Intelligent control system and method for electrogalvanizing pre-plating impurity removal

Abstract

The invention discloses an intelligent control system and method for pre-plating impurity removal of electrogalvanizing, and belongs to the technical field of intelligent control of pre-plating impurity removal. The system comprises a bubble influence correction module, a pre-plating state optimization module, a workpiece thickness adjustment module and a plating solution component impurity removal module. The measurement result of the thickness gauge is dynamically corrected according to the bubble influence parameters in the pre-plating process, and the influence of generated bubbles on the accuracy of the measurement result of the thickness gauge is reduced; pre-plating state optimization treatment is conducted according to pre-plating state parameters in the pre-plating process, and the influence of plating solution quality fluctuation on the plating solution performance and the pre-plating layer quality is reduced; anode configuration is dynamically optimized according to the thickness of the workpiece at each position point, and the influence of the thickness of the workpiece at each position point on the uniformity of the pre-plating layer is reduced; and auxiliary impurity removal is carried out according to the components of the pre-plated plating solution, and the plating thickness measurement accuracy is improved by solving the problems of bubble attachment and air gaps of the plating solution, so that the evaluation and control of the pre-plating quality are optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of pre-plating impurity removal intelligent control, and in particular to an intelligent control system and method for electrogalvanizing pre-plating impurity removal. Background Art

[0002] Pre-plating zinc cleaning involves a series of cleaning and treatment steps prior to zinc plating to remove impurities, oxides, oil, and other contaminants from the metal surface to ensure the quality and adhesion of the coating. Pre-plating cleaning typically includes pickling, degreasing, and rust removal. During the pre-plating process, a layer of metal is electroplated onto the substrate using a plating solution to further clean and activate the metal surface.

[0003] Existing intelligent control methods for pre-plating impurity removal in electrogalvanizing usually use integrated sensors to monitor parameters such as the temperature, acidity, current density, and metal ion concentration of the plating solution in real time. Based on the sensor data, the plating current, voltage, and plating solution composition are automatically adjusted to achieve precise metal deposition. The electroplating process is then optimized through data analysis, anomalies are identified, and the process is automatically adjusted to ensure the impurity removal effect and stable coating quality.

[0004] For example, the patent application with publication number CN118859862A discloses an intelligent control method and system for vacuum coating equipment, which includes: a first acquisition unit, a second acquisition unit, a preprocessing unit, a data calculation unit, a data processing unit, a data analysis unit and an execution unit. Through the coordinated work of multiple units, the vacuum coating equipment is monitored and adjusted in all directions, and data processing and analysis technology is used to enable the equipment to be intelligently adjusted according to real-time production data and performance status.

[0005] For example, the patent application with publication number CN115755800A discloses a cyanide-free cadmium-titanium electroplating process automation control system, which includes: a control subsystem, and a pH monitoring subsystem, a pH control subsystem, a sample pretreatment subsystem, a titration subsystem, and an EDTA and NTA concentration control subsystem, all of which are connected to the control subsystem. The sample pretreatment subsystem is connected to the electroplating operation subsystem and the titration subsystem respectively, and the pH monitoring subsystem, the pH control subsystem, and the EDTA and NTA concentration control subsystem are all connected to the electroplating operation subsystem.

[0006] However, in the process of implementing the technical solutions of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the existing technology, during the impurity removal process of electrogalvanizing pre-plating, the thickness of the pre-plating layer will directly affect the quality and performance of the coating. However, when using a thickness gauge to obtain the thickness of the pre-plating layer, bubbles in the plating solution may adhere to the surface of the coating or between the thickness gauge probe and the workpiece, forming an air gap, causing the thickness gauge to be unable to accurately contact the coating surface, thereby affecting the thickness gauge's accurate measurement of the pre-plating thickness, and further affecting the evaluation and control of the pre-plating quality. Summary of the Invention

[0008] The embodiments of the present application provide an intelligent control system and method for electrogalvanizing pre-plating impurity removal, which solves the problem in the prior art that during the electrogalvanizing pre-plating impurity removal process, the thickness of the pre-plated layer directly affects the quality and performance of the coating. However, when using a thickness gauge to obtain the thickness of the pre-plated layer, bubbles in the plating solution may adhere to the coating surface or between the thickness gauge probe and the workpiece, forming an air gap, which makes it impossible for the thickness gauge to accurately contact the coating surface, thereby affecting the thickness gauge's accurate measurement of the pre-plated layer thickness, and further affecting the evaluation and control of the pre-plating quality. By solving the problems of plating solution bubble attachment and air gap, the accuracy of the coating thickness measurement is improved, thereby optimizing the evaluation and control of the pre-plating quality.

[0009] An embodiment of the present application provides an intelligent control system for electrogalvanizing pre-plating impurity removal, comprising: a bubble influence correction module, a pre-plating state optimization module, a workpiece thickness adjustment module, a plating solution component impurity removal module, and a pre-plating impurity removal database; wherein the bubble influence correction module is used to dynamically correct the thickness gauge measurement result according to the bubble influence parameter during the pre-plating process to obtain the workpiece thickness at each position point, and the dynamic correction of the thickness gauge measurement result is used to reduce the influence of the generated bubbles on the accuracy of the thickness gauge measurement result; the pre-plating state optimization module is used to perform pre-plating state optimization processing according to the pre-plating state parameter during the pre-plating process, and the pre-plating state optimization processing is used to reduce the influence of plating solution quality fluctuation on plating solution performance and pre-plating layer quality; the workpiece thickness adjustment module is used to dynamically optimize the anode configuration according to the workpiece thickness at each position point, and the dynamic optimization of the anode configuration is used to reduce the influence of the workpiece thickness at each position point on the uniformity of the pre-plating layer; the plating solution component impurity removal module is used to perform auxiliary impurity removal according to the plating solution composition after pre-plating.

[0010] The embodiment of the present application also provides an intelligent control method for impurity removal in electrogalvanizing pre-plating, including: dynamically correcting the thickness gauge measurement result according to the bubble influencing parameters during the pre-plating process to obtain the thickness of the workpiece at each position point, and the dynamic correction of the thickness gauge measurement result is used to reduce the influence of the generated bubbles on the accuracy of the thickness gauge measurement result; performing pre-plating state optimization processing according to the pre-plating state parameters during the pre-plating process, and the pre-plating state optimization processing is used to reduce the influence of plating solution quality fluctuations on plating solution performance and pre-plating layer quality; dynamically optimizing the anode configuration according to the workpiece thickness at each position point, and dynamically optimizing the anode configuration is used to reduce the influence of the workpiece thickness at each position point on the uniformity of the pre-plating layer; and performing auxiliary impurity removal according to the composition of the plating solution after pre-plating.

