Dyeing machine automatic control method and system combined with dyeing residual liquid concentration monitoring

Abstract

The invention provides a dyeing machine automatic control method and system combined with dyeing residual liquid concentration monitoring, and relates to the technical field of automatic control, and the method comprises the steps: obtaining the dyeing residual liquid concentration monitored by a dyeing machine in real time; constructing a residual concentration change curve according to the component concentration difference between the dyeing residual liquid concentration and the input dyeing liquid concentration; according to the sequential relationship of the residual concentration change curve, identifying and controlling a switching node; comparing the component concentration difference of the residual concentration change curve with a target residual liquid concentration range of a control switching node, and compensating the residual concentration difference by using a dyeing control parameter to obtain a compensation control parameter; and dynamically controlling the dyeing machine according to the compensation control parameters. The technical problems that the control strategy is too simple and the optimal dyeing effect cannot be achieved due to the fact that a traditional dyeing machine is generally operated only according to a preset program and is difficult to quickly adjust according to the real-time dye adsorption condition in the dyeing process are solved.

Description

Technical Field

[0001] The invention relates to the technical field of automatic control, and in particular to an automatic control method and system for a dyeing machine combined with dyeing residual liquid concentration monitoring. Background Art

[0002] The dyeing industry is an important part of the textile industry. It involves applying colorants or dyes to textiles to give these materials the desired color. With the development of industrial automation, automatic control systems for dyeing machines have been gradually introduced, aiming to improve production efficiency, reduce energy and material consumption, and ensure the consistency of product quality. However, although modern dyeing machines have a certain degree of automatic control functions, they still have limitations in some key technical areas. Specifically, traditional dyeing control systems are mostly based on preset programs and lack sufficient flexibility to cope with factors such as fluctuations in raw material quality and environmental changes. This may lead to the inability to achieve the optimal dyeing effect and require manual intervention for adjustment. In addition, due to the lack of real-time feedback mechanism and dynamic adjustment capabilities, the control system cannot respond promptly to changes in the actual dyeing process, which leads to inconsistent dyeing quality. Summary of the invention

[0003] The present application provides an automatic control method and system for a dyeing machine combined with monitoring of the concentration of residual dyeing liquid, aiming to solve the technical problem that traditional dyeing machine control usually only operates according to a preset program and is difficult to make rapid adjustments based on the real-time dye adsorption situation during the dyeing process, resulting in a control strategy that is too simple and cannot achieve the optimal dyeing effect.

[0004] The first aspect disclosed in the present application provides an automatic control method for a dyeing machine combined with monitoring of the concentration of dyeing residual liquid, the method comprising: obtaining the concentration of the dyeing residual liquid monitored in real time by the dyeing machine; constructing a residual concentration change curve according to the component concentration difference between the dyeing residual liquid concentration and the input dyeing liquid concentration; identifying a control switching node according to the time series relationship of the residual concentration change curve; comparing the component concentration difference of the residual concentration change curve with the target residual liquid concentration range of the control switching node, compensating for the residual concentration difference using dyeing control parameters, and obtaining compensation control parameters; and dynamically controlling the dyeing machine according to the compensation control parameters.

[0005] The second aspect disclosed in the present application provides an automatic control system for a dyeing machine combined with monitoring of the concentration of dyeing residual liquid. The system is used for the above-mentioned automatic control method for a dyeing machine combined with monitoring of the concentration of dyeing residual liquid, and the system includes: a dyeing residual liquid concentration acquisition module, used to obtain the dyeing residual liquid concentration monitored in real time by the dyeing machine; a concentration change curve construction module, used to construct a residual concentration change curve according to the component concentration difference between the dyeing residual liquid concentration and the input dye liquid concentration; a control switching node identification module, used to identify the control switching node according to the time series relationship of the residual concentration change curve; a residual concentration difference compensation module, used to compare the component concentration difference of the residual concentration change curve with the target residual liquid concentration range of the control switching node, and use the dyeing control parameters to compensate for the residual concentration difference to obtain the compensation control parameters; a dyeing machine dynamic control module, used to dynamically control the dyeing machine according to the compensation control parameters.

[0006] One or more technical solutions provided in this application have at least the following beneficial effects:

[0007] By obtaining the concentration of the residual dyeing liquid monitored in real time by the dyeing machine, basic data support is provided for the entire control process. This real-time monitoring ensures the timeliness and accuracy of the data and provides a real-time, data-driven basis for the decision-making of subsequent steps. According to the concentration difference between the residual dyeing liquid concentration and the input dyeing liquid concentration, a residual concentration change curve is constructed to reflect the deviation between the actual dyeing process and the expected target, so that the process control can be dynamically adjusted according to the actual situation, rather than relying solely on the preset fixed parameters. According to the time series relationship of the residual concentration change curve, the control switching node is identified so that the control strategy can be adjusted at the critical moment. This control node identification method based on time series analysis improves the accuracy and efficiency of control. The residual concentration difference is compensated by using the dyeing control parameters to further refine the control process. The concentration deviation is compensated by adjusting the dyeing control parameters to ensure that the dyeing effect meets the quality standards. The dyeing machine is dynamically controlled according to the compensation control parameters to ensure that the entire dyeing process can flexibly respond to changes according to the adjustment of the compensation control parameters, improve the process's adaptability and overall production efficiency, achieve a higher level of automation and better production efficiency, and also improve product quality and production flexibility.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1A schematic flow chart of a dyeing machine automatic control method combined with dyeing residual liquid concentration monitoring provided in an embodiment of the present application.

