CN115033560B - Dyeing model establishing method, dyeing equipment and storage medium - Google Patents
Dyeing model establishing method, dyeing equipment and storage medium Download PDFInfo
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Abstract
The application discloses a method for establishing a dyeing model, a dyeing method, equipment and a storage medium, which are applied to the technical field of dyeing processes and comprise the following steps: acquiring historical data of workpiece dyeing, wherein the historical data comprises historical dyeing time of the workpiece and historical color values of the dyed workpiece; and training the initial model based on historical data to obtain a dyeing model. A dyeing model which can correspond the dyeing time to the color value of the dyed workpiece is established through historical data, and the time required for dyeing can be determined according to the color value of the dyed workpiece based on the dyeing model. The dyeing model replaces manual confirmation of dyeing time, and an accurate dyeing process can be realized.
Description
Technical Field
The present disclosure relates to the field of dyeing technologies, and in particular, to a method for establishing a dyeing model, a dyeing method, a dyeing apparatus, and a computer-readable storage medium.
Background
The surface treatment of metal is basically divided into mechanical surface treatment, chemical surface treatment, electrochemical surface treatment and modern surface treatment, which are commonly known as powder spraying, electroplating, etching, polishing, wire drawing, sand blasting, anodic oxidation and the like, and anodic oxidation is a very common and very basic surface treatment process and is widely applied in the fields of aluminum alloy, titanium alloy and magnesium alloy.
Dyeing of metal articles is typically carried out by multiple anodic processes, including: degreasing, alkali biting, chemical polishing, neutralization, anodic oxidation, acid treatment before dyeing, hole sealing and the like, and parameters of each process such as anodic oxidation time, anodic oxidation voltage, time of pretreatment before dyeing, acid concentration of pretreatment before dyeing, acid pH of pretreatment before dyeing, dyeing time, dyeing dye proportion, dye concentration, dyeing tank temperature, dyeing tank pH, hole sealing time, hole sealing temperature and the like all influence the specific color finally obtained. Therefore, the dyeing of a specific color is always controlled by the experience of production personnel, the experience requirement of the production personnel is high, and meanwhile, the setting of parameters in the dyeing process is carried out according to the subjective experience of the production personnel, so that automation and intellectualization cannot be realized, and the yield cannot be guaranteed. Therefore, how to provide a technical scheme capable of accurately dyeing is an urgent problem to be solved by the technical personnel in the field.
Disclosure of Invention
The application aims to provide a method for establishing a dyeing model, wherein the established model can accurately perform dyeing control; another object of the present application is to provide a dyeing method, a dyeing apparatus, and a computer-readable storage medium, which can precisely perform dyeing control.
In order to solve the above technical problem, the present application provides a method for establishing a dyeing model, including:
acquiring historical data of workpiece dyeing, wherein the historical data comprises historical dyeing time of the workpiece and historical color values of the dyed workpiece;
and training the initial model based on the historical data to obtain a dyeing model.
Optionally, after the acquiring the historical data of the dyeing of the workpiece, the method further includes:
determining a historical dyeing rate of the workpiece according to the historical dyeing time and the historical color value;
training the initial model based on the historical data to obtain a dyeing model comprises:
and training an initial model based on the historical data and the historical dyeing rate to obtain a dyeing model.
Optionally, the historical dyeing time includes historical primary dyeing time for performing primary dyeing on the workpiece, and historical secondary dyeing time for performing secondary dyeing on the workpiece;
the historical color values comprise historical first color values after the workpiece is subjected to primary dyeing and historical second color values after the workpiece is subjected to secondary dyeing;
training an initial model based on the historical data and the historical staining rate to obtain a staining model comprises:
obtaining a historical color difference parameter value based on the historical first color value and the historical second color value;
and training an initial model based on the historical chromatic aberration parameter value, the historical dyeing rate and the historical dyeing time to obtain a dyeing model.
Optionally, the historical staining rate comprises a historical first staining rate corresponding to one staining;
training an initial model based on the historical data and the historical staining rate to obtain a staining model comprises:
obtaining the historical first dyeing rate based on the historical first color value and the historical one-time dyeing time;
training an initial model based on the historical chromatic aberration parameter value, the historical first dyeing rate and the historical dyeing time to obtain a dyeing model.
Optionally, the historical staining rate comprises a historical second staining rate corresponding to the secondary staining;
training an initial model based on the historical data and the historical staining rate to obtain a staining model comprises:
obtaining the historical second dyeing rate based on the historical second color value and the historical secondary dyeing time;
and training an initial model based on the historical chromatic aberration parameter value, the historical second dyeing rate and the historical dyeing time to obtain a dyeing model.
Optionally, the historical first color value is a statistical value of a plurality of historical first color values, and the historical second color value is a statistical value of a plurality of historical second color values.
Optionally, the acquiring historical data of workpiece dyeing includes:
acquiring historical data of workpiece dyeing, wherein the historical data also comprises historical device parameters of the workpiece during preparation.
Optionally, the initial model is a model preset with corresponding weight coefficients for input data input into the initial model.
Optionally, the weight coefficient includes a weight coefficient matrix, one of the number of the parameter types in the input data and the total number of the input data is equal to the number of rows of the weight coefficient matrix, and the other is equal to the number of columns of the weight coefficient matrix.
Optionally, the historical device parameter is a historical device parameter of the dyeing device when the workpiece is in the dyeing process.
Optionally, the historical device parameters include any one or any combination of the following:
dye concentration value, pH value and temperature value.
The present application also provides a dyeing method comprising:
acquiring a color value of the workpiece subjected to primary dyeing;
determining a target secondary dyeing time required for secondary dyeing based on the color value and a dyeing model;
secondarily dyeing the workpiece based on the target secondary dyeing time;
the dyeing model is obtained by training an initial model based on historical data of workpiece dyeing; the historical data includes historical staining times of the workpiece and historical color values of the stained workpiece.
