Optimization Device and Method for Textile Material Dyeing Process Based on Intelligent Temperature Control

Abstract

The present application provides an optimization device and method for textile material dyeing process based on intelligent temperature control, which relates to the technical field of textile material manufacturing, and includes: a textile dyeing task receiving module for receiving textile dyeing tasks; an adsorption temperature control optimization module for obtaining the first optimization result of the textile material dyeing process; a dye uptake temperature control optimization module for obtaining the second optimization result of the textile material dyeing process; a color fixation temperature control optimization module for obtaining the third optimization result of the textile material dyeing process; and a textile dyeing module for dyeing textile materials. Through the present application, the technical problem in the prior art that the dyeing quality is low due to often only focusing on the temperature control optimization of a single dyeing stage and failing to achieve the overall optimization of the entire dyeing process flow can be solved. By optimizing and adjusting the temperature control parameters at each stage, the technical effect of improving the stability and consistency of the dyeing process and thus enhancing the color quality of the final textile products can be achieved.

Description

Technical Field

[0001] This application relates to the technical field of textile material manufacturing, and particularly to an optimization device and method for the dyeing process of textile materials based on intelligent temperature control. Background Art

[0002] The dyeing process of textile materials is one of the key steps in textile production, directly affecting the color effect and quality of the final product. However, traditional dyeing processes often rely on experience and manual adjustment, making it difficult to achieve precise control of the dyeing process, especially in terms of temperature control. During the dyeing process, temperature changes have a crucial impact on the adsorption, dyeing, and fixation effects of dyes. A slight oversight may lead to problems such as uneven dyeing, color deviation, and poor dye fixation, thereby affecting the market competitiveness of the product.

[0003] In recent years, with the development of intelligent control technology, how to optimize the dyeing process of textile materials through an intelligent temperature control system has become a research hotspot in the industry. The intelligent temperature control system can automatically adjust the temperature curve according to real-time process parameters, thereby improving the adsorption uniformity and fixation fastness of dyes and achieving an efficient and high-quality dyeing process. However, existing intelligent temperature control systems often only focus on the temperature control optimization of a single dyeing stage and fail to achieve a comprehensive optimization of the entire dyeing process flow, resulting in low dyeing quality. Summary of the Invention

[0004] The purpose of this application is to provide an optimization device and method for the dyeing process of textile materials based on intelligent temperature control, so as to solve the technical problem in the prior art that due to often only focusing on the temperature control optimization of a single dyeing stage and failing to achieve a comprehensive optimization of the entire dyeing process flow, the dyeing quality is low.

[0005] In view of the above problems, this application provides an optimization device and method for the dyeing process of textile materials based on intelligent temperature control.

[0006] In a first aspect, the present application provides an optimization device for textile material dyeing process based on intelligent temperature control, which is used to execute an optimization method for textile material dyeing process based on intelligent temperature control. Among them, the optimization device for textile material dyeing process based on intelligent temperature control includes: a textile dyeing task receiving module, which is used to receive a textile dyeing task, where the textile dyeing task includes predetermined textile material dyeing process information; an adsorption temperature control optimization module, which is used to perform temperature control optimization in the adsorption stage on the predetermined textile material dyeing process information based on a preset dye adsorption uniformity and a preset dye adsorption depth to obtain a first optimized result of the textile material dyeing process; a dyeing temperature control optimization module, which is used to perform temperature control optimization in the dyeing stage on the first optimized result of the textile material dyeing process based on a preset dyeing temperature rising smoothness coefficient to obtain a second optimized result of the textile material dyeing process; a color fixation temperature control optimization module, which is used to perform temperature control optimization in the color fixation stage on the second optimized result of the textile material dyeing process based on a preset color fastness and a preset color fixation uniformity to obtain a third optimized result of the textile material dyeing process; a textile dyeing module, which is used to perform textile material dyeing based on the third optimized result of the textile material dyeing process.

[0007] In a second aspect, the present application also provides an optimization method for textile material dyeing process based on intelligent temperature control. The optimization method for textile material dyeing process based on intelligent temperature control is implemented by the optimization device for textile material dyeing process based on intelligent temperature control described in the first aspect. Among them, the optimization method for textile material dyeing process based on intelligent temperature control includes: receiving a textile dyeing task, where the textile dyeing task includes predetermined textile material dyeing process information; performing temperature control optimization in the adsorption stage on the predetermined textile material dyeing process information based on a preset dye adsorption uniformity and a preset dye adsorption depth to obtain a first optimized result of the textile material dyeing process; performing temperature control optimization in the dyeing stage on the first optimized result of the textile material dyeing process based on a preset dyeing temperature rising smoothness coefficient to obtain a second optimized result of the textile material dyeing process; performing temperature control optimization in the color fixation stage on the second optimized result of the textile material dyeing process based on a preset color fastness and a preset color fixation uniformity to obtain a third optimized result of the textile material dyeing process; performing textile material dyeing based on the third optimized result of the textile material dyeing process.

[0008] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0009] Textile Dyeing Task Receiving Module, which is used to receive textile dyeing tasks. Among them, the textile dyeing task includes predetermined textile material dyeing process information; Adsorption Temperature Control Optimization Module, which is used to optimize the temperature control in the adsorption stage of the predetermined textile material dyeing process information based on the preset dye adsorption uniformity and preset dye adsorption depth to obtain the first optimized result of the textile material dyeing process; Dyeing Temperature Control Optimization Module, which is used to optimize the temperature control in the dyeing stage of the first optimized result of the textile material dyeing process based on the preset dyeing temperature rise smoothness coefficient to obtain the second optimized result of the textile material dyeing process; Fixation Temperature Control Optimization Module, which is used to optimize the temperature control in the fixation stage of the second optimized result of the textile material dyeing process based on the preset color fastness and preset fixation uniformity to obtain the third optimized result of the textile material dyeing process; Textile Dyeing Module, which is used to dye textile materials based on the third optimized result of the textile material dyeing process. By optimizing the temperature control in the adsorption stage, dyeing stage and fixation stage of the dye, and combining with the intelligent prediction model, the temperature control parameters of each stage are optimized and adjusted, achieving the technical effect of improving the stability and consistency of the dyeing process, and further enhancing the color quality of the final textile products.

[0010] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the following specifically gives the specific implementation manners of the present application. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easily understood through the following description of the specification. Brief Description of the Drawings

[0011] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings required to be used in the description of the embodiments or the prior art. Obviously, the drawings described below are only exemplary, and for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the provided drawings.

[0012] Figure 1 It is a schematic structural diagram of the textile material dyeing process optimization device based on intelligent temperature control of the present application;

[0013] Figure 2 It is a schematic flowchart of the textile material dyeing process optimization method based on intelligent temperature control of the present application.

