Automatic control system for gray fabric dyeing

Abstract

The invention belongs to the field of dyeing control, relates to a data analysis technology, and aims to solve the problem that an automatic control system for gray fabric dyeing in the prior art cannot directly optimize abnormal links when dyeing is abnormal, in particular to an automatic control system for gray fabric dyeing, which comprises a control platform, the control platform is in communication connection with a processing monitoring module, an operation monitoring module, an optimization analysis module and a storage module; the treatment monitoring module comprises a pretreatment unit, a dyeing treatment unit and a post-treatment unit; the pretreatment unit, the dyeing treatment unit and the post-treatment unit are used for monitoring treatment effects respectively when pretreatment, dyeing treatment and post-treatment of the gray fabric are completed; according to the method, various process treatment effects of the gray fabric in the dyeing process can be monitored and analyzed, reworking is carried out in time when the treatment effects are abnormal, invalid processing in the subsequent process due to the abnormality of the previous process is avoided, and data support is provided for dyeing optimization analysis while the dyeing efficiency is improved.

Description

Technical Field

[0001] The invention belongs to the field of dyeing control, relates to data analysis technology, and specifically is an automatic control system for grey cloth dyeing. Background Art

[0002] The process of grey cloth dyeing includes three stages: pretreatment, dyeing and post-treatment. Pretreatment is mainly to remove impurities and grease on the fabric to ensure that the dye can evenly penetrate into the fabric fibers. The dyeing stage is to contact the fabric with the dye solution so that the dye can penetrate into the fabric fibers and change the color of the fabric. The post-treatment stage is mainly to improve the feel and appearance of the fabric, making the dyed fabric more beautiful and comfortable.

[0003] The grey cloth dyeing automation control system in the prior art generally monitors the dyeing effect after completing the entire dyeing process, but is unable to monitor the processing effect of each link in the dyeing process. As a result, when dyeing is abnormal, it is impossible to directly optimize the abnormal link, resulting in the inability to guarantee dyeing efficiency and dyeing effect.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a grey cloth dyeing automation control system, which is used to solve the problem that the grey cloth dyeing automation control system in the prior art cannot directly optimize the abnormal link when dyeing is abnormal; The technical problem to be solved by the present invention is: how to provide a grey cloth dyeing automation control system which can directly optimize the abnormal links when dyeing is abnormal.

[0006] The purpose of the present invention can be achieved through the following technical solutions: An automatic control system for grey cloth dyeing, comprising a control platform, wherein the control platform is communicatively connected with a processing monitoring module, an operation monitoring module, an optimization analysis module and a storage module; The processing monitoring module is used to monitor and analyze the effects of various process treatments of the grey cloth during the dyeing process. The processing monitoring module includes a pre-processing unit, a dyeing processing unit and a post-processing unit. The pre-processing unit, the dyeing processing unit and the post-processing unit monitor the processing effects when the grey cloth completes pre-processing, dyeing and post-processing respectively. The operation monitoring module is used to monitor and analyze the operation status of the dyeing equipment: generate a monitoring cycle, obtain the number of times the control platform receives a preprocessing abnormal signal, a dyeing abnormal signal, and a post-processing abnormal signal within the monitoring cycle, and mark them as a preprocessing value, a dyeing value, and a post-processing value respectively, mark the sum of the preprocessing value, the dyeing value, and the post-processing value as an abnormal value of the monitoring cycle, mark the ratio of the abnormal value to the number of times the grey cloth dyeing process is completed within the monitoring cycle as an abnormal coefficient of the monitoring cycle, and determine whether the operation status of the dyeing equipment within the monitoring cycle meets the requirements through the abnormal coefficient; The optimization analysis module is used to optimize the dyeing process.

