An automatic control system for an alkali shrinking machine

Abstract

The present invention relates to the field of mechanical engineering, and discloses an automated control system for an alkali shrinking machine. The system includes: an alkali solution concentration analysis module for constructing a material identification module for the alkali shrinking machine and adjusting the alkali solution concentration of the alkali shrinking machine; a product state analysis module for determining the initial process parameters of the alkali shrinking machine, constructing a process monitoring module for the alkali shrinking machine, and analyzing the product state of the product to be processed; a parameter optimization module for adjusting the initial process parameters, analyzing the adjusted product state of the product to be processed, and outputting the alkali-treated product of the alkali shrinking machine; a product washing module for determining the washing exchange material of the alkali-treated product, analyzing the alkali solution content of the alkali-treated product, calculating the material exchange amount of the washing exchange material, and washing the alkali-treated product; a milling control module for calculating the milling reaction parameters of the washed product, performing milling treatment on the washed product, and obtaining a target product. The present invention can improve the intelligent control effect of the alkali shrinking machine.

Description

Technical Field

[0001] The invention relates to the field of mechanical engineering, in particular to an automatic control system of an alkali shrinking machine. Background Art

[0002] Alkali shrinkage machines are a type of equipment commonly used in the chemical and pharmaceutical industries. Their primary function is to perform alkali treatment and condensation reactions on materials. Alkali shrinkage machine operation can involve high temperatures, high pressures, and corrosive chemicals. Automated control can reduce direct operator exposure to hazardous environments and improve workplace safety.

[0003] At present, the control method of alkali shrinkage machine mainly relies on manual operation and simple electrical control. This control method requires the operator to have high skills and experience, and is easily affected by human factors, resulting in low control accuracy and slow response speed, thus leading to low production efficiency. Summary of the Invention

[0004] The present invention provides an automatic control system for an alkali shrinking machine, the main purpose of which is to improve the intelligent control effect of the alkali shrinking machine.

[0005] To achieve the above object, the present invention provides an automatic control system for an alkali shrinking machine, comprising: an alkali solution concentration analysis module, a product status analysis module, a parameter optimization module, a product washing module, and a shrinking control module;

[0006] The alkali solution concentration analysis module is used to construct a material identification module for the alkali shrinking machine. Based on the material identification module, the module identifies the material type of the product to be processed by the alkali shrinking machine, determines the alkali solution concentration requirement of the alkali shrinking machine according to the material type, and adjusts the alkali solution concentration of the alkali shrinking machine using a preset concentration control algorithm based on the alkali solution concentration requirement.

[0007] The product status analysis module is used to obtain historical operating data of the alkali shrinking machine, determine initial process parameters of the alkali shrinking machine based on the historical operating data, configure a sensor network for the alkali shrinking machine, build a process monitoring module for the alkali shrinking machine based on the sensor network, collect real-time process data of the alkali shrinking machine based on the process monitoring module, and analyze the product status of the product to be processed based on the real-time process data using a trained product alkali treatment analysis model;

[0008] The parameter optimization module is configured to, when the product state does not conform to a preset product standard state, identify an abnormality factor of the alkali shrinkage machine, adjust the initial process parameters according to the abnormality factor to obtain an adjusted process parameter, analyze the adjusted product state of the product to be processed according to the adjusted process parameter, and output the alkali-treated product of the alkali shrinkage machine when the adjusted product state conforms to the product standard state;

[0009] The product washing module is used to determine the washing exchange material of the alkali-treated product, analyze the alkali liquor content of the alkali-treated product, calculate the material exchange amount of the washing exchange material based on the alkali liquor content, and wash the alkali-treated product based on the material exchange amount to obtain a washed product;

[0010] The fulling control module is used to analyze the fulling requirements of the alkali shrinking machine, configure the fulling liquid of the washed product based on the fulling requirements, calculate the fulling reaction parameters of the washed product, and perform fulling treatment on the washed product based on the fulling reaction parameters and the fulling liquid to obtain the target product.

[0011] The embodiment of the present invention can automatically identify the material type by constructing a material identification module for the alkali shrinking machine, reduce manual intervention, improve the automation level of the production line, and realize intelligent production; optionally, the embodiment of the present invention can optimize the processing effect of the material by adjusting the alkali solution concentration of the alkali shrinking machine based on the alkali solution concentration requirement using a preset concentration control algorithm, reduce processing defects caused by improper concentration, and lower the defective rate; the embodiment of the present invention can quickly identify process deviations by collecting real-time process data of the alkali shrinking machine based on the process monitoring module, take timely measures to prevent accidents; the embodiment of the present invention can detect the product status when it does not meet the expected When the product is in the standard state set, identifying the abnormal factors of the alkali shrinking machine can ensure that the quality of the final product meets the preset standards by identifying and adjusting the factors that cause the abnormal product state, thereby reducing the production of unqualified products; the embodiment of the present invention calculates the material exchange amount of the water washing exchange material according to the alkali solution content, and can accurately calculate the required material exchange amount to ensure that the water washing process effectively removes the alkali solution and avoids excessive or insufficient treatment. Finally, the embodiment of the present invention performs a shrinking treatment on the washed product based on the shrinking reaction parameters and the shrinking liquid to obtain the target product, which can reduce errors in the processing process, reduce the defective rate, and improve production efficiency. Therefore, the intelligent control effect of the alkali shrinking machine is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A functional module diagram of an automatic control system for an alkali shrinking machine provided in one embodiment of the present invention;

[0013] Figure 2 A schematic flow chart of an automated control method for an alkali shrinking machine provided in one embodiment of the present invention;

[0014] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0015] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0016] In addition, the step sequence in the following method embodiments is only an example and not a strict limitation.