[0011] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0012] 1. The present invention provides an intelligent control system and method for impurity removal in electrogalvanizing pre-plating, thereby achieving precise control of bubble influence, pre-plating status, workpiece thickness and plating solution composition, ensuring the stability and consistency of the coating quality, and further achieving high efficiency, precision and controllability of the electrogalvanizing pre-plating process, thereby improving the production efficiency during pre-plating and the process quality after pre-plating.

[0013] 2. The present invention corrects the measurement results of the thickness gauge through bubble influence parameters, ensuring the accuracy and reliability of the measurement data, thereby effectively eliminating the interference of bubbles on the workpiece thickness measurement, reducing the error caused by bubbles, and further realizing the precise measurement of the workpiece thickness at each position point, optimizing the quality control in the electroplating process, and improving the stability of the production process and the consistency of the workpiece.

[0014] 3. The present invention optimizes the pre-plating state parameters to effectively adjust the main salt concentration, plating solution temperature and current density, avoiding performance fluctuations caused by process fluctuations or plating solution quality problems, thereby improving the stability and accuracy of the production process, and further achieving stable control of the workpiece surface quality, thereby improving the overall efficiency and consistency of the electroplating process.

[0015] 4. The present invention adjusts and feeds back the pre-plating quality through the thickness of the workpiece at each position, can adjust the anode spacing and pre-plating state parameters in real time, effectively control the consistency of the workpiece surface thickness, thereby reducing thickness deviation and ensuring the formation of a uniform coating, thereby minimizing the thickness difference in the production process and improving the quality stability and production efficiency of the workpiece. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic structural diagram of an intelligent control system for electrogalvanizing pre-plating impurity removal provided in an embodiment of the present application.

[0017] Figure 2 A mind map of the bubble impact correction module provided in an embodiment of the present application.

[0018] Figure 3 A mind map of the pre-plating state optimization and workpiece thickness adjustment modules provided in the embodiments of the present application.

[0019] Figure 4 A mind map of the plating solution component impurity removal module provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] The embodiment of the present application provides an intelligent control system and method for electrogalvanizing pre-plating impurity removal, which solves the problem in the prior art that in the electrogalvanizing pre-plating impurity removal process, the thickness of the pre-plated layer directly affects the quality and performance of the plating layer. However, when using a thickness gauge to obtain the thickness of the pre-plated layer, bubbles in the plating solution may adhere to the surface of the plating layer or between the thickness gauge probe and the workpiece, forming an air gap, which makes it impossible for the thickness gauge to accurately contact the surface of the plating layer, thereby affecting the thickness gauge's accurate measurement of the thickness of the pre-plating layer, and further affecting the evaluation and control of the pre-plating quality. The thickness of the workpiece at each position point is obtained by dynamically correcting the thickness gauge measurement result according to the bubble influencing parameters during the pre-plating process; the pre-plating state is optimized according to the pre-plating state parameters during the pre-plating process; the anode configuration is dynamically optimized according to the thickness of the workpiece at each position point; and auxiliary impurities are removed according to the plating solution composition after pre-plating. By solving the problems of bubble attachment and air gap in the plating solution, the accuracy of the plating thickness measurement is improved, thereby optimizing the evaluation and control of the pre-plating quality.

[0021] The technical solution in the embodiment of the present application is to solve the above-mentioned problem that the thickness of the pre-plating layer directly affects the quality and performance of the coating during the impurity removal process of the electrogalvanizing pre-plating. However, when using a thickness gauge to obtain the thickness of the pre-plating layer, bubbles in the plating solution may adhere to the surface of the coating or between the thickness gauge probe and the workpiece, forming an air gap, causing the thickness gauge to be unable to accurately contact the coating surface, thereby affecting the thickness gauge's accurate measurement of the pre-plating thickness, and further affecting the evaluation and control of the pre-plating quality. The overall idea is as follows:

[0022] Precise optimization of the electrogalvanizing pre-plating process is achieved through multi-dimensional intelligent control: first, the thickness gauge data is dynamically corrected based on the bubble influence parameters to eliminate bubble interference and obtain the accurate workpiece thickness at each location; second, the process is optimized based on the real-time monitored pre-plating state parameters, and the plating bath performance is stabilized by graded adjustment of the main salt replenishment, temperature control, and current compensation; then, the anode spacing configuration is dynamically adjusted based on the thickness measurement results, specifically increasing the thick area spacing and reducing the thin area spacing to improve the uniformity of the coating; finally, targeted impurity removal is implemented in combination with the plating bath composition analysis, maintaining the purity of the plating bath through metal impurity replacement, organic pollutant adsorption, and suspended matter filtration. The bubble influence correction module obtains the precise workpiece thickness by dynamically correcting the thickness gauge data, providing key input parameters for the pre-plating state optimization module, ensuring that the impact of plating bath quality fluctuations on the process is offset in real time; at the same time, after the pre-plating state optimization module stabilizes the plating bath composition, the workpiece thickness adjustment module can achieve uniform thickness distribution by dynamically adjusting the anode configuration based on uniform plating bath performance. Through the closed-loop control of "measurement-correction-optimization-purification", the system simultaneously solves the four core problems of bubble interference, process fluctuations, uneven thickness and plating solution contamination, and achieves a coordinated improvement in pre-plating quality and process stability.

[0023] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0024] like Figure 1 As shown, it is a structural schematic diagram of an intelligent control system for electrogalvanizing pre-plating impurity removal provided by an embodiment of the present application. The intelligent control system for electrogalvanizing pre-plating impurity removal provided by an embodiment of the present application includes: a bubble influence correction module, a pre-plating state optimization module, a workpiece thickness adjustment module, a plating solution component impurity removal module and a pre-plating impurity removal database; wherein the bubble influence correction module is used to dynamically correct the thickness gauge measurement result according to the bubble influence parameter during the pre-plating process to obtain the workpiece thickness at each position point, and the dynamic correction of the thickness gauge measurement result is used to reduce the influence of the generated bubbles on the accuracy of the thickness gauge measurement result; the pre-plating state optimization module is used to perform pre-plating state optimization processing according to the pre-plating state parameter during the pre-plating process, and the pre-plating state optimization processing is used to reduce the influence of plating solution quality fluctuation on plating solution performance and pre-plating layer quality; the workpiece thickness adjustment module is used to dynamically optimize the anode configuration according to the workpiece thickness at each position point, and the dynamic optimization of the anode configuration is used to reduce the influence of the workpiece thickness at each position point on the uniformity of the pre-plating layer; the plating solution component impurity removal module is used to perform auxiliary impurity removal according to the plating solution composition after pre-plating.