[0010] Figure 2 A schematic diagram of the structure of a dyeing machine automatic control system combined with dyeing residual liquid concentration monitoring provided in an embodiment of the present application.

[0011] Explanation of the reference numerals: dyeing residual liquid concentration acquisition module 10, concentration change curve construction module 20, control switching node identification module 30, residual concentration difference compensation module 40, dyeing machine dynamic control module 50. DETAILED DESCRIPTION

[0012] The embodiments of the present application provide a dyeing machine automatic control method and system combined with dye residual liquid concentration monitoring, thereby solving the technical problem that traditional dyeing machine control usually only runs according to a preset program and is difficult to make rapid adjustments based on the real-time dye adsorption situation during the dyeing process, resulting in the control strategy being too simple and unable to achieve the optimal dyeing effect.

[0013] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically introduced below in conjunction with the accompanying drawings of the specification. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0014] Embodiment 1, as Figure 1 As shown, the embodiment of the present application provides a dyeing machine automatic control method combined with dyeing residual liquid concentration monitoring, the method comprising:

[0015] Get the residual dyeing liquid concentration monitored by the dyeing machine in real time.

[0016] The dyeing machine is equipped with a concentration sensor to measure the concentration of dyes or chemical components in the residual dyeing liquid. The sensor can be an electrochemical sensor, an optical sensor (such as an absorbance sensor), etc., which can continuously collect concentration data during the real-time dyeing process. During the dyeing process, the dyeing liquid is constantly circulated and replaced in the machine, so the sensor will monitor the concentration of the liquid in real time. The frequency of data collection matches the dynamic changes of the dyeing process to ensure that the data is timely and accurate, avoid uneven dyeing or waste of resources caused by lags, and obtain the concentration of the residual dyeing liquid through concentration monitoring.

[0017] A residual concentration variation curve is constructed according to the component concentration difference between the dyeing residual solution concentration and the input dyeing solution concentration.

[0018] The input dye concentration refers to the concentration of the dye liquid entering the dyeing machine at the initial stage of dyeing. This concentration is usually set at the start of the dyeing machine or obtained through real-time monitoring, such as real-time monitoring through flow meters and online concentration sensors to ensure that the addition of dyes and auxiliaries meets the requirements.

[0019] During the dyeing process, the dye reacts with the fabric and the dye concentration gradually decreases, while the dye that is not adsorbed or reacted will remain in the liquid. Therefore, there will be a concentration difference between the dyeing residual liquid concentration and the input dyeing liquid concentration, which is called the component concentration difference. The component concentration difference is specifically the input dyeing liquid concentration minus the dyeing residual liquid concentration.

[0020] As the dyeing process proceeds, the dye in the dyeing solution is gradually adsorbed or reacted, and the residual liquid concentration will change over time. Therefore, a residual concentration change curve is constructed in chronological order to describe the trend of dye concentration change over time during the dyeing process. This curve can be constructed based on real-time monitoring data and optimized through fitting methods such as least squares method and curve fitting. The constructed residual concentration change curve can reflect the temporal change characteristics of concentration change, such as change rate, volatility, stability, etc., and provide a basis for subsequent dyeing control.

[0021] According to the time series relationship of the residual concentration variation curve, a control switching node is identified.

[0022] The residual concentration change curve is used to analyze the changes in dye concentration over time, with a focus on analyzing the rate of decrease, stability and fluctuation pattern of the concentration. Significant trend change points in the curve are determined through peak detection and change point analysis. Control switching nodes refer to the points in the dyeing process when a certain concentration value or range is reached based on the concentration change trend, and thus the control parameters need to be adjusted. These nodes may be key turning points such as when the dye is adsorbed to a certain saturation or the dye is exhausted to a certain extent.

[0023] The component concentration difference of the residual concentration variation curve is compared with the target residual liquid concentration range of the control switching node, and the residual concentration difference is compensated by using the dyeing control parameter to obtain the compensation control parameter.

[0024] Compare the actual concentration on the residual concentration change curve with the target concentration range, and calculate the concentration difference that needs to be adjusted. The target concentration range is usually set by the quality control department based on product requirements or historical data. Dyeing control parameters include dye dosage, auxiliary dosage, drainage speed, temperature control, etc. Use optimization algorithms, such as gradient descent and genetic algorithms, to adjust these parameters according to the residual concentration difference and the target concentration range, such as increasing or decreasing the dye dosage, adjusting the heating temperature, changing the drainage speed, etc., to achieve an effect closer to the target concentration, and obtain compensation control parameters through adjustment.