[0007] As a preferred embodiment of the present invention, the specific process of the preprocessing unit monitoring the processing effect includes: taking an image of the preprocessed grey cloth and marking it as a preprocessing image, enlarging the preprocessing image into a pixel grid image and performing grayscale conversion, obtaining the grayscale range corresponding to the type of grey cloth through a storage module and marking it as the preprocessing range, marking the pixel grids whose grayscale values ​​are within the preprocessing range as normal grids, marking the ratio of the number of normal grids to pixel grids as a normal coefficient, obtaining a normal threshold through the storage module, and comparing the normal coefficient of the preprocessing image with the normal threshold: if the normal coefficient is less than the normal threshold, it is determined that the preprocessing effect of the grey cloth does not meet the requirements, a preprocessing abnormality signal is generated and the preprocessing abnormality signal is sent to the control platform; if the normal coefficient is greater than or equal to the normal threshold, it is determined that the preprocessing effect of the grey cloth meets the requirements, a dyeing signal is generated and the dyeing signal is sent to the control platform.

[0008] As a preferred embodiment of the present invention, the specific process of monitoring the processing effect by the dyeing processing unit includes: taking an image of the grey cloth that has completed the dyeing processing and marking it as a dyeing image, enlarging the dyeing image into a pixel grid image and performing a grayscale transformation, obtaining the grayscale range corresponding to the dye through the storage module and marking it as the dyeing range, and then using the same method as the preprocessing unit to determine whether the dyeing effect meets the requirements, and generating a dyeing abnormality signal when the dyeing processing effect does not meet the requirements and sending the dyeing abnormality signal to the control platform; generating a post-processing signal when the dyeing processing effect meets the requirements and sending the post-processing signal to the control platform.

[0009] As a preferred embodiment of the present invention, the specific process of monitoring the processing effect by the post-processing unit includes: taking an image of the post-processed grey cloth and marking it as a post-processing image, enlarging the post-processing image into a pixel grid image and performing a grayscale transformation, obtaining the grayscale range corresponding to the dye through the storage module and marking it as the dyeing range, and then using the same method as the pre-processing unit to determine whether the post-processing effect meets the requirements, and generating a post-processing abnormal signal when the post-processing effect does not meet the requirements and sending the post-processing abnormal signal to the control platform; generating a dyeing completion signal when the post-processing effect meets the requirements and sending the dyeing completion signal to the control platform.

[0010] As a preferred embodiment of the present invention, the specific process of determining whether the operating state of the dyeing equipment during the monitoring period meets the requirements includes: obtaining an abnormal threshold through a storage module, and comparing the abnormal coefficient with the abnormal threshold: if the abnormal coefficient is less than the abnormal threshold, it is determined that the operating state of the dyeing equipment during the monitoring period meets the requirements; if the abnormal coefficient is greater than or equal to the abnormal threshold, it is determined that the operating state of the dyeing equipment during the monitoring period does not meet the requirements, and a value is randomly selected from the pre-processing value, the dyeing value and the post-processing value as the basic value, and the absolute value of the difference between the sum of the remaining two values ​​and the basic value is marked as the deviation value of the basic value, and then the deviation value when the remaining two values ​​are used as the basic values ​​is calculated, and the processing link corresponding to the basic value with the smallest deviation value is marked as an abnormal link. If the abnormal link is a dyeing process, a dyeing optimization signal is generated and the dyeing optimization signal is sent to the optimization analysis module through the control platform; otherwise, a control calibration signal is generated and the control calibration signal is sent to the mobile phone terminal of the administrator through the control platform.

[0011] As a preferred embodiment of the present invention, the specific process of the optimization and analysis module optimizing and analyzing the dyeing processing link includes: classifying the grey cloth according to the raw materials, marking the dye formulas used for the same type of grey cloth as matching objects, marking the number of times the dyeing abnormality signal is received when the corresponding type of grey cloth is dyed with the matching object as the dyeing abnormality value RY, marking the average value of the maximum and minimum values ​​of the dyeing time range corresponding to the matching object as the dyeing standard value JR, and obtaining the optimization coefficient YH of the matching object by numerically calculating the dyeing abnormality value RY and the dyeing standard value JR; marking the matching object with the smallest optimization coefficient YH as the optimized formula of the corresponding type of grey cloth; and then sending the optimized formulas of all types of grey cloth to the storage module through the control platform for storage; at the beginning of the next monitoring cycle, firstly obtain the corresponding optimized formula according to the type of grey cloth, and then dye the grey cloth according to the dye corresponding to the optimized formula.

