized or distributed, can be dedicated, or can be serviced by other devices or systems at the same time. In some embodiments, the server 110 may be regional or remote. In some embodiments, the server 110 may be implemented on a cloud platform, or provided in a virtual manner.
In some embodiments, the server 110 may include a processing device. The processing device may process data and/or information obtained from other devices or system components. The processing device may execute program instructions based on the data, information, and/or processing results to perform one or more of the functions described herein.
In some embodiments, network 120 may be used for the exchange of information and/or data. In some embodiments, one or more components of the application scenario 100 (e.g., the server 110, the production device 130, and the database 140) may send information and/or data to other components of the application scenario 100 via the network 120. For example, the production facility 130 may obtain the target post-processing parameters from the server 110.
The production apparatus 130 may be a series of apparatuses for producing filter cloth. In some embodiments, the production equipment 130 may include raw material mixing equipment, blank making equipment, extrusion equipment, drying equipment, stretching equipment, and heat treatment equipment. Wherein, the raw material mixing equipment can be used for uniformly mixing the production raw materials with the organic solvent to obtain a mixture; a blank-making device may be used to make the mixture into a blank of a certain shape (e.g., cylindrical, etc.); an extrusion apparatus may be used to extrude the billet into a flat ribbon of material of a certain thickness (e.g., 90 μm to 120 μm); the drying equipment can be used for drying the extruded material to remove the organic solvent; the stretching device can be used for stretching the dried material into a film-like material; the heat treatment equipment can be used for carrying out heat setting treatment on the film to obtain the filter cloth meeting the target production specification.
In some embodiments, the production equipment 130 may obtain target post-processing parameters output by the server 110, such as stretching time of the stretching equipment, processing time of the heat treatment equipment, and the like. In some embodiments, the production equipment 130 may process the blank to be processed according to the target post-processing parameters to produce a filter cloth meeting the target production specification.
In some embodiments, database 140 may be used to store data and/or instructions. In some embodiments, database 140 may be a process parameter database for storing historical production data. The processing parameter database may include a plurality of reference data sets, each reference data set including a first reference vector, a second reference vector, and corresponding reference post-processing data. In some embodiments, the database 140 may continuously update the production data. In some embodiments, database 140 may store data and/or instructions used by server 110 to perform or use to perform the exemplary methods described in this specification. In some embodiments, the storage device 150 may be implemented on a cloud platform.
In some embodiments, a database 140 may be connected to the network 120 to communicate with one or more components of the application scenario 100 (e.g., the server 110, the production device 130). One or more components of the application scenario 100 may access data or instructions stored in the database 140 via the network 120. In some embodiments, the database 140 may be directly connected to or in communication with one or more components of the application scenario 100. In some embodiments, database 140 may be part of server 110.
It is noted that the above description of the production control system for filter cloths is merely for convenience of description and does not limit the present description to the scope of the illustrated embodiments. It will be appreciated by those skilled in the art that, given the teachings of the present system, any combination of modules or sub-system configurations may be used to connect to other modules without departing from such teachings.
Fig. 2 is an exemplary flow chart of a method of controlling production of a filter cloth according to some embodiments of the present disclosure. In some embodiments, the process may be performed by a processor. As shown in fig. 2, the process 200 includes the following steps:
and step 210, acquiring parameters and target production specifications of the blank to be processed.
The blank to be treated can refer to the product obtained after the raw material is pretreated. Wherein, the raw material may include, but is not limited to, polytetrafluoroethylene, cellulose acetate, polypropylene, polycarbonate or polyamide material, etc., and the pretreatment process may include, but is not limited to, the steps of raw material mixing, blank making, extruding and/or drying, etc.
In some embodiments, the blank to be treated may include, but is not limited to, a flat, sheet-like, or film-like material.
The parameters of the blank to be processed can refer to parameters related to the material of the blank to be processed and the processing technology. For example, the blank parameters to be processed may include, but are not limited to, material composition, thickness, and/or dryness, among others.
The target production specification may refer to preset filter cloth production specification data. For example, the target production specification may refer to a filter cloth production specification set in advance according to user demand information. As another example, the target production specification may include, but is not limited to, filter cloth air permeability per unit time and average pore size values.
In some embodiments, the server 110 may obtain the parameters of the green body to be processed and/or the target production specification based on user input, sensor acquisition, and/or equipment monitoring. For example, the user may input relevant information according to his/her own needs, and then determine the target production specification. For another example, a micrometer or a laser range finder may be used to obtain the parameters of the blank to be processed.
And 220, determining target post-processing parameters based on the parameters of the blank to be processed and the target production specification, and processing the blank to be processed based on the target post-processing parameters to obtain the filter cloth meeting the target production specification.
Wherein the target post-processing parameters include the stretching forces of the stretching apparatus in different directions and corresponding stretching times.