[0025] The dyeing machine is dynamically controlled according to the compensation control parameters.

[0026] The control system uses real-time input of the adjusted compensation control parameters to dynamically control the operation of the dyeing machine to ensure that the dyeing process runs stably in the optimal state. The above steps constitute a comprehensive automatic control framework. From data collection to real-time control, each step is to ensure the efficiency, accuracy and sustainability of the dyeing process. Through this method, the operating efficiency and product quality of the dyeing machine can be improved, while reducing resource waste and environmental impact.

[0027] Further, according to the time sequence relationship of the residual concentration change curve, the control switching node is identified, which includes:

[0028] The concentration variation mechanism of the whole cycle in the dyeing machine treatment process is decomposed to determine the concentration timing characteristics and control parameters of the process cycle; clustering is performed according to the dye liquor adsorption characteristics of different target fabrics; a mapping relationship between various target fabrics and the concentration timing characteristics of the process cycle is established, and a standard concentration node sequence library is constructed; the concentration change gradient of the process cycle node is identified according to the concentration timing characteristics and control parameters of the process cycle to obtain the node change gradient characteristics; and the node change gradient characteristics are fitted into the standard concentration node sequence library according to the relationship between the node change gradient characteristics and the process cycle nodes and the target fabric categories.

[0029] During the whole process from dyeing into dye liquor to final fixation on fabric, the concentration of dye will go through different stages of change, such as rapid adsorption of dye in the early stage, slow adsorption and saturation in the middle stage, and fixation of dye in the later stage. Chemical engineering principles and kinetic models are used to describe these changes. Time series analysis tools such as fast Fourier transform or wavelet transform are used to analyze the variation characteristics of dye concentration over time, identify key concentration variation nodes such as rapid change area, stable area and transition area, and determine the concentration time series characteristics of process cycle. According to the concentration variation characteristics, control parameters are determined, such as dye delivery rate, water flow rate, heating temperature, etc., where the adjustment of parameters is based on achieving the best dyeing effect and resource efficiency.

[0030] Fabric types are classified according to their physical and chemical properties, such as cotton, polyester, silk, etc. These properties affect the adsorption behavior and color fixation of dyes. Specifically, the adsorption performance data of different fabrics under various dyeing conditions are collected, including adsorption rate, color saturation, etc. Cluster analysis methods, such as K-means, are used to group fabrics based on their adsorption performance data in dyeing solutions. In this way, fabrics with similar dyeing characteristics can be classified in order to implement more specialized dyeing control strategies.

[0031] According to the classification results, the dyeing characteristics of different fabrics are associated with specific dyeing process stages and concentration change nodes, and a mapping model from fabric type to concentration change nodes is established. Based on the mapping relationship, a database is constructed, which contains the standard concentration node sequence of each type of fabric under different dyeing conditions. This library can provide a reference point for actual dyeing operations, such as when to adjust the dye concentration and when to add auxiliaries.

[0032] Mathematical tools, such as derivative calculations, are used to perform gradient analysis on concentration time series data to identify key nodes with rapid changes. These nodes usually represent rapid changes in dye adsorption rates, which are related to fabric type, dye type, and their interactions. The gradients of these nodes are determined to obtain node change gradient characteristics, which helps to more accurately control the dyeing process. The relationship between the control parameters and the identified concentration change gradients is analyzed to determine which control parameter adjustments will lead to significant changes in the gradient, thereby providing adjustment strategies for the automatic control system.

[0033] The concentration change gradient characteristics are integrated with the corresponding fabric type and process cycle node information to form a comprehensive data set, which is then fitted into the standard concentration node sequence library. The model and node information in the database are dynamically updated based on the actual dyeing results and new data input. This information will be applied to the real-time control system to automatically adjust the dyeing process to ensure optimal dyeing quality and efficiency.

[0034] Furthermore, according to the time series relationship of the residual concentration change curve, identifying the control switching node includes:

[0035] Acquire a target dyed fabric; use the target dyed fabric as an index to search for the target fabric in the standard concentration node sequence library to obtain a matching process cycle concentration timing feature; use the timing relationship of the residual concentration change curve to match the concentration timing feature of the matching process cycle to match the concentration change feature and determine a processing process cycle node; obtain adjustment parameters, increase parameters, and node change gradient features based on the processing process cycle node; based on the node change gradient features, identify the control intervention node and the corresponding adjustment parameters and increase parameters to obtain the control switching node.

[0036] Determine the target dyeing fabric to be dyed, which can be done in the preparation stage before dyeing, and can be done by barcode scanning, RFID or manual input. The physical and chemical properties of the fabric are recorded in the product specifications or batch information. Using the target dyeing fabric as an index, search in the established standard concentration node sequence library to obtain the matching process cycle concentration timing characteristics.