[0025] In addition, the pre-plating impurity removal database is used to store relevant data of the intelligent control system based on electrogalvanizing pre-plating impurity removal, including: critical bubble number, critical average bubble size and critical bubble density, bubble impact first threshold and bubble impact second threshold, etc. The data in the pre-plating impurity removal database can be obtained by directly querying from relevant public databases such as the electrogalvanizing technology platform or the electrogalvanizing academic resource platform, or through cooperation with electroplating production enterprises or universities, scientific research institutions and other industries engaged in electroplating technology research.

[0026] In this embodiment, the bubble impact correction module compensates for thickness measurement data by real-time monitoring of bubble impact parameters, eliminating bubble interference on thickness measurement and improving measurement accuracy. The pre-plating state optimization module dynamically adjusts based on pre-plating state parameters to reduce the impact of bath quality fluctuations, stabilize bath performance, and improve pre-plating quality. The workpiece thickness adjustment module intelligently adjusts anode layout and current distribution based on workpiece thickness data at each location to improve pre-plating uniformity. The bath component removal module analyzes bath composition and specifically removes impurity ions and contaminants, purifying the bath and improving subsequent coating quality. Through multi-parameter coordinated control and intelligent optimization, this system comprehensively improves pre-plating quality and consistency.

[0027] like Figure 2The figure shows a mind map of the bubble influence correction module provided in an embodiment of the present application. The steps of dynamically correcting the thickness gauge measurement results according to the bubble influence parameters during the pre-plating process to obtain the workpiece thickness at each location include: first, quantifying the influence of bubbles on the accuracy of the thickness gauge measurement results according to the bubble influence parameters to obtain a bubble influence index. The bubble influence parameters include the number of bubbles, average bubble size, and bubble density. The bubble influence index represents quantitative data on the degree of influence of the bubble influence parameters on the accuracy of the thickness gauge measurement results.

[0028] Among them, the steps of quantifying the influence of bubbles on the accuracy of the thickness gauge measurement results according to the bubble influence parameters and obtaining the bubble influence index include: obtaining bubble influence parameter reference data from a preset pre-plating impurity removal database, specifically including: critical bubble number, critical average bubble size and critical bubble density; performing a proportion approximation operation on the bubble number, average bubble size and bubble density with the critical bubble number, critical average bubble size and critical bubble density respectively, and using the bubble influence parameter influence factors to weight the proportion approximation operation results respectively, and then coupling the weighted processing results to obtain the bubble influence index, and the bubble influence parameter influence factors include bubble number influence factor, average bubble size influence factor and bubble density influence factor.

[0029] The bubble influence index is obtained as follows:

[0030]

[0031] Where BI represents the bubble influence index, α1 represents the bubble number influence factor, α2 represents the average bubble size influence factor, α3 represents the bubble density influence factor, BN1 represents the bubble number, BN0 represents the critical bubble number, BS1 represents the average bubble size, BS0 represents the critical average bubble size, BD1 represents the bubble density, and BD0 represents the critical bubble density.

[0032] α1, α2 and α3 are the influence factors corresponding to the number of bubbles, average bubble size and bubble density preset in the pre-plating impurity removal database, respectively. These influence factors are numerical indicators that measure the influence of the above-mentioned bubble influence parameters on the bubble influence index. Specifically, there is a mapping relationship table for each bubble number, average bubble size and bubble density, which records each possible bubble influence parameter value and its corresponding influence factor. These mapping relationships can be one-to-one or many-to-one. For example, in actual applications, when it is necessary to evaluate the bubble influence index, the measured number of bubbles, average bubble size and bubble density can be input into their respective corresponding mapping relationship tables, and the influence factors corresponding to these values ​​can be quickly found, where the value range of the influence factor is between 0 and 1.

[0033] Then, a first bubble impact threshold and a second bubble impact threshold are obtained from a preset pre-plating impurity removal database. The first bubble impact threshold is a preset critical value that defines the degree of bubble impact on the pre-plating process as being within a relatively low and tolerable range. The second bubble impact threshold is a preset critical value that indicates that the impact of bubbles on the pre-plating process has reached a relatively serious level and exceeds the tolerable limit of the process. The two together constitute a hierarchical judgment system, which divides the degree of bubble impact into three intervals. The bubble impact index is compared with the first bubble impact threshold and the second bubble impact threshold respectively. If the bubble impact index is not greater than the first bubble impact threshold, the pre-plating state optimization process is directly performed. If the bubble impact index is greater than the first bubble impact threshold and not greater than the second bubble impact threshold, a deviation bubble impact index is obtained based on the second bubble impact threshold and the bubble impact index. The deviation bubble impact index is matched with the thickness gauge measurement result correction value corresponding to each deviation bubble impact index interval preset in the pre-plating impurity removal database to obtain the thickness gauge measurement result correction value corresponding to the deviation bubble impact index. The thickness gauge measurement result correction value is summed with the thickness gauge measurement data to obtain the corrected thickness gauge measurement result. Among them, in the pre-plating impurity removal database, each deviation bubble influence index and the thickness gauge measurement result correction value are mapped one by one to form a mapping relationship table, and the table records each deviation bubble influence index and its corresponding thickness gauge measurement result correction value. These relationships can be one-to-one or many-to-one. When obtaining the thickness gauge measurement result correction value, it is only necessary to input the deviation bubble influence index into the mapping relationship table, and the pre-plating impurity removal database can quickly locate and return the thickness gauge measurement result correction value corresponding to the deviation bubble influence index.

[0034] If the bubble impact index is greater than the second bubble impact threshold, the bubble removal device is turned on, including turning on the vacuum pump to reduce the plating solution pressure and using ultrasonic equipment to use ultrasonic vibrations to break the bubbles so that the bubbles are discharged from the plating solution, and when the monitored bubble impact index is not greater than the second bubble impact threshold, the bubble removal device is turned off.

[0035] In this embodiment, the number of bubbles can be determined by real-time monitoring of the plating solution using sensors such as a bubble counter. The average bubble size can be determined by directly measuring the bubble size in the plating solution using a laser particle size analyzer or by using a high-speed camera to capture the bubble morphology and measure the bubble size in the image, and then calculating the average value. The bubble size is the average bubble size. The bubble density can be determined by comparing the number of bubbles with the total volume of the plating solution. The three are interrelated. For example, the number of bubbles directly affects the bubble density: the greater the number of bubbles, the higher the bubble density per unit volume. The greater the number of small bubbles per unit volume, the higher the bubble density may be, but this may result in a faster rise rate and a smaller surface contact area. The bubble impact index, derived from a comprehensive analysis, can reflect the combined impact of bubbles on reaction efficiency, mass transfer efficiency, and gas solubility. By monitoring and correcting the bubble impact in real time during the electroplating process, unstable production processes caused by bubble interference can be avoided. Using the bubble impact index to precisely control bubble parameters can ensure product quality stability and avoid unevenness or surface defects.