The post-processing parameters may refer to process parameters related to the subsequent processing of the blank to be processed; the target post-processing parameters may refer to process parameters that meet certain requirements and are relevant to the subsequent processing of the blank to be processed.
In some embodiments, the target post-processing parameters may include stretching process parameters of the stretching apparatus. For example, the stretching process parameters of the stretching apparatus can be represented by vectors (F1, T1, F2, T2), wherein F1 and T1 can represent the values of the stretching force and the stretching time of the stretching apparatus in one horizontal direction, respectively; f2 and T2 may represent the values of the stretching force and the stretching time, respectively, of the stretching apparatus in the other horizontal direction. For example, the target post-processing parameters (80, 60, 12, 20) may be expressed as a stretching force of 80N in the horizontal X-axis direction of the stretching apparatus for a stretching time of 12s; the stretching force in the horizontal Y-axis direction was 60N, and the stretching time was 20s.
The stretching apparatus may refer to an apparatus for stretching a green body to be treated. For example, the stretching apparatus may include a film biaxial stretching stretcher or uniaxial stretcher or the like; it can be understood that by using the stretching apparatus, a certain stretching force is applied to the green body to be treated in two horizontal directions perpendicular to each other for a certain time, and a product satisfying certain requirements can be obtained.
In some embodiments, the target post-processing parameters may also include sintering process parameters of the heat treatment apparatus. For more details on the heat treatment equipment and the sintering process parameters, see fig. 4 and its associated description.
In some embodiments, the processor may determine the target post-processing parameters using a variety of methods including modeling, empirical estimation, and data fitting. For example, the target post-processing parameters can be determined by analyzing the parameters of the blank to be processed, combining with the target production specification, and according to the relevant historical production experience. For another example, the target post-processing parameters can be determined by data fitting according to the historical data of successful processing and the difference between the parameters of the blank to be processed and the target production specification and the historical data. For more details on how to determine the target post-processing parameters, see the contents of other parts of this specification (e.g., fig. 3 and its associated description).
In some embodiments, processing the blank to be processed may refer to performing stretching and sintering on the blank to be processed by using a stretching device and a heat treatment device in sequence, so as to obtain a filter cloth meeting requirements. For more explanation of the stretching apparatus and stretching process, reference may be made to fig. 3 and its associated description; for more description of the heat treatment apparatus and the sintering process, reference may be made to fig. 4 and its associated description.
In some embodiments of the present description, by analyzing parameters of a blank to be processed, reasonable production parameters are determined quickly and accurately according to different user requirements on the premise of a target production specification, so as to realize automatic production control of filter cloth, and improve production efficiency and production quality.
FIG. 3 is an exemplary diagram illustrating a method of determining target post-processing parameters according to some embodiments herein. In some embodiments, the process 300 may be performed by a processor.
In step 310, a first matching relationship and a second matching relationship are determined.
In some embodiments, the processor may determine a first vector to be matched based on the parameters of the blank to be processed, determine a second vector to be matched based on the target production specification, and then match the first vector to be matched and the second vector to be matched in the processing parameter database; the processing parameter database is determined based on historical production data and comprises a plurality of reference data sets, each reference data set comprises a first reference vector, a second reference vector and reference post-processing parameters corresponding to a data set formed by the first reference vector and the second reference vector, the first reference vector is a vector corresponding to historical blank parameters to be processed, and the second reference vector is a vector corresponding to historical target production specifications. And matching the first vector to be matched with the first reference vector in each reference data group to determine a first matching relationship, and matching the second vector to be matched with the second reference vector in each reference data group to determine a second matching relationship.
In some embodiments, the processor may determine the target post-processing parameter based on data in the first reference data set in response to the first reference data set existing in the processing parameter database such that the first matching relationship and the second matching relationship both satisfy a first preset condition; the first preset condition is that the values of the first matching relation and the second matching relation are smaller than a first threshold value.
The first vector to be matched can refer to a vector determined based on parameters of a blank to be processed. For example, the first to-be-matched vector can be represented by a vector (E, TH, D, S), where E represents the material composition, TH represents the thickness of the blank to be processed, D represents the dryness of the blank to be processed, and S represents the tensile strength of the blank to be processed. As another example, the vector (PTFE, 0.2,0.95, 1.3) may indicate that the material composition of the green body to be treated is polytetrafluoroethylene, the thickness is 0.2mm, the dryness is 95%, and the tensile strength is 1.3MPa.
The second to-be-matched vector may refer to a vector determined based on the target production specification. For example, the second to-be-matched vector may be represented by a vector (a, P), wherein a may represent the air permeability per unit time of the filter cloth and P may represent the average pore size of the filter cloth. As another example, (2.02, 1.31) can be expressed as a gas permeability per unit time of 2.02cm in a target production specification 3 24 h.0.1 MPa, and the average pore diameter is 1.31um.