[0014] Explanation of the Reference Numerals in the Drawings:

[0015] Textile dyeing task receiving module 11, adsorption temperature control optimization module 12, dyeing temperature control optimization module 13, fixation temperature control optimization module 14, textile dyeing module 15. Detailed implementation manner

[0016] By providing a textile material dyeing process optimization device and method based on intelligent temperature control, the present application solves the technical problem in the prior art that due to often only focusing on the temperature control optimization of a single dyeing stage and failing to achieve the overall optimization of the entire dyeing process flow, the dyeing quality is low. By optimizing the temperature control in the dye adsorption stage, dyeing stage, and fixation stage, and combining with an intelligent prediction model, the temperature control parameters of each stage are optimized and adjusted, achieving the technical effect of improving the stability and consistency of the dyeing process and further enhancing the color quality of the final textile product.

[0017] Next, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the example embodiments described herein. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application. Additionally, it should be noted that for the sake of description, only the parts related to the present application are shown in the drawings rather than all of them.

[0018] Example 1. Please refer to the attached Figure 1 , the present application provides a textile material dyeing process optimization device based on intelligent temperature control, including:

[0019] A textile dyeing task receiving module 11, which is used to receive textile dyeing tasks. Among them, the textile dyeing tasks include predetermined textile material dyeing process information.

[0020] Specifically, the textile dyeing task receiving module is responsible for receiving and processing textile dyeing tasks. In this process, the textile dyeing task receiving module receives information related to specific dyeing tasks from an external system or a user interface. These information are collectively referred to as textile dyeing tasks. The textile dyeing tasks include predetermined textile material dyeing process information. The predetermined textile material dyeing process information refers to the dyeing process and requirements that have been predefined in advance, usually based on historical data, expert experience, or specific process standards, including all the parameters and steps required in the dyeing process, such as the type of dye used, the target color, the dyeing time, the temperature curve, etc., facilitating subsequent precise temperature control and optimization.

[0021] The adsorption temperature control optimization module 12 is used to optimize the temperature control in the adsorption stage of the predetermined textile material dyeing process based on a preset dye adsorption uniformity and a preset dye adsorption depth, so as to obtain an optimized result of the first textile material dyeing process.

[0022] Specifically, the adsorption temperature control optimization module is used to optimize the temperature control in the adsorption stage of dyeing. In this stage, the textile material makes initial contact with the dye, and the dye gradually adsorbs onto the surface or inside of the material. The preset dye adsorption uniformity refers to the expected degree of uniformity of the dye distribution on the surface or inside of the textile material, which is an important indicator affecting the final dyeing effect. Uniform adsorption can ensure that there are no spots or color differences on the material surface, thus achieving color consistency. The preset dye adsorption depth refers to the depth to which the dye penetrates into the textile material. An appropriate adsorption depth can enhance the fixation of the dye and prevent the color from fading easily during subsequent use. The preset dye adsorption uniformity and the preset dye adsorption depth are set by professionals in the field in combination with actual needs.

[0023] First, it will read and analyze the predetermined textile material dyeing process information, and automatically adjust the temperature control parameters in the adsorption stage according to the preset dye adsorption uniformity and the preset dye adsorption depth to optimize the dye adsorption process. Through this temperature control optimization, an optimized result of the first textile material dyeing process is finally generated, which is a set of optimized dyeing process parameters and lays a foundation for the subsequent dyeing and fixation stages.

[0024] The dyeing temperature control optimization module 13 is used to optimize the temperature control in the dyeing stage of the optimized result of the first textile material dyeing process based on a preset dyeing temperature rising smoothness coefficient, so as to obtain an optimized result of the second textile material dyeing process.

[0025] Specifically, the main function of the dyeing temperature control optimization module is to precisely control and optimize the temperature during the dyeing stage. During this stage, the textile material is gradually heated in the dye solution, and the dye molecules further penetrate and fix onto the material. To ensure the smooth progress of this process, the dyeing temperature control optimization module will optimize and adjust the dyeing process according to the preset dyeing temperature rising smoothness coefficient. The preset dyeing temperature rising smoothness coefficient refers to the smoothness index of the temperature rise during the dyeing process, and it is an important parameter to measure whether the temperature change is uniform and appropriate. A smooth temperature rise can prevent the sudden rise or fall of temperature from causing uneven adsorption of the dye or damage to the textile material. The smoothness of temperature control is crucial for the dyeing effect because improper temperature fluctuations may lead to uneven dye distribution or color deviation, affecting the quality of the final product. The optimization result of the first textile material dyeing process is the result after the temperature control optimization in the previous adsorption stage. Based on the optimization result of the first textile material dyeing process, the temperature change curve in the dyeing stage is simulated, and by evaluating the smoothness of these curves, the predicted dyeing temperature rising smoothness coefficient is generated. If the predicted temperature rising smoothness coefficient is lower than the preset standard, the temperature control strategy is automatically adjusted to ensure the smoothness of the temperature rise process. After this optimization, the optimization result of the second textile material dyeing process is generated, which provides ideal temperature control parameters for the subsequent fixing stage and ensures the quality and consistency of the entire dyeing process.

[0026] The fixing temperature control optimization module 14 is used to perform temperature control optimization on the optimization result of the second textile material dyeing process based on the preset fixing fastness and preset fixing uniformity to obtain the optimization result of the third textile material dyeing process.

[0027] Specifically, the main task of the fixing temperature control optimization module is to precisely control and optimize the temperature during the fixing stage to ensure that the dye is firmly fixed on the textile material and to ensure the uniformity and durability of the color. The preset fixing fastness refers to the ability of the dye to firmly adhere to the textile material. This index is directly related to the color durability of the dyed textile material during daily use and washing. A higher fixing fastness means that the dye is not easily detached or faded, thus ensuring the durability of the textile product. The preset fixing uniformity refers to the uniformity of the dye fixation on the surface or inside of the material. Uniform fixing can prevent problems such as color inconsistency, such as color spots or color differences, thus ensuring the appearance quality of the final product.

[0028] The optimization result of the second textile material dyeing process is the result obtained after temperature control optimization in the dye uptake stage. Based on the preset color fastness and preset color fastness uniformity, a temperature control model for the fixing stage is constructed. Based on the optimization result of the second textile material dyeing process, by optimizing and adjusting the temperature control parameters in the fixing stage, the fastness and uniformity of the dye on the textile material can be ensured, thereby generating the optimization result of the third textile material dyeing process. This optimization result marks the completion of the entire dyeing process and ensures the high-quality dyeing effect of the final textile product.

[0029] The textile dyeing module 15 is used to dye the textile material based on the optimization result of the third textile material dyeing process.

[0030] Specifically, the core task of the textile dyeing module is to perform the actual textile material dyeing operation based on the previously obtained optimization result of the third textile material dyeing process. This module is responsible for applying all the optimized process parameters to the actual dyeing process, thereby achieving efficient and precise dyeing of the textile material. After each stage of adsorption temperature control optimization, dye uptake temperature control optimization, and fixing temperature control optimization, the optimal dyeing process parameters, that is, the optimization result of the third textile material dyeing process, have been generated. The textile dyeing module takes the optimization result of the third textile material dyeing process as input to ensure that the actual dyeing operation can be carried out strictly according to the optimized parameters to ensure that the dyeing effect meets the expected process standards. Through the precise execution of this module, the dyed textile material will exhibit the characteristics of uniform color and high color fastness, meeting the high-quality dyeing requirements, and ultimately ensuring the efficiency of the entire textile dyeing process and the excellent quality of the product.

