Integrated plating control module multi-parameter closed loop management system and method

Abstract

The application discloses an integrated electroplating control module multi-parameter closed-loop management system and method, relates to the technical field of intelligent control, and comprises the following units: an analysis unit which extracts impedance response characteristics of a multi-frequency electrochemical response sequence, decomposes into real and imaginary parts under different time constants, and analyzes a real-time electrochemical state parameter set; an evaluation unit which logically compares the real-time electrochemical state parameter set with macro-environment data collected by a physical sensor and outputs a sensor state evaluation result; a decision unit which, according to the sensor state evaluation result, replaces the failed physical signal with the real-time electrochemical state parameter set when determining that the physical sensor data is abnormal, and outputs a control law optimization instruction set; and an execution unit which, based on the control law optimization instruction set, drives an execution mechanism to carry out linkage adjustment on an electroplating process, and simultaneously updates a target plating species initial control reference. The application ensures production continuity under extreme working conditions and improves the precision management capability of the electroplating process.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, and in particular to a multi-parameter closed-loop management system and method for an integrated electroplating control module. Background Technology

[0002] The technological evolution in integrated electroplating control has progressed from simple analog control to a stage of digital and intelligent multi-parameter collaborative management. Existing industrial electroplating control systems primarily rely on arrays of physical sensors deployed around the electroplating tank, such as high-precision pH sensors, thermistor thermometers, and inductive level gauges. These sensors collect macroscopic process parameters in real time through industrial control networks and utilize programmable logic controllers (PLCs) to execute closed-loop feedback regulation based on PID algorithms, thereby maintaining the relative stability of the electroplating solution's physicochemical properties. With the development of power electronics technology, some systems have begun to integrate high-frequency pulse rectifier power supplies. By adjusting the frequency and duty cycle of the current pulses, the microcrystalline structure of the coating is optimized, achieving significant engineering application results in improving deposition rates and ensuring coating uniformity.

[0003] However, during long-term continuous electroplating operations, physical sensors are constantly exposed to extreme corrosive environments such as high temperatures, strong acids or alkalis, and complex electromagnetic interference. The sensor probes are prone to chemical passivation or physical drift, resulting in deviations between the acquired feedback data and the actual electrochemical state of the electrode interface. Due to the lack of a real-time in-situ verification mechanism for sensor effectiveness, once the physical sensor fails, the closed-loop control logic will make incorrect adjustments based on the erroneous feedback signal, leading to loss of control of the electroplating production process and deterioration of the finished product quality. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides an integrated electroplating control module multi-parameter closed-loop management system to solve the problem of decreased system control accuracy and process runaway caused by the drift failure of physical sensors under extreme environments.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, the present invention provides an integrated electroplating control module multi-parameter closed-loop management system, comprising:

[0008] The excitation unit acquires the initial control reference of the target plating type, generates a composite detection sequence, injects it into the electroplating tank to excite the electrolytic interface to generate induction feedback, and outputs a multi-frequency electrochemical response sequence.

[0009] The analytical unit extracts the impedance response characteristics of the multi-frequency electrochemical response sequence, decomposes them into real and imaginary components under different time constants, and analyzes the real-time electrochemical state parameter set.

[0010] The evaluation unit logically compares the real-time electrochemical state parameter set with the macroscopic environmental data collected by the physical sensors and outputs the sensor state evaluation results.

[0011] The decision-making unit, based on the sensor status evaluation results, when it determines that the physical sensor data is abnormal, replaces the failed physical signal with the real-time electrochemical state parameter set and outputs a control law optimization instruction set.

[0012] The execution unit, based on the control law optimization instruction set, drives the actuator to perform linkage adjustment of the electroplating process, and at the same time updates the initial control reference of the target plating type, using the updated initial control reference of the target plating type as the starting reference for the next cycle.

[0013] Preferably, the method for generating the composite detector sequence includes:

[0014] After receiving the production task instruction, the process formula database is searched to obtain the initial control benchmark of the target plating type. Based on the upper limit of current density and the rated value of electrolyte temperature in the initial control benchmark of the target plating type, the corresponding electrochemical stability envelope boundary is extracted as the coordinate of the safe region of the impedance complex plane.

