An automated operation control method and system for electrophoresis equipment

Abstract

The present invention belongs to the field of automatic control technology. The present invention discloses an automatic operation control method and system for electrophoresis equipment, including: obtaining coating work data including workpiece parameters, coating thickness and electrophoresis working parameters to form a coating work data set; using the data set to train a working parameter acquisition model to obtain electrophoresis working parameters according to workpiece parameters and coating thickness; obtaining real-time workpiece parameters and coating thickness, and inputting the model to obtain electrophoresis working parameters; using the working current, temperature, pole distance and duration in the electrophoresis working parameters as target parameters; controlling the electrophoresis equipment for coating according to the target parameters; determining the acquisition frequency according to the target duration, and collecting the electrophoresis solvent temperature and current data in real time; correcting the target duration in combination with the real-time acquisition data, and controlling the coating time. Compared with the traditional method, it can more accurately adapt to the differences in the size, conductive properties and other aspects of various workpieces, and improve the coating quality.

Description

Technical Field

[0001] The present invention relates to the field of automatic control, and more specifically, to an automatic operation control method and system for electrophoresis equipment. Background Art

[0002] Electrophoresis is a technology that uses electric field force to act on charged particles to make them migrate in the medium. It is widely used in the field of material surface treatment and coating. Through electrophoresis, a layer of coating can be evenly deposited on the surface of the workpiece to improve its corrosion resistance, wear resistance and aesthetics. As an efficient and environmentally friendly coating method, electrophoretic coating has become an important coating process in the automotive, home appliance, metal products and other industries.

[0003] Although electrophoretic technology has many advantages, the existing electrophoretic equipment operation technology still faces some challenges and limitations. The traditional electrophoretic coating process is relatively extensive in terms of control parameters, and often relies on the experience of the staff to preset, and it is difficult to accurately adapt to the differences in size, conductivity, etc. of various workpieces. This control method dominated by human factors can easily lead to fluctuations in coating quality and affect the overall quality of the product. At the same time, in the electrophoretic coating process, although PID control and other automated means are often used to maintain the relative stability of control parameters, in actual situations, these parameters are often in dynamic change. In the existing electrophoretic process, the electrophoretic time is often a pre-set fixed value, and the actual impact of parameter fluctuations is not fully considered, which can easily cause the problem of the coating being too thick or too thin, which not only wastes material resources, but may also have an adverse effect on the functionality and appearance of the product, thereby reducing product quality. Summary of the invention

[0004] In order to overcome the problem that the prior art relies on personal experience and leads to unstable product quality, the present invention proposes an automatic operation control method and system for electrophoresis equipment to solve the above problem.

[0005] The present invention provides the following technical solutions:

[0006] An automatic operation control method for electrophoresis equipment, comprising:

[0007] S1. Acquire a number of coating work data to form a coating work data set, wherein the coating work data includes workpiece parameters, coating thickness and electrophoresis work parameters, and the electrophoresis work parameters include working current, working temperature, distance between two electrodes and working time;

[0008] S2. Using the coating work data set to train a working parameter acquisition model, the working parameter acquisition model is used to acquire electrophoresis working parameters according to workpiece parameters and coating thickness;

[0009] S3, obtaining real-time workpiece parameters and coating thickness of the workpiece to be coated, and inputting the real-time workpiece parameters and coating thickness into a working parameter acquisition model to obtain electrophoresis working parameters;

[0010] S4, using the working current among the obtained electrophoresis working parameters as the target current, the working temperature as the target electrophoresis solvent temperature, the distance between the two poles as the target distance, and the working time as the target time;

[0011] S5, controlling the electrophoresis equipment to perform coating work according to the target current, target electrophoresis solvent temperature and the distance between the two electrodes;

[0012] S6. Determine the collection frequency according to the target duration, and collect the electrophoresis solvent temperature data and current data according to the collection frequency during the coating process;

[0013] S7. Correct the target duration according to the collected electrophoresis solvent temperature data and current data, combined with the target current and the target electrophoresis solvent temperature, and control the coating working duration according to the corrected target duration.

[0014] Preferably, the workpiece parameters include workpiece conductivity and workpiece surface area; the step of acquiring a plurality of coating work data to form a coating work data set includes:

[0015] Obtain any object to be coated, obtain workpiece parameters of the object to be coated, and use electrophoresis equipment to coat the object to be coated;

[0016] The electrophoresis solvent temperature and current in the coating process are collected at a preset frequency to form an electrophoresis solvent temperature determination array and a current determination array, respectively, and whether the current coating process can be used as reference data is determined based on the electrophoresis solvent temperature determination array and the current determination array;

[0017] If the judgment result is that it can be used as reference data, then the average value of the electrophoresis solvent temperature determination array is obtained as the working temperature, and the average value of the current determination array is obtained as the working current;

[0018] The distance between the cathode and the anode during the coating process is obtained as the distance between the two electrodes, the coating thickness is measured after the coating is completed as the coating thickness, and the total coating time is obtained as the working time;

[0019] Working temperature, working current and working time are used to form electrophoresis working parameters, and workpiece parameters of the object to be coated, coating thickness and electrophoresis working parameters are used to form a coating working data;

[0020] Use different objects to be painted to obtain corresponding painting work data to form a painting work data set.