Optionally, before the determining, based on the color value and the dyeing model, a target secondary dyeing time required for secondary dyeing, the method further includes:
acquiring the primary dyeing time for primary dyeing;
the determining a target secondary staining time required for secondary staining based on the color values and a staining model comprises:
determining a primary staining rate based on the primary staining time and the color value;
determining a target secondary staining time required for secondary staining based on the color values, the primary staining rate, and a staining model.
Optionally, before the determining the target secondary dyeing time required for secondary dyeing based on the color value, the primary dyeing rate and the dyeing model, the method further includes:
acquiring a target color value of a workpiece;
determining a target color difference value based on the color value and the target color value;
the determining a target secondary staining time required for secondary staining based on the color values, the primary staining rate, and a staining model comprises:
and determining the target secondary dyeing time required by secondary dyeing based on the target color difference value, the primary dyeing rate and a dyeing model.
Optionally, before the determining the target secondary dyeing time required for secondary dyeing based on the color value, the primary dyeing rate and the dyeing model, the method further includes:
acquiring device parameters during workpiece preparation;
the determining a target secondary staining time required for secondary staining based on the color values, the primary staining rate, and a staining model comprises:
determining a target secondary staining time required for secondary staining based on the color values, the primary staining rate, the device parameters, and a staining model.
Optionally, the device parameters include device parameters of a dyeing tank of the workpiece during a dyeing process.
The present application also provides a dyeing apparatus comprising:
a memory for storing a computer program;
a processor for executing the computer program to perform the steps of the method of building a staining model as described in any of the above, and/or the steps of the staining method as described in any of the above.
The present application also provides a computer-readable storage medium having stored thereon a computer program for execution by a processor to perform the steps of the method of building a staining model according to any of the above and/or the steps of the method of staining according to any of the above.
The application provides a method for establishing a dyeing model, which comprises the following steps: acquiring historical data of workpiece dyeing, wherein the historical data comprises historical dyeing time of the workpiece and historical color values of the dyed workpiece; and training the initial model based on historical data to obtain a dyeing model. And establishing a dyeing model capable of corresponding the dyeing time to the color value of the dyed workpiece through historical data, and determining the time required for dyeing according to the color value of the dyed workpiece based on the dyeing model. The dyeing model replaces manual confirmation of dyeing time, and accurate dyeing process can be realized.
The application also provides a dyeing method, a dyeing device and a computer readable storage medium, which also have the beneficial effects.
Drawings
For a clearer explanation of the embodiments or technical solutions of the prior art of the present application, the drawings needed for the description of the embodiments or prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flowchart of a method for establishing a dyeing model according to an embodiment of the present disclosure;
FIG. 2 is a flowchart of a first specific method for building a staining model according to an embodiment of the present disclosure;
FIG. 3 is a flowchart of a second specific method for building a staining model provided in an embodiment of the present application;
FIG. 4 is a flowchart of a third specific method for building a staining model provided in the examples of the present application;
fig. 5 is a block diagram illustrating a structure of an apparatus for creating a dyeing model according to an embodiment of the present disclosure;
FIG. 6 is a flow chart of a dyeing method provided by an embodiment of the present application;
FIG. 7 is a flow chart of a first specific dyeing method provided in the examples herein;
FIG. 8 is a flow chart of a second specific dyeing method provided in the examples of the present application;
fig. 9 is a block diagram of a dyeing apparatus provided in an embodiment of the present application;
fig. 10 is a block diagram of a dyeing apparatus provided in an embodiment of the present application.
Detailed Description
The core of the application is to provide a dyeing method. In the prior art, when dyeing, especially when processes such as forming gradient color by performing a plurality of dyeing processes are required, dyeing time needs to be automatically judged by people. The dyeing time is not accurate enough, scientific judgment is lacked, and poor dyeing is easy to cause due to manual misjudgment.
The method for establishing the dyeing model provided by the application comprises the following steps: acquiring historical data of workpiece dyeing, wherein the historical data comprises historical dyeing time of the workpiece and historical color values of the dyed workpiece; and training the initial model based on historical data to obtain a dyeing model. And establishing a dyeing model capable of corresponding the dyeing time to the color value of the dyed workpiece through historical data, and determining the time required for dyeing according to the color value of the dyed workpiece based on the dyeing model. The dyeing model replaces manual confirmation of dyeing time, and accurate dyeing process can be realized.
In order that those skilled in the art will better understand the disclosure, the following detailed description is given with reference to the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Referring to fig. 1, fig. 1 is a flowchart illustrating a method for establishing a staining model according to an embodiment of the present disclosure.
Referring to fig. 1, in the embodiment of the present application, a method for establishing a staining model includes:
s101: acquiring historical data of workpiece dyeing, wherein the historical data comprises historical dyeing time of the workpiece and historical color values of the dyed workpiece.
In this step, it is necessary to acquire data when the workpiece is dyed in history, that is, history data. The historical data needs to include historical dyeing time, which is the length of time it takes to dye a workpiece in history, and the historical color value of the workpiece after dyeing the workpiece in history. In the embodiment of the application, each color value can be characterized in an L/A/B color mode. Of course, in the embodiment of the present application, other color modes may also be used to represent each color value, and the specific content may be set according to an actual situation, which is not specifically limited herein.
In the embodiment of the present application, in the history dyeing process corresponding to the history data, it is necessary to keep the apparatus parameters of the dyeing apparatus substantially the same when dyeing. The device parameters of the dyeing device used in the historical dyeing process need to be non-variable, so that the dyeing model can accurately represent the corresponding relation between the historical dyeing time and the historical color value of the dyed workpiece. The parameters of the device may include the temperature of the tank, the pH of the liquid, and the like, and are not limited in particular.