[0036] like Figure 3 The figure shows a mind map of the pre-plating state optimization and workpiece thickness adjustment module provided in an embodiment of the present application. The steps of optimizing the pre-plating state according to the pre-plating state parameters during the pre-plating process include: first, quantifying the effect of the plating solution state on the pre-plating efficiency according to the pre-plating state parameters to obtain a pre-plating state index. The pre-plating state parameters include current density, plating solution temperature, and plating solution concentration. The pre-plating state index represents quantitative data on the degree of influence of the pre-plating state parameters on the quality of the pre-plating layer and the performance of the plating solution.

[0037] Among them, the steps of quantifying the influence of the plating solution state on the pre-plating efficiency according to the pre-plating state parameters and obtaining the pre-plating state index include: obtaining pre-plating state parameter reference data from a preset pre-plating impurity removal database, specifically including: reference current density, allowable deviation current density, reference plating solution temperature, allowable deviation plating solution temperature, reference plating solution concentration and allowable deviation plating solution concentration; performing relative deviation compliance calculation on the current density and the reference current density and the allowable deviation current density, and then using the current density influencing factor to perform weighted calculation on the deviation compliance calculation result to obtain the current density influencing parameter; and performing relative deviation compliance calculation on the plating solution temperature and the allowable deviation current density. A relative deviation compliance calculation is performed on the reference plating solution temperature and the allowable deviation plating solution temperature, and then the plating solution temperature influence factor is used to perform a weighted calculation on the deviation compliance calculation result to obtain the plating solution temperature influence parameter; a relative deviation compliance calculation is performed on the plating solution concentration and the reference plating solution concentration and the allowable deviation plating solution concentration, and then the plating solution concentration influence factor is used to perform a weighted calculation on the deviation compliance calculation result to obtain the plating solution concentration influence parameter; the current density influence parameter, the plating solution temperature influence parameter and the plating solution concentration influence parameter are coupled, and then the coupling processing result is inversely proportionally calculated to obtain the pre-plating state index.

[0038] The pre-plating status index is obtained as follows:

[0039]

[0040] Wherein, PS represents the pre-plating state index, α4 represents the current density influencing factor, α5 represents the plating solution temperature influencing factor, α6 represents the plating solution concentration influencing factor, CD1 represents the current density, CD0 represents the reference current density, CD2 represents the allowable deviation current density, PT1 represents the plating solution temperature, PT0 represents the reference plating solution temperature, PT2 represents the allowable deviation plating solution temperature, PC1 represents the plating solution concentration, PC0 represents the reference plating solution concentration, and PC2 represents the allowable deviation plating solution concentration.

[0041] α4, α5 and α6 are the influence factors corresponding to the current density, plating solution temperature and plating solution concentration preset in the pre-plating impurity removal database, respectively. These influence factors are numerical indicators that measure the influence of the above-mentioned pre-plating state parameters on the pre-plating state index. Specifically, there is a mapping relationship table for each of the current density, plating solution temperature and plating solution concentration, which records each possible pre-plating state parameter value and its corresponding influence factor. These mapping relationships can be one-to-one or many-to-one. For example, in actual applications, when it is necessary to evaluate the pre-plating state index, the measured current density, plating solution temperature and plating solution concentration can be input into their respective corresponding mapping relationship tables, and the influence factors corresponding to these values ​​can be quickly found, where the value range of the influence factor is between 0 and 1.

[0042] Then, the first threshold value of the pre-plating state and the second threshold value of the pre-plating state are obtained from the preset pre-plating impurity removal database. The first threshold value of the pre-plating state represents the critical value of the pre-plating state at a relatively poor level, and the second threshold value of the pre-plating state represents the critical value of the pre-plating state at a relatively ideal or acceptable good level. The two together construct a hierarchical judgment system, which divides the pre-plating state into three intervals and corresponds to different processing strategies; the pre-plating state index is compared with the first threshold value of the pre-plating state and the second threshold value of the pre-plating state respectively. When the pre-plating state index is not less than the second threshold value of the pre-plating state, no additional processing is performed; when the pre-plating state index is less than the second threshold value of the pre-plating state and not less than the first threshold value of the pre-plating state, the main salt concentration monitored by the salt concentration meter is obtained. If the main salt concentration is If the concentration of the main salt in the plating solution is lower than the standard main salt concentration range preset in the pre-plating impurity removal database, the main salt concentration in the plating solution is supplemented according to the second threshold of the pre-plating state, the first threshold of the pre-plating state and the current main salt concentration. If the main salt concentration is within the standard main salt concentration range, the plating solution temperature is increased according to the preset temperature amplitude. After the plating solution temperature is evenly distributed, if the pre-plating state index is still less than the second threshold of the pre-plating state, the current is increased according to the preset current amplitude to accelerate the ion mobility, but it must be ensured that it does not exceed the upper limit of the optimal range to avoid process fluctuations until the pre-plating state index reaches the second threshold of the pre-plating state; if the main salt concentration is higher than the standard main salt concentration range, deionized water is added to dilute the electrolyte according to the current main salt concentration until the main salt concentration is within the standard main salt concentration range. The volume of deionized water added is: Where V water Indicates the volume of deionized water added, C current Indicates the current main salt concentration, C target Indicates the upper limit of standard main salt concentration, V water Indicates the total volume of the plating tank.

[0043] The step of replenishing the main salt concentration in the plating solution based on the second pre-plating state threshold, the first pre-plating state threshold, and the current main salt concentration includes: subtracting the lower limit of the standard main salt concentration in a preset pre-plating impurity removal database from the current main salt concentration, marking the difference as the main salt concentration shortfall; marking the ratio of the difference between the second pre-plating state threshold and the pre-plating state index and the difference between the second pre-plating state threshold and the first pre-plating state threshold as a difference ratio; matching the difference ratio with the main salt concentration weight coefficient corresponding to the difference ratio range preset in the pre-plating impurity removal database to obtain the main salt concentration weight coefficient corresponding to the difference ratio; obtaining a main salt concentration adjustment value based on the main salt concentration weight coefficient and the main salt concentration shortfall, and replenishing the main salt concentration based on the main salt concentration adjustment value. The main salt concentration adjustment value is obtained as follows: CA = β × SC; where CA represents the main salt concentration adjustment value, β represents the main salt concentration weight coefficient, and SC represents the main salt concentration shortfall.