The process parameter database may refer to a database established based on historical process data and including a plurality of reference data sets.
The reference data set may refer to a data set established based on the parameters of the blank to be processed, the target production specification and the post-processing parameters, and includes a first reference vector, a second reference vector and corresponding reference post-processing parameters.
The first reference vector may refer to a vector determined based on historical parameters of the blank to be processed. The second reference vector may refer to a vector determined based on historical target production specifications. For the determination of the first reference vector and the second reference vector, reference may be made to the relevant contents of the first vector to be matched and the second vector to be matched in this specification.
Matching may refer to a method of analyzing two vectors to obtain a relationship between the two. For example, matching may be calculating a vector distance between two vectors. Wherein the vector distance may include, but is not limited to, euclidean distance, chebyshev distance, manhattan distance, or the like.
A match relationship may refer to a distance value between two vectors. For example, the first matching relationship may refer to a distance value between the first to-be-matched vector and the first reference vector in each reference data set; the second matching relationship may refer to a distance value between the second vector to be matched and the second reference vector in each reference data set.
The first reference data group may refer to a reference data group that satisfies a certain preset condition, which is determined based on the matching relationship. The first reference data set may include a first reference vector, a second reference vector, and corresponding reference post-processing parameters.
The first threshold may refer to a value associated with a vector distance for determining whether the first reference data set exists in the processing parameter database. For example, the first threshold may be 2, which may indicate that the first matching relationship and the second matching relationship are determined to satisfy the first preset condition when both values of the first matching relationship and the second matching relationship are less than 2. Typically the first threshold value may be predetermined manually.
In some embodiments, after the processor determines the first reference data set, the reference post-processing parameter in the first reference data set may be determined as the target post-processing parameter. For example, if the reference post-processing parameter in the first reference data set is (80, 60, 12, 20), then (80, 60, 12, 20) may be determined as the target post-processing parameter.
In some embodiments of the present description, a processing parameter database is established based on the historical data of successful processing, and the current relevant data is matched in the database, so that the appropriate processing parameters can be determined relatively quickly and accurately, and the production requirements can be met.
At step 320, a second reference data set is determined.
In some embodiments, in response to the first reference data set not being present in the processing parameter database, the first matching relationship and the second matching relationship both satisfying the first predetermined condition, the second reference data set is determined in the processing parameter database, the second reference data set causing the first matching relationship to satisfy the second predetermined condition and causing the second matching relationship to satisfy the third predetermined condition. And the second threshold value in the second preset condition is smaller than the third threshold value in the third preset condition, and both the second threshold value and the third threshold value are larger than the first threshold value.
The second reference data set may refer to a reference data set that satisfies a certain condition, which is screened from the processing parameter database. The second reference data set may include the first reference vector, the second reference vector, and corresponding reference post-processing parameters. For further description of the reference data set, see the contents of the rest of the description.
The second preset condition and the third preset condition may refer to a rule set in advance for screening the reference data group. For example, the second preset condition may include a second threshold, and the third preset condition may include a third threshold, where the second threshold and the third threshold may be numerical values related to a vector distance. For example, the first threshold may be 2, the second distance threshold may be 3, the third distance threshold may be 4, the second distance threshold is less than the third distance threshold, and both the second distance threshold and the third distance threshold are less than the first distance threshold. The first threshold, the second threshold, and the third threshold may indicate that when the first matching relationship is greater than or equal to 2 and less than 3, and the value of the second matching relationship is greater than or equal to 2 and less than 4, it is determined that the first matching relationship satisfies the second preset condition, and the second matching relationship satisfies the third preset condition. Typically the second threshold and the third threshold may be predetermined manually.
At step 330, candidate post-processing parameters are determined.
In some embodiments, candidate post-processing parameters may be determined based on data in the second reference data set.
The candidate post-processing parameter may refer to a post-processing parameter satisfying a certain condition. For example, the reference post-processing parameters in the second reference data set may be determined as candidate post-processing parameters.
In some embodiments, the target post-processing parameter may be determined by performing multiple iterations of updating the candidate post-processing parameter based on a preset algorithm.
In some embodiments, the plurality of candidate post-processing parameters may be used as initial data in a first iteration, and in the first iteration, the plurality of candidate post-processing parameters may be updated based on the initial parameter variation vector to obtain updated candidate post-processing parameters. And determining the updated candidate post-processing parameters as the post-processing parameters to be processed, and determining the initial parameter variation vector as the parameter variation vector to be processed in the next round.