[0031] Furthermore, the adsorption temperature control optimization module 12 in the textile material dyeing process optimization device based on intelligent temperature control is also used for:

[0032] Identifying the process in the adsorption stage according to the predetermined textile material dyeing process information to obtain the predetermined adsorption stage process information; disassembling the predetermined adsorption stage process information to obtain the predetermined temperature control information in the adsorption stage and the predetermined auxiliary control information in the adsorption stage; obtaining the predicted dye adsorption uniformity and the predicted dye adsorption depth based on the predetermined temperature control information in the adsorption stage and the predetermined auxiliary control information in the adsorption stage; judging whether the predicted dye adsorption uniformity is less than the preset dye adsorption uniformity and judging whether the predicted dye adsorption depth is less than the preset dye adsorption depth; if the predicted dye adsorption uniformity is less than the preset dye adsorption uniformity and / or the predicted dye adsorption depth is less than the preset dye adsorption depth, performing temperature control optimization according to the predetermined auxiliary control information in the adsorption stage to obtain the temperature control optimization result in the adsorption stage; optimizing the predetermined textile material dyeing process information according to the temperature control optimization result in the adsorption stage to generate the optimization result of the first textile material dyeing process.

[0033] Further, the adsorption temperature control optimization module 12 in the textile material dyeing process optimization device based on intelligent temperature control is further configured to:

[0034] Activate the adsorption feature prediction dual channels, where the adsorption feature prediction dual channels include an adsorption uniformity prediction channel and an adsorption depth prediction channel; based on the predetermined temperature control information in the adsorption stage and the predetermined auxiliary control information in the adsorption stage, generate the predicted dye adsorption uniformity according to the adsorption uniformity prediction channel; based on the predetermined temperature control information in the adsorption stage and the predetermined auxiliary control information in the adsorption stage, generate the predicted dye adsorption depth according to the adsorption depth prediction channel.

[0035] Further, the adsorption temperature control optimization module 12 in the textile material dyeing process optimization device based on intelligent temperature control is further configured to:

[0036] Retrieve the temperature control records according to the predetermined auxiliary control information in the adsorption stage to obtain the adsorption stage temperature control record library; sort out the adsorption stage temperature control record library to establish the adsorption stage temperature control adjustment space; generate the first adsorption stage temperature control adjustment decision based on the adsorption stage temperature control adjustment space; obtain the first updated predicted dye adsorption uniformity and the first updated predicted dye adsorption depth based on the first adsorption stage temperature control adjustment decision and the predetermined auxiliary control information in the adsorption stage; if the first updated predicted dye adsorption uniformity is greater than or equal to the preset dye adsorption uniformity, and the first updated predicted dye adsorption depth is greater than or equal to the preset dye adsorption depth, add the first adsorption stage temperature control adjustment decision to the adsorption stage temperature control optimization result.

[0037] Specifically, in the adsorption stage of the textile material dyeing process, it is first necessary to identify the adsorption stage process based on the predetermined textile material dyeing process information. This step is to determine the specific process requirements in the adsorption stage during the dyeing process and generate the predetermined adsorption stage process information. After the process identification, disassemble the predetermined adsorption stage process information and subdivide it into the predetermined temperature control information in the adsorption stage and the predetermined auxiliary control information in the adsorption stage. The predetermined temperature control information in the adsorption stage is the specific parameters related to temperature control, while the predetermined auxiliary control information in the adsorption stage is other control parameters of the adsorption stage process except for the temperature control parameters, such as dye concentration, stirring speed, addition rate of the dye bath solution, etc. Next, based on the disassembled predetermined temperature control information in the adsorption stage and the predetermined auxiliary control information in the adsorption stage, calculate and obtain the predicted dye adsorption uniformity and the predicted dye adsorption depth.

[0038] Specifically, based on the predetermined temperature control information and the predetermined auxiliary control information in the adsorption stage, the specific acquisition steps for obtaining the predicted dye adsorption uniformity and the predicted dye adsorption depth include: First, it is necessary to activate the dual channels for predicting adsorption characteristics. The dual channels for predicting adsorption characteristics include the adsorption uniformity prediction channel and the adsorption depth prediction channel. These two channels are respectively responsible for predicting the distribution uniformity and the penetration depth of the dye on the textile material.

[0039] The adsorption uniformity prediction channel is used to predict the uniform distribution of the dye on the surface or inside of the textile material based on the predetermined temperature control information and the predetermined auxiliary control information in the adsorption stage, and generate the predicted dye adsorption uniformity. This predicted value will be used to determine whether the quality of the dyeing meets the expectations. Similarly, the adsorption depth prediction channel is responsible for predicting the penetration depth of the dye in the textile material. Similarly, the predetermined temperature control information and the predetermined auxiliary control information in the adsorption stage will be used for depth prediction to generate the predicted dye adsorption depth. Through the collaborative work of these two channels, the dyeing effect in the adsorption stage can be comprehensively evaluated, ensuring that every detail of the dyeing process is precisely controlled, thereby optimizing the final dyeing quality.

[0040] Among them, the adsorption uniformity prediction channel and the adsorption depth prediction channel are obtained by training based on existing machine learning models with a large amount of historical dyeing data. Exemplarily, a large amount of dyeing process data is collected, and these data include the actual dye adsorption uniformity and adsorption depth results under various temperature control and auxiliary control conditions. The machine learning model (such as a neural network model) is trained using the supervised learning method based on the dyeing process data, and the accuracy of the model is verified through cross-validation and the test data set. When necessary, the model parameters are optimized to improve the prediction accuracy. The adsorption uniformity prediction channel and the adsorption depth prediction channel are obtained through training in this way, which is a commonly used technical means for those skilled in the art.

[0041] Subsequently, it is judged whether the predicted dye adsorption uniformity is lower than the preset dye adsorption uniformity, and it is judged whether the predicted dye adsorption depth is lower than the preset dye adsorption depth. If any of these two predicted values is lower than the preset standard, it indicates that the adsorption process may not meet the expected effect. That is to say, if the predicted dye adsorption uniformity is less than the preset dye adsorption uniformity and / or the predicted dye adsorption depth is less than the preset dye adsorption depth, temperature control optimization is carried out according to the predetermined auxiliary control information in the adsorption stage, that is, the temperature control parameters are further optimized and adjusted. The optimized temperature control parameters will be used to update the predetermined textile material dyeing process information, thereby generating the first optimized result of the textile material dyeing process, which is used to guide the subsequent dyeing stage to ensure that the entire dyeing process meets the expected quality standard.