[0017] In fact, the server-side equipment deployed by the automation control system of the alkali shrinking machine may be composed of one or more devices. The automation control system of the above-mentioned alkali shrinking machine can be implemented as: business instance, virtual machine, hardware equipment. For example, the automation control system of this alkali shrinking machine can be implemented as a business instance on one or more devices deployed in the cloud node. In simple terms, the automation control system of this alkali shrinking machine can be understood as a kind of software deployed on the cloud node, for providing the service of the automation control of the alkali shrinking machine to each user terminal. Alternatively, the automation control system of this alkali shrinking machine can also be implemented as a kind of virtual machine deployed on one or more devices in the cloud node. The application software for managing each user terminal is installed in this virtual machine. Alternatively, the automation control system of this alkali shrinking machine can also be implemented as a server consisting of numerous identical or different types of hardware devices, and one or more hardware devices are set to provide the automation control service of the alkali shrinking machine to each user terminal.

[0018] In terms of implementation, the automated control system of the alkali shrinking machine and the user end are mutually compatible. That is, if the automated control system of the alkali shrinking machine is an application installed on the cloud service platform, the user end is the client that establishes a communication connection with the application; or if the automated control system of the alkali shrinking machine is implemented as a website, the user end is implemented as a webpage; or if the automated control system of the alkali shrinking machine is implemented as a cloud service platform, the user end is implemented as a mini-program in an instant messaging application.

[0019] Reference Figure 1 FIG. 1 is a functional module diagram of an automatic control system of an alkali shrinking machine provided by an embodiment of the present invention.

[0020] The automated control system 100 of the alkali shrinking machine of the present invention can be arranged in a cloud server. In terms of implementation, it can be implemented as one or more service devices, or as an application installed in the cloud (e.g., a server or server cluster of the automated control of the alkali shrinking machine), or it can also be developed as a website. According to the implemented functions, the automated control system 100 of the alkali shrinking machine includes an alkali solution concentration analysis module 101, a product status analysis module 102, a parameter optimization module 103, a product washing module 104, and a shrinkage control module 105.

[0021] In the embodiment of the present invention, in the tracking of the automation control based on alkali shrinking machine, above-mentioned each module all can realize independently, and call with other modules.Calling here can be understood as, a certain module can connect the multiple modules of another type, and the multiple modules for which it is connected provide corresponding services, in the automation control system of the alkali shrinking machine that the embodiment of the present invention provides, without the need to modify program code, the scope of application of the automation control framework of alkali shrinking machine can be adjusted by increasing module and the form of directly calling, realize cluster type horizontal expansion, in order to reach the purpose of the automation control system of expanding alkali shrinking machine quickly and flexibly.In actual application, above-mentioned module can be arranged in same equipment or different equipment, also can be to be arranged in virtual device, for example the service instance in cloud server.

[0022] The following describes the various components and specific workflows of the automation control system of the alkali shrinking machine in conjunction with specific embodiments.

[0023] The alkali solution concentration analysis module 101 is used to construct a material identification module for an alkali shrinking machine. Based on the material identification module, the material type of the product to be processed corresponding to the alkali shrinking machine is identified. According to the material type, the alkali solution concentration requirement of the alkali shrinking machine is determined. Based on the alkali solution concentration requirement, the alkali solution concentration of the alkali shrinking machine is adjusted using a preset concentration control algorithm.

[0024] By constructing a material identification module for an alkali shrinking machine, embodiments of the present invention can automatically identify material types, reduce manual intervention, improve the automation level of the production line, and achieve intelligent production. The material identification module is a hardware and software complex integrated into the alkali shrinking machine system, whose main function is to identify and confirm the type of product to be processed.

[0025] As an embodiment of the present invention, the material identification module for constructing the alkali shrinkage machine includes:

[0026] Constructing an identification module framework of the alkali shrinking machine and determining a material database of the identification module framework;

[0027] A data acquisition unit is configured for the identification module framework, and material data of the product to be processed corresponding to the alkali shrinking machine is collected based on the data acquisition unit;

[0028] defining a data matching algorithm for the recognition module framework, and matching the material data with the material database according to the data matching algorithm to obtain a material matching degree;

[0029] Determining a material type analysis unit of the recognition module framework according to the material matching degree;

[0030] The material type analysis unit, the data acquisition unit and the data matching algorithm are integrated into the identification module framework to obtain the material identification module of the alkali shrinking machine.

[0031] Among them, the identification module framework refers to an architecture for alkali shrink machine material identification, which includes all necessary components and interfaces to realize the function of material identification. The material database refers to a database specifically used to store and manage the characteristics of the materials to be processed. The data acquisition unit refers to the part of the alkali shrink machine material identification module that is responsible for collecting information related to the materials to be processed. The material data refers to a series of characteristic information obtained from the materials to be processed through the data acquisition unit. This information is used to characterize the properties of the material to facilitate identification and analysis by the material identification module. The data matching algorithm refers to an algorithm used to compare input material data with data in a known material database to identify and determine the type of material. The material matching degree refers to the degree of similarity or consistency between the input material data calculated by the data matching algorithm and a certain material standard data in a known material database when identifying the material. The material type analysis unit refers to a key component in the material identification module, whose function is to analyze and determine the type of input material.