In some embodiments, the number of candidate post-processing parameters may be set to N, and each candidate post-processing parameter may have a dimension of 2, where the elements in each dimension may be represented as a combination of stretching force and stretching time. The vector corresponding to the ith candidate post-processing parameter may be represented as:
vectors corresponding to N candidate post-processing parameters
Can be expressed as:
wherein, 0 is an identifier, which represents the 0 th iteration, i.e. the initial value of the iteration is not started yet, and i is the number of the candidate post-processing parameter, wherein i is less than or equal to N.
The parameter variation vector, the initial parameter variation vector and the parameter variation vector to be processed may be system default values, empirical values, artificial preset values, or any combination thereof set according to actual requirements.
And in each subsequent iteration updating, updating the variable quantity of the to-be-processed parameter of the iteration updating to obtain the updated parameter variable quantity. And updating the to-be-processed machining parameters based on the updated parameter variation to obtain the updated to-be-processed machining parameters. And determining the updated to-be-processed machining parameters as to-be-processed machining parameters of the next round, and determining the updated parameter variation as to-be-processed parameter variation vectors of the next round.
In some embodiments, the updating of the variable quantity of the parameter to be processed may be implemented by updating the variable element to be processed. The variable element may be an element of each dimension of the parameter variation, and the parameter variation may include a plurality of variable elements. There may be a one-to-one correspondence between the candidate post-processing parameters and the elements and variable elements of the post-processing parameters to be processed. The variable elements may be used to characterize the adjustment magnitude of the corresponding element. For example, the variable element may represent the magnitude of adjustment of the stretching force or stretching time.
In some embodiments, the variable elements to be processed may be updated based on the current loss amount of the previous round, and the updated variable elements are used as the variable elements to be processed of the next round. And determining the current loss amount of the previous round based on the processing result difference corresponding to the candidate post-processing parameter obtained in the previous round and the historical optimal post-processing parameter.
For example, after the k +1 th iteration, the updated variable elements can be calculated by the following formula (1):
wherein i represents the number of candidate post-processing parameters, wherein i is less than or equal to N; d represents the number of elements in the candidate post-processing parameters, wherein D is less than or equal to D; k represents the number of iteration rounds, and k is more than or equal to 0;
representing a variable element to be processed obtained after the ith candidate post-processing parameter is iterated in the kth round;
representing the ith candidate post-processing parameter obtained after the kth iteration; ω represents an inertial weight constant; c. C 1 Represents an individual learning factor, c 2 Representing a population learning factor; r is 1 And r 2 Is the interval [0,1]Arbitrary value of, for increasing the randomness of the searchSex;
and the optimal solution in the past iteration process is the value of the ith candidate post-processing parameter after the kth iteration on the d-th dimension in the candidate post-processing parameters. The optimal solution at this time may refer to a parameter set of each dimension corresponding to a certain candidate post-processing parameter (i.e., an individual historical optimal solution) when the filter cloth parameter corresponding to the candidate post-processing parameter is closest to the target production specification among a plurality of filter cloth parameters corresponding to the candidate post-processing parameter in the previous iteration after the kth iteration;
after the k-th iteration, the optimal solution in the previous iteration is the value of the optimal solution in the d-th dimension of the candidate post-processing parameters in the previous iteration, and the optimal solution at this time may refer to the parameter set (i.e. the group history optimal solution) of each dimension corresponding to the candidate post-processing parameter closest to the target production specification in the previous multiple candidate post-processing parameters with the optimal filter cloth parameter in the previous iteration after the k-th iteration.
The inertia weight constant ω and the individual learning factor c 1 Group learning factor c 2 And a random constant r 1 And r 2 And the system default value, the empirical value, the artificial preset value and the like or any combination thereof can be set according to actual requirements.
In some embodiments of the present description, when a target post-processing parameter cannot be matched, iterative updating is performed on a candidate post-processing parameter based on a preset algorithm, and whether a result of the iterative updating meets a requirement is detected based on a preset condition and a preset method, so that the target post-processing parameter meeting a production requirement can be determined reasonably; in addition, based on the relation between the relevant data of the candidate post-processing parameters and the historical optimal solution of the candidate post-processing parameters and the historical optimal solutions of all the candidate post-processing parameters in the iteration process, the iteration step and the iteration direction are adjusted, the iteration efficiency can be improved, and the time for terminating the iteration is shortened.
The filter cloth parameters may refer to filter cloth production specification data determined based on post-processing parameters. For example, filter cloth parameters may include, but are not limited to, air permeability per unit time and average pore size values. For more explanations of the filter cloth parameters, reference may be made to the relevant explanations in fig. 2 regarding the target production specifications.
In some embodiments, filter cloth parameters may be determined using a variety of methods, such as table building, statistical analysis, vector matching, or modeling.
For example, the filter cloth parameters can be determined by processing the candidate post-processing parameters and the parameters of the blank to be processed by using the filter cloth performance evaluation model. The filter cloth performance evaluation model can be a model obtained by a convolution neural network, a deep neural network or a combination of the convolution neural network and the deep neural network.