[0042] Among them, if the predicted dye adsorption uniformity is less than the preset dye adsorption uniformity and / or the predicted dye adsorption depth is less than the preset dye adsorption depth, the specific steps of performing temperature control optimization according to the predetermined auxiliary control information in the adsorption stage to obtain the temperature control optimization result in the adsorption stage are as follows: Retrieve the temperature control records according to the predetermined auxiliary control information in the adsorption stage, that is, extract the temperature control records similar to the current process conditions from the historical data to form a temperature control record library for the adsorption stage. The temperature control record library for the adsorption stage contains the temperature control data records under similar conditions in the past. Next, organize the temperature control record library for the adsorption stage and extract the range where the temperature control parameters are located as the temperature control adjustment space in the adsorption stage.

[0043] Furthermore, within the temperature control adjustment space in the adsorption stage, adjust the temperature control parameters to generate the first temperature control adjustment decision for the adsorption stage. Then, input the first temperature control adjustment decision for the adsorption stage combined with the predetermined auxiliary control information in the adsorption stage into the dual-channel prediction of adsorption characteristics to analyze and obtain the first updated predicted dye adsorption uniformity and the first updated predicted dye adsorption depth. If the first updated predicted dye adsorption uniformity reaches or exceeds the preset dye adsorption uniformity, and the first updated predicted dye adsorption depth reaches or exceeds the preset dye adsorption depth, it indicates that this temperature control adjustment decision is effective. At this time, add this decision to the temperature control optimization result in the adsorption stage to provide guidance for the actual dyeing operation. If the first updated predicted dye adsorption uniformity still does not reach the preset dye adsorption uniformity, or the first updated predicted dye adsorption depth does not reach the preset dye adsorption depth, continue to adjust the temperature control parameters within the temperature control adjustment space in the adsorption stage, and input them into the dual-channel prediction of adsorption characteristics combined with the predetermined auxiliary control information in the adsorption stage for iterative analysis until the updated predicted dye adsorption uniformity and the updated predicted dye adsorption depth after adjustment both meet the requirements. Thus, the uniformity and depth of dye adsorption are maximally improved, thereby ensuring the stability and consistency of the dyeing quality.

[0044] Furthermore, the dyeing temperature optimization module 13 in the textile material dyeing process optimization device based on intelligent temperature control is further used for:

[0045] Based on the optimization results of the first textile material dyeing process, identify the process information in the dyeing stage to obtain the predetermined dyeing stage process information; simulate according to the predetermined dyeing stage process information to establish a temperature rise simulation curve in the dyeing stage; evaluate the smoothness of the temperature rise in the dyeing stage according to the temperature rise simulation curve in the dyeing stage to obtain a predicted temperature rise smoothness coefficient; determine whether the predicted temperature rise smoothness coefficient is less than the preset temperature rise smoothness coefficient; if the predicted temperature rise smoothness coefficient is less than the preset temperature rise smoothness coefficient, extract the predetermined auxiliary control information in the dyeing stage according to the predetermined dyeing stage process information; retrieve and sort out the temperature control records according to the predetermined auxiliary control information in the dyeing stage to construct a temperature control adjustment space in the dyeing stage; based on the preset temperature rise smoothness coefficient, perform temperature control optimization in the temperature control adjustment space in the dyeing stage to obtain the temperature control optimization result in the dyeing stage; based on the temperature control optimization result in the dyeing stage, optimize the optimization result of the first textile material dyeing process to generate the optimization result of the second textile material dyeing process.

[0046] Specifically, in the dyeing stage of textile materials, identify the process parameters corresponding to the dyeing stage according to the optimization results of the first textile material dyeing process, and use this as the predetermined dyeing stage process information. The predetermined dyeing stage process information includes key parameters and steps in the dyeing process, such as dye concentration, heating rate, and time control. Next, simulate based on the predetermined dyeing stage process information and establish a temperature rise simulation curve in the dyeing stage. The temperature rise simulation curve in the dyeing stage depicts the trend of temperature change over time during the dyeing process.

[0047] Among them, the specific steps to establish the temperature rise simulation curve in the dyeing stage include: extract historical dyeing parameter records based on the predetermined dyeing stage process information, including the type, concentration, initial temperature, target temperature, heating rate, time node, etc. of the dye, so as to use existing mathematical models or machine learning models to simulate the heating process and generate a heating simulation model. Then, use the predetermined dyeing stage process information as input parameters and import them into the heating simulation model to simulate the temperature change situation in the dyeing stage, and establish a temperature rise simulation curve in the dyeing stage with time as the horizontal axis and temperature as the vertical axis. This curve describes the trend of temperature change over time during the entire dyeing process.

[0048] Then, the leveling property evaluation of the temperature rise during the dyeing stage is carried out according to the simulated temperature rise curve in the dyeing stage, and the predicted leveling coefficient of the temperature rise during dyeing is obtained therefrom. The predicted leveling coefficient of the temperature rise during dyeing is an important index to measure the leveling property during the temperature rise process, which determines whether the dye can uniformly penetrate and adhere to the textile material. If the temperature rises too fast or too slow, the quality of dyeing will be affected. Specifically, the temperature change rate within each time interval can be calculated based on the simulated temperature rise curve in the dyeing stage, and finally the standard deviation of the temperature change rate is calculated, and the obtained result is used as the predicted leveling coefficient of the temperature rise during dyeing. The system then judges whether the predicted leveling coefficient of the temperature rise during dyeing is lower than the preset leveling coefficient of the temperature rise during dyeing. The preset leveling coefficient of the temperature rise during dyeing is set by professionals in the field in combination with actual needs. If the predicted leveling coefficient of the temperature rise during dyeing is lower than the preset leveling coefficient of the temperature rise during dyeing, it indicates that the temperature rise process may be unsteady and further optimization is required. For this purpose, the predetermined auxiliary control information in the dyeing stage is extracted according to the predetermined dyeing stage process information. The predetermined auxiliary control information in the dyeing stage usually includes auxiliary control parameters other than the temperature control parameters, such as the power adjustment of the heater, the stirring speed of the dye liquor, etc. These information will be used as the basis for further optimizing the temperature control strategy. The temperature control records are retrieved and sorted according to the predetermined auxiliary control information in the dyeing stage, and the temperature control records similar to the current process conditions are extracted from the historical data to construct the temperature control range as the temperature control adjustment space in the dyeing stage.

[0049] Furthermore, based on the preset leveling coefficient of the temperature rise during dyeing, the temperature control optimization in the dyeing stage is carried out for the temperature control adjustment space in the dyeing stage, that is, the temperature control parameters in the dyeing stage are adjusted with the temperature control adjustment space in the dyeing stage as the constraint, and the predicted leveling coefficient of the temperature rise during dyeing is calculated again after the adjustment until the predicted leveling coefficient of the temperature rise during dyeing after the iterative adjustment reaches or exceeds the preset leveling coefficient of the temperature rise during dyeing, and the temperature control parameters at this time are used as the result of the temperature control optimization in the dyeing stage. Finally, based on the result of the temperature control optimization in the dyeing stage, the optimization result of the dyeing process of the first textile material is further updated to generate the optimization result of the dyeing process of the second textile material, providing ideal temperature control conditions for the subsequent fixing stage to ensure the smoothness and high efficiency of the entire dyeing process.