[0012] As a preferred embodiment of the present invention, the working method of the grey cloth dyeing automatic control system comprises the following steps: Step 1: monitor the pretreatment effect, dyeing effect and post-treatment effect of the grey cloth through the pretreatment unit, dyeing unit and post-treatment unit respectively; Step 2: Monitor and analyze the operating status of the dyeing equipment: generate a monitoring cycle, obtain the number and value of the pre-processing abnormal signal, dyeing abnormal signal and post-processing abnormal signal received by the control platform during the monitoring cycle and mark them as the abnormal value of the monitoring cycle, mark the ratio of the abnormal value to the number of times the grey cloth dyeing process is completed during the monitoring cycle as the abnormal coefficient of the monitoring cycle, and judge whether the operating status of the dyeing equipment during the monitoring cycle meets the requirements through the abnormal coefficient; Step 3: Optimize and analyze the dyeing process: classify the grey cloth according to the raw materials, mark the dye formula used for the same type of grey cloth as matching objects, obtain the dyeing abnormality value RY and the immersion dyeing standard value JR of the matching objects, and perform numerical calculations to obtain the optimization coefficient YH. The optimization coefficient YH is used to screen the optimized formula for the grey cloth type.

[0013] The present invention has the following beneficial effects: 1. The processing monitoring module can monitor and analyze the effects of various process treatments during the dyeing process of the grey cloth. When the grey cloth completes pre-treatment, dyeing and post-treatment, the processing effect is monitored by image processing. When the processing effect is abnormal, rework is carried out in time to avoid invalid processing in the subsequent process due to abnormalities in the previous process, improve dyeing efficiency and provide data support for dyeing optimization analysis; 2. The operation monitoring module can monitor and analyze the operation status of the dyeing equipment. Within the monitoring period, the number of times the control platform receives various abnormal signals is retrieved and numerical analysis is performed to obtain the abnormal coefficient. The overall status of the dyeing equipment is fed back through the abnormal coefficient, and the abnormal links that need to be optimized are screened out in the event of an abnormality, thereby improving the efficiency of abnormality handling. 3. The optimization analysis module can be used to optimize and analyze the dyeing process. The effect and efficiency of dyeing different types of grey fabrics with different dye formulas can be comprehensively analyzed to obtain the optimization coefficient. The formula can be screened based on the optimization coefficient, so as to perform periodic dynamic matching optimization between the grey fabric material and the dye formula. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0015] Figure 1is a system block diagram of Embodiment 1 of the present invention; Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0016] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Embodiment 1 like Figure 1 As shown, a grey cloth dyeing automation control system includes a control platform, and the control platform is communicatively connected with a processing monitoring module, an operation monitoring module, an optimization analysis module and a storage module.