[0037] The residual concentration change curve monitored in real time is compared with the standard concentration time series characteristics matched in the database to analyze the similarity between the two, especially the alignment of key nodes, such as when the dye adsorption starts to slow down and reaches the saturation point. According to the feature matching results, the treatment process cycle nodes that need to be adjusted are determined, such as the specific time points for adding dye, adjusting temperature or changing pH value. The determination of these nodes is based on the goal of achieving the best dyeing effect and fabric quality.

[0038] According to the processing process cycle nodes, the parameters that need to be adjusted are determined, such as dye dosage, water temperature, flow rate, etc.; according to the process requirements and fabric characteristics, the parameters to be added are determined, that is, new control parameters are introduced, such as adding specific auxiliaries (for example, auxiliaries that enhance color fastness) or changing the pH value of the dye solution, etc.; the optimal time for parameter adjustment is determined by using the obtained node change gradient characteristics. These gradient characteristics help determine the speed and amplitude of concentration changes during the dyeing process. Considering that there may be a lag in the switching of control, a dynamic adjustment strategy is used to compensate for this time difference to ensure that the control measures can take effect in a timely manner.

[0039] Based on the node change gradient characteristics, the control intervention nodes, that is, the best nodes for control intervention, are determined. These nodes are derived from the deviation analysis based on real-time data and preset standard models, and can indicate when the dyeing process needs to be adjusted. According to the identified control intervention nodes, necessary parameter adjustments are made, such as increasing or decreasing dye delivery, adjusting the type and amount of auxiliaries, changing mechanical operating parameters, etc., as well as adding parameters. These adjustments are based on real-time process monitoring and data analysis results to ensure that the dyeing effect is consistent with expectations.

[0040] Furthermore, the concentration change gradient of the process cycle node is identified according to the process cycle concentration timing characteristics and the control parameters to obtain the node change gradient characteristics, including:

[0041] The process cycle is segmented and aligned according to the process cycle concentration timing characteristics to establish an aligned concentration timing characteristic; the control parameter switching node is used as the segmentation point, and the feature similarity in the continuous interval on both sides of the segmentation point is identified according to the aligned concentration timing characteristics; based on the feature similarity, a difference timing feature search is performed starting from the segmentation point to obtain the node change gradient feature, which is a feature of continuous concentration change that distinguishes each process cycle node, including a difference timing feature and a similar timing feature.

[0042] Collect dyeing concentration data for the entire cycle, which includes the entire process from dye addition to dyeing completion. Use time series analysis techniques, such as peak detection and time window segmentation, to identify key time periods of concentration changes. According to the analysis results, segment the concentration time series data into several intervals. Each interval represents a specific process stage, such as the initial, middle and stable stages of dye adsorption. Align the segmented data to ensure that the concentration data structure of each cycle is consistent for easy comparison and analysis. Standardize the segmented time series data and establish aligned concentration time series features to reflect the concentration change patterns between different production batches and provide a standardized reference framework.

[0043] According to the characteristics of the aligned concentration time series, the key nodes of dye concentration change in the dyeing process are identified. These nodes may require adjustment of control parameters. Based on these key nodes, the control parameter switching nodes are determined. The control parameter switching nodes are usually selected at the location where the concentration change rate changes significantly, such as the point from rapid decline to slow decline. In the continuous interval on both sides of the control parameter switching node, the similarity of concentration changes is analyzed. This can be achieved by calculating similarity indicators, such as Pearson correlation coefficient and cosine similarity, so as to adjust the control parameters more accurately.

[0044] Starting from the identified process cycle segmentation point, the concentration change characteristics in the adjacent time period are searched through similarity measurement to identify the difference time series characteristics that are significantly different from the main trend. These characteristics indicate the nodes where the control strategy may need to be adjusted. The difference time series characteristics can include sudden changes in the concentration change rate, periodic fluctuation increases, or deviations from expected concentration behavior. Based on the identified difference time series characteristics, the node change gradient characteristics are calculated. These gradient characteristics describe the rate and direction of concentration change between nodes in the process cycle. The gradient characteristics help to accurately locate the specific time point where intervention adjustment is required, such as adjusting the control parameters when a certain gradient value reaches a specific threshold.

[0045] Further, identifying feature similarity in continuous intervals on both sides of the segmentation point according to the aligned concentration time series features includes:

[0046] The concentration change data is standardized and decomposed into layers according to the data length; based on the decomposition layers, the standardized concentration change data is decomposed into high-frequency components and low-frequency components in turn; the key trend nodes that align the concentration time series characteristics are extracted based on the low-frequency components, and the concentration gradient change rate is calculated on both sides of the key trend nodes; based on the high-frequency components, the abnormal fluctuation nodes are obtained, and the abnormal fluctuation nodes are fluctuation nodes whose deviations between the high-frequency characteristics and the standard characteristics are greater than the threshold.