[0050] Furthermore, the fixing temperature control optimization module 14 in the textile material dyeing process optimization device based on intelligent temperature control is further used for:

[0051] Identify the process in the color fixation stage based on the optimization result of the second textile material dyeing process to obtain the predetermined process information for the color fixation stage; based on the predetermined process information for the color fixation stage, use the color fixation stage feature prediction model to obtain the predicted color fastness and the predicted color fixation uniformity; determine whether the predicted color fastness is less than the preset color fastness and determine whether the predicted color fixation uniformity is less than the preset color fixation uniformity; if the predicted color fastness is less than the preset color fastness and / or the predicted color fixation uniformity is less than the preset color fixation uniformity, perform temperature control optimization based on the predetermined process information for the color fixation stage to obtain the temperature control optimization result for the color fixation stage; according to the temperature control optimization result for the color fixation stage, optimize the optimization result of the second textile material dyeing process to generate the optimization result of the third textile material dyeing process.

[0052] Furthermore, the color fixation temperature control optimization module 14 in the textile material dyeing process optimization device based on intelligent temperature control is further configured to:

[0053] Extract the predetermined auxiliary control information for the color fixation stage according to the predetermined process information for the color fixation stage; perform temperature control record retrieval according to the predetermined auxiliary control information for the color fixation stage to obtain the temperature control record library for the color fixation stage; sort out the temperature control record library for the color fixation stage to establish the temperature control adjustment space for the color fixation stage; based on the temperature control adjustment space for the color fixation stage, generate the first temperature control adjustment decision for the color fixation stage; based on the first temperature control adjustment decision for the color fixation stage and the predetermined auxiliary control information for the color fixation stage, use the color fixation stage feature prediction model to obtain the first updated predicted color fastness and the first updated predicted color fixation uniformity; if the first updated predicted color fastness is greater than or equal to the preset color fastness and, the first updated predicted color fixation uniformity is greater than or equal to the preset color fixation uniformity, add the first temperature control adjustment decision for the color fixation stage to the temperature control optimization result for the color fixation stage.

[0054] Specifically, extract the process parameters corresponding to the color fixation stage according to the optimization result of the second textile material dyeing process, and use this as the predetermined process information for the color fixation stage. The predetermined process information for the color fixation stage includes the key parameters and operation steps that must be followed during the color fixation process, such as the color fixation temperature, duration, pressure conditions, etc. These factors directly affect the fixation effect of the dye on the material. Next, based on the predetermined process information for the color fixation stage, apply the color fixation stage feature prediction model to generate the predicted color fastness and the predicted color fixation uniformity. Color fastness is an evaluation of the durability of the dye fixation on the textile material, which is crucial for maintaining the color of the material during use and washing. The color fixation uniformity measures the degree of uniformity of the dye fixation on the material, ensuring the color consistency and aesthetics of the final product.

[0055] Among them, the input of the color fixation stage feature prediction model is the color fixation stage process information, and the output is the corresponding color fastness and color fixation uniformity. Specifically, it can be constructed by collecting a large amount of historical color fixation process information and the corresponding actual color fastness and actual color fixation uniformity, and training existing machine learning models, such as neural network models. This is a common technical means for those skilled in the art and will not be elaborated here.

[0056] Then, it is judged whether the predicted color fastness is lower than the preset color fastness, and whether the predicted color fixation uniformity is lower than the preset color fixation uniformity. The preset color fastness and preset color fixation uniformity are the desired color fastness and color fixation uniformity, that is, the preset color fixation standard, which is set by professional technical personnel in the field in combination with actual needs. If any of the predicted results is lower than the preset color fixation standard, it means that the current color fixation process may not be sufficient to achieve the ideal effect, which may lead to phenomena such as dye shedding or uneven color.

[0057] In other words, if the predicted color fastness is less than the preset color fastness and / or the predicted color fixation uniformity is less than the preset color fixation uniformity, temperature control optimization is performed according to the predetermined color fixation stage process information, that is, the temperature control strategy in the color fixation stage is adjusted and optimized to ensure that the dye can be more firmly fixed on the textile material and ensure the uniform distribution of color, and a temperature control strategy with a color fastness reaching or exceeding the preset color fastness and a color fixation uniformity reaching or exceeding the preset color fixation uniformity is generated as the result of temperature control optimization in the color fixation stage, thereby improving the quality of the color fixation process.

[0058] Finally, the result of temperature control optimization in the color fixation stage is used to update the optimization result of the second textile material dyeing process, generating the optimization result of the third textile material dyeing process, ensuring the efficiency and reliability of the color fixation process, enabling the textile material to meet the expected quality standards in terms of color fastness and uniformity, and thus ensuring the quality of the final product.

[0059] Among them, if the predicted color fastness is less than the preset color fastness and / or the predicted color fastness uniformity is less than the preset color fastness uniformity, the steps of performing temperature control optimization according to the process information of the predetermined color fixing stage to obtain the temperature control optimization result in the color fixing stage include: in the color fixing stage of textile material dyeing, extracting the predetermined auxiliary control information in the color fixing stage according to the process information of the predetermined color fixing stage. The predetermined auxiliary control information in the color fixing stage includes auxiliary control parameters other than the temperature control parameters during the color fixing process, such as heating rate, pressure adjustment, cooling rate, etc. Then, perform temperature control record retrieval according to the predetermined auxiliary control information in the color fixing stage, extract temperature control records similar to the current process conditions from historical data, and construct a temperature control record library for the color fixing stage. The temperature control record library for the color fixing stage collects temperature control data under similar conditions in the past, providing a reference basis for further process optimization. Subsequently, organize the temperature control record library for the color fixing stage to obtain the temperature control parameter range in the color fixing stage as the temperature control adjustment space in the color fixing stage.

[0060] Within the temperature control adjustment space range in the color fixing stage, randomly generate temperature control parameters to obtain the first temperature control adjustment decision in the color fixing stage. Then, combine the first temperature control adjustment decision in the color fixing stage with the predetermined auxiliary control information in the color fixing stage and input it into the color fixing stage characteristic prediction model for analysis to generate the first updated predicted color fastness and the first updated predicted color fastness uniformity. The first updated predicted color fastness and the first updated predicted color fastness uniformity reflect the color fixing effect after applying the new temperature control strategy.