[0032] Optionally, the data matching algorithm defining the recognition module framework may be defined by a machine learning algorithm.

[0033] In the embodiment of the present invention, by identifying the material type of the product to be processed by the alkali shrinking machine based on the material identification module, the material type can be quickly and accurately identified, allowing the alkali shrinking machine to immediately adjust to appropriate processing parameters, shortening preparation time and improving processing efficiency. The material type refers to the various types of materials used in the product to be processed during the alkali shrinking machine processing.

[0034] By determining the required alkali concentration of the alkali shrinking machine based on the material type, embodiments of the present invention can ensure optimal processing results for each material by precisely controlling the alkali concentration. The required alkali concentration refers to the concentration range of the alkali solution (typically sodium hydroxide or potassium hydroxide solution) required to achieve a specific material processing effect (such as shrinkage, softening, degreasing, bleaching, etc.) during the alkali shrinking machine process.

[0035] Optionally, as an embodiment of the present invention, the alkali solution concentration requirement of the alkali shrinkage machine determined according to the material type can be determined by chemical kinetic simulation.

[0036] By adjusting the alkali concentration of the alkali shrinking machine based on the required alkali concentration using a preset concentration control algorithm, the present invention optimizes material processing, reduces processing defects caused by improper concentration, and lowers the defective rate. The preset concentration control algorithm adjustment refers to a pre-designed program or instruction set for automatically adjusting the alkali concentration in the alkali shrinking machine. The alkali concentration refers to the concentration of the active ingredient (typically sodium hydroxide (NaOH) or potassium hydroxide (KOH)) in the alkali solution, typically expressed as a mass percentage (mass fraction) or molar concentration.

[0037] As an embodiment of the present invention, adjusting the alkali concentration of the alkali shrink machine using a preset concentration control algorithm based on the alkali concentration requirement includes:

[0038] Collecting the real-time alkali solution concentration of the alkali shrinking machine, and calculating the concentration error between the alkali solution concentration requirement and the real-time alkali solution concentration;

[0039] Determining algorithm parameters of the concentration control algorithm, wherein the algorithm parameters include: a proportional gain coefficient, an integral gain coefficient, and a differential gain coefficient;

[0040] According to the concentration error and the algorithm parameters, the concentration control signal of the alkali shrinkage machine is calculated using the following formula:

[0041]

[0042] in, Indicates time The concentration control signal, Indicates the collection time corresponding to the real-time alkali concentration, represents the proportional gain coefficient, Indicates time The concentration error, represents the integral gain coefficient, Indicates the collection time interval, Indicates time The concentration error, represents the differential gain coefficient, Indicates time Concentration error;

[0043] The alkali concentration of the alkali shrinkage machine is adjusted according to the concentration control signal.

[0044] Among them, the real-time alkali solution concentration refers to the actual concentration value of the alkali solution measured and obtained in real time during the processing process by the sensor or detection equipment installed in the alkali shrink machine system. The concentration error refers to the deviation between the actually measured alkali solution concentration and the target alkali solution concentration. The algorithm parameters refer to various configurable variables used to adjust and control the algorithm behavior in the concentration control algorithm. The proportional gain coefficient refers to the gain of the proportional part in the controller in the control system. The integral gain coefficient refers to the gain of the integral part in the controller in the control system. The differential gain coefficient refers to the gain of the differential part in the controller in the control system. The concentration control signal refers to the command signal generated by the controller in the concentration control system for adjusting the process to maintain or change the alkali solution concentration.

[0045] The product status analysis module 102 is used to obtain the historical working data of the alkali shrinkage machine, determine the initial process parameters of the alkali shrinkage machine based on the historical working data, configure the sensor network of the alkali shrinkage machine, and construct the process monitoring module of the alkali shrinkage machine based on the sensor network. Based on the process monitoring module, the real-time process data of the alkali shrinkage machine is collected, and based on the real-time process data, the product status of the product to be processed is analyzed using the trained product alkali treatment analysis model.

[0046] The embodiment of the present invention can establish a relationship between product quality and process parameters by acquiring the historical operating data of the alkali shrinking machine, thereby better controlling product quality in real-time production. Wherein, the historical operating data refers to a series of data records accumulated during the past operation of the alkali shrinking machine.

[0047] In an embodiment of the present invention, by determining the initial process parameters of the alkali shrinking machine based on the historical operating data, it is possible to help set optimal initial parameters to stabilize and ensure product quality. The initial process parameters refer to a set of process parameters, such as temperature, pressure, flow rate, etc., set when the alkali shrinking machine is initially started or a new production batch begins.

[0048] As an embodiment of the present invention, determining the initial process parameters of the alkali shrinkage machine based on the historical working data includes:

[0049] Preprocessing the historical working data to obtain preprocessed data;

[0050] Identifying key process parameters of the pre-processed data, and analyzing the relationship between the key process parameters and the quality of the corresponding product of the alkali shrinking machine;

[0051] The correlation coefficients between the key process parameters were calculated using the following formula:

[0052]

[0053] in, represents the correlation coefficient between key process parameters, n represents the number of groups of preprocessed data, α i Represents one of the key process parameters α, β corresponding to the i-th group of preprocessing data i represents another key process parameter β corresponding to the i-th group of pre-processed data;

[0054] Analyzing the interdependence between the key process parameters according to the correlation coefficient;

[0055] According to the mutual dependence relationship and the influence relationship, the initial process parameters of the alkali shrinkage machine are determined.