The inputs to the filter cloth performance evaluation model may include candidate post-processing parameters and blank parameters to be processed, and the outputs may include filter cloth parameters. For more explanation of the parameters of the blank to be processed, refer to fig. 2 and its associated description.
In some embodiments, the filter cloth performance evaluation model may be obtained by training a plurality of labeled training samples, where the training samples may include at least sample candidate post-processing parameters and sample to-be-processed blank parameters, and the label may be a filter cloth parameter corresponding to the training sample. For example, a plurality of first training samples with labels may be input into an initial filter cloth performance evaluation model, a loss function may be constructed from the labels and the output of the initial filter cloth performance evaluation model, and parameters of the initial filter cloth performance evaluation model may be iteratively updated by gradient descent or other methods based on the loss function. And when the preset conditions are met, completing model training to obtain a trained filter cloth performance evaluation model. The preset condition may be that the loss function converges, the number of iterations reaches a threshold, and the like.
In some embodiments of the present disclosure, by using a trained filter cloth performance evaluation model, filter cloth parameters can be determined relatively quickly and accurately, and data processing efficiency is improved. In addition, the model training data can use not only the data in the processing parameter database, but also unqualified processing parameters except the database, so that the model training efficiency is improved.
In some embodiments, the maximum absolute value of the variable element in each iteration update may be v max I.e. representing the maximum adjustment amplitude for each dimension in the candidate post-machining parameters. For example, v max The maximum adjustment width of the stretching force may be (0.5, 0.2), which means that the maximum adjustment width of the stretching force is 0.5N and the maximum adjustment width of the stretching time is 0.2s.
In the (k + 1) th iteration, a parameter change vector V formed by the adjustment amplitude of each dimension in the candidate post-processing parameters i Can be expressed as (v) i1 ,v i2 ). The vector of the parameter variation vectors corresponding to the N candidate post-processing parameters can be represented as ((v) 11 ,v 12 ),(v 21 ,v 22 ),…,(v N1 ,v N2 )). Wherein, the value of any variable element in the vector can be a negative value, but the absolute value is not more than v max 。
In some embodiments, each post-processing parameter to be processed may be updated based on the variable elements in the updated parameter change vector. For example, after the (k + 1) th iteration, the updated candidate post-processing parameters may be calculated by the following formula (2):
for example, after 1 st iteration, the updated i-th candidate post-processing parameter can be calculated by the following formula (3):
the vector expression form corresponding to the N updated candidate post-processing parameters can be calculated by the following formula (4):
in some embodiments, constraints may exist for each dimension in each candidate post-processing parameter in each iteration update. For example, there are maximum and minimum values for the stretching force and stretching time, respectively, for each candidate post-processing parameter. For example only, the maximum and minimum values of the stretching force may be 1.2kN and 500N, respectively, and the maximum and minimum values of the stretching time may be 125s and 8s, respectively. It will be appreciated that when the stretching force and/or stretching time is greater than a maximum or less than a minimum, a satisfactory product may not be obtained.
In some embodiments, the maximum and minimum values of the stretching time vary as a result of a change in the magnitude of the stretching force. It will be appreciated that when the stretching force is increased, the stretching time is suitably reduced to avoid damage to the green body to be treated due to excessive tensile strength.
In some embodiments, if after an iteration, the value of a dimension in a candidate post-processing parameter is greater than a specified maximum value or less than a specified minimum value, a value satisfying the constraint condition may be randomly assigned. Preferably, it may be a value close to the locally optimal solution.
In some embodiments, the preset algorithm may be used to continuously perform iterative update on the candidate post-processing parameters until a preset condition is met, and the iterative update is ended. The preset condition may be that the filter cloth parameter is the same as the target production specification, or the similarity between the obtained filter cloth parameter and the target production specification is greater than a certain percentage, or the iteration number reaches a threshold value, and the like.
In some embodiments of the present description, when an appropriate target post-processing parameter cannot be matched from the processing parameter database, multiple rounds of iterative updating are performed on multiple candidate post-processing parameters by using a preset algorithm, and the target post-processing parameter is determined by combining a model output result, so that defects of the processing parameter database can be compensated to a certain extent, and a reasonable processing parameter is determined, thereby improving the processing efficiency.
FIG. 4 is an exemplary flow chart of another method of determining target post-processing parameters, according to some embodiments described herein.
In some embodiments, the target post-processing parameters further include sintering process parameters of the heat treatment apparatus. In some embodiments, determining the target post-processing parameter further comprises: and matching the first vector to be matched and the second vector to be matched in the processing parameter database, and determining target sintering process parameters.
The heat treatment apparatus may refer to an apparatus for heat-setting the filter cloth, including, but not limited to, a hot roll, etc.