[0061] If the first updated predicted color fastness reaches or exceeds the preset color fastness and the first updated predicted color fastness uniformity reaches or exceeds the preset color fastness uniformity, it indicates that the temperature control adjustment decision is successful. In this case, add the first temperature control adjustment decision in the color fixing stage to the temperature control optimization result in the color fixing stage as the final temperature control strategy to ensure that the color fixing process achieves the expected effect, thereby ensuring the fastness and uniformity of the dye and improving the dyeing quality of textile materials.

[0062] In summary, the textile material dyeing process optimization device based on intelligent temperature control provided by the present application has the following technical effects:

[0063] A textile dyeing task receiving module, which is used to receive textile dyeing tasks. Among them, the textile dyeing task includes predetermined textile material dyeing process information; an adsorption temperature control optimization module, which is used to perform temperature control optimization in the adsorption stage on the predetermined textile material dyeing process information based on a preset dye adsorption uniformity and a preset dye adsorption depth to obtain a first optimized result of the textile material dyeing process; a dyeing temperature control optimization module, which is used to perform temperature control optimization in the dyeing stage on the first optimized result of the textile material dyeing process based on a preset dyeing temperature rise stability coefficient to obtain a second optimized result of the textile material dyeing process; a color fixation temperature control optimization module, which is used to perform temperature control optimization in the color fixation stage on the second optimized result of the textile material dyeing process based on a preset color fastness and a preset color fixation uniformity to obtain a third optimized result of the textile material dyeing process; a textile dyeing module, which is used to dye textile materials based on the third optimized result of the textile material dyeing process. By performing temperature control optimization on the adsorption stage, dyeing stage, and color fixation stage of the dye, and combining an intelligent prediction model, the temperature control parameters of each stage are optimized and adjusted, achieving the technical effect of improving the stability and consistency of the dyeing process, and further enhancing the color quality of the final textile products.

[0064] Embodiment 2. Based on the textile material dyeing process optimization device based on intelligent temperature control in the foregoing embodiment and with the same inventive concept, the present application also provides a textile material dyeing process optimization method based on intelligent temperature control. Please refer to the appendix Figure 2 , the textile material dyeing process optimization method based on intelligent temperature control includes:

[0065] Receive a textile dyeing task, where the textile dyeing task includes predetermined textile material dyeing process information.

[0066] Perform temperature control optimization in the adsorption stage on the predetermined textile material dyeing process information based on a preset dye adsorption uniformity and a preset dye adsorption depth to obtain a first optimized result of the textile material dyeing process.

[0067] Perform temperature control optimization in the dyeing stage on the first optimized result of the textile material dyeing process based on a preset dyeing temperature rise stability coefficient to obtain a second optimized result of the textile material dyeing process.

[0068] Perform temperature control optimization in the color fixation stage on the second optimized result of the textile material dyeing process based on a preset color fastness and a preset color fixation uniformity to obtain a third optimized result of the textile material dyeing process.

[0069] Dye textile materials based on the third optimized result of the textile material dyeing process.

[0070] Further, the adsorption temperature control optimization module is used to optimize the temperature control in the adsorption stage for the predetermined textile material dyeing process information based on a preset dye adsorption uniformity and a preset dye adsorption depth, and obtain an optimized result of the first textile material dyeing process, including:

[0071] Identify the process in the adsorption stage according to the predetermined textile material dyeing process information to obtain the predetermined adsorption stage process information; disassemble the predetermined adsorption stage process information to obtain the predetermined temperature control information and the predetermined auxiliary control information in the adsorption stage; based on the predetermined temperature control information and the predetermined auxiliary control information in the adsorption stage, obtain the predicted dye adsorption uniformity and the predicted dye adsorption depth; determine whether the predicted dye adsorption uniformity is less than the preset dye adsorption uniformity and determine whether the predicted dye adsorption depth is less than the preset dye adsorption depth; if the predicted dye adsorption uniformity is less than the preset dye adsorption uniformity and / or the predicted dye adsorption depth is less than the preset dye adsorption depth, perform temperature control optimization according to the predetermined auxiliary control information in the adsorption stage to obtain the temperature control optimization result in the adsorption stage; optimize the predetermined textile material dyeing process information according to the temperature control optimization result in the adsorption stage to generate the optimized result of the first textile material dyeing process.

[0072] Further, obtaining the predicted dye adsorption uniformity and the predicted dye adsorption depth based on the predetermined temperature control information and the predetermined auxiliary control information in the adsorption stage includes:

[0073] Activate the dual channels for predicting adsorption characteristics, where the dual channels for predicting adsorption characteristics include an adsorption uniformity prediction channel and an adsorption depth prediction channel; based on the predetermined temperature control information and the predetermined auxiliary control information in the adsorption stage, generate the predicted dye adsorption uniformity according to the adsorption uniformity prediction channel; based on the predetermined temperature control information and the predetermined auxiliary control information in the adsorption stage, generate the predicted dye adsorption depth according to the adsorption depth prediction channel.

[0074] Further, if the predicted dye adsorption uniformity is less than the preset dye adsorption uniformity and / or the predicted dye adsorption depth is less than the preset dye adsorption depth, performing temperature control optimization according to the predetermined auxiliary control information in the adsorption stage to obtain the temperature control optimization result in the adsorption stage includes:

[0075] Retrieve the temperature control records for the adsorption stage according to the predetermined auxiliary control information for the adsorption stage to obtain the temperature control record library for the adsorption stage; organize the temperature control record library for the adsorption stage to establish the temperature control adjustment space for the adsorption stage; generate the first temperature control adjustment decision based on the temperature control adjustment space for the adsorption stage; obtain the first updated predicted dye adsorption uniformity and the first updated predicted dye adsorption depth based on the first temperature control adjustment decision and the predetermined auxiliary control information for the adsorption stage; if the first updated predicted dye adsorption uniformity is greater than or equal to the preset dye adsorption uniformity, and the first updated predicted dye adsorption depth is greater than or equal to the preset dye adsorption depth, add the first temperature control adjustment decision to the temperature control optimization result for the adsorption stage.

[0076] Furthermore, the dyeing temperature control optimization module is used to optimize the temperature control for the dyeing stage of the optimized result of the first textile material dyeing process based on the preset smooth rising coefficient of the dyeing temperature, to obtain the optimized result of the second textile material dyeing process, including:

[0077] Identify the dyeing stage process according to the optimized result of the first textile material dyeing process to obtain the predetermined process information for the dyeing stage; simulate according to the predetermined process information for the dyeing stage to establish the simulated temperature rising curve for the dyeing stage; evaluate the smoothness of the temperature rising for the dyeing stage according to the simulated temperature rising curve for the dyeing stage to obtain the predicted smooth rising coefficient of the dyeing temperature; determine whether the predicted smooth rising coefficient of the dyeing temperature is less than the preset smooth rising coefficient of the dyeing temperature; if the predicted smooth rising coefficient of the dyeing temperature is less than the preset smooth rising coefficient of the dyeing temperature, extract the predetermined auxiliary control information for the dyeing stage according to the predetermined process information for the dyeing stage; retrieve and organize the temperature control records according to the predetermined auxiliary control information for the dyeing stage to construct the temperature control adjustment space for the dyeing stage; perform temperature control optimization for the dyeing stage on the temperature control adjustment space for the dyeing stage based on the preset smooth rising coefficient of the dyeing temperature to obtain the temperature control optimization result for the dyeing stage; optimize the optimized result of the first textile material dyeing process based on the temperature control optimization result for the dyeing stage to generate the optimized result of the second textile material dyeing process.