[0056] The preprocessed data refers to a data set that has undergone a series of data preprocessing steps (such as data cleaning and data conversion). The key process parameters refer to process variables that have a significant impact on product quality, efficiency, and safety. The influence relationship refers to the causal relationship or correlation between the key process parameters and the quality of the corresponding product of the alkali shrink machine. The correlation coefficient is a statistic used to measure the strength and direction of the linear relationship between two variables. The interdependence relationship refers to the correlation between two or more variables, which indicates that changes in one variable may affect changes in another variable.

[0057] Optionally, the key process parameters for identifying the pre-processing data may be identified by principal component analysis.

[0058] By configuring the sensor network of the alkali shrink machine, the embodiment of the present invention can collect a large amount of process data through the sensor network, providing a basis for subsequent data analysis and process optimization. The sensor network refers to a system composed of multiple sensors that are arranged on the alkali shrink machine and its related process equipment to monitor and control various parameters in the production process.

[0059] Optionally, as an embodiment of the present invention, the sensor network configuring the alkali shrink machine may be configured by using an adaptive network technology.

[0060] In the embodiment of the present invention, by constructing a process monitoring module for the alkali shrinkage machine based on the sensor network, process parameters can be monitored in real time, any abnormalities that deviate from the normal range can be quickly detected, and immediate feedback can be provided to the operator or control system. The process monitoring module is an integrated system or software solution responsible for collecting, processing, analyzing, and displaying real-time data from various sensors and equipment in the production process.

[0061] As an embodiment of the present invention, the process monitoring module of the alkali shrinkage machine is constructed based on the sensor network, including:

[0062] Clarify the monitoring frequency and alarm threshold of the alkali shrinking machine, and build a data processing unit of the alkali shrinking machine;

[0063] determining a transmission mechanism of the sensor network and the data processing unit according to the monitoring frequency;

[0064] defining a data processing algorithm for the data processing unit, and determining real-time presentation data for the data processing unit based on the data processing algorithm;

[0065] Determining a safety early warning mechanism for the alkali shrinkage machine according to the real-time presentation data and the alarm threshold;

[0066] A data storage library and a system log of the alkali shrinking machine are constructed, and a process monitoring module of the alkali shrinking machine is integrated according to the data storage library, the system log, the transmission mechanism, the data processing unit and the safety early warning mechanism.

[0067] Among them, the monitoring frequency refers to the fixed time interval for sensors to collect and transmit data in the alkali shrink machine process monitoring system. The alarm threshold refers to the limit value of the parameter used to trigger the alarm in the process monitoring system. When the monitored process parameters exceed these preset thresholds, the system will issue an alarm to notify the operator or the automated control system to take appropriate measures. The data processing unit refers to the hardware and software system used to receive, store, process and analyze data collected by the sensor network. The data processing algorithm refers to a series of calculation steps and rules used to process, analyze and interpret sensor data. The real-time display data refers to data that can be updated and displayed in real time on the monitoring interface or display screen after being processed by the data processing unit. The safety warning mechanism refers to a set of systematic procedures and measures designed to identify potential risks and dangers and trigger alarms when specific conditions are met. The data repository refers to a system or facility specifically used to collect, store and manage large amounts of data. The system log refers to a record file automatically generated by a computer system, network equipment, application or service during operation.

[0068] Optionally, the data processing algorithm defining the data processing unit can be defined by a data analysis and machine learning framework.

[0069] In the embodiment of the present invention, by collecting real-time process data of the alkali shrinkage machine based on the process monitoring module, process deviations can be quickly identified, and timely measures can be taken to prevent accidents. The real-time process data refers to data directly related to the production process that is continuously collected during the production process through various sensors, monitoring equipment, and other data collection methods.

[0070] In embodiments of the present invention, by analyzing the product status of the product to be treated based on the real-time process data and utilizing a trained product alkali treatment analysis model, process parameters can be more accurately predicted and adjusted through model analysis to optimize product quality. The trained product alkali treatment analysis model refers to a mathematical model trained with a large amount of data that can predict and analyze the product status during the alkali treatment process. The product status refers to the physical, chemical, or quality characteristics of the product at a specific point in time during the production process.

[0071] As an embodiment of the present invention, the analyzing the product status of the product to be treated based on the real-time process data and using a trained product alkali treatment analysis model includes:

[0072] Standardizing the real-time process data to obtain standardized data;

[0073] extracting data features of the standardized data;

[0074] Analyzing model parameters of the product alkali treatment analysis model;

[0075] Based on the data features and the model parameters, the product status of the product to be processed is calculated using the following formula:

[0076] Among them, represents the product status, represents the number of data features, represents the data feature, represents the model parameter corresponding to the data feature, and represents a constant.

[0077] Standardized data refers to the process of applying a series of mathematical transformations to raw data to conform to specific statistical standards. Data features refer to the attributes or variables used to describe each data point in a dataset. Model parameters refer to the variables used in machine learning or statistical models to describe the relationship between data features and prediction targets.

[0078] Optionally, the model parameters of the product alkali treatment analysis model can be analyzed by least squares method.

[0079] The parameter optimization module 103 is used to identify the abnormal factors of the alkali shrinkage machine when the product status does not meet the preset product standard status, adjust the initial process parameters according to the abnormal factors to obtain adjusted process parameters, analyze the adjusted product status of the product to be processed according to the adjusted process parameters, and output the alkali-treated product of the alkali shrinkage machine when the adjusted product status meets the product standard status.