[0047] The concentration change data is converted to a unified standardized scale, usually by subtracting the mean and dividing by the standard deviation, which can eliminate the impact between different batches or different concentration levels and facilitate comparison and analysis between data. According to the total length n of the data, the number of decomposition layers L is calculated using the formula L = log2(n). This method is based on the multi-resolution analysis theory in signal processing and is suitable for capturing the multi-scale characteristics of time series data. The number of decomposition layers is usually controlled at 2 to 4 layers, which is sufficient to capture the main trends and key fluctuations in the data without over-refinement.

[0048] High-frequency components are separated from the data using wavelet transform or Fourier transform methods. These components reflect local fluctuations and possible anomalies in concentration changes. High-frequency components are particularly suitable for capturing rapid fluctuations or temporary deviations in concentration changes, which may be caused by operating errors, equipment performance fluctuations, or changes in raw material quality. Similarly, wavelet transform or Fourier transform are used to extract low-frequency components from concentration change data. These components represent the global trend of concentration changes during the process cycle. Low-frequency components help identify stable areas and key nodes of the process, such as the beginning and end of dye adsorption and fixation.

[0049] The key trend nodes that characterize the key stages of the entire dyeing cycle are identified from the low-frequency components. These nodes may include the acceleration point where the dye begins to adsorb, the stable point where the adsorption equilibrium is reached, or the decline point where the dye is exhausted. These nodes mark the main turning points of the dye concentration change during the dyeing process. Mathematical methods such as the difference method are used before and after the key trend nodes to calculate the concentration gradient change rate, which represents the speed of dye concentration change near the key node, and is used to decide when to adjust the parameters.

[0050] Analyze the fluctuation characteristics in the high-frequency component, especially the short-term fluctuations that are significantly different from the normal fluctuation pattern, and set a threshold to determine when the fluctuation should be considered abnormal. This threshold is usually based on statistical analysis of historical data, such as multiples of the standard deviation. Compare the high-frequency fluctuations monitored in real time with the standard fluctuation pattern in the dyeing process. When the actual fluctuation exceeds the threshold, it is marked as an abnormal fluctuation node. These abnormal nodes may be caused by equipment failure, raw material quality changes, or operational errors, requiring immediate attention and possible intervention.

[0051] Furthermore, the method of compensating the residual concentration difference by using the dyeing control parameter to obtain the compensation control parameter includes:

[0052] A control relationship between dyeing control parameters and residual liquid concentration is established, wherein the dyeing control parameters include dye dosage, auxiliary agent dosage, drainage speed, and temperature control; the adjustment parameters and increase parameters of the control switching node are used as constraints to determine the compensation target parameters; according to the control relationship of the compensation target parameters, the residual concentration difference is compensated and calculated to obtain the compensation control parameters.

[0053] Determine the main dyeing control parameters that affect the residual liquid concentration, including dye dosage, auxiliary agent dosage, drainage speed and temperature control. Through experiments or historical data analysis, establish a mathematical model between these dyeing control parameters and the residual liquid concentration, including a linear or nonlinear regression model to describe how parameter changes affect the concentration of dyes and chemical components in the residual liquid. Use statistical methods to verify and optimize the model to ensure its predictive accuracy and applicability.

[0054] The adjustment parameters and the added parameters of the control switching nodes are taken as constraints, that is, the range and mode of the adjustment parameters are formulated as constraints for the compensation calculation, and the compensation target parameters are determined to achieve the predetermined dyeing effect.

[0055] Based on the control relationship model and the residual concentration difference, mathematical calculations or optimization algorithms are performed to determine how to adjust the control parameters to compensate for these differences. The calculated compensation control parameters are applied to the control system of the dyeing machine to adjust related operating parameters, such as increasing the amount of dye added, adjusting the discharge speed or changing the heating temperature to ensure that the predetermined quality standards are met.

[0056] Furthermore, according to the control relationship of the compensation target parameter, the residual concentration difference is compensated and calculated to obtain the compensation control parameter, including:

[0057] Based on the adjustment parameters of the control switching node, the adjustment range of the increased parameters and the adjustment mode are used as constraints; the current dyeing state characteristics are obtained; the dyeing state deviation parameters are identified according to the current dyeing state characteristics; based on the constraints, with the maximization of the dyeing state deviation parameter compensation as the goal, parameter search is performed according to the control relationship of the compensation target parameter, and when the target interval is reached or the number of searches is reached, the compensation control parameter is obtained.

[0058] According to the design of the dyeing machine and the quality requirements of the product, set a safe and effective adjustment range for each control parameter. For example, the amount of dye added should not exceed the maximum amount that the machine can handle to avoid waste or overload. Determine the adjustment mode, such as whether to adjust gradually, adjust in place at one time, or adjust dynamically according to certain trigger conditions in the dyeing process. Use these as constraints to ensure that when adjusting the control parameters, all adjustments meet the preset constraints.

[0059] Sensors and data acquisition systems are used to collect key data in the dyeing process in real time, such as concentration, temperature, pH value, flow rate, etc. These data reflect the current working status of the dyeing machine and generate the current dyeing status characteristics.