[0044] When the pre-plating state index is less than the first pre-plating state threshold, check whether the pre-plating equipment has any abnormalities such as anode passivation, plating solution contamination, etc. If an abnormality occurs, stop production immediately and notify the preset personnel to carry out maintenance. If there is no abnormality, further conduct a comprehensive test on the plating solution composition. If the plating solution composition is contaminated, such as the presence of unknown precipitates or color changes in the plating solution, harmful impurities such as metal ions, acid and alkali substances exceeding the standard concentration, start the plating solution cleaning device, specifically including: using a precision filter to filter impurities, adding activated carbon adsorption and using oxidants such as hydrogen peroxide to decompose organic pollutants, using chelating agents such as EDTA to remove harmful metal ions. If there is no pollution but the cumulative use time of the plating solution exceeds the preset use time threshold, replace the aged plating solution. If there is no pollution and the cumulative use time of the plating solution does not exceed the use time threshold, increase the preset pre-plating time. By extending the electroplating process, the distribution and concentration of the plating ions in the plating solution are improved, thereby ensuring the uniformity and density of the coating and improving the electroplating quality.

[0045] In this embodiment, the current density is usually obtained by measuring the current passing through the electrode using a current sensor and comparing the current with the surface area of ​​the electrode; the plating solution temperature can be obtained by real-time monitoring using a temperature sensor; and the plating solution concentration can be obtained by real-time monitoring using an online ion selective electrode. The three are interrelated. For example, under normal circumstances, a higher plating solution temperature helps to increase the reaction rate under current density and avoid the problem of rough coating. However, a combination of too high current density and temperature may cause uneven coating surface. The higher the current density, the higher the plating solution concentration is required to provide sufficient metal ions to support the electroplating reaction. Too low a plating solution concentration may cause coating defects at high current density. The pre-plating state index obtained by comprehensive analysis can reflect the overall state of the electroplating process, help optimize the electroplating parameters, and help to accurately control the electroplating process to ensure higher electroplating quality and production efficiency. By comparing the pre-plating state index with the preset first and second thresholds of the pre-plating state index, the quality of the current pre-plating state can be judged. If the pre-plating state index is lower than the second threshold of the pre-plating state index, the system will make necessary adjustments to the pre-plating state parameters to ensure the quality of the plating solution and the consistency of the process, and prevent the low pre-plating state from affecting the quality of the subsequent coating. If the pre-plating state index is lower than the first threshold of the pre-plating state index, the system will conduct more rigorous inspections on the equipment and plating solution to promptly detect and correct abnormalities, such as equipment failure (such as anode passivation) or plating solution contamination. This helps ensure that the process can be quickly and effectively repaired when deviations occur, avoiding long-term unqualified products. When the pre-plating state index reaches or approaches the preset second threshold of the pre-plating state index, the system will stop further adjustments to prevent over-replenishment or over-adjustment, ensuring the stability of the plating solution and production process.

[0046] Furthermore, the step of dynamically optimizing the anode configuration according to the thickness of the workpiece at each position point includes: first, performing a mean operation on the workpiece thickness at each position point to obtain the average workpiece thickness; performing a variance operation on the average workpiece thickness and the workpiece thickness at each position point to obtain the workpiece thickness variance; obtaining the maximum workpiece thickness and the minimum workpiece thickness from the workpiece thickness at each position point, and marking the difference between the maximum workpiece thickness and the minimum workpiece thickness as the maximum thickness difference; quantifying the influence of the thickness at each position point on the workpiece on the pre-plating quality evaluation according to the average workpiece thickness, the workpiece thickness variance and the maximum thickness difference to obtain a pre-plating quality index, which represents quantitative data on the degree of influence of the average workpiece thickness, the workpiece thickness variance and the maximum thickness difference on the pre-plating quality evaluation.

[0047] Among them, the steps of quantifying the influence of the thickness of each position point on the workpiece on the pre-plating quality evaluation according to the average workpiece thickness, workpiece thickness variance and maximum thickness difference, and obtaining the pre-plating quality index include: obtaining workpiece thickness reference data from a preset pre-plating impurity removal database, specifically including: reference average workpiece thickness, allowable deviation average workpiece thickness, critical workpiece thickness variance and critical maximum thickness difference; performing relative deviation conformity operation on the allowable deviation average workpiece thickness, the average workpiece thickness and the reference average workpiece thickness to obtain the average workpiece thickness influencing parameter; performing proportion approximation operation on the critical workpiece thickness variance and the critical maximum thickness difference with the workpiece thickness variance and the maximum thickness difference respectively to obtain the workpiece thickness variance influencing parameter and the maximum thickness difference influencing parameter; using the workpiece thickness influencing factor to weight the average workpiece thickness influencing parameter, the workpiece thickness variance influencing parameter and the maximum thickness difference influencing parameter, and then coupling the weighted processing results to obtain the pre-plating quality index, and the workpiece thickness influencing factor includes the average workpiece thickness influencing factor, the workpiece thickness variance influencing factor and the maximum thickness difference influencing factor.

[0048] The pre-plating quality index is obtained as follows:

[0049]

[0050] Wherein, PQ represents the pre-plating quality index, α7 represents the influence factor of the average workpiece thickness, α8 represents the influence factor of the workpiece thickness variance, α9 represents the influence factor of the maximum thickness difference, AT1 represents the average workpiece thickness, AT0 represents the reference average workpiece thickness, AT2 represents the allowable deviation of the average workpiece thickness, TV1 represents the workpiece thickness variance, TV0 represents the critical workpiece thickness variance, MT1 represents the maximum thickness difference, and MT0 represents the critical maximum thickness difference.

[0051] α7, α8 and α9 are the influencing factors corresponding to the average workpiece thickness, workpiece thickness variance and maximum thickness difference preset in the pre-plating impurity removal database, respectively. These influencing factors are numerical indicators that measure the influence of the above-mentioned pre-plating quality parameters on the pre-plating quality index. Specifically, there is a mapping relationship table for each of the average workpiece thickness, workpiece thickness variance and maximum thickness difference, which records each possible pre-plating quality parameter value and its corresponding influencing factor. These mapping relationships can be one-to-one or many-to-one. For example, in actual applications, when it is necessary to evaluate the pre-plating quality index, the measured average workpiece thickness, workpiece thickness variance and maximum thickness difference can be input into their respective corresponding mapping relationship tables, and the influencing factors corresponding to these values ​​can be quickly found, where the value range of the influencing factor is between 0 and 1.