[0078] Furthermore, the color fixation temperature control optimization module is used to optimize the temperature control for the color fixation stage of the optimized result of the second textile material dyeing process based on the preset color fastness and the preset color fixation uniformity, to obtain the optimized result of the third textile material dyeing process, including:

[0079] Identify the process in the color fixation stage based on the optimization result of the second textile material dyeing process to obtain the predetermined process information for the color fixation stage; based on the predetermined process information for the color fixation stage, obtain the predicted color fastness and the predicted color uniformity according to the color fixation stage feature prediction model; determine whether the predicted color fastness is less than the preset color fastness and determine whether the predicted color uniformity is less than the preset color uniformity; if the predicted color fastness is less than the preset color fastness and / or the predicted color uniformity is less than the preset color uniformity, perform temperature control optimization according to the predetermined process information for the color fixation stage to obtain the temperature control optimization result for the color fixation stage; according to the temperature control optimization result for the color fixation stage, optimize the optimization result of the second textile material dyeing process to generate the optimization result of the third textile material dyeing process.

[0080] Further, if the predicted color fastness is less than the preset color fastness and / or the predicted color uniformity is less than the preset color uniformity, performing temperature control optimization according to the predetermined process information for the color fixation stage to obtain the temperature control optimization result for the color fixation stage includes:

[0081] Extract the predetermined auxiliary control information for the color fixation stage according to the predetermined process information for the color fixation stage; perform temperature control record retrieval according to the predetermined auxiliary control information for the color fixation stage to obtain the temperature control record library for the color fixation stage; organize the temperature control record library for the color fixation stage to establish the temperature control adjustment space for the color fixation stage; generate the first temperature control adjustment decision based on the temperature control adjustment space for the color fixation stage; based on the first temperature control adjustment decision and the predetermined auxiliary control information for the color fixation stage, obtain the first updated predicted color fastness and the first updated predicted color uniformity according to the color fixation stage feature prediction model; if the first updated predicted color fastness is greater than or equal to the preset color fastness and the first updated predicted color uniformity is greater than or equal to the preset color uniformity, add the first temperature control adjustment decision to the temperature control optimization result for the color fixation stage.

[0082] The various embodiments in this specification are described in a progressive manner, and the key point of each embodiment is the difference from other embodiments. The Figure 1 Based on the intelligent temperature control textile material dyeing process optimization device and specific examples in the first embodiment are equally applicable to the intelligent temperature control textile material dyeing process optimization method in this embodiment. Through the detailed description of the intelligent temperature control textile material dyeing process optimization device above, those skilled in the art can clearly know the intelligent temperature control textile material dyeing process optimization method in this embodiment. Therefore, for the sake of brevity of the specification, it will not be described in detail here. For the method disclosed in the embodiment, since it corresponds to the device disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method part.

[0083] The foregoing description of the disclosed embodiments enables those skilled in the art to practice or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0084] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is also intended to include these changes and modifications.

Claims

1. A textile material dyeing process optimization device based on intelligent temperature control, characterized in that: include: A textile dyeing task receiving module, the textile dyeing task receiving module is used to receive a textile dyeing task, wherein the textile dyeing task includes predetermined textile material dyeing process information; An adsorption temperature control optimization module, the adsorption temperature control optimization module is used to optimize the temperature control of the predetermined textile material dyeing process information in the adsorption phase based on a preset dye adsorption uniformity and a preset dye adsorption depth, and obtain a first textile material dyeing process optimization result; A dyeing temperature control optimization module, which is used to optimize the temperature control of the dyeing process optimization result of the first textile material based on a preset dyeing temperature rise stability coefficient to obtain a second textile material dyeing process optimization result; A color fixing temperature control optimization module, wherein the color fixing temperature control optimization module is used to optimize the temperature control in the color fixing stage of the second textile material dyeing process optimization result based on a preset color fixing fastness and a preset color fixing uniformity, so as to obtain a third textile material dyeing process optimization result; A textile dyeing module, wherein the textile dyeing module is used to dye the textile material based on the third textile material dyeing process optimization result; The adsorption temperature control optimization module is used to optimize the temperature control of the predetermined textile material dyeing process information in the adsorption phase based on the preset dye adsorption uniformity and the preset dye adsorption depth, and obtain the first textile material dyeing process optimization result, including: Performing adsorption stage process identification according to the predetermined textile material dyeing process information to obtain predetermined adsorption stage process information; Disassembling the predetermined adsorption stage process information to obtain predetermined temperature control information and predetermined auxiliary control information of the adsorption stage; Based on the predetermined temperature control information of the adsorption stage and the predetermined auxiliary control information of the adsorption stage, a predicted dye adsorption uniformity and a predicted dye adsorption depth are obtained; Determining whether the predicted dye adsorption uniformity is less than the preset dye adsorption uniformity, and determining whether the predicted dye adsorption depth is less than the preset dye adsorption depth; If the predicted dye adsorption uniformity is less than the preset dye adsorption uniformity and / or the predicted dye adsorption depth is less than the preset dye adsorption depth, temperature control optimization is performed according to the predetermined auxiliary control information of the adsorption stage to obtain the temperature control optimization result of the adsorption stage; According to the temperature control optimization result of the adsorption stage, the predetermined textile material dyeing process information is optimized to generate the first textile material dyeing process optimization result.

2. The textile material dyeing process optimization device based on intelligent temperature control according to claim 1, characterized in that: Based on the predetermined temperature control information of the adsorption stage and the predetermined auxiliary control information of the adsorption stage, the predicted dye adsorption uniformity and the predicted dye adsorption depth are obtained, including: Activating an adsorption characteristic prediction dual channel, wherein the adsorption characteristic prediction dual channel includes an adsorption uniformity prediction channel and an adsorption depth prediction channel; Based on the predetermined temperature control information of the adsorption stage and the predetermined auxiliary control information of the adsorption stage, and according to the adsorption uniformity prediction channel, the predicted dye adsorption uniformity is generated; Based on the predetermined temperature control information of the adsorption stage and the predetermined auxiliary control information of the adsorption stage, the predicted dye adsorption depth is generated according to the adsorption depth prediction channel.