[0080] The embodiment of the present invention can identify the abnormal factors of the alkali shrinkage machine when the product state does not meet the preset product standard state, and can ensure that the quality of the final product meets the preset standards by identifying and adjusting the factors that cause the abnormal product state, thereby reducing the production of unqualified products. The preset product standard state refers to a set of product quality indicators and performance parameters that are pre-set according to factors such as product quality requirements, process specifications, laws and regulations, and customer needs during the production process. The abnormal factors refer to specific factors that cause the product state to deviate from the preset standard state during the production process, equipment operation or product quality control, such as abnormal operating parameters, equipment performance problems, environmental factors, etc.

[0081] Optionally, as an embodiment of the present invention, when the product state does not conform to a preset product standard state, identifying the abnormal factor of the alkali shrinkage machine can be identified by data analysis technology.

[0082] In the embodiment of the present invention, by adjusting the initial process parameters based on the abnormal factors, the adjusted process parameters can be adjusted to adapt to optimal production conditions, improve the operating efficiency of the production line, and reduce downtime. The adjusted process parameters refer to a series of modifications to the original process parameters during the production process to correct situations where the product status does not meet preset standards.

[0083] As an embodiment of the present invention, adjusting the initial process parameters according to the abnormal factors to obtain the adjusted process parameters includes:

[0084] Analyze the degree of influence of the abnormal factor on the product status corresponding to the abnormal factor;

[0085] Determining adjustment targets and adjustment sequences for the initial process parameters based on the degree of impact;

[0086] defining a parameter optimization algorithm for the initial process parameters, and determining an adjustment range for the initial process parameters according to the parameter optimization algorithm;

[0087] The initial process parameters are adjusted according to the adjustment range, the adjustment target, and the adjustment sequence to obtain adjusted process parameters.

[0088] The degree of impact refers to the specific magnitude and importance of the abnormal factor's impact on the product status or quality. The adjustment target refers to the specific goal or desired condition set during the process parameter adjustment process to improve or optimize the product status. The adjustment sequence refers to the order in which parameters are adjusted according to a certain logic or priority when adjusting process parameters. The parameter optimization algorithm refers to a series of mathematical methods and procedures used to find the optimal process parameter settings in order to optimize a specific objective function within given constraints. The adjustment amplitude refers to the size or degree of change in parameter values ​​when adjusting process parameters.

[0089] Optionally, the parameter optimization algorithm for defining the initial process parameters may be defined by a conjugate gradient method.

[0090] By analyzing the adjusted product state of the processed product based on the adjusted process parameters, embodiments of the present invention can more accurately control the product's size, shape, performance, and reliability, thereby reducing product defects and improving overall product quality. The adjusted product state refers to the new physical, chemical, or performance state achieved by the product after changing the process parameters during the production process.

[0091] In the embodiment of the present invention, when the adjusted product state meets the product standard state, the alkali-treated product of the alkali shrinking machine is output, thereby ensuring that the product meets the predetermined quality standards, reducing product defects and rework rates, lowering the scrap rate, and improving product reliability. The alkali-treated product refers to a material or product that has been treated with an alkaline solution in an alkali shrinking machine (also known as an alkali cleaning machine or alkali treatment equipment).

[0092] The product washing module 104 is used to determine the water washing exchange material of the alkali-treated product, analyze the alkali solution content of the alkali-treated product, calculate the material exchange amount of the water washing exchange material based on the alkali solution content, and wash the alkali-treated product based on the material exchange amount to obtain a water-washed product.

[0093] In the embodiments of the present invention, by determining a water-wash exchange material for the alkali-treated product, alkaline residues on the product surface can be effectively removed, thereby reducing the impact on subsequent process steps. The water-wash exchange material refers to a substance used to exchange or remove residual alkaline solution on the product surface during the water-washing process of the alkali-treated product, such as dilute hydrochloric acid or ammonium sulfate.

[0094] Optionally, as an embodiment of the present invention, the water-wash exchange material of the alkali-treated product may be determined by chemical analysis.

[0095] The embodiment of the present invention can analyze the alkali content of the alkali-treated product to ensure that the product achieves a predetermined treatment effect and meets quality standards by accurately measuring the alkali content. The alkali content refers to the content of alkali attached to the alkali-treated product.

[0096] Optionally, the analysis of the alkali content of the alkali-treated product may be performed by atomic absorption spectroscopy.

[0097] By calculating the mass exchange amount of the wash exchange material based on the alkali solution content, embodiments of the present invention can accurately calculate the required mass exchange amount, ensuring effective alkali solution removal during the wash process and avoiding over- or undertreatment. The mass exchange amount refers to the amount of a substance (the wash exchange material) used to exchange or remove the target substance (in this case, alkali solution) during a chemical or physical treatment process.

[0098] As an embodiment of the present invention, the calculating of the material exchange amount of the water-washing exchange material according to the alkali solution content includes:

[0099] Analyzing the diffusion coefficient of the water-wash exchange material and the wash solution concentration;

[0100] According to the alkali content, analyzing the alkali contamination degree and alkali diffusion distance of the alkali-treated product of the water-wash exchange material;

[0101] The material exchange amount of the water wash exchange material is calculated using the following formula based on the diffusion coefficient, the degree of alkali solution contamination, the alkali solution diffusion distance, and the washing solution concentration:

[0102] Among them, represents the amount of material exchange, represents the diffusion coefficient, represents the diffusion distance of the alkali solution, represents the degree of alkali solution contamination, and represents the concentration of the washing solution.