[0021] Preferably, the step of judging whether the current coating process can be used as reference data according to the electrophoresis solvent temperature judgment array and the current judgment array includes:

[0022] A difference coefficient is preset, and a ratio between an average value and a standard deviation of the electrophoresis solvent temperature determination array is calculated to determine whether it is less than the difference coefficient; if so, a stable label is marked on the electrophoresis solvent temperature determination array; otherwise, an unstable label is marked on the electrophoresis solvent temperature determination array;

[0023] Calculate whether the ratio between the mean value and the standard deviation of the current determination array is less than the coefficient of variation; if so, label the current determination array as stable; otherwise, label the current determination array as unstable;

[0024] Obtain the labels of the electrophoresis solvent temperature determination array and the current determination array; if both are stable labels, it is determined that this coating process can be used as reference data; otherwise, it is determined that this coating process cannot be used as reference data.

[0025] Preferably, the step of using the painting work data set to train the work parameter acquisition model comprises:

[0026] Obtain the coating work data set, extract the feature data of workpiece parameters and coating thickness, and divide the cutting data set into a training set and a test set;

[0027] Build a machine learning framework and define the input layer and output layer, set the loss function and optimizer, and build a machine learning model;

[0028] The feature data is used as the input layer data, the electrophoresis working parameters are used as the output layer data, and the training set is used to train the constructed machine learning model according to the set batch size and number of training rounds;

[0029] Use the test set to test the trained machine learning model, and output the machine learning model that meets the preset accuracy as the working parameter acquisition model.

[0030] Preferably, the step of determining the acquisition frequency according to the target duration includes:

[0031] Obtaining a target duration, a preset number of analysis segments, and a preset minimum amount of data, and evenly dividing the target duration into multiple analysis periods according to the preset number of analysis segments;

[0032] Get the length of a single analysis period; use the minimum amount of data divided by the length of a single segment to get the acquisition frequency.

[0033] Preferably, the step of modifying the target duration includes:

[0034] During the coating process, when the time of any analysis period has passed, the electrophoresis solvent temperature data collected in the analysis period is obtained to form an electrophoresis solvent temperature array corresponding to the analysis period, and the current data collected in the analysis period is obtained to form a current array corresponding to the analysis period;

[0035] Establish the relationship model between current, temperature and coating speed;

[0036] Calculate the time impact value according to the current array, the target current, the electrophoresis solvent temperature array, the target electrophoresis solvent temperature and the relationship model between the current and temperature and the coating speed;

[0037] The sum of the time impact value and the target duration is used as the new target duration to complete the correction of the target duration.

[0038] Preferably, the step of establishing the relationship model between current, temperature and coating speed includes:

[0039] When using electrophoresis equipment to coat a workpiece, the coating speeds at different currents and electrophoresis solvent temperatures are collected to obtain a fitting data set, where the coating speed is obtained by dividing the coating thickness change during the coating process by the time taken;

[0040] According to the fitting data set, the current value and the electrophoresis solvent temperature value are used as independent variables, and the coating speed value is used as the dependent variable. The fitting method is used to obtain the corresponding fitting equation as the relationship model between current, temperature and coating speed.

[0041] Preferably, the step of calculating the time impact value includes:

[0042] Subtract each value in the current array from the target current to obtain a current difference, and use the sum of all current differences as the current change, and use the sum of the target current and the current change as the comparison current;

[0043] Subtract each value in the electrophoresis solvent temperature array from the target electrophoresis solvent temperature to obtain a temperature difference value, and use the sum of all temperature differences as the temperature change amount, and use the sum of the target electrophoresis solvent temperature and the temperature change amount as the comparison temperature;

[0044] Input the target current and the target electrophoresis solvent temperature into the temperature and current and temperature and coating speed relationship model to obtain the target speed; input the current and comparison temperature into the temperature and current and temperature and coating speed relationship model to obtain the comparison speed;

[0045] Use the following formula to calculate the time impact value:

[0046] ,

[0047] In the formula, represents the time impact value, Indicates the length of a single analysis period, represents the target speed, Indicates comparison speed.