The sintering process parameters can refer to processing parameters when heat treatment equipment carries out heat setting treatment on the filter cloth. In some embodiments, the sintering process parameters may include sintering temperature and sintering time. For example, the sintering process parameters (50, 20) can be expressed as a sintering temperature of 50 ℃ and a sintering time of 20s. The sintering temperature may be a temperature set when the heat treatment equipment performs heat setting treatment on the filter cloth. The sintering time may refer to a time required for the heat treatment equipment to heat-set the filter cloth.
In some embodiments, the data in the reference data set further comprises a reference sintering process parameter. The reference sintering process parameters may refer to processing parameters associated with a heat setting process for a good product in historical production.
In some embodiments, the target sintering process parameters may be determined based on a vector search matching approach. For example, the server matches the first matching vector with the first reference vector to obtain a first matching relationship, matches the second to-be-matched vector with the second reference vector in the processing parameter database to obtain a second matching relationship, and if both the first matching relationship and the second matching relationship satisfy a first preset condition, the processing parameter database has a first reference data set, and at this time, the reference sintering process parameters in the first reference data set can be directly determined as the target sintering process parameters.
For more contents of the first to-be-matched vector, the first reference vector, the second to-be-matched vector, the second reference vector, the processing parameter database, the first predetermined condition, and the first reference data set, reference may be made to fig. 3 and its related description.
In some embodiments, if the first matching relationship and/or the second matching relationship does not satisfy the first predetermined condition, the first reference data set does not exist in the processing parameter database, and the target sintering process parameter may be determined by using the process 400.
In some embodiments, flow 400 may be performed by server 110. As shown in fig. 4, the process 400 may include the following steps:
and step 410, after the target post-processing parameters are determined based on the preset algorithm, predicting the target post-processing parameters by using the filter cloth performance evaluation model to obtain corresponding predicted filter cloth parameters.
In some embodiments, the predetermined algorithm may be a predetermined algorithm program. With regard to the preset algorithm and how to determine the specific contents of the target post-processing parameters based on the preset algorithm, reference may be made to fig. 3 and its related description.
In some embodiments, the filter cloth performance evaluation model may be a machine learning model. In some embodiments, the filter cloth performance evaluation model may process the target post-processing parameters, the blank parameters to be processed, and determine corresponding predicted filter cloth parameters. The input of the filter cloth performance evaluation model can comprise target post-processing parameters and parameters of a blank to be processed, and the output of the filter cloth performance evaluation model can comprise corresponding predicted filter cloth parameters. For more on the filter cloth performance evaluation model, see fig. 3 and its associated description.
In step 420, a second reference vector in the reference data set with the best first matching relationship and second matching relationship in the processing parameter database is determined.
In some embodiments, the server may match the first vector to be matched with the first reference vector in the processing parameter database to obtain a first matching relationship, match the second vector to be matched with the second reference vector in the processing parameter database to obtain a second matching relationship, and determine the second reference vector (i.e., the vector corresponding to the filter cloth parameter) in the reference data group with the best matching relationship in the processing parameter database based on the first matching relationship and the second matching relationship.
The reference data set with the best matching relationship may be the reference data set with the smallest difference between the first matching relationship and the first preset condition. The reference data set with the best matching relationship may be determined based on the distance between the first matching relationship and the first preset condition and the second matching relationship. For example, the reference data set with the smallest sum of the two distances may be determined as the reference data set with the best matching relationship; for another example, the two distances may be averaged, and the reference data set with the smallest average may be determined as the reference data set with the best matching relationship.
And 430, adjusting the reference sintering process parameters in the reference data group with the best matching relation based on the difference relation between the predicted filter cloth parameters and the second reference vector, and determining target process parameters.
The target sintering process parameters may refer to processing parameters related to the heat setting process that may meet the requirements.
In some embodiments, the reference sintering process parameters in the reference data set with the best matching relationship may be adjusted by an adjustment factor. The adjustment factor may be an adjustment coefficient, the value of which is positively correlated with the value of the difference between the second reference vector and the predicted filter cloth parameter. For example, when the difference between the second reference vector and the predicted filter cloth parameter is large, a large sintering process parameter adjustment factor may be set such that the difference value between the second reference vector and the predicted filter cloth parameter is smaller than a preset value; when the difference between the second reference vector and the predicted filter cloth parameter is small, a small adjustment factor for the sintering process parameter may be set so that the difference between the second reference vector and the predicted filter cloth parameter is also smaller than a preset value. When the difference between the second reference vector and the predicted filter cloth parameter is smaller than a preset value, the corresponding reference sintering process parameter may be determined as the target sintering process parameter. The preset value may be a value set in advance, and may be determined in various manners based on historical experience, an algorithm program, and the like.