S102: and training the initial model based on historical data to obtain a dyeing model.
In this step, the initial model needs to be trained through the historical dyeing time and the historical color value based on the historical data, so that the corresponding relation between the dyeing time and the color value of the workpiece is established, and the dyeing model is obtained. The initial model may be a regression model, a neural network model, or the like, as long as the corresponding relationship between the dyeing time and the color value of the workpiece can be represented. It should be noted that, according to different specific types of the initial models, the training process may adopt a corresponding training procedure. The following embodiments will be described in detail with respect to the specific training process, and will not be described herein again.
After S101, the history data may be further cleaned. That is, after S101 described above, the embodiment of the present application may further include: and cleaning abnormal data in the historical data to obtain training data. Correspondingly, S102 specifically includes: and training the initial model based on the training data to obtain a dyeing model. The data can be cleaned by adopting a box separation method, a clustering method or a regression method, and the accuracy and the integrity of the historical data can be ensured by cleaning the historical data.
The method for establishing the dyeing model provided by the embodiment of the application comprises the following steps: acquiring historical data of workpiece dyeing, wherein the historical data comprises historical dyeing time of the workpiece and historical color values of the dyed workpiece; and training the initial model based on historical data to obtain a dyeing model. A dyeing model which can correspond the dyeing time to the color value of the dyed workpiece is established through historical data, and the time required for dyeing can be determined according to the color value of the dyed workpiece based on the dyeing model. The dyeing model replaces manual confirmation of dyeing time, and accurate dyeing process can be realized.
The following embodiments will be described in detail with respect to a method for creating a staining model provided in the present application.
Referring to fig. 2, fig. 2 is a flowchart illustrating a first specific method for building a staining model according to an embodiment of the present disclosure.
Referring to fig. 2, in the embodiment of the present application, a method for establishing a staining model includes:
s201: historical data of workpiece dyeing is obtained.
This step is substantially the same as S101 in the above embodiment, and for details, reference is made to the above embodiment, which is not repeated herein.
S202: and determining the historical dyeing rate of the workpiece according to the historical dyeing time and the historical color value.
In this step, the historical color value may be divided by the corresponding historical dyeing time to determine a historical dyeing rate characterizing how fast the workpiece is dyed in the historical data, and the initial model may be trained in a subsequent step in combination with the historical dyeing rate. The color values correspond to a plurality of color components, and taking the LAB color model as an example, a set of color values may specifically correspond to three color components of L value, a value, and B value. Correspondingly, in this step, the dyeing component rate corresponding to each color component may be specifically determined by combining the corresponding historical dyeing time according to each color component in the historical color values. For example, if the historical color value is L 1 /A 1 /B 1 And the historical dyeing time is T, the step can pass through V L =L 1 /T、V A =A 1 /T、V B =B 1 T, obtaining three dyeing component rates V L 、V A 、V B Thereby obtaining a historical dyeing rate V L /V A /V B 。
S203: and training the initial model based on the historical data and the historical dyeing rate to obtain a dyeing model.
In this step, the initial model is trained based on the historical data including the historical dyeing time and the historical color value of the dyed workpiece in combination with the historical dyeing rate, so as to obtain a final dyeing model.
The embodiment of the application provides a method for establishing a dyeing model, establishes a dyeing model corresponding to dyeing time and dyeing workpiece color values through historical data, combines the dyeing rate to promote the accuracy of the dyeing model during establishment, and determines the time required for dyeing according to the dyeing workpiece color values based on the dyeing model. The dyeing model replaces manual confirmation of dyeing time, and accurate dyeing process can be realized.
The following embodiments will be described in detail with respect to a method for creating a staining model provided by the present application.
Referring to fig. 3, fig. 3 is a flowchart illustrating a second specific method for building a staining model according to an embodiment of the present disclosure.
Referring to fig. 3, in the embodiment of the present application, a method for establishing a staining model includes:
s301: historical data of workpiece dyeing is obtained.
In the embodiment of the application, the historical dyeing time comprises historical primary dyeing time for performing primary dyeing on the workpiece and historical secondary dyeing time for performing secondary dyeing on the workpiece; the historical color values include historical first color values after the workpiece is dyed for the first time and historical second color values after the workpiece is dyed for the second time.
That is, in the embodiment of the present application, specifically, a scene in which a workpiece is dyed twice may be targeted, where the parameter input to the initial model during training includes a color value of the workpiece after the workpiece is dyed once in history, that is, a historical first color value; and the color value of the workpiece after the workpiece is dyed for the second time, namely the historical second color value. The time taken for the workpiece to be dyed once, i.e., the historical primary dyeing time, and the time taken for the workpiece to be dyed twice, i.e., the historical secondary dyeing time, are included at the same time. And training the initial model by combining the historical dyeing rate in subsequent steps, so that the trained model can specifically define the corresponding relation between the color value and the secondary dyeing time.
Specifically, in this embodiment of the application, the historical first color value is a statistical value of a plurality of historical first color values, and the historical second color value is a statistical value of a plurality of historical second color values. The statistical value may be a median, an average, a maximum, a minimum, etc. of the corresponding parameter, and may specifically represent a statistical result of the corresponding parameter over a period of time. For example, the historical first color value may be a median of a plurality of historical first color values, and the historical second color value may be a median of a plurality of historical second color values, so as to exclude an influence of a measurement error on the historical color value. Of course, the specific content of the above statistical value may be set according to the actual situation, and is not limited specifically herein.
S302: historical color difference parameter values are obtained based on the historical first color values and the historical second color values.