[0048] Preferably, the step of controlling the coating working time according to the corrected target time comprises:

[0049] The target duration is monitored in real time, and compared with the duration of the coating work. When it is monitored that the duration of the coating work is greater than or equal to the target duration, the electrophoretic equipment is controlled to complete the coating work.

[0050] The present invention also provides an electrophoresis equipment automatic operation control system, which is used to implement an electrophoresis equipment automatic operation control method, including:

[0051] A data set acquisition module, used for acquiring a number of coating work data to form a coating work data set, wherein the coating work data includes workpiece parameters, coating thickness and electrophoresis work parameters, wherein the electrophoresis work parameters include working current, working temperature, distance between two electrodes and working time;

[0052] A model training module, used for training a working parameter acquisition model using a coating working data set, wherein the working parameter acquisition model is used for acquiring electrophoresis working parameters according to workpiece parameters and coating thickness;

[0053] A parameter acquisition module is used to acquire real-time workpiece parameters and coating thickness of the workpiece to be coated, and input the real-time workpiece parameters and coating thickness into a working parameter acquisition model to obtain electrophoresis working parameters;

[0054] The working current among the obtained electrophoresis working parameters is used as the target current, the working temperature is used as the target electrophoresis solvent temperature, the distance between the two electrodes is used as the target distance, and the working time is used as the target time;

[0055] An equipment control module is used to control the electrophoresis equipment to perform coating work according to the target current, target electrophoresis solvent temperature and the distance between the two electrodes;

[0056] The real-time acquisition module is used to determine the acquisition frequency according to the target duration, and to collect the electrophoresis solvent temperature data and current data according to the acquisition frequency during the coating process;

[0057] The duration control module is used to correct the target duration according to the collected electrophoresis solvent temperature data and current data, combined with the target current and the target electrophoresis solvent temperature, and control the coating working duration according to the corrected target duration.

[0058] The present invention provides an automatic operation control method and system for electrophoresis equipment, which has the following beneficial effects:

[0059] By collecting actual working data during the coating process and using the working parameter acquisition model trained with these data, the most suitable electrophoretic working parameters can be automatically calculated for different workpieces. Compared with the traditional method that relies on experience-based presets, this method can more accurately adapt to the differences in size, conductivity, and other aspects of various workpieces, improve coating quality, reduce fluctuations in coating quality due to human factors, and ensure the overall quality of the product. During the coating process, the temperature and current data of the electrophoretic solvent are collected in real time. By analyzing these data and comparing them with the target parameters, the target duration of the coating work is dynamically corrected. This real-time monitoring and dynamic adjustment mechanism ensures that the coating process can adapt to the dynamic changes of parameters, effectively avoids the problem of too thick or too thin coating, reduces the waste of material resources, and improves the functionality and appearance quality of the product. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A schematic diagram of a flow chart of an automatic operation control method of an electrophoresis device according to the present invention;

[0061] Figure 2 The present invention is a schematic diagram of a module of an automatic operation control system of an electrophoresis device. DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. 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. Example 1

[0063] See also Figure 1 In this embodiment, a method for controlling the automatic operation of an electrophoresis device includes:

[0064] S1. Acquire a number of coating work data to form a coating work data set, wherein the coating work data includes workpiece parameters, coating thickness and electrophoresis work parameters, and the electrophoresis work parameters include working current, working temperature, distance between two electrodes and working time;

[0065] The workpiece parameters include workpiece conductivity and workpiece surface area; the step of acquiring a plurality of coating work data to form a coating work data set includes:

[0066] Obtain any object to be coated, obtain workpiece parameters of the object to be coated, and use electrophoresis equipment to coat the object to be coated;

[0067] The electrophoresis solvent temperature and current in the coating process are collected at a preset frequency to form an electrophoresis solvent temperature determination array and a current determination array, respectively, and whether the current coating process can be used as reference data is determined based on the electrophoresis solvent temperature determination array and the current determination array;

[0068] If the judgment result is that it can be used as reference data, then the average value of the electrophoresis solvent temperature determination array is obtained as the working temperature, and the average value of the current determination array is obtained as the working current;

[0069] The distance between the cathode and the anode during the coating process is obtained as the distance between the two electrodes, the coating thickness is measured after the coating is completed as the coating thickness, and the total coating time is obtained as the working time;

[0070] Working temperature, working current and working time are used to form electrophoresis working parameters, and workpiece parameters of the object to be coated, coating thickness and electrophoresis working parameters are used to form a coating working data;

[0071] Use different objects to be painted to obtain corresponding painting work data to form a painting work data set.