[0060] Statistical analysis and comparison techniques, such as standard deviation and control chart technology, are used to identify deviations between the current state and the standard or expected state. These deviations indicate problems in the dyeing process, such as improper temperature control, inaccurate dosing of dyes or auxiliaries, etc. The dyeing state deviation parameters are determined based on the deviations. These deviation parameters will be used as the basis for adjusting the control parameters to correct the dyeing process to achieve the predetermined quality standards.

[0061] According to the quality control requirements and technical specifications, the target range and tolerance of the control parameter adjustment are set. The target range refers to the ideal state range that should be achieved after the parameters are adjusted, and the tolerance allows a certain degree of deviation to adapt to changes in actual production conditions. Optimization algorithms, such as gradient descent and genetic algorithms, are used to search for the optimal control parameter settings. These algorithms can iteratively adjust parameters according to preset performance indicators, such as minimizing residuals and maximizing output quality, and the search process follows the established constraints. Key parameters and results are monitored in real time during the dyeing process, and the control parameters are dynamically adjusted according to the feedback data. This process is iterated multiple times to gradually approach the target range. During the adjustment process, the results of each search and adjustment are recorded, and their impact on the dyeing quality is evaluated. The search strategy is adjusted based on these data. When the dyeing state after the control parameters are adjusted reaches the target range, or when the number of searches performed reaches the predetermined limit, the parameter search is stopped. This ensures that there will be no over-adjustment, avoids causing new problems or excessive consumption of resources, and obtains compensating control parameters based on the search results.

[0062] This data-driven dynamic adjustment strategy can ensure that the control parameters of the dyeing process can be effectively adjusted in a real-time production environment, so that the use of each batch of dyes can be optimized, ultimately achieving the goal of improving product quality and production efficiency.

[0063] In summary, the automatic control method of the dyeing machine combined with the monitoring of the concentration of the residual dyeing liquid provided in the embodiment of the present application has the following technical effects:

[0064] By obtaining the concentration of the residual dyeing liquid monitored in real time by the dyeing machine, basic data support is provided for the entire control process. This real-time monitoring ensures the timeliness and accuracy of the data and provides a real-time, data-driven basis for the decision-making of subsequent steps. According to the concentration difference between the residual dyeing liquid concentration and the input dyeing liquid concentration, a residual concentration change curve is constructed to reflect the deviation between the actual dyeing process and the expected target, so that the process control can be dynamically adjusted according to the actual situation, rather than relying solely on the preset fixed parameters. According to the time series relationship of the residual concentration change curve, the control switching node is identified so that the control strategy can be adjusted at the critical moment. This control node identification method based on time series analysis improves the accuracy and efficiency of control. The residual concentration difference is compensated by using the dyeing control parameters to further refine the control process. The concentration deviation is compensated by adjusting the dyeing control parameters to ensure that the dyeing effect meets the quality standards. The dyeing machine is dynamically controlled according to the compensation control parameters to ensure that the entire dyeing process can flexibly respond to changes according to the adjustment of the compensation control parameters, improve the process's adaptability and overall production efficiency, achieve a higher level of automation and better production efficiency, and also improve product quality and production flexibility.

[0065] Embodiment 2, based on the same inventive concept as the automatic control method of the dyeing machine combined with the monitoring of the concentration of the residual dyeing liquid in the previous embodiment, Figure 2 As shown, the embodiment of the present application provides an automatic control system for a dyeing machine combined with dyeing residual liquid concentration monitoring, the system comprising:

[0066] A dyeing residual liquid concentration acquisition module 10 is used to obtain the dyeing residual liquid concentration monitored in real time by the dyeing machine; a concentration change curve construction module 20 is used to construct a residual concentration change curve according to the component concentration difference between the dyeing residual liquid concentration and the input dyeing liquid concentration; a control switching node identification module 30 is used to identify the control switching node according to the time series relationship of the residual concentration change curve; a residual concentration difference compensation module 40 is used to compare the component concentration difference of the residual concentration change curve with the target residual liquid concentration range of the control switching node, and use the dyeing control parameters to compensate for the residual concentration difference to obtain the compensation control parameters; a dyeing machine dynamic control module 50 is used to dynamically control the dyeing machine according to the compensation control parameters.

[0067] Furthermore, the system also includes a standard concentration node sequence library construction module, including:

[0068] A control parameter determination unit is used to decompose the concentration change mechanism of the whole cycle in the dyeing machine processing process, determine the concentration time series characteristics of the process cycle and the control parameters; a clustering unit is used to cluster according to the dye liquid adsorption characteristics of different target fabrics; a sequence library construction unit is used to establish a mapping relationship between various target fabrics and the concentration time series characteristics of the process cycle, and construct a standard concentration node sequence library; a change gradient identification unit is used to identify the concentration change gradient of the process cycle node according to the process cycle concentration time series characteristics and control parameters, and obtain the node change gradient characteristics; a fitting unit is used to fit the node change gradient characteristics to the standard concentration node sequence library according to the relationship between the process cycle node and the target fabric category.