In this step, the variation of the color value of the workpiece before and after the second dyeing, that is, the value of the historical color difference parameter, can be determined based on the historical first color value and the historical second color value. And training the initial model based on the historical color difference parameter value, so that the trained model can specifically define the corresponding relation between the historical color difference parameter value and the historical secondary dyeing time.
In this step, the historical color difference parameter value may be obtained by performing a difference operation according to the historical first color value and the historical second color value. Taking the LAB color model as an example, if the historical second color value is L 2 /A 2 /B 2 The historical first color value is L 1 /A 1 /B 1 Then in this step can beSubtracting each color component in the historical first color value from each color component in the historical second color value, namely, passing through L 2 -L 1 =ΔL、A 2 -A 1 =ΔA、B 2 -B 1 And = Delta B, obtaining historical color difference parameter values Delta L/Delta A/Delta B.
S303: and determining the historical dyeing rate of the workpiece according to the historical dyeing time and the historical color value.
This step is substantially similar to S202 in the above-described embodiment. Specifically, the historical staining rate may include a historical first staining rate corresponding to one staining. That is, in the embodiment of the present application, the historical first color value corresponding to the same workpiece during the same dyeing process may be divided by the historical one-time dyeing time to obtain the corresponding dyeing rate, that is, the historical first dyeing rate. The detailed calculation process of the dyeing rate is described in the above embodiments, and will not be described herein. In a subsequent step, the initial model may be trained based on the historical first staining rate, resulting in a staining model.
Specifically, the historical staining rates may include a historical second staining rate corresponding to the second staining. That is, in the embodiment of the present application, the historical second color value corresponding to the same workpiece during the same dyeing process may be divided by the historical second dyeing time to obtain the dyeing rate corresponding to the second dyeing process, i.e., the historical second dyeing rate. The detailed calculation process of the dyeing rate is described in the above embodiments, and will not be described herein. In a subsequent step, the initial model may be trained based on the historical second staining rate, resulting in a staining model.
S304: and training the initial model based on the historical chromatic aberration parameter value, the historical dyeing rate and the historical dyeing time to obtain a dyeing model.
In this step, the initial model may be trained based on the historical color difference parameter values, the historical dyeing rate, and the historical dyeing time to obtain a dyeing model. Specifically, when the historical staining rate comprises a historical first staining rate, the step may comprise: and training the initial model based on the historical chromatic aberration parameter value, the historical first dyeing rate and the historical dyeing time to obtain a dyeing model. When the historical staining rate comprises a historical second staining rate, this step may comprise: and training the initial model based on the historical chromatic aberration parameter value, the historical second dyeing rate and the historical dyeing time to obtain a dyeing model. Details of the training of the initial model will be described in detail in the following embodiments, and will not be described herein.
The method for establishing the dyeing model provided by the embodiment of the application establishes the dyeing model which can correspond to the dyeing time and the dyed workpiece color value through the historical data, combines the dyeing speed and the color difference parameter value during establishment, can improve the accuracy of the dyeing model, and can determine the time required by dyeing according to the dyed workpiece color value based on the dyeing model. The dyeing model replaces manual confirmation of dyeing time, and accurate dyeing process can be realized.
The following embodiments will be described in detail with respect to a method for creating a staining model provided by the present application.
Referring to fig. 4, fig. 4 is a flowchart of a third specific method for establishing a dyeing model provided in the embodiment of the present application.
Referring to fig. 4, in the embodiment of the present application, a method for establishing a staining model includes:
s401: and acquiring historical data of workpiece dyeing, wherein the historical data also comprises historical device parameters during workpiece preparation.
In this step, the historical data may include historical device parameters at the time of workpiece preparation, in addition to the above-described historical dyeing time and historical color values. The historical device parameters are parameters generated when each device or device runs in the manufacturing process of the workpiece. It should be noted that, in the manufacturing process, the workpiece may undergo not only one dyeing treatment but a plurality of processes, including oxidation degreasing, alkali-bite, chemical polishing, neutralization, anodic oxidation, acid treatment before dyeing, hole sealing, etc., each process corresponds to one process, and when the corresponding process works, the device or equipment thereof may generate corresponding parameters, i.e., device parameters; after each step, the workpiece is affected, and corresponding workpiece parameters are generated.
For example, the pH of the solution may be used as a device parameter during the acid treatment process prior to dyeing, and correspondingly, the thickness of the oxide layer may be used as a workpiece parameter after the anodization process. In an embodiment of the present application, the historical device parameter may be a historical device parameter of the dyeing device when the workpiece is in the dyeing process, that is, a device parameter generated by the dyeing device in the history. Furthermore, the historical data may further include historical workpiece parameters of the workpiece after the dyeing process, that is, workpiece parameters carried by the workpiece after each process in the history. The historical color value may be used as one of the workpiece parameters. Of course, the historical device parameters may also include other process parameters as a reference, and the specific content thereof may be set according to the actual situation, and is not limited herein. Of course, the target parameter in the training of the initial model in the embodiment of the present application is the historical dyeing time, such as the historical secondary dyeing time, which is focused on the dyeing process. The historical device parameters used in the embodiments of the present application may also be only device parameters generated when the dye vat is in operation.
Specifically, in the embodiment of the present application, the history device parameters include: dye concentration value, pH value and temperature value. Of course, other parameters may also be selected as the history device parameters, and are not specifically limited herein.
It should be noted that, in the embodiment of the present application, the history device parameters include various parameters, and the data thereof is numerous and complicated. Correspondingly, after the step, the method can comprise the following steps: completing missing values of the historical device parameters, and processing abnormal values of the historical device parameters. The accuracy of the final dyeing model can be further improved by completing missing values of the parameters of the historical device and carrying out exception handling.