[0072] The step of judging whether the current coating process can be used as reference data according to the electrophoresis solvent temperature judgment array and the current judgment array comprises:

[0073] A difference coefficient is preset, and a ratio between an average value and a standard deviation of the electrophoresis solvent temperature determination array is calculated to determine whether it is less than the difference coefficient; if so, a stable label is marked on the electrophoresis solvent temperature determination array; otherwise, an unstable label is marked on the electrophoresis solvent temperature determination array;

[0074] Calculate whether the ratio between the mean value and the standard deviation of the current determination array is less than the coefficient of variation; if so, label the current determination array as stable; otherwise, label the current determination array as unstable;

[0075] Obtain the labels of the electrophoresis solvent temperature determination array and the current determination array; if both are stable labels, it is determined that this coating process can be used as reference data; otherwise, it is determined that this coating process cannot be used as reference data.

[0076] In this embodiment, firstly, a plurality of articles to be coated of different materials and shapes are prepared, such as steel plates, aluminum alloy parts, iron shells, etc. For each article to be coated, the conductivity of the workpiece can be measured using a conductivity tester, and the surface area of ​​the workpiece can be measured using an area calculation method or an image size measuring instrument.

[0077] Next, the electrophoresis device is used to coat the object to be coated. During the coating process, the electrophoresis solvent temperature and current data are continuously collected at a preset collection frequency (e.g., once per second). These data are recorded in the electrophoresis solvent temperature determination array and the current determination array, respectively.

[0078] In order to determine whether this coating process can be used as valid reference data, these two arrays are analyzed. The mean and standard deviation of each array are calculated. If the ratio of the standard deviation to the mean (i.e., the coefficient of variation) is less than the preset threshold (e.g., 0.05), the parameter is considered to remain stable during the coating process. Only when the electrophoretic solvent temperature and current remain stable, this coating process is judged to be reference data. For the coating process that is judged to be reference data, the average value of the electrophoretic solvent temperature determination array is taken as the working temperature, and the average value of the current determination array is taken as the working current. At the same time, the distance between the cathode and the anode during the coating process is measured using a rangefinder and recorded as the distance between the two poles. After the coating is completed, the coating thickness is measured using a coating thickness gauge, and the duration of the entire coating process is recorded as the working time. The working temperature, working current, distance between the two poles, and working time obtained above are combined into electrophoretic working parameters. These electrophoretic working parameters are then combined with the previously measured workpiece parameters and coating thickness to form a complete coating working data.

[0079] Repeat the above steps to conduct multiple painting experiments on objects of different materials, shapes, and sizes. Each experiment may generate a piece of painting work data. In this way, a large amount of painting work data can be collected and eventually form a comprehensive painting work data set.

[0080] This coating work data set contains coating parameters and results under various conditions, providing a rich data foundation for the subsequent training of work parameter acquisition models. It should be noted that in the electrophoretic coating process, current intensity and the temperature of the electrophoretic solution are two crucial control parameters, which directly affect the migration rate of charged particles in the electrophoretic solution, and thus directly affect the quality and efficiency of the coating. Therefore, for the electrophoretic coating process, precise control of current and temperature is the key to achieving high-quality coating and improving production efficiency; in addition, the workpiece needs to be cleaned, degreased, and derusted before electrophoretic coating, and then cleaned and dried. These steps can be completed using existing technologies.

[0081] S2. Using the coating work data set to train a working parameter acquisition model, the working parameter acquisition model is used to acquire electrophoresis working parameters according to workpiece parameters and coating thickness;

[0082] The step of using the painting work data set to train the work parameter acquisition model includes:

[0083] Obtain the coating work data set, extract the feature data of workpiece parameters and coating thickness, and divide the cutting data set into a training set and a test set;

[0084] Build a machine learning framework and define the input layer and output layer, set the loss function and optimizer, and build a machine learning model;

[0085] The feature data is used as the input layer data, the electrophoresis working parameters are used as the output layer data, and the training set is used to train the constructed machine learning model according to the set batch size and number of training rounds;

[0086] Use the test set to test the trained machine learning model, and output the machine learning model that meets the preset accuracy as the working parameter acquisition model.

[0087] In this embodiment, the training method of the working parameter acquisition model can be performed as follows:

[0088] First, a data set containing 5000 coating work data is obtained. Each data contains workpiece parameters, coating thickness and corresponding electrophoresis working parameters. Next, the workpiece parameters and coating thickness are combined into a feature vector. For example, a feature vector can be expressed as [workpiece conductivity, workpiece surface area, coating thickness]. In order to ensure the training effect of the model, these feature data can be normalized. Then, using the stratified sampling method, the data set is divided into a training set and a test set in a ratio of 7:3 to ensure that the distribution ratio of each type of data in the two sets is consistent.