[0015] The phase step value is determined based on the coordinates of the safe region of the impedance complex plane. The phase step value is accumulated to obtain the address index. The instantaneous amplitude value of the sine wave is retrieved from the storage area where the instantaneous amplitude value of the sine wave is stored, and a specific sine wave frequency point is generated.

[0016] The instantaneous amplitude values ​​of the sine wave corresponding to each specific sine wave frequency point are accumulated and summarized to generate a composite detection sequence.

[0017] Preferably, the method for outputting the multi-frequency electrochemical response sequence includes:

[0018] The composite detection sequence is converted into an analog voltage disturbance signal through digital-to-analog conversion; the analog voltage disturbance signal is coupled to the electroplating DC power supply using a superposition circuit to inject it into the electroplating tank, thereby stimulating the electrolytic interface to generate inductive feedback.

[0019] The induced current and induced voltage signals at the electrolysis interface are collected and converted from analog to digital. The converted induced current and induced voltage signals are then truncated in the time domain and frequency aligned and packaged to output a multi-frequency electrochemical response sequence.

[0020] Preferably, the method for obtaining the real component and the imaginary component includes:

[0021] The multi-frequency electrochemical response sequence is multiplied and integrated with the orthogonal reference signal to obtain the complex impedance value corresponding to each frequency point as the impedance response characteristic.

[0022] The complex impedance values ​​are projected onto the complex plane coordinate system, and the real part of the impedance corresponding to the horizontal axis and the imaginary part of the impedance corresponding to the vertical axis are separated. They are then classified into real and imaginary components under different time constants according to frequency.

[0023] Preferably, the method for resolving the real-time electrochemical state parameter set includes:

[0024] Pre-determine the electrochemical equivalent circuit structure and assign initial physical quantity values ​​to the components to generate a theoretical trajectory;

[0025] Based on the positional deviation between the theoretical trajectory and the measured trajectory composed of the real and imaginary components, the physical quantity values ​​of each component in the electrochemical equivalent circuit structure are adjusted to make the theoretical trajectory approach the measured trajectory until the residual meets the preset threshold.

[0026] When the residual meets the preset threshold, the parameter values ​​of each component in the current electrochemical equivalent circuit structure are extracted to identify the physical quantity values ​​corresponding to the electrolyte bulk resistance, polarization resistance and double layer capacitance, and output the real-time electrochemical state parameter set.

[0027] Preferably, the method for outputting the sensor state evaluation result includes:

[0028] Based on timestamp information, the real-time electrochemical state parameter set is time-aligned with the macroscopic environmental data collected by physical sensors;

[0029] The electrolyte bulk resistance in the real-time electrochemical state parameter set is mapped and converted into a theoretical conductivity value, which is then compared with the measured conductivity value in the macroscopic environmental data to obtain the Euclidean distance between the two.

[0030] The Euclidean distance is used as the fault confidence score and compared with a preset confidence threshold. If the Euclidean distance is less than the preset confidence threshold, the physical sensor is determined to be effective; if the Euclidean distance is greater than the preset confidence threshold, the physical sensor is determined to be ineffective, and the sensor status evaluation result is output.

[0031] Preferably, the method for optimizing the output control law instruction set includes:

[0032] When the sensor status evaluation result determines that the physical sensor is invalid, that is, when the physical sensor data is abnormal, the input path of the macroscopic environmental data collected by the physical sensor is blocked.

[0033] The polarization resistance physical quantity value in the real-time electrochemical state parameter set is converted into a compensatory feedback signal with physical dimensions, and the compensatory feedback signal is used to replace the failed physical signal.

[0034] The compensation feedback signal is compared with the preset expected value in the initial control benchmark of the target plating type to obtain the instantaneous deviation of the physical parameters and retrieve the corresponding basic control gain.

[0035] The control gain is corrected based on the instantaneous deviation and the physical value of the double-layer capacitance in the real-time electrochemical state parameter set, and the control law optimization instruction set is output.

[0036] Preferably, the method for the drive actuator to adjust the electroplating process in conjunction with the electroplating process includes:

[0037] The control law optimization instruction set is parsed into the underlying control code corresponding to the voltage regulation amplitude, pumping frequency variable and dosing pump pulse width.