S402: and obtaining a historical color difference parameter value based on the historical first color value and the historical second color value.
S403: and determining the historical dyeing rate of the workpiece according to the historical dyeing time and the historical color value.
S404: and training the initial model based on the historical data and the historical dyeing rate to obtain a dyeing model.
S402 to S404 are substantially the same as S302 to S304 in the above embodiment, and for details, reference is made to the above embodiment, which is not repeated herein.
In an embodiment of the present application, the initial model may be a local weighted linear regression model. The principle of the local weighted linear regression model is: the data set is examined to consider only data points that lie within a certain range around the point to be predicted. And performing linear regression (local linear regression) on the points in the region, adding weight consideration when solving regression parameters by using a least square method, endowing each point in the range with certain weight, gradually attenuating the weight along with the increase of the distance from the point to be predicted, and reducing the weight along with the increase of the distance from the point to be predicted. And finally, evaluating and predicting the point to be predicted according to the fitting straight line.
That is, in the embodiment of the present application, it is preferable to use a local weighted linear regression model as the initial model, and train the local weighted linear regression model to obtain the staining model. Of course, models of other algorithms may also be selected in the embodiment of the present application, and are not specifically limited herein. Specifically, in the embodiment of the present application, the initial model is a model that is preset with corresponding weight coefficients for input data of the initial model. Namely, in the embodiment of the present application, a corresponding weight coefficient is additionally set for each input data.
Specifically, when the distance calculation is performed by the locally weighted linear regression model, different weights are given to different features of the sample in the embodiment of the present application. Specifically, for the conventional local weighted linear regression model, for each training data point, the following should be performed:
and a minimum, where i is the number corner mark of the training data,
x （i） is the ith training data, since a set of training data has m features in the embodiment of the present application, the present invention is not limited to the above-mentioned embodimentIt is a m × 1 vector, y （i） Is the target value of the ith training data, and θ is the coefficient vector of the regression equation; ω is a Gaussian weight coefficient, which is expressed as:
wherein x is （i） Is the ith training data, x is the data point to be predicted; τ is the bandwidth, the greater τ, the greater the intensity of the local regression.
When the local weighted linear regression is used for prediction in the embodiment of the present application, because different features have different influence weights on the target result, the weight coefficient of the feature is increased during distance calculation, and at this time, the original gaussian weight coefficient becomes:
wherein x is （i） Is the ith training data, x is the data point to be predicted; τ is the bandwidth, the greater τ, the greater the intensity of the local regression; α is a weight matrix of the sample point feature to represent different weights of different features in the distance calculation.
Thus, the model solves for the regression coefficients as:
wherein X is a group consisting of 1 (constant term) and X （i） An n × (m + 1) dimensional matrix of composition, n being the number of training data, m being the number of data features, X can be written as: />
Therefore, in the embodiment of the present application, the weight coefficients include a weight coefficient matrix, one of the number of the parameter types in the input data and the total number of the input data is equal to the number of rows of the weight coefficient matrix, and the other is equal to the number of columns of the weight coefficient matrix. By training the initial model comprising the weight coefficient matrix, the obtained dyeing model is more accurate.
The utility model provides a through historical data establishment including historical device parameter can be with the dyeing model that dyeing time and dyeing back work piece colour value correspond, combines dyeing rate and colour difference parameter value during the establishment, can promote the accuracy of dyeing model, can confirm the required time of dyeing according to the work piece colour value after the colour based on this dyeing model. The dyeing model replaces manual confirmation of dyeing time, and accurate dyeing process can be realized.
The following describes an apparatus for establishing a dyeing model provided in an embodiment of the present application, and the apparatus for establishing a dyeing model described below and the method for establishing a dyeing model described above may be referred to in correspondence with each other.
Fig. 5 is a block diagram illustrating a structure of an apparatus for creating a dyeing model according to an embodiment of the present application, where the apparatus for creating a dyeing model according to fig. 5 may include:
the history acquisition module 100 is configured to acquire history data of workpiece dyeing, where the history data includes a history dyeing time of the workpiece and a history color value of the dyed workpiece.
And the training module 200 is configured to train the initial model based on the historical data to obtain a dyeing model.
Optionally, in an embodiment of the present application, the method further includes:
and the dyeing rate module is used for determining the historical dyeing rate of the workpiece according to the historical dyeing time and the historical color value.
The training module 200 is specifically configured to:
and training the initial model based on the historical data and the historical dyeing rate to obtain a dyeing model.
Optionally, in this embodiment of the application, the historical dyeing time includes a historical primary dyeing time for performing primary dyeing on the workpiece, and a historical secondary dyeing time for performing secondary dyeing on the workpiece;
the historical color values comprise historical first color values obtained after the workpiece is subjected to primary dyeing and historical second color values obtained after the workpiece is subjected to secondary dyeing;
the training module 200 includes:
a historical color difference parameter value unit, configured to obtain a historical color difference parameter value based on the historical first color value and the historical second color value;
and the first training unit is used for training the initial model based on the historical chromatic aberration parameter value, the historical dyeing rate and the historical dyeing time to obtain a dyeing model.
Optionally, in this embodiment of the present application, the historical staining rate includes a historical first staining rate corresponding to one staining;
the training module 200 includes:
a historical first dyeing rate unit, configured to obtain a historical first dyeing rate based on a historical first color value and a historical one-time dyeing time;
and the second training unit is used for training the initial model based on the historical chromatic aberration parameter value, the historical first dyeing rate and the historical dyeing time to obtain a dyeing model.