[0089] When building a machine learning framework, this embodiment uses the PyTorch framework to build a neural network model. The model structure includes an input layer, three hidden layers, and an output layer. The input layer receives 3 features, corresponding to the dimensions of the feature vector; the output layer produces 4 values, corresponding to four electrophoresis working parameters. The hidden layer can use the LeakyReLU activation function to enhance the nonlinear expression ability of the model. For the loss function, the mean square logarithmic error can be used, which helps to deal with possible outliers and is more sensitive to relative errors. The optimizer selects the AdamW algorithm, which is a variant of Adam that adds weight decay to help prevent overfitting. When compiling the model, you can also set the R² score as an additional evaluation indicator to measure the goodness of fit of the model.

[0090] During the training process, the batch size is set to 64, the initial learning rate is set to 0.001, and the number of training rounds is set to 200. During the training process, the learning rate scheduler can be used to gradually reduce the learning rate to help the model converge better. During training, 85% of the training set is used for training, and the remaining 15% is used for validation to monitor whether the model is overfitting.

[0091] After training is complete, the model performance is evaluated using the previously divided test set. The preset accuracy requirements are an R² score greater than 0.95 and an average relative error less than 5%. If the test results meet these conditions, the model is used as the final working parameter acquisition model.

[0092] The model can predict the appropriate electrophoretic working parameters based on the input workpiece parameters and target coating thickness, providing an accurate reference for the actual electrophoretic coating operation. In this way, the automation and efficiency of the electrophoretic coating process can be improved, the manual debugging time can be reduced, and the consistency of coating quality can be ensured.

[0093] S3, obtaining real-time workpiece parameters and coating thickness of the workpiece to be coated, and inputting the real-time workpiece parameters and coating thickness into a working parameter acquisition model to obtain electrophoresis working parameters;

[0094] S4, using the working current among the obtained electrophoresis working parameters as the target current, the working temperature as the target electrophoresis solvent temperature, the distance between the two poles as the target distance, and the working time as the target time;

[0095] S5, controlling the electrophoresis equipment to perform coating work according to the target current, target electrophoresis solvent temperature and the distance between the two electrodes;

[0096] In this embodiment, the real-time workpiece parameters and coating thickness of the workpiece to be coated can be obtained through manual entry or coding recognition according to actual work requirements; after inputting these data into the working parameter acquisition model, the electrophoresis working parameters output by the model are obtained, and the electrophoresis equipment is controlled to work according to these parameters, and the distance between the cathode and the anode in the equipment is adjusted according to the distance between the two poles. It should be noted that depending on the equipment model, the workpiece can be used as both a cathode and an anode; the current of the electrophoresis process is controlled according to the target current, and the target electrophoresis solvent temperature is controlled according to the target temperature to control the temperature of the electrophoresis solvent in the electrophoresis process; specifically, methods such as PID controller can be used.

[0097] S6. Determine the collection frequency according to the target duration, and collect the electrophoresis solvent temperature data and current data according to the collection frequency during the coating process;

[0098] The step of determining the acquisition frequency according to the target duration includes:

[0099] Obtaining a target duration, a preset number of analysis segments, and a preset minimum amount of data, and evenly dividing the target duration into multiple analysis periods according to the preset number of analysis segments;

[0100] Get the length of a single analysis period; use the minimum amount of data divided by the length of a single segment to get the acquisition frequency.

[0101] In this embodiment, the collection frequency of the painting process is determined according to the target duration. Generally speaking, the shorter the collection duration, the higher the collection frequency. In a specific embodiment, the target duration of the painting process is 120 seconds, the preset number of analysis segments is 6, and the preset minimum data volume is 20. The minimum data volume 20 is divided by the duration of a single segment 20 seconds, and the collection frequency is 1 time per second;

[0102] S7. Correct the target duration according to the collected electrophoresis solvent temperature data and current data, combined with the target current and the target electrophoresis solvent temperature, and control the coating working duration according to the corrected target duration.

[0103] The step of correcting the target duration according to the collected electrophoresis solvent temperature data and current data in combination with the target current and the target electrophoresis solvent temperature comprises:

[0104] During the coating process, when the time of any analysis period has passed, the electrophoresis solvent temperature data collected in the analysis period is obtained to form an electrophoresis solvent temperature array corresponding to the analysis period, and the current data collected in the analysis period is obtained to form a current array corresponding to the analysis period;

[0105] Establish the relationship model between current, temperature and coating speed;

[0106] Calculate the time impact value according to the current array, the target current, the electrophoresis solvent temperature array, the target electrophoresis solvent temperature and the relationship model between the current and temperature and the coating speed;

[0107] The sum of the time impact value and the target duration is used as the new target duration to complete the correction of the target duration.