[0038] The underlying control code is sent to the electroplating DC power supply, the circulating filter pump and the automatic dosing machine respectively, so as to drive the electroplating DC power supply to adjust the output potential, drive the circulating filter pump to change the flow rate of the tank liquid, and drive the automatic dosing machine to perform additive replenishment.

[0039] The system acquires the hardware status parameters after the actuator completes its action, compares these parameters with the control law optimization instruction set, and determines the controlled adjustment state of the electroplating process. It also maintains the operating state of the actuator after the linkage adjustment and acquires the adjusted process feedback.

[0040] Preferably, the method for updating the initial control benchmark of the target plating type includes:

[0041] Extract the hardware status parameters after the linkage adjustment is completed, as well as the physical quantity values ​​of each component in the real-time electrochemical status parameter set; use the hardware status parameters and the physical quantity values ​​of each component to overwrite the corresponding stored values ​​in the initial control reference of the target plating type.

[0042] The updated data packet is used as the initial control reference for the updated target plating type, and the updated initial control reference for the target plating type is sent to the start of the next cycle as a starting reference.

[0043] Secondly, the present invention provides a multi-parameter closed-loop management method for an integrated electroplating control module, including:

[0044] The initial control benchmark of the target plating type is obtained, a composite detection sequence is generated and injected into the electroplating tank to stimulate the electrolytic interface to generate inductive feedback, and a multi-frequency electrochemical response sequence is output.

[0045] The impedance response characteristics of the multi-frequency electrochemical response sequence are extracted, decomposed into real and imaginary components under different time constants, and the real-time electrochemical state parameter set is analyzed.

[0046] The real-time electrochemical state parameter set is logically compared with the macroscopic environmental data collected by physical sensors, and the sensor state evaluation results are output.

[0047] Based on the sensor status evaluation results, when the physical sensor data is determined to be abnormal, the failed physical signal is replaced by the real-time electrochemical state parameter set, and the control law optimization instruction set is output.

[0048] Based on the control law optimization instruction set, the actuator is driven to adjust the electroplating process in a coordinated manner, while updating the initial control reference of the target plating type, and using the updated initial control reference of the target plating type as the starting reference for the next cycle.

[0049] The beneficial effects of this invention are as follows: by extracting the boundary of the electrochemical stability envelope as the coordinates of the safe area and generating a composite detection sequence accordingly, the dynamic adaptation of the excitation signal and the instantaneous physical limit of the electroplating tank interface is realized. Under the premise of ensuring that side reactions such as hydrogen evolution reaction or abnormal decomposition of additives are not triggered, multi-frequency electrochemical responses can be obtained more specifically, thereby improving the reliability and security of monitoring data while maintaining the stability of the production environment.

[0050] By logically calibrating the real-time electrochemical state parameter set with physical sensor data, and using polarization resistance and double-layer capacitance for signal compensation and control law correction when anomalies are detected, a deep verification mechanism for the macroscopic physical environment and microscopic electrochemical mechanism is constructed. This enables the continuous operation of the process based on microscopic characteristic quantities even under complex conditions such as physical sensor drift or failure, enhancing the system's fault tolerance and the level of intelligence in closed-loop control. It ensures production continuity under extreme conditions and significantly improves the precision management capability of the electroplating process through complementary data dimensions. Attached Figure Description

[0051] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart of the multi-parameter closed-loop management system for the integrated electroplating control module in this invention;

[0053] Figure 2 This is a schematic diagram of the multi-parameter closed-loop management method of the integrated electroplating control module in this invention;

[0054] Figure 3 This is a flowchart illustrating the output of the real-time electrochemical state parameter set in this invention;

[0055] Figure 4 This is a flowchart of the output control law optimization instruction set in this invention. Detailed Implementation

[0056] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0057] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0058] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0059] Reference Figure 1 , Figure 2 , Figure 3 and Figure 4 As one embodiment of the present invention, this embodiment provides an integrated electroplating control module multi-parameter closed-loop management system, including the following steps:

[0060] Methods for generating composite probe sequences include:

[0061] Upon receiving the production task instruction, the system retrieves the initial control benchmark for the target plating type from the process formula database. Based on the upper limit of current density and the rated value of electrolyte temperature in the initial control benchmark for the target plating type, the system extracts the corresponding electrochemical stability envelope boundary as the coordinates of the safe region of the impedance complex plane.