[0018] The processing monitoring module is used to monitor and analyze the effects of various process treatments of the grey cloth during the dyeing process. The processing monitoring module includes a preprocessing unit, a dyeing processing unit and a post-processing unit. The preprocessing unit, the dyeing processing unit and the post-processing unit monitor the processing effects when the grey cloth completes preprocessing, dyeing and post-processing respectively. The specific process of the preprocessing unit monitoring the processing effects includes: taking an image of the grey cloth that has completed preprocessing and marking it as a preprocessing image, amplifying the preprocessing image into a pixel grid image and performing grayscale conversion, obtaining the grayscale range corresponding to the grey cloth type through the storage module and marking it as the preprocessing range, marking the pixel grids whose grayscale values ​​are within the preprocessing range as positive The normal grid is formed, the ratio of the number of normal grids to the number of pixel grids is marked as a normal coefficient, the normal threshold is obtained through the storage module, and the normal coefficient of the preprocessed image is compared with the normal threshold: if the normal coefficient is less than the normal threshold, it is determined that the preprocessing effect of the grey cloth does not meet the requirements, a preprocessing abnormality signal is generated and the preprocessing abnormality signal is sent to the control platform; if the normal coefficient is greater than or equal to the normal threshold, it is determined that the preprocessing effect of the grey cloth meets the requirements, a dyeing signal is generated and the dyeing signal is sent to the control platform; the specific process of the dyeing processing unit performing processing effect monitoring includes: taking an image of the grey cloth that has completed the dyeing process and marking it as a dyeing image, enlarging the dyeing image into a pixel grid image and graying it The grayscale range corresponding to the dye is obtained through the storage module and marked as the dyeing range, and then the dyeing effect is judged in the same way as the pre-processing unit, and when the dyeing treatment effect does not meet the requirements, a dyeing abnormality signal is generated and the dyeing abnormality signal is sent to the control platform; when the dyeing treatment effect meets the requirements, a post-processing signal is generated and the post-processing signal is sent to the control platform; the specific process of the post-processing unit monitoring the treatment effect includes: taking an image of the grey cloth after the treatment and marking it as a post-processing image, enlarging the post-processing image into a pixel grid image and performing grayscale transformation, obtaining the grayscale range corresponding to the dye through the storage module and marking it as the dyeing range, and then Afterwards, the same method as the preprocessing unit is used to determine whether the post-processing effect meets the requirements, and when the post-processing effect does not meet the requirements, a post-processing abnormal signal is generated and the post-processing abnormal signal is sent to the control platform; when the post-processing effect meets the requirements, a dyeing completion signal is generated and the dyeing completion signal is sent to the control platform; the various process treatment effects of the grey cloth in the dyeing process are monitored and analyzed, and the treatment effect is monitored by image processing when the grey cloth completes pretreatment, dyeing and post-processing. When the treatment effect is abnormal, rework is carried out in time to avoid invalid processing in the subsequent process due to abnormalities in the previous process, improve dyeing efficiency and provide data support for dyeing optimization analysis.

[0019] The operation monitoring module is used to monitor and analyze the operation status of the dyeing equipment: generate a monitoring cycle, obtain the number of times the control platform receives the preprocessing abnormal signal, the dyeing abnormal signal and the post-processing abnormal signal during the monitoring cycle, and mark them as the preprocessing value, the dyeing value and the post-processing value respectively, mark the sum of the preprocessing value, the dyeing value and the post-processing value as the abnormal value of the monitoring cycle, mark the ratio of the abnormal value to the number of times the grey cloth dyeing process is completed during the monitoring cycle as the abnormal coefficient of the monitoring cycle, obtain the abnormal threshold through the storage module, and compare the abnormal coefficient with the abnormal threshold: if the abnormal coefficient is less than the abnormal threshold, it is determined that the operation status of the dyeing equipment during the monitoring cycle meets the requirements; if the abnormal coefficient is greater than or equal to the abnormal threshold, it is determined that the operation status of the dyeing equipment during the monitoring cycle does not meet the requirements, and a random value is selected among the preprocessing value, the dyeing value and the post-processing value. A value is selected as the basic value, and the absolute value of the difference between the sum of the remaining two values ​​and the basic value is marked as the deviation value of the basic value. Then, the deviation value when the remaining two values ​​are used as the basic value is calculated, and the processing link corresponding to the basic value with the smallest deviation value is marked as the abnormal link. If the abnormal link is dyeing processing, a dyeing optimization signal is generated and sent to the optimization analysis module through the control platform; otherwise, a control calibration signal is generated and sent to the mobile phone terminal of the manager through the control platform; the operating status of the dyeing equipment is monitored and analyzed, and the number of times the control platform receives various abnormal signals within the monitoring period is retrieved and numerically analyzed to obtain the abnormal coefficient. The overall status of the dyeing equipment is fed back through the abnormal coefficient, and the abnormal links that need to be optimized are screened out in the event of an abnormality, thereby improving the efficiency of abnormal processing.