[0108] The steps of establishing the relationship model between current, temperature and coating speed include:

[0109] When using electrophoresis equipment to coat a workpiece, the coating speeds at different currents and electrophoresis solvent temperatures are collected to obtain a fitting data set, where the coating speed is obtained by dividing the coating thickness change during the coating process by the time taken;

[0110] According to the fitting data set, the current value and the electrophoresis solvent temperature value are used as independent variables, and the coating speed value is used as the dependent variable. The fitting method is used to obtain the corresponding fitting equation as the relationship model between current, temperature and coating speed.

[0111] The step of calculating the time impact value comprises:

[0112] Subtract each value in the current array from the target current to obtain a current difference, and use the sum of all current differences as the current change, and use the sum of the target current and the current change as the comparison current;

[0113] Subtract each value in the electrophoresis solvent temperature array from the target electrophoresis solvent temperature to obtain a temperature difference value, and use the sum of all temperature differences as the temperature change amount, and use the sum of the target electrophoresis solvent temperature and the temperature change amount as the comparison temperature;

[0114] Input the target current and the target electrophoresis solvent temperature into the temperature and current and temperature and coating speed relationship model to obtain the target speed; input the current and comparison temperature into the temperature and current and temperature and coating speed relationship model to obtain the comparison speed;

[0115] Use the following formula to calculate the time impact value:

[0116] ,

[0117] In the formula, represents the time impact value, Indicates the length of a single analysis period, represents the target speed, Indicates comparison speed.

[0118] In this embodiment, first, during the coating process, according to the length of the analysis period, such as 20 seconds, after the electrophoresis equipment starts working, all the electrophoresis solvent temperature data collected in the period are obtained in every 20 seconds to form an electrophoresis solvent temperature array. At the same time, all the current data in the period are also collected to form a current array. These arrays provide basic data for subsequent calculations and analysis.

[0119] In order to establish a relationship model between current and temperature and coating speed, a large amount of data can be collected during the coating process in an actual or experimental environment. Specifically, the coating speed is measured under different current and electrophoretic solvent temperature conditions. The coating speed can be calculated by measuring the change in coating thickness over a specific period of time, that is, the change in coating thickness divided by the time taken. These data constitute a fitting data set. Using this fitting data set, a multivariate regression model can be established. In this model, the current value and electrophoretic solvent temperature value are used as independent variables, and the coating speed value is used as the dependent variable. Polynomial regression or other appropriate regression methods can be used, for example, a polynomial model can be used:

[0120] ,in is the coating speed, is the current, is the temperature, , , and These coefficients can be determined by the least square method or other optimization methods to obtain the relationship model between current, temperature and coating speed.

[0121] Calculate the current change and temperature change. The current change is the sum of the differences between each value in the current array and the target current, and the temperature change is the sum of the differences between each value in the temperature array and the target temperature. Then, the sum of the target current and the current change is used as the comparison current, and the sum of the target temperature and the temperature change is used as the comparison temperature.

[0122] Next, the target speed and the comparison speed are calculated using the established relationship model. The target speed is the result obtained by substituting the target current and the target temperature into the model, while the comparison speed is the result obtained by substituting the comparison current and the comparison temperature into the model.

[0123] Finally, the time impact value is calculated using the formula. The calculated time impact value is added to the original target duration to obtain the corrected new target duration. This new target duration will be used to control the subsequent coating work duration, thereby achieving dynamic adjustment and optimization of the coating process.

[0124] The step of controlling the coating working time according to the corrected target time comprises:

[0125] The target duration is monitored in real time, and compared with the duration of the coating work. When it is monitored that the duration of the coating work is greater than or equal to the target duration, the electrophoretic equipment is controlled to complete the coating work.

[0126] In this embodiment, the system monitors the duration of the coating work and the target duration in real time to ensure accurate control of the coating process. The duration of the coating work is continuously monitored by a timer, and it is constantly compared with the corrected target duration in real time. When it is detected that the duration is greater than or equal to the corrected target duration, the system immediately sends a stop signal to the electrophoretic device to control it to complete the coating work. This method can effectively deal with current and temperature fluctuations caused by factors such as equipment aging and control system problems, and reduce the problem of too thick or too thin coating. For example, if the original target duration is 120 seconds, but the current is slightly lower than expected due to equipment aging, the system can dynamically correct the target duration to 130 seconds and control the coating process until this duration is reached to avoid the problem of too thin coating. The reliability of the electrophoretic coating process is improved, thereby improving product quality. Example 2

[0127] See also Figure 2 The present invention provides an electrophoresis equipment automatic operation control system, which is used to implement an electrophoresis equipment automatic operation control method, including:

[0128] A data set acquisition module, used for acquiring a number of coating work data to form a coating work data set, wherein the coating work data includes workpiece parameters, coating thickness and electrophoresis work parameters, wherein the electrophoresis work parameters include working current, working temperature, distance between two electrodes and working time;