Optionally, in this embodiment of the present application, the historical dyeing rate includes a historical second dyeing rate corresponding to the secondary dyeing;
the training module 200 includes:
the historical second dyeing rate unit is used for obtaining a historical second dyeing rate based on the historical second color value and the historical secondary dyeing time;
and the third training unit is used for training the initial model based on the historical chromatic aberration parameter value, the historical second dyeing rate and the historical dyeing time to obtain a dyeing model.
Optionally, in this embodiment of the application, the historical first color value is a statistical value of a plurality of historical first color values, and the historical second color value is a statistical value of a plurality of historical second color values.
Optionally, in this embodiment of the application, the history obtaining module 100 is configured to:
and acquiring historical data of workpiece dyeing, wherein the historical data also comprises historical device parameters during workpiece preparation.
Optionally, in this embodiment of the application, the initial model is a model that presets corresponding weight coefficients for input data that is input to the initial model.
Optionally, in this embodiment of the application, the weight coefficient includes a weight coefficient matrix, one of the number of the parameter types in the input data and the total number of the input data is equal to the number of rows of the weight coefficient matrix, and the other is equal to the number of columns of the weight coefficient matrix.
Optionally, in this embodiment, the historical device parameter is a historical device parameter of the dyeing device when the workpiece is in the dyeing process.
Optionally, in this embodiment of the present application, the historical device parameter includes any one or any combination of the following:
dye concentration value, pH value and temperature value.
The dyeing model establishing apparatus of this embodiment is configured to implement the aforementioned dyeing model establishing method, and therefore specific embodiments in the dyeing model establishing apparatus may refer to the embodiment parts of the dyeing model establishing method in the foregoing, for example, the history obtaining module 100 and the training module 200, which are respectively configured to implement steps S101 and S102 in the dyeing model establishing method, so that specific embodiments thereof may refer to descriptions of corresponding embodiments of the respective parts, and details thereof are not repeated herein.
Referring to fig. 6, fig. 6 is a flowchart of a dyeing method according to an embodiment of the present disclosure.
Referring to fig. 6, in an embodiment of the present application, a dyeing method includes:
s501: and acquiring the color value of the workpiece after the primary dyeing.
In this step, the color value of the workpiece after the workpiece is dyed for the first time needs to be acquired, so that the dyeing time corresponding to the secondary dyeing is determined according to the dyeing model and the color value. It should be noted that, in the embodiment of the present application, the parameters finally input to the staining model substantially correspond to the parameters used for training the staining model in the embodiment described above, in the embodiment of the present application, the result finally output based on the staining model is the target secondary staining time and corresponds to the historical secondary staining time, and the color value in this step corresponds to the historical first color value in the embodiment described above.
S502: based on the color values and the staining model, a target secondary staining time required for secondary staining is determined.
In the embodiment of the application, the dyeing model is a model obtained by training an initial model based on historical data of workpiece dyeing; the historical data includes historical staining times of the workpiece and historical color values of the stained workpiece. The process of establishing the staining model is described in detail in the above embodiments, and will not be described herein.
In this step, the color values are input into the dyeing model, and the target secondary dyeing time required for secondary dyeing is output through the dyeing model. Details regarding this step will be described in detail in the following embodiments, and will not be described herein.
S503: and carrying out secondary dyeing on the workpiece based on the target secondary dyeing time.
In this step, the workpiece is secondarily dyed based on the target secondary dyeing time, thereby realizing an accurate secondary dyeing process.
According to the dyeing method provided by the embodiment of the application, the dyeing model capable of enabling the dyeing time to correspond to the color value of the dyed workpiece is established through the historical data, and the time required by dyeing can be determined according to the color value of the dyed workpiece based on the dyeing model. The dyeing model replaces manual confirmation of dyeing time, and accurate dyeing process can be realized.
The details of a dyeing method provided in the examples of the present application will be described in detail in the following examples.
Referring to fig. 7, fig. 7 is a flowchart illustrating a first specific dyeing method according to an embodiment of the present disclosure.
Referring to fig. 7, in an embodiment of the present application, a dyeing method includes:
s601: and acquiring the color value of the workpiece after the primary dyeing.
This step is substantially the same as S501, and is not described herein again.
S602: the one-time dyeing time for one dyeing is obtained.
In this step, a dyeing time corresponding to the color value may be obtained for the calculation of a subsequent dyeing rate. The one-time dyeing time corresponds to the historical one-time dyeing time in the above embodiment, and is the time spent by the workpiece in the one-time dyeing process. This step and the above S601 may be executed in any order or in parallel, and are not limited specifically herein according to specific situations.
S603: determining a primary staining rate based on the primary staining time and the color value.
In this step, the color value may be divided by a dyeing time to obtain a corresponding first dyeing rate. The detailed calculation process of the dyeing rate is described in the above embodiments, and will not be described herein. In step (ii), the first staining rate corresponds to the historical first staining rate in the above example.
S604: based on the color values, the primary staining rate and the staining model, a target secondary staining time required for secondary staining is determined.
In this step, the color values and the primary dyeing rate are input into a dyeing model, and the target secondary dyeing time required by secondary dyeing is obtained.
Before this step, the embodiment of the present application may further include: acquiring a target color value of a workpiece; a target color difference value is determined based on the color value and the target color value. The target color value is a color value that the workpiece needs to reach after the second dyeing, and specifically corresponds to the historical second color value in the above embodiment. In the process of obtaining the dyeing model by training the initial model by using the historical data, all the used historical data are data after successful dyeing. And the historical second color value is the color value of the workpiece after the workpiece is dyed twice successfully in the history. In the current dyeing process, the workpiece is dyed for the second time, so that the color value of the workpiece reaches the target color value after the workpiece is dyed for the second time, in other words, the target color value corresponds to the historical second color value in the historical data.