[0052] Then, a pre-plating quality index threshold and a deviation thickness threshold are obtained from a preset pre-plating impurity removal database, and the pre-plating quality index is compared with the pre-plating quality index threshold. If the pre-plating quality index is greater than or equal to the pre-plating quality index threshold, no additional operation is performed; if the pre-plating quality index is less than the pre-plating quality index threshold and the maximum thickness difference exceeds the deviation thickness threshold, the workpiece surface is parallel to the anode, and the anode module corresponding to the workpiece thickness exceeding the average workpiece thickness controls the motor to drive the anode support and the workpiece to increase the preset anode distance, and the anode module corresponding to the workpiece thickness below the average workpiece thickness shortens the preset anode distance until the maximum thickness difference does not exceed the deviation thickness threshold; if the pre-plating quality index is less than the pre-plating quality index threshold and the maximum thickness difference does not exceed the deviation thickness threshold, the difference between the pre-plating quality index and the pre-plating quality index threshold is marked as the deviation pre-plating quality index, and matched with the pre-plating state parameter upper limit correction value corresponding to each deviation pre-plating quality index interval preset in the pre-plating impurity removal database to obtain the pre-plating state parameter upper limit correction value corresponding to the deviation pre-plating quality index, and the pre-plating state parameter upper limit is corrected based on the pre-plating state parameter upper limit correction value. Among them, the pre-plating state parameters are respectively summed with the upper limit correction value of the pre-plating state parameters to obtain the corrected pre-plating state parameters, and each deviation pre-plating quality index is mapped to the upper limit correction value of the pre-plating state parameters in the pre-plating impurity removal database to form a mapping relationship table, which records each deviation pre-plating quality index and its corresponding upper limit correction value of the pre-plating state parameters. These relationships can be one-to-one or many-to-one. When obtaining the upper limit correction value of the pre-plating state parameters, it is only necessary to input the deviation pre-plating quality index into the mapping relationship table, and the pre-plating impurity removal database can quickly locate and return the upper limit correction value of the pre-plating state parameters corresponding to the deviation pre-plating quality index. The thickness of the workpiece is re-detected within the next time monitoring point after the adjustment. If the adjusted pre-plating quality index reaches the pre-plating quality index threshold, the post-pre-plating plating solution component auxiliary impurity removal is performed. If the adjusted pre-plating quality index is still less than the pre-plating quality index threshold, the auxiliary anode is started to optimize the current distribution and electrolysis efficiency during the electroplating or electrolysis process.

[0053] In this embodiment, the closer the average workpiece thickness is to the reference average workpiece thickness, the better the coating quality is. The smaller the workpiece thickness variance is, the more uniform the coating thickness is and the process is properly controlled. The maximum thickness difference reflects the most extreme variation in coating thickness. Excessive differences may indicate that the local coating is too thick or too thin, affecting the function and appearance quality of the workpiece. The three are interrelated. For example, if the thickness variance is small and the maximum thickness difference is small, it means that the coating uniformity is good, the electroplating process is more stable, and the workpiece surface quality is high. On the contrary, if the thickness variance and the maximum thickness difference are large, it indicates that the coating uniformity is poor and there may be problems with process control, resulting in some workpieces being too thin or too thick, affecting product quality. The pre-plating quality index obtained by comprehensive analysis can reflect the overall quality of the coating during the electroplating process, including the uniformity and consistency of its thickness. A high-quality pre-plating quality index (pre-plating quality index exceeds the pre-plating quality index threshold) usually means that the coating thickness is uniform as a whole and the process is stable, which can ensure the functionality and aesthetics of the product. By comparing the pre-plating quality index with the preset pre-plating quality index threshold, potential quality problems such as excessive thickness deviation or excessively high quality index can be discovered in a timely manner during the production process, which helps to quickly adjust the process, ensure that the workpiece meets the expected quality standards, and avoid rework or product failure due to quality problems.

[0054] like Figure 4 The figure shows a mind map of the plating solution component impurity removal module provided in the embodiment of the present application. The steps of auxiliary impurity removal according to the plating solution composition after pre-plating include: obtaining the threshold value of each metal impurity ion content from a preset pre-plating impurity removal database; using ion selective electrodes to monitor the content of each metal impurity ion (including Fe 2 +、Fe 3 +、Cu 2 +、Pb 2 + and Ni 2 +) Whether the content of each metal impurity ion exceeds the threshold value of each metal impurity ion; if not, no additional treatment is performed; if so, the subsequent pre-plating process is suspended, and a preset content of zinc powder is added to stir and filter the plating solution; at the same time, it is monitored whether the reduction amount of each metal impurity ion in the current impurity removal cycle exceeds the preset threshold value of each metal impurity ion reduction; if so, continue to add the preset content of zinc powder to stir and filter the plating solution until the content of each metal impurity ion does not exceed the threshold value of each metal impurity ion content; if not, add a complexing agent for impurity removal, and after the content of each metal impurity ion does not exceed the threshold value of the metal impurity ion content, use the plating solution to continue with the next round of pre-plating.

[0055] In this embodiment, by monitoring, controlling, and adjusting the metal impurity ions in the plating solution, the goal is to ensure that the impurity ion content in the plating solution is within a certain range, thereby ensuring the quality of the plating solution during the electroplating process, thereby improving the quality of the final product and production efficiency, and reducing environmental pollution and equipment loss. The use of zinc powder can react with or adsorb metal impurities, effectively absorbing and removing impurities. Stirring and filtering help to evenly distribute the zinc powder and efficiently remove impurities, while also reducing the amount of waste plating solution that needs to be processed, thus playing a certain environmental role. The complexing agent can combine with metal ions to form a soluble complex, thereby effectively removing impurity ions dissolved in the plating solution.

[0056] In summary, this embodiment achieves precise optimization of the electrogalvanizing pre-plating process through multi-dimensional intelligent control: first, the thickness gauge data is dynamically corrected based on the bubble influencing parameters to eliminate bubble interference and obtain the accurate workpiece thickness at each location; second, the process is optimized based on the real-time monitored pre-plating state parameters, and the plating bath performance is stabilized by graded adjustment of the main salt replenishment, temperature control, and current compensation; then, the anode spacing configuration is dynamically adjusted based on the thickness measurement results, targetedly increasing the thick area spacing and reducing the thin area spacing to improve the uniformity of the coating; finally, targeted impurity removal is implemented in combination with the plating bath composition analysis, and the purity of the plating bath is maintained through the replacement of metal impurities, adsorption of organic pollutants, and filtration of suspended matter. Through the closed-loop control of "measurement-correction-optimization-purification", the system simultaneously solves the four core problems of bubble interference, process fluctuations, uneven thickness, and plating bath contamination, achieving a synergistic improvement in pre-plating quality and process stability.

[0057] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems and methods, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0058] The present invention is described with reference to flowcharts and / or block diagrams of systems and methods, devices (systems and methods), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0059] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0060] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0061] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0062] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. An intelligent control system for electrogalvanizing pre-plating impurity removal, characterized in that: include: Bubble impact correction module, pre-plating state optimization module, workpiece thickness adjustment module, plating solution component removal module and pre-plating impurity removal database; Among them, the bubble influence correction module is used to dynamically correct the thickness gauge measurement results according to the bubble influence parameters in the pre-plating process to obtain the thickness of the workpiece at each position point. The dynamic correction of the thickness gauge measurement results is used to reduce the influence of the generated bubbles on the accuracy of the thickness gauge measurement results; The pre-plating state optimization module is used to perform pre-plating state optimization processing according to the pre-plating state parameters during the pre-plating process, and the pre-plating state optimization processing is used to reduce the impact of plating solution quality fluctuations on plating solution performance and pre-plating layer quality; The workpiece thickness adjustment module is used to dynamically optimize the anode configuration according to the thickness of the workpiece at each position point, and the dynamic optimization of the anode configuration is used to reduce the influence of the thickness of the workpiece at each position point on the uniformity of the pre-plating layer; The plating solution component impurity removal module is used to perform auxiliary impurity removal according to the plating solution components after pre-plating.