[0129] A model training module, used for training a working parameter acquisition model using a coating working data set, wherein the working parameter acquisition model is used for acquiring electrophoresis working parameters according to workpiece parameters and coating thickness;

[0130] A parameter acquisition module is used to acquire real-time workpiece parameters and coating thickness of the workpiece to be coated, and input the real-time workpiece parameters and coating thickness into a working parameter acquisition model to obtain electrophoresis working parameters;

[0131] The working current among the obtained electrophoresis working parameters is used as the target current, the working temperature is used as the target electrophoresis solvent temperature, the distance between the two electrodes is used as the target distance, and the working time is used as the target time;

[0132] An equipment control module is used to control the electrophoresis equipment to perform coating work according to the target current, target electrophoresis solvent temperature and the distance between the two electrodes;

[0133] The real-time acquisition module is used to determine the acquisition frequency according to the target duration, and to collect the electrophoresis solvent temperature data and current data according to the acquisition frequency during the coating process;

[0134] The duration control module is used to correct the target duration according to the collected electrophoresis solvent temperature data and current data, combined with the target current and the target electrophoresis solvent temperature, and control the coating working duration according to the corrected target duration.

[0135] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only one, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0136] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

[0137] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for controlling the automatic operation of an electrophoresis device, characterized in that: include: S1. Acquire a number of coating work data to form a coating work data set, wherein the coating work data includes workpiece parameters, coating thickness and electrophoresis work parameters, and the electrophoresis work parameters include working current, working temperature, distance between two electrodes and working time; The workpiece parameters include workpiece conductivity and workpiece surface area; The step of acquiring a plurality of painting work data to form a painting work data set comprises: Obtain any object to be coated, obtain workpiece parameters of the object to be coated, and use electrophoresis equipment to coat the object to be coated; The electrophoresis solvent temperature and current in the coating process are collected at a preset frequency to form an electrophoresis solvent temperature determination array and a current determination array, respectively, and whether the current coating process can be used as reference data is determined based on the electrophoresis solvent temperature determination array and the current determination array; If the judgment result is that it can be used as reference data, then the average value of the electrophoresis solvent temperature determination array is obtained as the working temperature, and the average value of the current determination array is obtained as the working current; The distance between the cathode and the anode during the coating process is obtained as the distance between the two electrodes, the coating thickness is measured after the coating is completed as the coating thickness, and the total coating time is obtained as the working time; The electrophoresis working parameters are composed of the working temperature, working current and working time, and the workpiece parameters of the object to be coated, the coating thickness and the electrophoresis working parameters are composed of a coating working data; Use different objects to be painted to obtain corresponding painting work data to form a painting work data set; The step of judging whether the current coating process can be used as reference data according to the electrophoresis solvent temperature judgment array and the current judgment array comprises: A difference coefficient is preset, and a ratio between an average value and a standard deviation of the electrophoresis solvent temperature determination array is calculated to determine whether it is less than the difference coefficient; if so, a stable label is marked on the electrophoresis solvent temperature determination array; otherwise, an unstable label is marked on the electrophoresis solvent temperature determination array; Calculate whether the ratio between the mean value and the standard deviation of the current determination array is less than the coefficient of variation; if so, label the current determination array as stable; otherwise, label the current determination array as unstable; Obtain the labels of the electrophoresis solvent temperature determination array and the current determination array; if both are stable labels, it is determined that this coating process can be used as reference data; otherwise, it is determined that this coating process cannot be used as reference data; S2. Using the coating work data set to train a working parameter acquisition model, the working parameter acquisition model is used to acquire electrophoresis working parameters according to workpiece parameters and coating thickness; S3, obtaining real-time workpiece parameters and coating thickness of the workpiece to be coated, and inputting the real-time workpiece parameters and coating thickness into a working parameter acquisition model to obtain electrophoresis working parameters; S4, using the working current among the obtained electrophoresis working parameters as the target current, the working temperature as the target electrophoresis solvent temperature, the distance between the two poles as the target distance, and the working time as the target time; S5, controlling the electrophoresis equipment to perform coating work according to the target current, target electrophoresis solvent temperature and the distance between the two electrodes; S6. Determine the collection frequency according to the target duration, and collect the electrophoresis solvent temperature data and current data according to the collection frequency during the coating process; S7, according to the collected electrophoresis solvent temperature data and current data, combined with the target current and the target electrophoresis solvent temperature, the target duration is corrected, and the coating working duration is controlled according to the corrected target duration; The steps of modifying the target duration include: During the coating process, when the time of any analysis period has passed, the electrophoresis solvent temperature data collected in the analysis period is obtained to form an electrophoresis solvent temperature array corresponding to the analysis period, and the current data collected in the analysis period is obtained to form a current array corresponding to the analysis period; Establish the relationship model between current, temperature and coating speed; Calculate the time impact value according to the current array, the target current, the electrophoresis solvent temperature array, the target electrophoresis solvent temperature and the relationship model between the current and temperature and the coating speed; The sum of the time impact value and the target duration is used as the new target duration to complete the correction of the target duration; The step of calculating the time impact value comprises: Subtract each value in the current array from the target current to obtain a current difference, and use the sum of all current differences as the current change, and use the sum of the target current and the current change as the comparison current; Subtract each value in the electrophoresis solvent temperature array from the target electrophoresis solvent temperature to obtain a temperature difference value, and use the sum of all temperature differences as the temperature change amount, and use the sum of the target electrophoresis solvent temperature and the temperature change amount as the comparison temperature; Inputting the target current and the target electrophoresis solvent temperature into the current and temperature and coating speed relationship model to obtain the target speed; inputting the comparison current and the comparison temperature into the current and temperature and coating speed relationship model to obtain the comparison speed; Use the following formula to calculate the time impact value: ， In the formula, represents the time impact value, Indicates the length of a single analysis period, represents the target speed, Indicates comparison speed.