In this application embodiment, can further make a difference with target color value and color value, can make a difference respectively with the color component that two above-mentioned color values correspond, obtain the target color difference value, it expresses as Δ L/Δ a/Δ B. And then, inputting the target color difference value into a dyeing model to obtain the target secondary dyeing time.
Correspondingly, the method comprises the following steps: and determining the target secondary dyeing time required by secondary dyeing based on the target color difference value, the primary dyeing rate and the dyeing model. And inputting the target color difference value and the primary dyeing rate into a pre-trained dyeing model to obtain the secondary dyeing time of the target.
S605: and secondarily dyeing the workpiece based on the target secondary dyeing time.
In this step, the workpiece is secondarily dyed based on the target secondary dyeing time, thereby realizing an accurate secondary dyeing process.
According to the dyeing method provided by the embodiment of the application, the dyeing model capable of enabling the dyeing time to correspond to the color value of the dyed workpiece is established through the historical data, and the time required by dyeing can be determined according to the color value of the dyed workpiece based on the dyeing model. The dyeing model replaces manual confirmation of dyeing time, and accurate dyeing process can be realized.
Details of a dyeing method provided in the embodiments of the present application will be described in detail in the following embodiments.
Referring to fig. 8, fig. 8 is a flowchart illustrating a second specific dyeing method according to an embodiment of the present disclosure.
Referring to fig. 8, in an embodiment of the present application, a dyeing method includes:
s701: and acquiring the color value of the workpiece after the primary dyeing.
S702: and acquiring the one-time dyeing time for one-time dyeing.
S701 to S702 are substantially the same as S601 to S602 in the above embodiment, and for details, reference is made to the above embodiment, which is not repeated herein.
S703: and acquiring device parameters during workpiece preparation.
In this step, parameters at the time of operation of the color device when dyeing the workpiece, that is, device parameters, can be acquired. The specific type and the related preprocessing process of the device parameter corresponding to the historical device parameter may refer to the above embodiments, and are not described herein again.
Specifically, in the embodiment of the present application, the device parameters include device parameters of a dyeing tank of the workpiece during the dyeing process, and in this case, the device parameters may include: dye concentration value, pH value, and temperature value. Of course, other parameters may also be selected as the device parameters, and are not specifically limited herein.
S704: determining a primary staining rate based on the primary staining time and the color value.
This step is substantially the same as S603 in the above embodiment, and is not described herein again.
S705: and determining the target secondary dyeing time required by secondary dyeing based on the color value, the primary dyeing rate, the device parameter and the dyeing model.
In this step, the color values, the primary dyeing rate and the device parameters can be input into the dyeing model, and the secondary dyeing time of the target output by the dyeing model is obtained.
S706: and carrying out secondary dyeing on the workpiece based on the target secondary dyeing time.
In this step, the workpiece is secondarily dyed based on the target secondary dyeing time, thereby realizing an accurate secondary dyeing process.
According to the dyeing method provided by the embodiment of the application, the dyeing model capable of enabling the dyeing time to correspond to the color value of the dyed workpiece is established through the historical data, and the time required by dyeing can be determined according to the color value of the dyed workpiece based on the dyeing model. The dyeing model replaces manual confirmation of dyeing time, and accurate dyeing process can be realized.
The dyeing apparatus provided in the embodiments of the present application is described below, and the dyeing apparatus described below and the dyeing method described above may be referred to in correspondence.
Fig. 9 is a block diagram of a dyeing apparatus provided in an embodiment of the present application, and with reference to fig. 9, the dyeing apparatus may include:
and the color value obtaining module 300 is configured to obtain a color value of the workpiece after the workpiece is dyed once.
A target secondary dyeing time module 400, configured to determine a target secondary dyeing time required for secondary dyeing based on the color value and the dyeing model;
a dyeing module 500 for performing secondary dyeing on the workpiece based on the target secondary dyeing time;
the dyeing model is obtained by training an initial model based on historical data of workpiece dyeing; the historical data includes historical staining times of the workpieces and historical color values of the stained workpieces.
Optionally, in an embodiment of the present application, the method further includes:
and the primary dyeing time acquisition module is used for acquiring primary dyeing time for primary dyeing.
The target secondary staining time module 400 includes:
a primary dyeing rate unit for determining a primary dyeing rate based on the primary dyeing time and the color value;
and the first target secondary dyeing time unit is used for determining the target secondary dyeing time required by secondary dyeing based on the color value, the primary dyeing rate and the dyeing model.
Optionally, in this embodiment of the present application, the method further includes:
the target color value acquisition module is used for acquiring a target color value of the workpiece;
a target color difference module to determine a target color difference based on the color values and the target color values;
the target secondary staining time module 400 is used to:
and determining the target secondary dyeing time required by secondary dyeing based on the target color difference value, the primary dyeing rate and the dyeing model.
Optionally, in an embodiment of the present application, the method further includes:
the device parameter acquisition module is used for acquiring device parameters during workpiece preparation;
the target secondary staining time module 400 is used to:
and determining the target secondary dyeing time required by secondary dyeing based on the color value, the primary dyeing rate, the device parameter and the dyeing model.
Optionally, in the embodiment of the present application, the device parameters include device parameters of the dyeing tank during the dyeing process of the workpiece.
The dyeing apparatus of this embodiment is configured to implement the foregoing dyeing method, and therefore specific embodiments in the dyeing apparatus may be seen in example portions of the dyeing method in the foregoing, for example, the color value obtaining module 300, the target secondary dyeing time module 400, and the dyeing module 500, which are respectively configured to implement steps S501 to S503 in the method for establishing the dyeing model, and therefore, the specific embodiments thereof may refer to descriptions of corresponding partial embodiments, which are not described herein again.
In the following, a dyeing apparatus provided by an embodiment of the present application is introduced, and the dyeing apparatus described below and the method for establishing the dyeing model and the dyeing method described above may be referred to correspondingly.