[0020] The optimization analysis module is used to optimize the dyeing process: the grey cloth is classified according to the raw materials, the dye formula used for the same type of grey cloth is marked as the matching object, the number of times the dyeing abnormality signal is received when the corresponding type of grey cloth is dyed with the matching object is marked as the dyeing abnormality value RY, and the average value of the maximum and minimum values ​​of the dyeing time range corresponding to the matching object is marked as the dyeing standard value JR. The optimization coefficient YH of the matching object is obtained by the formula YH=α1*RY+α2*JR, where α1 and α2 are both proportional coefficients, and α1>α2>1; the optimization coefficient YH is minimized. The matching object is marked as the optimized formula of the corresponding type of grey cloth; then the optimized formula of all types of grey cloth is sent to the storage module through the control platform for storage; at the beginning of the next monitoring cycle, the corresponding optimized formula is first obtained according to the type of grey cloth, and then the grey cloth is dyed according to the dye corresponding to the optimized formula; the dyeing process is optimized and analyzed, and the effect and efficiency of dyeing different types of grey cloth with different dye formulas are comprehensively analyzed to obtain the optimization coefficient, and the optimized formula is screened according to the optimization coefficient, so as to perform periodic dynamic matching optimization of the grey cloth material and the dye formula.

[0021] When the grey cloth is dyed with the dye corresponding to the optimized formula, the optimal range of dyeing process parameters such as dyeing temperature and dyeing water level corresponding to the optimized formula can be optimized and analyzed according to the receiving state of dyeing abnormality signals when the grey cloth is dyed at different temperatures and water levels. Then, the dyeing temperature, dyeing water level and other parameters are collected by temperature sensors and liquid level sensors before dyeing, and the collected data are compared with the optimal range. Dyeing is not performed until the collected data is within the optimal range, thereby further improving dyeing efficiency and dyeing effect.

[0022] Embodiment 2 like Figure 2 As shown, a method for controlling the automatic dyeing of grey cloth comprises the following steps: Step 1: monitor the pretreatment effect, dyeing effect and post-treatment effect of the grey cloth through the pretreatment unit, dyeing unit and post-treatment unit respectively; Step 2: Monitor and analyze the operating status of the dyeing equipment: generate a monitoring cycle, obtain the number and value of the pre-processing abnormal signal, dyeing abnormal signal and post-processing abnormal signal received by the control platform during the monitoring cycle and mark them as the abnormal value of the monitoring cycle, mark the ratio of the abnormal value to the number of times the grey cloth dyeing process is completed during the monitoring cycle as the abnormal coefficient of the monitoring cycle, and judge whether the operating status of the dyeing equipment during the monitoring cycle meets the requirements through the abnormal coefficient; Step 3: Optimize and analyze the dyeing process: classify the grey cloth according to the raw materials, mark the dye formula used for the same type of grey cloth as matching objects, obtain the dyeing abnormality value RY and the immersion dyeing standard value JR of the matching objects, and perform numerical calculations to obtain the optimization coefficient YH. The optimization coefficient YH is used to screen the optimized formula for the grey cloth type.

[0023] The invention discloses an automatic control system for grey cloth dyeing. When working, the pretreatment effect, dyeing effect and post-treatment effect of the grey cloth are monitored through a pretreatment unit, a dyeing unit and a post-treatment unit respectively. A monitoring cycle is generated, the number and value of the pretreatment abnormality signal, the dyeing abnormality signal and the post-treatment abnormality signal received by the control platform in the monitoring cycle are obtained and marked as the abnormal value of the monitoring cycle, the ratio of the abnormal value to the number of times the grey cloth dyeing process is completed in the monitoring cycle is marked as the abnormal coefficient of the monitoring cycle, and whether the operation state of the dyeing equipment in the monitoring cycle meets the requirements is judged by the abnormal coefficient; the grey cloth is classified according to the raw materials, the dye formula used for the same type of grey cloth is marked as a matching object, the dyeing abnormality value RY and the immersion dyeing standard value JR of the matching object are obtained and numerical calculation is performed to obtain the optimization coefficient YH, and the optimization formula of the grey cloth type is screened by the optimization coefficient YH.