In some embodiments of the present description, the target sintering parameter is directly determined by using a vector search matching method, the reference sintering process parameter is determined by using a filter cloth performance evaluation model in combination with the vector search matching method, and the reference sintering process parameter is continuously adjusted by using an adjustment factor, so that the target sintering process parameter is determined, which is beneficial to improving the accuracy of the sintering process parameter and further ensuring the production quality of the filter cloth.
Fig. 5 is an exemplary block diagram of a production control system for filter cloth according to some embodiments of the present disclosure.
One or more embodiments of the present disclosure provide a filter cloth production control system, and as shown in fig. 5, the system 500 may include an obtaining module 510 and a determining module 520.
The obtaining module 510 may be configured to obtain parameters of the blank to be processed and target production specifications. For details of the parameters of the blank to be processed and the target production specification, reference may be made to fig. 2 and its associated description.
The determining module 520 may be configured to determine a target post-processing parameter based on the parameters of the blank to be processed and the target production specification, and process the blank to be processed based on the target post-processing parameter to obtain filter cloth meeting the target production specification; wherein the target post-processing parameters include the stretching forces of the stretching apparatus in different directions and the corresponding stretching times. For a detailed description of the target post-processing parameters, the green body to be treated, the stretching equipment, the stretching force and the stretching time, reference may be made to fig. 2 and its associated description.
In some embodiments, the determining module 520 may be configured to determine a first vector to be matched based on the parameters of the blank to be processed, determine a second vector to be matched based on the target production specification, and perform matching in the processing parameter database based on the first vector to be matched and the second vector to be matched; matching the first vector to be matched with the first reference vector in each reference data group to determine a first matching relationship, and matching the second vector to be matched with the second reference vector in each reference data group to determine a second matching relationship; and in response to the first reference data group existing in the machining parameter database, enabling the first matching relation and the second matching relation to both meet a first preset condition, and determining target post-machining parameters based on the reference post-machining parameters in the first reference data group. For specific contents of the first vector to be matched, the second vector to be matched, the processing parameter database, the reference data set, the first reference vector, the first matching relationship, the second reference vector, the second matching relationship, the first reference data set, and the first preset condition, reference may be made to fig. 3 and its related description.
In some embodiments, the determining module 520 may be configured to determine the second reference data set in the processing parameter database in response to the first reference data set not existing in the processing parameter database and the first matching relationship and the second matching relationship both satisfying a first preset condition, the second reference data set causing the first matching relationship to satisfy a second preset condition and the second matching relationship to satisfy a third preset condition; determining candidate post-processing parameters based on the reference post-processing parameters in the second reference data set; and performing multiple iterations on the candidate post-processing parameters based on a preset algorithm to determine target post-processing parameters. For a specific description of the second reference data set, the second preset condition, the third preset condition, the candidate post-processing parameters and the preset algorithm, reference may be made to fig. 3 and its related description.
In some embodiments, the obtaining module and the determining module disclosed in fig. 5 may be different modules in a system, or may be a module that implements the functions of two or more modules described above. For example, each module may share one memory module, and each module may have its own memory module. Such variations are within the scope of the present disclosure.
Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be regarded as illustrative only and not as limiting the present specification. Various modifications, improvements and adaptations to the present description may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present specification and thus fall within the spirit and scope of the exemplary embodiments of the present specification.
Also, the description uses specific words to describe embodiments of the description. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the specification is included. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the specification may be combined as appropriate.
Additionally, the order in which the elements and sequences of the process are recited in the specification, the use of alphanumeric characters, or other designations, is not intended to limit the order in which the processes and methods of the specification occur, unless otherwise specified in the claims. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.
Similarly, it should be noted that in the preceding description of embodiments of the present specification, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to imply that more features than are expressly recited in a claim. Indeed, the embodiments may be characterized as having less than all of the features of a single disclosed embodiment.
Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the number allows a variation of ± 20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that may vary depending upon the desired properties of the individual embodiments. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.
For each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., cited in this specification, the entire contents of each are hereby incorporated by reference into this specification. Except where the application history document does not conform to or conflict with the contents of the present specification, it is to be understood that the application history document, as used herein in the present specification or appended claims, is intended to define the broadest scope of the present specification (whether presently or later in the specification) rather than the broadest scope of the present specification. It is to be understood that the descriptions, definitions and/or uses of terms in the accompanying materials of this specification shall control if they are inconsistent or contrary to the descriptions and/or uses of terms in this specification.
Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present disclosure. Other variations are also possible within the scope of the present description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.
Claims (10)
1. A production control method of a filter cloth, characterized by comprising:
acquiring parameters and target production specifications of a blank body to be processed;
determining target post-processing parameters based on the parameters of the blank to be processed and the target production specification, and processing the blank to be processed based on the target post-processing parameters to obtain filter cloth meeting the target production specification; wherein, the first and the second end of the pipe are connected with each other,
the target post-processing parameters include the stretching forces of the stretching apparatus in different directions and the corresponding stretching times.