Referring to fig. 10, fig. 10 is a block diagram of a dyeing apparatus according to an embodiment of the present disclosure.
Referring to fig. 10, the dyeing apparatus may include a processor 11 and a memory 12.
The memory 12 is used for storing a computer program; the processor 11 is configured to implement the method for establishing the dyeing model in the above embodiments and/or the specific contents of the dyeing method when executing the computer program.
The processor 11 of the dyeing apparatus of the present embodiment is used for installing the device for establishing the dyeing model in the above embodiments, and/or the dyeing device, and the processor 11 and the memory 12 can be combined to implement the method for establishing the dyeing model in any of the above embodiments, and/or the dyeing method. Therefore, the specific implementation manner of the dyeing apparatus can be seen in the above embodiment sections of the method for establishing the dyeing model and the dyeing method, and the specific implementation manner thereof can refer to the description of the corresponding embodiments of each section, which is not described herein again.
The present application further provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements a method for building a staining model, and/or a staining method as described in any of the above embodiments.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the technical solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Finally, it should also be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a component of' 8230; \8230;" does not exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.
A method of establishing a dyeing model, a dyeing method, a dyeing apparatus, and a computer-readable storage medium provided by the present application are described in detail above. The principles and embodiments of the present application are explained herein using specific examples, which are provided only to help understand the method and the core idea of the present application. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
Claims (11)
1. A method for establishing a dyeing model is characterized by comprising the following steps:
acquiring historical data of workpiece dyeing, wherein the historical data comprises historical dyeing time of a workpiece, historical color values of the dyed workpiece and historical device parameters of the workpiece during preparation; the historical dyeing time comprises historical primary dyeing time for performing primary dyeing on the workpiece and historical secondary dyeing time for performing secondary dyeing on the workpiece; the historical color values comprise historical first color values after the workpiece is subjected to primary dyeing and historical second color values after the workpiece is subjected to secondary dyeing;
subtracting each color component in the historical first color value from each color component in the historical second color value to obtain a historical color difference parameter value;
determining dyeing component rates corresponding to the color components according to the color components in the historical color values and combining the corresponding historical dyeing time to form the historical dyeing rate of the workpiece;
training an initial model based on the historical device parameters, the historical chromatic aberration parameter values, the historical dyeing rate and the historical dyeing time to obtain a dyeing model; the initial model is a model with preset corresponding weight coefficients for input data input into the initial model.
2. The method of claim 1, wherein the historical staining rates comprise a historical first staining rate corresponding to one staining;
the training of the initial model based on the historical device parameters, the historical color difference parameter values, the historical dyeing rate and the historical dyeing time to obtain the dyeing model comprises:
obtaining the historical first dyeing rate based on the historical first color value and the historical one-time dyeing time;
and training an initial model based on the historical device parameters, the historical chromatic aberration parameter values, the historical first dyeing rate and the historical dyeing time to obtain a dyeing model.
3. The method of claim 2, wherein the historical staining rates comprise historical second staining rates corresponding to secondary staining;
the training an initial model based on the historical device parameters, the historical color difference parameter values, the historical dyeing rate and the historical dyeing time to obtain a dyeing model comprises:
obtaining the historical second dyeing rate based on the historical second color value and the historical secondary dyeing time;
and training an initial model based on the historical device parameters, the historical chromatic aberration parameter values, the historical first dyeing rate, the historical second dyeing rate and the historical dyeing time to obtain a dyeing model.
4. The method of claim 1 wherein the historical first color value is a statistical value of a plurality of historical first color values and the historical second color value is a statistical value of a plurality of historical second color values.
5. The method of claim 1, wherein the weight coefficients comprise a weight coefficient matrix, and wherein one of the number of the parameter types in the input data and the total number of the input data is equal to the number of rows of the weight coefficient matrix, and the other is equal to the number of columns of the weight coefficient matrix.
6. The method of claim 1, wherein the historical device parameters are historical device parameters of a dyeing device during a dyeing process of the workpiece.
7. The method of claim 6, wherein the historical device parameters comprise any one or any combination of the following:
dye concentration value, pH value and temperature value.
8. A method of dyeing, comprising:
acquiring the color value of the workpiece after primary dyeing, the target color value of the workpiece, device parameters during workpiece preparation and primary dyeing time for primary dyeing;
determining a target color difference value based on the color value and the target color value;
determining a primary staining rate based on the primary staining time and the color value;
determining a target secondary dyeing time required for secondary dyeing based on the target color difference, the primary dyeing rate, the device parameters and a dyeing model;
secondarily dyeing the workpiece based on the target secondary dyeing time;
the dyeing model is obtained by training an initial model based on historical device parameters, historical chromatic aberration parameter values, historical dyeing speed and historical dyeing time; the historical dyeing speed comprises determining the dyeing component speed corresponding to each color component by combining the corresponding historical dyeing time according to each color component in the historical color values; the historical color difference parameter value is obtained by subtracting each color component in the historical first color value from each color component in the historical second color value; the initial model is a model with preset corresponding weight coefficients for input data input into the initial model.
9. The method of claim 8, wherein the device parameters comprise device parameters of a dye bath of the workpiece during a dyeing process.
10. A dyeing apparatus, characterized by comprising:
a memory for storing a computer program;
processor for executing said computer program for carrying out the steps of the method for establishing a staining model according to any one of claims 1 to 7 and/or the steps of the staining method according to any one of claims 8 to 9.
11. A computer-readable storage medium, in which a computer program is stored which is executable by a processor for carrying out the steps of the method for building a staining model according to any one of claims 1 to 7 and/or the steps of the method for staining according to any one of claims 8 to 9.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
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