[0103] The diffusion coefficient describes the rate at which a substance is transported through molecular diffusion in a medium (usually a continuous medium such as a gas, liquid, or solid). The wash solution concentration refers to the amount of active ingredient contained in the wash solution during the washing or cleaning process. The alkali contamination level refers to the concentration of alkali on the product surface. The alkali diffusion path refers to the distance the alkali travels in the alkali-treated product, i.e., the depth or distance the alkali diffuses along the product's internal structure or through the product material from the time it initially contacts the product surface.

[0104] Optionally, the analysis of the diffusion coefficient of the water exchange material and the wash solution concentration can be performed by molecular dynamics simulation.

[0105] In the embodiment of the present invention, by washing the alkali-treated product according to the mass exchange amount, a washed product is obtained. By controlling the washing process, corrosion or performance degradation of the material caused by residual alkali solution can be avoided, thereby improving the long-term stability of the product. The washed product refers to the alkali-treated product after the washing process.

[0106] The fulling control module is used to analyze the fulling requirements of the alkali shrinking machine, configure the fulling liquid of the washed product based on the fulling requirements, calculate the fulling reaction parameters of the washed product, and perform fulling treatment on the washed product based on the fulling reaction parameters and the fulling liquid to obtain the target product.

[0107] The present invention can help avoid excessive or insufficient shrinking by analyzing the shrinking requirements of the alkali shrinking machine, reduce the production of substandard products, and reduce rework rates and material waste. The shrinking requirements refer to a series of technical and process requirements that must be met during the shrinking process to achieve specific product quality and performance goals.

[0108] The embodiment of the present invention can ensure that the feel and appearance of the fabric achieve the expected softness, fullness and coverage by configuring the felting liquid of the washed product based on the felting requirements. The felting liquid refers to a special solution used in the felting process.

[0109] As an embodiment of the present invention, configuring the milling liquid of the washed product based on the milling requirement includes:

[0110] Determining the milling agent, auxiliary agent and softener for the washing product according to the milling requirement;

[0111] Calculating the mass ratio of the milling agent, the milling agent and the softening agent;

[0112] Based on the mass ratio, the milling agent, the milling agent and the softener are mixed to obtain a mixed solvent;

[0113] Analyzing the pH value of the mixed solvent, and adjusting the mixed solvent according to the pH value and a preset pH value threshold to obtain an adjusted solvent;

[0114] The adjusted solvent is diluted according to the concentration requirement corresponding to the milling requirement to obtain a milling liquid.

[0115] The term "fulling agent" refers to a chemical substance used in the fulling treatment of textiles. Its function is to change the properties of fibers through a chemical reaction, causing the surface fibers of the fabric to shrink, thereby increasing the fabric's density, improving its feel and appearance, and enhancing its warmth retention. Examples include sodium hydroxide and sodium sulfate. Auxiliary agents refer to chemical substances used with the fulling agent during the fulling process to enhance the fulling effect, improve the processing, or impart specific properties to the fabric, such as phosphoric acid and phosphates. Softeners refer to a class of chemical substances used to improve the feel, flexibility, and handling properties of materials, such as polyethylene glycol and polyvinyl alcohol. The mass ratio refers to the relative proportions of the fulling agent, auxiliary agent, and softener components, calculated by mass. The term "mixed solvent" refers to a solvent uniformly mixed with the fulling agent, auxiliary agent, and softener. The term "pH value" refers to a measure of the acidity or alkalinity of the mixed solvent. The term "pre-set pH threshold" refers to a pH range or specific point set in advance to achieve the desired effect or ensure process safety. The term "adjusted solvent" refers to a solvent that has reached the pH threshold after acid-base neutralization.

[0116] The embodiment of the present invention can determine the optimal milling process conditions, such as temperature, time, milling agent concentration, pH value, etc., by calculating the milling reaction parameters of the washed product, thereby improving production efficiency and product quality. The milling reaction parameters refer to various condition parameters that affect the milling effect during the milling process.

[0117] Optionally, as an embodiment of the present invention, the calculation of the milling reaction parameters of the washed product can be calculated by computer simulation.

[0118] In the embodiment of the present invention, the washed product is subjected to a milling treatment based on the milling reaction parameters and the milling liquid to obtain a target product, which can reduce errors in the processing process, lower the defective product rate, and improve production efficiency.

[0119] The embodiment of the present invention can automatically identify the material type by constructing a material identification module for the alkali shrinking machine, reduce manual intervention, improve the automation level of the production line, and realize intelligent production; optionally, the embodiment of the present invention can optimize the processing effect of the material by adjusting the alkali solution concentration of the alkali shrinking machine based on the alkali solution concentration requirement using a preset concentration control algorithm, reduce processing defects caused by improper concentration, and lower the defective rate; the embodiment of the present invention can quickly identify process deviations by collecting real-time process data of the alkali shrinking machine based on the process monitoring module, take timely measures to prevent accidents; the embodiment of the present invention can detect the product status when it does not meet the expected When the product is in the standard state set, the abnormal factors of the alkali shrinking machine can be identified and adjusted to ensure that the quality of the final product meets the preset standards and reduce the production of unqualified products. The embodiment of the present invention calculates the material exchange amount of the water-washing exchange material according to the alkali solution content, and can accurately calculate the required material exchange amount to ensure that the water washing process effectively removes the alkali solution and avoids excessive or insufficient treatment. Finally, the embodiment of the present invention performs a shrinking treatment on the water-washed product based on the shrinking reaction parameters and the shrinking liquid to obtain the target product, which can reduce errors in the processing process, reduce the defective rate, and improve production efficiency. Therefore, the present invention can improve the intelligent control effect of the alkali shrinking machine.