2. The intelligent control system for removing impurities from electrogalvanizing pre-plating as claimed in claim 1, characterized in that: The step of dynamically correcting the thickness gauge measurement result according to the bubble influence parameter during the pre-plating process to obtain the thickness of the workpiece at each position includes: quantifying the influence of bubbles on the accuracy of the thickness gauge measurement results according to the bubble influence parameters, obtaining a bubble influence index, wherein the bubble influence parameters include the number of bubbles, the average bubble size, and the bubble density, and the bubble influence index represents quantitative data of the degree of influence of the bubble influence parameters on the accuracy of the thickness gauge measurement results; Obtaining a first bubble impact threshold and a second bubble impact threshold from a preset pre-plating impurity removal database; The bubble influence index is compared with the first bubble influence threshold and the second bubble influence threshold respectively. If the bubble influence index is not greater than the first bubble influence threshold, the pre-plating state optimization process is directly performed; If the bubble influence index is greater than the first bubble influence threshold and not greater than the second bubble influence threshold, a deviation bubble influence index is obtained based on the second bubble influence threshold and the bubble influence index, the deviation bubble influence index is matched with the thickness gauge measurement result correction value corresponding to each deviation bubble influence index interval preset in the pre-plating impurity removal database, and the thickness gauge measurement result correction value corresponding to the deviation bubble influence index is obtained, and the thickness gauge measurement data is corrected based on the thickness gauge measurement result correction value; If the bubble influence index is greater than the second bubble influence threshold, the bubble removal device is turned on, and when the monitored bubble influence index is not greater than the second bubble influence threshold, the bubble removal device is turned off.

3. The intelligent control system for removing impurities from electrogalvanizing pre-plating as claimed in claim 2, characterized in that: The step of quantifying the influence of bubbles on the accuracy of the thickness gauge measurement result according to the bubble influence parameter to obtain the bubble influence index comprises: Obtain reference data of bubble influencing parameters from a preset pre-plating impurity removal database, including: critical bubble number, critical average bubble size, and critical bubble density; The number of bubbles, average bubble size and bubble density are respectively subjected to proportion approximation calculation with the critical number of bubbles, critical average bubble size and critical bubble density. The results of the proportion approximation calculation are weighted using the bubble influence parameter influencing factors. The weighted processing results are then coupled to obtain the bubble influence index. The bubble influence parameter influencing factors include the bubble number influencing factor, the average bubble size influencing factor and the bubble density influencing factor.

4. The intelligent control system for electrogalvanizing pre-plating impurity removal according to claim 1, characterized in that: The step of performing pre-plating state optimization processing according to the pre-plating state parameters in the pre-plating process comprises: quantifying the effect of the plating solution state on the pre-plating efficiency according to the pre-plating state parameters to obtain a pre-plating state index, wherein the pre-plating state parameters include current density, plating solution temperature, and plating solution concentration, and the pre-plating state index represents quantitative data on the degree of influence of the pre-plating state parameters on the quality of the pre-plating layer and the performance of the plating solution; Obtaining a first threshold value of a pre-plating state and a second threshold value of a pre-plating state from a preset pre-plating impurity removal database; Comparing the pre-plating state index with the first pre-plating state threshold and the second pre-plating state threshold respectively, and when the pre-plating state index is not less than the second pre-plating state threshold, no additional processing is performed; When the pre-plating state index is less than the second threshold value of the pre-plating state and not less than the first threshold value of the pre-plating state, if the main salt concentration is lower than the standard main salt concentration range, the main salt concentration in the plating solution is replenished according to the second threshold value of the pre-plating state, the first threshold value of the pre-plating state and the current main salt concentration; if the main salt concentration is within the standard main salt concentration range, the plating solution temperature is increased according to the preset temperature amplitude; after the plating solution temperature is evenly distributed, if the pre-plating state index is still less than the second threshold value of the pre-plating state, the current is increased according to the preset current amplitude until the pre-plating state index reaches the second threshold value of the pre-plating state; if the main salt concentration is higher than the standard main salt concentration range, the electrolyte is diluted according to the current main salt concentration until the main salt concentration is within the standard main salt concentration range; When the pre-plating status index is less than the first pre-plating status threshold, check whether the pre-plating equipment has any abnormality. If an abnormality occurs, stop production immediately and notify the preset personnel to carry out maintenance. If there is no abnormality, further conduct a comprehensive test on the plating solution components. If the plating solution components are contaminated, start the plating solution cleaning device. If there is no contamination but the cumulative usage time of the plating solution exceeds the preset usage time threshold, replace the aged plating solution. If there is no contamination and the cumulative usage time of the plating solution does not exceed the usage time threshold, increase the pre-plating time.

5. The intelligent control system for removing impurities from electrogalvanizing pre-plating as claimed in claim 4, characterized in that: The step of quantifying the influence of the plating solution state on the pre-plating efficiency according to the pre-plating state parameter to obtain the pre-plating state index comprises: Obtaining pre-plating state parameter reference data from a preset pre-plating impurity removal database, specifically including: reference current density, allowable deviation current density, reference plating solution temperature, allowable deviation plating solution temperature, reference plating solution concentration, and allowable deviation plating solution concentration; The current density, the reference current density and the allowable deviation current density are subjected to relative deviation conformity calculation, and then the deviation conformity calculation result is weighted by the current density influence factor to obtain the current density influence parameter; The relative deviation compliance calculation is performed on the plating bath temperature, the reference plating bath temperature and the allowable deviation plating bath temperature, and then the plating bath temperature influencing factor is used to perform a weighted calculation on the deviation compliance calculation result to obtain the plating bath temperature influencing parameter; The relative deviation compliance calculation is performed on the plating solution concentration, the reference plating solution concentration and the allowable deviation plating solution concentration, and then the plating solution concentration influencing factor is used to perform a weighted calculation on the deviation compliance calculation result to obtain the plating solution concentration influencing parameter; The current density influencing parameter, the plating solution temperature influencing parameter and the plating solution concentration influencing parameter are coupled, and then the coupling processing result is inversely proportionally calculated to obtain the pre-plating state index.