[0069] Furthermore, the control switching node identification module 30 includes:

[0070] A target dyed fabric acquisition unit is used to acquire a target dyed fabric; a target fabric search unit is used to search for a target fabric in the standard concentration node sequence library using the target dyed fabric as an index to obtain a matching process cycle concentration timing feature; a feature matching unit is used to match concentration change features using the timing relationship of the residual concentration change curve with the matching process cycle concentration timing feature to determine a processing process cycle node; a feature acquisition unit is used to obtain adjustment parameters, increase parameters, and node change gradient features according to the processing process cycle node; a control switching node acquisition unit is used to identify a control intervention node and corresponding adjustment parameters and increase parameters based on the node change gradient feature to obtain the control switching node.

[0071] Furthermore, the change gradient identification unit includes:

[0072] A process cycle segmentation and alignment channel is used to perform process cycle segmentation and alignment according to the process cycle concentration timing characteristics, and establish an aligned concentration timing characteristic; a feature similarity identification channel is used to use the control parameter switching node as the segmentation point, and identify the feature similarity in the continuous interval on both sides of the segmentation point according to the aligned concentration timing characteristics; a node change gradient feature acquisition channel is used to perform a difference timing feature search based on feature similarity, starting from the segmentation point, to obtain the node change gradient feature, which is a feature that distinguishes the continuous concentration change characteristics of each process cycle node, including a difference timing feature and a similar timing feature.

[0073] Furthermore, the feature similarity identification channel includes:

[0074] The standardization processing node is used to standardize the concentration change data and decompose the data into layers according to the data length; the component decomposition node is used to decompose the standardized concentration change data into high-frequency components and low-frequency components in turn based on the decomposition layers; the gradient change rate calculation node is used to extract the key trend nodes that align the concentration time series characteristics according to the low-frequency components, and calculate the concentration gradient change rate on both sides of the key trend nodes; the abnormal fluctuation node acquisition node is used to obtain the abnormal fluctuation node according to the high-frequency component, and the abnormal fluctuation node is a fluctuation node whose deviation between the high-frequency feature and the standard feature is greater than the threshold.

[0075] Furthermore, the residual concentration difference compensation module 40 includes:

[0076] A control relationship establishing unit is used to establish a control relationship between dyeing control parameters and residual liquid concentration, wherein the dyeing control parameters include dye dosage, auxiliary agent dosage, drainage speed, and temperature control; a compensation target parameter determining unit is used to determine the compensation target parameter by taking the adjustment parameters and increase parameters of the control switching node as constraints; a compensation control parameter obtaining unit is used to perform compensation calculation on the residual concentration difference according to the control relationship of the compensation target parameter to obtain the compensation control parameter.

[0077] Furthermore, the compensation control parameter acquisition unit includes:

[0078] A constraint condition acquisition channel is used to use the adjustment parameters of the control switching node, the adjustment range of the increased parameters, and the adjustment mode as constraint conditions; a dyeing state feature acquisition channel is used to obtain the current dyeing state feature; a deviation parameter identification channel is used to identify the dyeing state deviation parameter according to the current dyeing state feature; a compensation control parameter acquisition channel is used to perform parameter search based on the control relationship of the compensation target parameter with the goal of maximizing the compensation of the dyeing state deviation parameter based on the constraint conditions, and obtain the compensation control parameter when the target interval is reached or the number of searches is reached.

[0079] Through the above-mentioned detailed description of the automatic control method of the dyeing machine combined with the monitoring of the concentration of the residual dyeing liquid, the technical personnel in this specification can clearly know the automatic control system of the dyeing machine combined with the monitoring of the concentration of the residual dyeing liquid in this embodiment. Since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0080] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be 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. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A dyeing machine automatic control method combined with dyeing residual liquid concentration monitoring, characterized in that: The method comprises: Obtain the concentration of residual dyeing liquid monitored in real time by the dyeing machine; Constructing a residual concentration variation curve according to the component concentration difference between the dyeing residual solution concentration and the input dyeing solution concentration; According to the time series relationship of the residual concentration variation curve, identifying the control switching node; Compare the component concentration difference of the residual concentration variation curve with the target residual liquid concentration range of the control switching node, compensate the residual concentration difference using the dyeing control parameter, and obtain the compensation control parameter; The dyeing machine is dynamically controlled according to the compensation control parameters.

2. The automatic control method for a dyeing machine combined with monitoring the concentration of dyeing residual liquid according to claim 1, characterized in that: According to the time sequence relationship of the residual concentration variation curve, the control switching node is identified, which includes: Decompose the concentration variation mechanism of the whole cycle in the dyeing machine treatment process, determine the concentration timing characteristics and control parameters of the process cycle; Clustering was performed according to the dye liquor adsorption characteristics of different target fabrics; Establish the mapping relationship between various target fabrics and process cycle concentration time series characteristics, and construct a standard concentration node sequence library; Identify the concentration change gradient of the process cycle node according to the process cycle concentration timing characteristics and control parameters to obtain the node change gradient characteristics; According to the relationship between the node change gradient characteristics, the process cycle nodes and the target fabric category, they are fitted into the standard concentration node sequence library.