[0024] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0025] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula YH=α1*RY+α2*JR; technicians in this field collect multiple groups of sample data and set corresponding optimization coefficients for each group of sample data; substitute the set optimization coefficients and the collected sample data into the formula, any three formulas constitute a three-variable linear equation group, screen the calculated coefficients and take the average, and obtain the values ​​of α1 and α2 as 3.25 and 2.47 respectively; The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the initial setting of the corresponding optimization coefficient for each group of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the optimization coefficient is proportional to the value of the staining outlier.

[0026] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0027] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An automatic control system for grey cloth dyeing, characterized in that: It includes a control platform, which is communicatively connected with a processing monitoring module, an operation monitoring module, an optimization analysis module and a storage module; The processing monitoring module is used to monitor and analyze the effects of various process treatments of the grey cloth during the dyeing process. The processing monitoring module includes a pre-processing unit, a dyeing processing unit and a post-processing unit. The pre-processing unit, the dyeing processing unit and the post-processing unit monitor the processing effects when the grey cloth completes pre-processing, dyeing and post-processing respectively. The operation monitoring module is used to monitor and analyze the operation status of the dyeing equipment: generate a monitoring cycle, obtain the number of times the control platform receives a preprocessing abnormal signal, a dyeing abnormal signal, and a post-processing abnormal signal within the monitoring cycle, and mark them as a preprocessing value, a dyeing value, and a post-processing value respectively, mark the sum of the preprocessing value, the dyeing value, and the post-processing value as an abnormal value of the monitoring cycle, mark the ratio of the abnormal value to the number of times the grey cloth dyeing process is completed within the monitoring cycle as an abnormal coefficient of the monitoring cycle, and determine whether the operation status of the dyeing equipment within the monitoring cycle meets the requirements through the abnormal coefficient; The optimization analysis module is used to optimize the dyeing process.

2. The automatic control system for grey cloth dyeing according to claim 1, characterized in that: The specific process of the preprocessing unit monitoring the processing effect includes: taking an image of the preprocessed grey cloth and marking it as a preprocessing image, enlarging the preprocessing image into a pixel grid image and performing grayscale conversion, obtaining the grayscale range corresponding to the grey cloth type through the storage module and marking it as the preprocessing range, marking the pixel grids whose grayscale values ​​are within the preprocessing range as normal grids, marking the ratio of the number of normal grids to pixel grids as a normal coefficient, obtaining the normal threshold through the storage module, and comparing the normal coefficient of the preprocessing image with the normal threshold: if the normal coefficient is less than the normal threshold, it is determined that the preprocessing effect of the grey cloth does not meet the requirements, a preprocessing abnormality signal is generated and the preprocessing abnormality signal is sent to the control platform; if the normal coefficient is greater than or equal to the normal threshold, it is determined that the preprocessing effect of the grey cloth meets the requirements, a dyeing signal is generated and the dyeing signal is sent to the control platform.

3. The automatic control system for grey cloth dyeing according to claim 2, characterized in that: The specific process of the dyeing processing unit to monitor the processing effect includes: taking an image of the grey cloth that has completed the dyeing process and marking it as a dyeing image, enlarging the dyeing image into a pixel grid image and performing a grayscale transformation, obtaining the grayscale range corresponding to the dye through the storage module and marking it as the dyeing range, and then using the same method as the preprocessing unit to determine whether the dyeing effect meets the requirements, and generating a dyeing abnormality signal when the dyeing processing effect does not meet the requirements and sending the dyeing abnormality signal to the control platform; generating a post-processing signal when the dyeing processing effect meets the requirements and sending the post-processing signal to the control platform.