6. The intelligent control system for removing impurities from electrogalvanizing pre-plating as claimed in claim 4, characterized in that: The step of replenishing the main salt concentration in the plating solution according to the second threshold value of the pre-plating state, the first threshold value of the pre-plating state and the current main salt concentration includes: The difference between the lower limit of the standard main salt concentration in the preset pre-plating impurity removal database and the current main salt concentration is marked as the main salt concentration shortage; The ratio of the difference between the second threshold value of the pre-plating state and the pre-plating state index and the difference between the second threshold value of the pre-plating state and the first threshold value of the pre-plating state is marked as a difference ratio, and the difference ratio is matched with the main salt concentration weight coefficient corresponding to the difference ratio range preset in the pre-plating impurity removal database to obtain the main salt concentration weight coefficient corresponding to the difference ratio; The main salt concentration adjustment value is obtained according to the main salt concentration weight coefficient and the main salt concentration shortage, and the main salt concentration is supplemented according to the main salt concentration adjustment value.

7. The intelligent control system for removing impurities from electrogalvanizing pre-plating as claimed in claim 1, characterized in that: The step of dynamically optimizing the anode configuration according to the thickness of the workpiece at each position point includes: The average thickness of the workpiece is calculated by averaging the thickness of each position point to obtain the average workpiece thickness; The variance calculation is performed using the average workpiece thickness and the workpiece thickness at each position to obtain the workpiece thickness variance; Obtain the maximum and minimum workpiece thickness values ​​from the workpiece thickness at each position point, and mark the difference between the maximum and minimum workpiece thickness values ​​as the maximum thickness difference; quantifying the influence of the thickness of each position point on the workpiece on the pre-plating quality assessment according to the average workpiece thickness, the workpiece thickness variance and the maximum thickness difference, and obtaining a pre-plating quality index, wherein the pre-plating quality index represents quantitative data on the degree of influence of the average workpiece thickness, the workpiece thickness variance and the maximum thickness difference on the pre-plating quality assessment; Obtaining a pre-plating quality index threshold and a deviation thickness threshold from a preset pre-plating impurity removal database, comparing the pre-plating quality index with the pre-plating quality index threshold, and if the pre-plating quality index is greater than or equal to the pre-plating quality index threshold, no additional operation is performed; If the pre-plating quality index is less than the pre-plating quality index threshold and the maximum thickness difference exceeds the deviation thickness threshold, the workpiece surface is parallel to the anode, the anode modules corresponding to the workpiece thickness exceeding the average workpiece thickness are increased by a preset anode spacing, and the anode modules corresponding to the workpiece thickness below the average workpiece thickness are shortened by a preset anode spacing until the maximum thickness difference does not exceed the deviation thickness threshold; If the pre-plating quality index is less than the pre-plating quality index threshold and the maximum thickness difference does not exceed the deviation thickness threshold, the difference between the pre-plating quality index and the pre-plating quality index threshold is marked as the deviation pre-plating quality index, and matched with the pre-plating state parameter upper limit correction value corresponding to each deviation pre-plating quality index interval preset in the pre-plating impurity removal database to obtain the pre-plating state parameter upper limit correction value corresponding to the deviation pre-plating quality index, and the pre-plating state parameter upper limit is corrected based on the pre-plating state parameter upper limit correction value. The workpiece thickness is re-detected within the next time monitoring point after the adjustment. If the adjusted pre-plating quality index reaches the pre-plating quality index threshold, auxiliary impurity removal of the plating solution components after pre-plating is performed. If the adjusted pre-plating quality index is still less than the pre-plating quality index threshold, the auxiliary anode is started.

8. The intelligent control system for removing impurities from electrogalvanizing pre-plating as claimed in claim 7, characterized in that: The step of quantifying the influence of the thickness of each position point on the workpiece on the pre-plating quality evaluation according to the average workpiece thickness, the workpiece thickness variance and the maximum thickness difference to obtain the pre-plating quality index comprises: Obtain workpiece thickness reference data from a preset pre-plating and impurity removal database, specifically including: reference average workpiece thickness, allowable deviation average workpiece thickness, critical workpiece thickness variance, and critical maximum thickness difference; Perform relative deviation conformity calculation on the allowable deviation average workpiece thickness, the average workpiece thickness and the reference average workpiece thickness to obtain the influencing parameter of the average workpiece thickness; The critical workpiece thickness variance and the critical maximum thickness difference are respectively subjected to a proportion approach operation with the workpiece thickness variance and the maximum thickness difference to obtain the workpiece thickness variance influencing parameters and the maximum thickness difference influencing parameters; The workpiece thickness influencing factors are used to respectively perform weighted processing on the average workpiece thickness influencing parameters, the workpiece thickness variance influencing parameters and the maximum thickness difference influencing parameters, and then the weighted processing results are coupled to obtain the pre-plating quality index. The workpiece thickness influencing factors include the average workpiece thickness influencing factor, the workpiece thickness variance influencing factor and the maximum thickness difference influencing factor.

9. The intelligent control system for removing impurities from electrogalvanizing pre-plating as claimed in claim 1, characterized in that: The step of performing auxiliary impurity removal according to the composition of the plating solution after pre-plating comprises: Obtaining the content threshold of each metal impurity ion from a preset pre-plating impurity removal database; Monitor whether the content of each metal impurity ion in the plating solution after pre-plating exceeds the threshold value of each metal impurity ion content. If not, no additional processing is performed. If so, suspend the subsequent pre-plating process, add a preset content of zinc powder, stir and filter the plating solution, and monitor whether the reduction of each metal impurity ion in the current impurity removal cycle exceeds the preset threshold value of each metal impurity ion reduction. If so, continue to add the preset content of zinc powder, stir and filter the plating solution until the content of each metal impurity ion does not exceed the threshold value of each metal impurity ion content. If not, add a chelating agent for impurity removal. After the content of each metal impurity ion does not exceed the threshold value of the metal impurity ion content, use the plating solution to continue the next round of pre-plating.

10. An intelligent control method for removing impurities from electrogalvanizing pre-plating, characterized in that: The following steps are involved: Dynamically correcting the thickness gauge measurement results according to the bubble influence parameters during the pre-plating process to obtain the thickness of the workpiece at each position point, wherein the dynamic correction of the thickness gauge measurement results is used to reduce the influence of the generated bubbles on the accuracy of the thickness gauge measurement results; Performing a pre-plating state optimization process according to the pre-plating state parameters during the pre-plating process, wherein the pre-plating state optimization process is used to reduce the influence of the plating solution quality fluctuation on the plating solution performance and the pre-plating layer quality; Dynamically optimizing the anode configuration according to the thickness of the workpiece at each position point, wherein the dynamically optimized anode configuration is used to reduce the influence of the thickness of the workpiece at each position point on the uniformity of the pre-plating layer; Auxiliary impurity removal is carried out according to the composition of the plating solution after pre-plating.

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