2. The method for controlling the automatic operation of an electrophoresis device according to claim 1, characterized in that: The step of using the painting work data set to train the work parameter acquisition model includes: Obtain the coating work data set, extract the feature data of workpiece parameters and coating thickness, and divide the cutting data set into a training set and a test set; Build a machine learning framework and define the input layer and output layer, set the loss function and optimizer, and build a machine learning model; The feature data is used as the input layer data, the electrophoresis working parameters are used as the output layer data, and the training set is used to train the constructed machine learning model according to the set batch size and number of training rounds; Use the test set to test the trained machine learning model, and output the machine learning model that meets the preset accuracy as the working parameter acquisition model.

3. The method for controlling the automatic operation of an electrophoresis device according to claim 2, characterized in that: The step of determining the acquisition frequency according to the target duration includes: Obtaining a target duration, a preset number of analysis segments, and a preset minimum amount of data, and evenly dividing the target duration into multiple analysis periods according to the preset number of analysis segments; Get the length of a single analysis period; use the minimum amount of data divided by the length of a single segment to get the acquisition frequency.

4. The method for controlling the automatic operation of an electrophoresis device according to claim 3, characterized in that: The steps of establishing the relationship model between current, temperature and coating speed include: When using electrophoresis equipment to coat a workpiece, the coating speeds at different currents and electrophoresis solvent temperatures are collected to obtain a fitting data set, where the coating speed is obtained by dividing the coating thickness change during the coating process by the time taken; According to the fitting data set, the current value and the electrophoresis solvent temperature value are used as independent variables, and the coating speed value is used as the dependent variable. The fitting method is used to obtain the corresponding fitting equation as the relationship model between current, temperature and coating speed.

5. The method for controlling the automatic operation of an electrophoresis device according to claim 4, characterized in that: The step of controlling the coating working time according to the corrected target time comprises: The target duration is monitored in real time, and compared with the duration of the coating work. When it is monitored that the duration of the coating work is greater than or equal to the target duration, the electrophoretic equipment is controlled to complete the coating work.

6. An electrophoresis equipment automatic operation control system, used to implement an electrophoresis equipment automatic operation control method according to any one of claims 1 to 5, characterized in that: include: A data set acquisition module, used for acquiring a number of coating work data to form a coating work data set, wherein the coating work data includes workpiece parameters, coating thickness and electrophoresis work parameters, wherein the electrophoresis work parameters include working current, working temperature, distance between two electrodes and working time; A model training module, used for training a working parameter acquisition model using a coating working data set, wherein the working parameter acquisition model is used for acquiring electrophoresis working parameters according to workpiece parameters and coating thickness; A parameter acquisition module is used to acquire real-time workpiece parameters and coating thickness of the workpiece to be coated, and input the real-time workpiece parameters and coating thickness into a working parameter acquisition model to obtain electrophoresis working parameters; The working current among the obtained electrophoresis working parameters is used as the target current, the working temperature is used as the target electrophoresis solvent temperature, the distance between the two electrodes is used as the target distance, and the working time is used as the target time; An equipment control module is used to control the electrophoresis equipment to perform coating work according to the target current, target electrophoresis solvent temperature and the distance between the two electrodes; The real-time acquisition module is used to determine the acquisition frequency according to the target duration, and to collect the electrophoresis solvent temperature data and current data according to the acquisition frequency during the coating process; The duration control module is used to correct the target duration according to the collected electrophoresis solvent temperature data and current data, combined with the target current and the target electrophoresis solvent temperature, and control the coating working duration according to the corrected target duration.

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