[0120] like Figure 2 FIG. 1 is a flow chart of an automatic control method for an alkali shrinking machine according to an embodiment of the present invention. In this embodiment, the automatic control method for the alkali shrinking machine includes:

[0121] Constructing a material identification module for the alkali shrinking machine, identifying the material type of the product to be processed by the alkali shrinking machine based on the material identification module, determining the alkali solution concentration requirement of the alkali shrinking machine based on the material type, and adjusting the alkali solution concentration of the alkali shrinking machine using a preset concentration control algorithm based on the alkali solution concentration requirement;

[0122] Acquiring historical operating data of the alkali shrinking machine, determining initial process parameters of the alkali shrinking machine based on the historical operating data, configuring a sensor network for the alkali shrinking machine, building a process monitoring module for the alkali shrinking machine based on the sensor network, collecting real-time process data of the alkali shrinking machine based on the process monitoring module, and analyzing the product status of the product to be processed based on the real-time process data using a trained product alkali treatment analysis model;

[0123] When the product state does not meet the preset product standard state, identifying the abnormal factors of the alkali shrinkage machine, adjusting the initial process parameters according to the abnormal factors to obtain adjusted process parameters, analyzing the adjusted product state of the product to be processed according to the adjusted process parameters, and outputting the alkali-treated product of the alkali shrinkage machine when the adjusted product state meets the product standard state;

[0124] Determining a water-wash exchange material for the alkali-treated product, analyzing the alkali liquor content of the alkali-treated product, calculating a substance exchange amount of the water-wash exchange material based on the alkali liquor content, and washing the alkali-treated product based on the substance exchange amount to obtain a water-washed product;

[0125] The fulling requirement of the alkali shrinking machine is analyzed, and based on the fulling requirement, the fulling liquid of the washed product is configured, and the fulling reaction parameters of the washed product are calculated. Based on the fulling reaction parameters and the fulling liquid, the washed product is subjected to fulling treatment to obtain a target product.

[0126] In the several embodiments provided by the present invention, it should be understood that the provided systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the module division is merely a logical function division, and actual implementation may employ other division methods.

[0127] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0128] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An automatic control system for an alkali shrink machine, characterized in that: The automatic control system of the alkali shrinking machine includes: an alkali solution concentration analysis module, a product status analysis module, a parameter optimization module, a product washing module and a shrinking control module; The alkali solution concentration analysis module is used to construct a material identification module for the alkali shrinking machine. Based on the material identification module, the module identifies the material type of the product to be processed by the alkali shrinking machine, determines the alkali solution concentration requirement of the alkali shrinking machine according to the material type, and adjusts the alkali solution concentration of the alkali shrinking machine using a preset concentration control algorithm based on the alkali solution concentration requirement. The product status analysis module is used to obtain historical operating data of the alkali shrinking machine, determine initial process parameters of the alkali shrinking machine based on the historical operating data, configure a sensor network for the alkali shrinking machine, build a process monitoring module for the alkali shrinking machine based on the sensor network, collect real-time process data of the alkali shrinking machine based on the process monitoring module, and analyze the product status of the product to be processed based on the real-time process data using a trained product alkali treatment analysis model; The parameter optimization module is configured to, when the product state does not conform to a preset product standard state, identify an abnormality factor of the alkali shrinkage machine, adjust the initial process parameters according to the abnormality factor to obtain an adjusted process parameter, analyze the adjusted product state of the product to be processed according to the adjusted process parameter, and output the alkali-treated product of the alkali shrinkage machine when the adjusted product state conforms to the product standard state; The product washing module is used to determine the washing exchange material of the alkali-treated product, analyze the alkali liquor content of the alkali-treated product, calculate the material exchange amount of the washing exchange material based on the alkali liquor content, and wash the alkali-treated product based on the material exchange amount to obtain a washed product; The fulling control module is used to analyze the fulling requirements of the alkali shrinking machine, configure the fulling liquid of the washed product based on the fulling requirements, calculate the fulling reaction parameters of the washed product, and perform fulling treatment on the washed product based on the fulling reaction parameters and the fulling liquid to obtain the target product.

2. The automatic control system of the alkali shrinkage machine according to claim 1, wherein The material identification module for constructing the alkali shrinking machine includes: Constructing an identification module framework of the alkali shrinking machine and determining a material database of the identification module framework; A data acquisition unit is configured for the identification module framework, and material data of the product to be processed corresponding to the alkali shrinking machine is collected based on the data acquisition unit; defining a data matching algorithm for the recognition module framework, and matching the material data with the material database according to the data matching algorithm to obtain a material matching degree; Determining a material type analysis unit of the recognition module framework according to the material matching degree; The material type analysis unit, the data acquisition unit and the data matching algorithm are integrated into the identification module framework to obtain the material identification module of the alkali shrinking machine.

3. The automatic control system of the alkali shrink machine according to claim 1, wherein The method of adjusting the alkali concentration of the alkali shrink machine by using a preset concentration control algorithm based on the alkali concentration requirement includes: Collecting the real-time alkali solution concentration of the alkali shrinking machine, and calculating the concentration error between the alkali solution concentration requirement and the real-time alkali solution concentration; Determining algorithm parameters of the concentration control algorithm, wherein the algorithm parameters include: a proportional gain coefficient, an integral gain coefficient, and a differential gain coefficient; Calculating a concentration control signal of the alkali shrinkage machine according to the concentration error and the algorithm parameters; The alkali concentration of the alkali shrinkage machine is adjusted according to the concentration control signal.