2. The method of claim 1, wherein the determining target post-processing parameters comprises: determining a first vector to be matched based on the parameters of the blank body to be processed, determining a second vector to be matched based on the target production specification, and matching in a machining parameter database based on the first vector to be matched and the second vector to be matched; wherein the content of the first and second substances,
the processing parameter database is determined based on historical production data and comprises a plurality of reference data sets, each reference data set comprises a first reference vector, a second reference vector and a corresponding reference post-processing parameter, the first reference vector is a vector corresponding to the historical blank parameter to be processed, and the second reference vector is a vector corresponding to the historical target production specification;
matching the first vector to be matched with the first reference vector in each reference data set to determine a first matching relationship, and matching the second vector to be matched with the second reference vector in each reference data set to determine a second matching relationship;
and in response to the existence of a first reference data group in the machining parameter database, enabling the first matching relation and the second matching relation to both meet a first preset condition, and determining the target post-machining parameter based on the reference post-machining parameter in the first reference data group.
3. The method of claim 2, wherein the determining target post-processing parameters further comprises:
in response to the first reference data group not existing in the machining parameter database, enabling the first matching relationship and the second matching relationship to both meet a first preset condition, and determining a second reference data group in the machining parameter database, wherein the second reference data group enables the first matching relationship to meet a second preset condition, and the second matching relationship to meet a third preset condition;
determining candidate post-processing parameters based on the reference post-processing parameters in the second reference data set;
and performing multiple rounds of iteration on the candidate post-processing parameters based on a preset algorithm, and determining the target post-processing parameters.
4. The method of claim 2, wherein the target post-processing parameters further comprise sintering process parameters of a heat treatment apparatus; the sintering process parameters comprise sintering temperature and sintering time;
the data in the plurality of reference data sets further comprises a reference sintering process parameter;
the determining target post-processing parameters further comprises:
and matching in the processing parameter database based on the first vector to be matched and the second vector to be matched, and determining target sintering process parameters.
5. A production control system for a filter cloth, characterized by comprising:
the acquisition module is used for acquiring parameters of a blank body to be processed and target production specifications;
the determining module is used for determining target post-processing parameters based on the parameters of the blank to be processed and the target production specification, and processing the blank to be processed based on the target post-processing parameters to obtain filter cloth meeting the target production specification; wherein the target post-processing parameters include stretching forces of the stretching apparatus in different directions and corresponding stretching times.
6. The system of claim 5, wherein the determination module is further configured to:
determining a first vector to be matched based on the parameters of the blank body to be processed, determining a second vector to be matched based on the target production specification, and matching in a machining parameter database based on the first vector to be matched and the second vector to be matched; wherein the content of the first and second substances,
the processing parameter database is determined based on historical production data and comprises a plurality of reference data sets, each reference data set comprises a first reference vector, a second reference vector and a corresponding reference post-processing parameter, the first reference vector is a vector corresponding to the historical blank parameter to be processed, and the second reference vector is a vector corresponding to the historical target production specification;
matching the first vector to be matched with a first reference vector in each reference data group to determine a first matching relationship, and matching the second vector to be matched with a second reference vector in each reference data group to determine a second matching relationship;
and in response to the existence of a first reference data group in the machining parameter database, enabling the first matching relation and the second matching relation to both meet a first preset condition, and determining the target post-machining parameter based on the reference post-machining parameter in the first reference data group.
7. The system of claim 6, wherein the determination module is further configured to:
in response to the first reference data set not existing in the machining parameter database, enabling the first matching relationship and the second matching relationship to both meet a first preset condition, and determining a second reference data set in the machining parameter database, wherein the second reference data set enables the first matching relationship to meet a second preset condition, and the second matching relationship to meet a third preset condition;
determining candidate post-processing parameters based on the reference post-processing parameters in the second reference data set;
and performing multiple iterations on the candidate post-processing parameters based on a preset algorithm to determine the target post-processing parameters.
8. The system of claim 5, wherein the post-processing parameters further comprise sintering process parameters of a heat treatment apparatus; the sintering process parameters comprise sintering temperature and sintering time;
the data in the plurality of reference data sets further comprises a reference sintering process parameter;
the determination module is further to:
and matching in the processing parameter database based on the first vector to be matched and the second vector to be matched, and determining target sintering process parameters.
9. A device for controlling the production of filter cloth, characterized in that it comprises at least one processor and at least one memory; the at least one memory is for storing computer instructions;
the at least one processor is configured to execute at least a part of the computer instructions to implement the method for controlling production of a filter cloth according to any one of claims 1 to 4.
10. A computer-readable storage medium storing computer instructions, which when read by a computer, execute the method for controlling production of a filter cloth according to any one of claims 1 to 4.
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