4. The automatic control system for grey cloth dyeing according to claim 3, characterized in that: The specific process of monitoring the processing effect by the post-processing unit includes: taking an image of the post-processed grey cloth and marking it as a post-processing image, enlarging the post-processing image into a pixel grid image and performing grayscale transformation, obtaining the grayscale range corresponding to the dye through the storage module and marking it as the dyeing range, and then using the same method as the pre-processing unit to determine whether the post-processing effect meets the requirements, and generating a post-processing abnormal signal when the post-processing effect does not meet the requirements and sending the post-processing abnormal signal to the control platform; generating a dyeing completion signal when the post-processing effect meets the requirements and sending the dyeing completion signal to the control platform.

5. The automatic control system for grey cloth dyeing according to claim 4, characterized in that: The specific process of determining whether the operating status of the dyeing equipment during the monitoring period meets the requirements includes: obtaining the abnormal threshold through the storage module, and comparing the abnormal coefficient with the abnormal threshold: if the abnormal coefficient is less than the abnormal threshold, it is determined that the operating status of the dyeing equipment during the monitoring period meets the requirements; if the abnormal coefficient is greater than or equal to the abnormal threshold, it is determined that the operating status of the dyeing equipment during the monitoring period does not meet the requirements, and a value is randomly selected from the pre-processing value, the dyeing value and the post-processing value as the basic value, and the absolute value of the difference between the sum of the remaining two values ​​and the basic value is marked as the deviation value of the basic value, and then the deviation value when the remaining two values ​​are used as the basic values ​​is calculated, and the processing link corresponding to the basic value with the smallest deviation value is marked as an abnormal link. If the abnormal link is dyeing processing, a dyeing optimization signal is generated and the dyeing optimization signal is sent to the optimization analysis module through the control platform; otherwise, a control calibration signal is generated and the control calibration signal is sent to the mobile terminal of the manager through the control platform.

6. The automatic control system for grey cloth dyeing according to claim 5, characterized in that: The specific process of the optimization analysis module optimizing and analyzing the dyeing process includes: classifying the grey cloth according to the raw materials, marking the dye formula used for the same type of grey cloth as matching objects, marking the number of times the abnormal dyeing signal is received when the corresponding type of grey cloth is dyed with the matching object as the abnormal dyeing value RY, marking the average value of the maximum and minimum values ​​of the dyeing time range corresponding to the matching object as the dyeing standard value JR, and obtaining the optimization coefficient YH of the matching object by numerically calculating the abnormal dyeing value RY and the dyeing standard value JR; marking the matching object with the smallest optimization coefficient YH as the optimized formula of the corresponding type of grey cloth; and then sending the optimized formula of all types of grey cloth to the storage module through the control platform for storage; at the beginning of the next monitoring cycle, first obtain the corresponding optimized formula according to the type of grey cloth, and then dye the grey cloth according to the dye corresponding to the optimized formula.

7. An automatic control system for grey cloth dyeing according to any one of claims 1 to 6, characterized in that: The working method of the grey cloth dyeing automatic control system comprises the following steps: Step 1: monitor the pretreatment effect, dyeing effect and post-treatment effect of the grey cloth through the pretreatment unit, dyeing unit and post-treatment unit respectively; Step 2: Monitor and analyze the operating status of the dyeing equipment: generate a monitoring cycle, obtain the number and value of the pre-processing abnormal signal, dyeing abnormal signal and post-processing abnormal signal received by the control platform during the monitoring cycle and mark them as the abnormal value of the monitoring cycle, mark the ratio of the abnormal value to the number of times the grey cloth dyeing process is completed during the monitoring cycle as the abnormal coefficient of the monitoring cycle, and judge whether the operating status of the dyeing equipment during the monitoring cycle meets the requirements through the abnormal coefficient; Step 3: Optimize and analyze the dyeing process: classify the grey cloth according to the raw materials, mark the dye formula used for the same type of grey cloth as matching objects, obtain the dyeing abnormality value RY and the immersion dyeing standard value JR of the matching objects, and perform numerical calculations to obtain the optimization coefficient YH. The optimization coefficient YH is used to screen the optimized formula for the grey cloth type.

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