4. The automatic control system of the alkali shrink machine according to claim 1, wherein Determining the initial process parameters of the alkali shrinkage machine based on the historical working data includes: Preprocessing the historical working data to obtain preprocessed data; Identifying key process parameters of the pre-processed data, and analyzing the influence relationship between the key process parameters and the quality of the corresponding product of the alkali shrinking machine; Calculating correlation coefficients between the key process parameters; Analyzing the interdependence between the key process parameters according to the correlation coefficient; According to the mutual dependence relationship and the influence relationship, the initial process parameters of the alkali shrinkage machine are determined.

5. The automatic control system of the alkali shrinkage machine according to claim 1, wherein: The process monitoring module of the alkali shrinkage machine is constructed based on the sensor network, including: Clarify the monitoring frequency and alarm threshold of the alkali shrinking machine, and build a data processing unit of the alkali shrinking machine; determining a transmission mechanism of the sensor network and the data processing unit according to the monitoring frequency; defining a data processing algorithm for the data processing unit, and determining real-time presentation data for the data processing unit based on the data processing algorithm; Determining a safety early warning mechanism for the alkali shrinkage machine according to the real-time presentation data and the alarm threshold; A data storage library and a system log of the alkali shrinking machine are constructed, and a process monitoring module of the alkali shrinking machine is integrated according to the data storage library, the system log, the transmission mechanism, the data processing unit and the safety early warning mechanism.

6. The automatic control system of the alkali shrinkage machine according to claim 1, wherein: The method of analyzing the product status of the product to be processed based on the real-time process data and utilizing the trained product alkali treatment analysis model comprises: Standardizing the real-time process data to obtain standardized data; extracting data features of the standardized data; Analyzing model parameters of the product alkali treatment analysis model; The product status of the product to be processed is calculated based on the data features and the model parameters.

7. The automatic control system of the alkali shrinkage machine according to claim 1, wherein: The adjusting the initial process parameters according to the abnormal factors to obtain the adjusted process parameters includes: Analyze the degree of influence of the abnormal factor on the product status corresponding to the abnormal factor; Determining adjustment targets and adjustment sequences for the initial process parameters based on the degree of impact; defining a parameter optimization algorithm for the initial process parameters, and determining an adjustment range for the initial process parameters according to the parameter optimization algorithm; The initial process parameters are adjusted according to the adjustment range, the adjustment target, and the adjustment sequence to obtain adjusted process parameters.

8. The automatic control system of the alkali shrink machine according to claim 1, wherein: The method of calculating the material exchange amount of the water-washing exchange material according to the alkali solution content comprises: Analyzing the diffusion coefficient of the water-wash exchange material and the wash solution concentration; According to the alkali content, analyzing the alkali contamination degree and alkali diffusion distance of the alkali-treated product of the water-wash exchange material; The material exchange amount of the water washing exchange material is calculated according to the diffusion coefficient, the degree of contamination of the alkali solution, the diffusion distance of the alkali solution and the concentration of the washing solution.

9. The automatic control system of the alkali shrinkage machine according to claim 1, wherein: The step of configuring the milling liquid for the washed product based on the milling requirement includes: Determining the milling agent, auxiliary agent and softener for the washing product according to the milling requirement; Calculating the mass ratio of the milling agent, the milling agent and the softening agent; Based on the mass ratio, the milling agent, the milling agent and the softener are mixed to obtain a mixed solvent; Analyzing the pH value of the mixed solvent, and adjusting the mixed solvent according to the pH value and a preset pH value threshold to obtain an adjusted solvent; The adjusted solvent is diluted according to the concentration requirement corresponding to the milling requirement to obtain a milling liquid.

10. An automatic control method for an alkali shrinking machine, characterized in that: The method comprises: Constructing a material identification module for the alkali shrinking machine, identifying the material type of the product to be processed by the alkali shrinking machine based on the material identification module, determining the alkali solution concentration requirement of the alkali shrinking machine based on the material type, and adjusting the alkali solution concentration of the alkali shrinking machine using a preset concentration control algorithm based on the alkali solution concentration requirement; Acquiring historical operating data of the alkali shrinking machine, determining initial process parameters of the alkali shrinking machine based on the historical operating data, configuring a sensor network for the alkali shrinking machine, building a process monitoring module for the alkali shrinking machine based on the sensor network, collecting real-time process data of the alkali shrinking machine based on the process monitoring module, and analyzing the product status of the product to be processed based on the real-time process data using a trained product alkali treatment analysis model; When the product state does not meet the preset product standard state, identifying the abnormal factors of the alkali shrinkage machine, adjusting the initial process parameters according to the abnormal factors to obtain adjusted process parameters, analyzing the adjusted product state of the product to be processed according to the adjusted process parameters, and outputting the alkali-treated product of the alkali shrinkage machine when the adjusted product state meets the product standard state; Determining a water-wash exchange material for the alkali-treated product, analyzing the alkali liquor content of the alkali-treated product, calculating a substance exchange amount of the water-wash exchange material based on the alkali liquor content, and washing the alkali-treated product based on the substance exchange amount to obtain a water-washed product; The fulling requirement of the alkali shrinking machine is analyzed, and based on the fulling requirement, the fulling liquid of the washed product is configured, and the fulling reaction parameters of the washed product are calculated. Based on the fulling reaction parameters and the fulling liquid, the washed product is subjected to fulling treatment to obtain a target product.

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