3. The automatic control method for a dyeing machine combined with monitoring the concentration of dyeing residual liquid according to claim 2, characterized in that: According to the time sequence relationship of the residual concentration change curve, identifying the control switching node includes: obtaining a target dyed fabric; Using the target dyed fabric as an index, searching for the target fabric in the standard concentration node sequence library to obtain a concentration time series feature of a matching process cycle; Using the time series relationship of the residual concentration change curve and the concentration time series characteristics of the matching process cycle to match the concentration change characteristics, determine the processing process cycle node; According to the processing process cycle nodes, adjusting parameters, increasing parameters, and node change gradient characteristics are obtained; Based on the node change gradient characteristics, the control intervention node and the corresponding adjustment parameters and increase parameters are identified to obtain the control switching node.

4. The automatic control method for a dyeing machine combined with monitoring the concentration of dyeing residual liquid according to claim 2, characterized in that: According to the process cycle concentration timing characteristics and control parameters, the concentration change gradient of the process cycle node is identified to obtain the node change gradient characteristics, including: Performing process cycle segmentation and alignment according to the process cycle concentration timing characteristics to establish an aligned concentration timing characteristic; Taking the control parameter switching node as the segmentation point, identifying the feature similarity in the continuous intervals on both sides of the segmentation point according to the aligned concentration time series features; Based on feature similarity, a difference timing feature search is performed starting from the segmentation point to obtain the node change gradient feature, which is a feature of continuous concentration change that distinguishes each process cycle node, including a difference timing feature and a similar timing feature.

5. The automatic control method for a dyeing machine combined with monitoring the concentration of dyeing residual liquid according to claim 4 is characterized in that: Identifying feature similarities in continuous intervals on both sides of a segmentation point according to the aligned concentration time series features includes: Standardize the concentration change data and decompose the data into layers according to the data length; Based on the number of decomposition layers, the standardized concentration change data is decomposed into high-frequency components and low-frequency components in turn; The key trend nodes of the concentration time series characteristics are extracted based on the low-frequency components, and the concentration gradient change rate is calculated on both sides of the key trend nodes; According to the high-frequency component, an abnormal fluctuation node is obtained, where the abnormal fluctuation node is a fluctuation node whose deviation between the high-frequency feature and the standard feature is greater than a threshold.

6. The automatic control method for a dyeing machine combined with monitoring the concentration of dyeing residual liquid according to claim 3 is characterized in that: The method of compensating the residual concentration difference by using the dyeing control parameter to obtain the compensation control parameter includes: Establishing a control relationship between dyeing control parameters and residual liquid concentration, wherein the dyeing control parameters include dye dosage, auxiliary agent dosage, liquid discharge speed, and temperature control; Taking the adjustment parameters and the added parameters of the control switching node as constraint conditions, determining the compensation target parameters; According to the control relationship of the compensation target parameter, the residual concentration difference is compensated and calculated to obtain the compensation control parameter.

7. The automatic control method for a dyeing machine combined with monitoring the concentration of dyeing residual liquid according to claim 6, characterized in that: According to the control relationship of the compensation target parameter, the residual concentration difference is compensated and calculated to obtain the compensation control parameter, including: Based on the adjustment parameters of the control switching node, the adjustment range of the increased parameters and the adjustment mode are used as constraint conditions; Get the current dyeing state characteristics; Identifying a dyeing state deviation parameter according to the current dyeing state feature; Based on the constraint conditions, with the goal of maximizing the compensation of the dyeing state deviation parameter, a parameter search is performed according to the control relationship of the compensation target parameter, and when the target interval is reached or the number of searches is reached, the compensation control parameter is obtained.

8. The automatic control system of the dyeing machine combined with the monitoring of the concentration of the dyeing residual liquid is characterized in that: The system is used to implement the automatic control method of a dyeing machine combined with monitoring the concentration of dyeing residual liquid according to any one of claims 1 to 7, and comprises: The dyeing residual liquid concentration acquisition module is used to obtain the dyeing residual liquid concentration monitored by the dyeing machine in real time; A concentration change curve construction module is used to construct a residual concentration change curve according to the component concentration difference between the dyeing residual solution concentration and the input dyeing solution concentration; A control switching node identification module, used to identify the control switching node according to the time sequence relationship of the residual concentration change curve; A residual concentration difference compensation module is used to compare the component concentration difference of the residual concentration change curve with the target residual liquid concentration range of the control switching node, and compensate the residual concentration difference using the dyeing control parameter to obtain the compensation control parameter; The dyeing machine dynamic control module is used to perform dynamic control of the dyeing machine according to the compensation control parameters.

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