3. The textile material dyeing process optimization device based on intelligent temperature control according to claim 1, characterized in that: If the predicted dye adsorption uniformity is less than the preset dye adsorption uniformity and / or the predicted dye adsorption depth is less than the preset dye adsorption depth, temperature control optimization is performed according to the predetermined auxiliary control information of the adsorption stage to obtain the temperature control optimization result of the adsorption stage, including: Perform temperature control record retrieval according to the predetermined auxiliary control information of the adsorption stage to obtain a temperature control record library of the adsorption stage; Arrange the temperature control record library of the adsorption stage and establish the temperature control adjustment space of the adsorption stage; Based on the temperature control adjustment space in the adsorption stage, generating a temperature control adjustment decision for the first adsorption stage; Based on the temperature control adjustment decision of the first adsorption stage and the predetermined auxiliary control information of the adsorption stage, obtaining a first updated predicted dye adsorption uniformity and a first updated predicted dye adsorption depth; If the first updated predicted dye adsorption uniformity is greater than / equal to the preset dye adsorption uniformity, and the first updated predicted dye adsorption depth is greater than / equal to the preset dye adsorption depth, the first adsorption stage temperature control adjustment decision is added to the adsorption stage temperature control optimization result.

4. The textile material dyeing process optimization device based on intelligent temperature control according to claim 1, characterized in that: The dyeing temperature control optimization module is used to optimize the temperature control of the dyeing process optimization result of the first textile material based on the preset dyeing temperature rise stability coefficient to obtain the dyeing process optimization result of the second textile material, including: Perform dyeing stage process identification according to the first textile material dyeing process optimization result to obtain predetermined dyeing stage process information; Perform simulation according to the predetermined dyeing stage process information to establish a dyeing stage temperature rise simulation curve; The temperature rise stability of dyeing is evaluated according to the temperature rise simulation curve of the dyeing stage, and a predicted temperature rise stability coefficient of dyeing is obtained; Determining whether the predicted dyeing temperature rise stability coefficient is less than the preset dyeing temperature rise stability coefficient; If the predicted dyeing temperature rise stability coefficient is less than the preset dyeing temperature rise stability coefficient, extracting the predetermined auxiliary control information of the dyeing stage according to the predetermined dyeing stage process information; Retrieve and organize temperature control records according to the predetermined auxiliary control information of the dyeing stage, and construct a temperature control adjustment space for the dyeing stage; Based on the preset dyeing temperature rise stability coefficient, the temperature control adjustment space of the dyeing stage is optimized for the temperature control of the dyeing stage to obtain the temperature control optimization result of the dyeing stage; Based on the temperature control optimization result of the dyeing stage, the optimization result of the dyeing process of the first textile material is optimized, and the optimization result of the dyeing process of the second textile material is generated.

5. The textile material dyeing process optimization device based on intelligent temperature control according to claim 1, characterized in that: The color fixing temperature control optimization module is used to optimize the temperature control in the color fixing stage of the second textile material dyeing process optimization result based on the preset color fixing fastness and the preset color fixing uniformity, and obtain the third textile material dyeing process optimization result, including: Performing fixation stage process identification according to the second textile material dyeing process optimization result to obtain predetermined fixation stage process information; Based on the predetermined color fixing stage process information, and according to the color fixing stage characteristic prediction model, the predicted color fastness and the predicted color fixing uniformity are obtained; Determining whether the predicted color fastness is less than the preset color fastness, and determining whether the predicted color fastness uniformity is less than the preset color fastness uniformity; If the predicted color fastness is less than the preset color fastness and / or the predicted color uniformity is less than the preset color uniformity, temperature control optimization is performed according to the predetermined color fixing stage process information to obtain a temperature control optimization result for the color fixing stage; According to the temperature control optimization result in the fixing stage, the second textile material dyeing process optimization result is optimized to generate the third textile material dyeing process optimization result.

6. The textile material dyeing process optimization device based on intelligent temperature control according to claim 5, characterized in that: If the predicted color fastness is less than the preset color fastness and / or the predicted color uniformity is less than the preset color uniformity, temperature control optimization is performed according to the predetermined color fixing stage process information to obtain a temperature control optimization result for the color fixing stage, including: Extracting the predetermined auxiliary control information for the color fixing stage according to the predetermined process information for the color fixing stage; Retrieve temperature control records according to the auxiliary control information scheduled for the color fixing stage to obtain a temperature control record library for the color fixing stage; Arrange the temperature control record library of the color fixing stage and establish the temperature control adjustment space of the color fixing stage; Based on the temperature control adjustment space in the color fixing stage, generating a temperature control adjustment decision for the first color fixing stage; Based on the temperature control adjustment decision of the first color fixing stage and the predetermined auxiliary control information of the color fixing stage, and according to the color fixing stage characteristic prediction model, obtaining a first updated predicted color fastness and a first updated predicted color fixing uniformity; If the first updated predicted color fastness is greater than / equal to the preset color fastness, and the first updated predicted color uniformity is greater than / equal to the preset color uniformity, the first color fixing stage temperature control adjustment decision is added to the color fixing stage temperature control optimization result.

7. A textile material dyeing process optimization method based on intelligent temperature control, characterized in that: The textile material dyeing process optimization device based on intelligent temperature control as described in any one of claims 1 to 6 comprises: Receiving a textile dyeing task, wherein the textile dyeing task includes predetermined textile material dyeing process information; Based on a preset dye adsorption uniformity and a preset dye adsorption depth, the predetermined textile material dyeing process information is subjected to temperature control optimization in the adsorption phase to obtain a first textile material dyeing process optimization result; Based on the preset dyeing temperature rise stability coefficient, the temperature control of the dyeing process optimization result of the first textile material is optimized in the dyeing stage to obtain the dyeing process optimization result of the second textile material; Based on the preset color fastness and the preset color uniformity, the temperature control of the second textile material dyeing process optimization result is optimized in the color fixing stage to obtain the third textile material dyeing process optimization result; Dyeing the textile material based on the third textile material dyeing process optimization result; The method further comprises: optimizing the temperature control of the predetermined textile material dyeing process information at the adsorption stage based on the preset dye adsorption uniformity and the preset dye adsorption depth to obtain a first textile material dyeing process optimization result, including: According to the predetermined textile material dyeing process information, process identification of the adsorption stage is performed to obtain the predetermined adsorption stage process information; the predetermined adsorption stage process information is disassembled to obtain the predetermined temperature control information of the adsorption stage and the predetermined auxiliary control information of the adsorption stage; based on the predetermined temperature control information of the adsorption stage and the predetermined auxiliary control information of the adsorption stage, a predicted dye adsorption uniformity and a predicted dye adsorption depth are obtained; it is determined whether the predicted dye adsorption uniformity is less than the preset dye adsorption uniformity, and it is determined whether the predicted dye adsorption depth is less than the preset dye adsorption depth; if the predicted dye adsorption uniformity is less than the preset dye adsorption uniformity and / or the predicted dye adsorption depth is less than the preset dye adsorption depth, temperature control optimization is performed according to the predetermined auxiliary control information of the adsorption stage to obtain the temperature control optimization result of the adsorption stage; according to the temperature control optimization result of the adsorption stage, the predetermined textile material dyeing process information is optimized to generate the first textile material dyeing process optimization result.

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