[0062] Specifically, upon receiving a production task instruction, the system accesses the process formula database, retrieves and calls up the corresponding initial control reference for the target plating type according to the plating type required for the current workpiece, and reads the upper limit value of the current density (example value). Production process parameters including the rated electrolyte temperature (example value is 45℃);

[0063] After obtaining the upper limit of current density and the rated value of electrolyte temperature, the electrochemical stability envelope data table pre-stored in the process memory is matched to extract the impedance real part that is not less than the example value under the conditions of the upper limit of current density and the rated value of electrolyte temperature, without the generation of hydrogen evolution side reaction and without causing oxidative decomposition of additives. Furthermore, the imaginary part of the impedance at a specific frequency is not greater than the example value. The nonlinear envelope curve is obtained and defined as the boundary of the electrochemical stability envelope.

[0064] The boundary of the electrochemical stability envelope is transformed and mapped to a complex plane coordinate system with the real part of impedance as the horizontal axis and the imaginary part of impedance as the vertical axis, generating a closed geometric figure composed of discrete complex points whose horizontal axis coordinates are greater than the example value of 0.5 and are located within a preset semi-circular trajectory.

[0065] It should be noted that the preset semicircular trajectory starts with an example value of 0.5 for the electrolyte bulk resistance and ends with an example value of 2.5 for the sum of the electrolyte bulk resistance and polarization resistance, forming a semicircular envelope region with an example value of 1.0 at the vertices of the arc. The coordinates of all points within this closed geometry are defined as the coordinates of the impedance complex plane safe region.

[0066] The phase step value is determined based on the coordinates of the safe region of the impedance complex plane. The phase step value is accumulated to obtain the address index. The instantaneous amplitude value of the sine wave is retrieved from the storage area that stores the instantaneous amplitude value of the sine wave, and a specific sine wave frequency point is generated.

[0067] It should be noted that the phase angle limit value corresponding to each frequency point is extracted from the coordinates of the safe region of the impedance complex plane, and combined with the preset clock frequency example value of 10MHz, the phase step value example value of 0.01rad is calculated by mapping the product of the target frequency and the sampling period to the phase space.

[0068] The address index is obtained by cyclically accumulating the phase step value. Then, the address index is used as the memory address offset to retrieve the instantaneous amplitude value of the sine wave at the corresponding phase point from the waveform storage area.

[0069] By changing the value of the phase step, the time to complete one full address cycle can be shortened or lengthened, thereby generating specific sine wave frequency points with different frequency characteristics (such as a frequency example of 10Hz and a frequency example of 1kHz) while maintaining the sampling rate.

[0070] The instantaneous amplitude values ​​of the sine wave corresponding to each specific sine wave frequency point are accumulated and summarized to generate a composite detection sequence.

[0071] Specifically, specific sine wave frequency points are aligned on the same time axis, and the instantaneous amplitude values ​​of the sine wave with a frequency example of 10Hz and the instantaneous amplitude values ​​of the sine wave with a frequency example of 1kHz are summed point by point at the same sampling time to obtain a discrete composite amplitude data stream.

[0072] The peak value of the composite amplitude data stream is scaled and verified against the maximum allowable voltage amplitude to synthesize a composite detection sequence containing multiple frequency components with a peak amplitude not exceeding 5% of the example value of the effective output voltage. This sequence is then used as the original excitation signal for detection in the electroplating tank.

[0073] In traditional electroplating monitoring, the state of the plating bath is typically assessed using impedance detection at a single frequency or simple empirical models. This approach struggles to isolate complex electrochemical overlap signals, and its signal-to-noise ratio and analog-to-digital conversion accuracy often fail to meet the demands of precision manufacturing when facing strong magnetic interference from high-power buses. Furthermore, traditional methods struggle to capture the microscopic physical evolution of the electrode interface under different time constants in real time, leading to a lag in the identification of interfacial reaction resistance and charge distribution. Therefore, this invention constructs a real-time extraction link for deep physical information through high-precision weighted resistor network excitation, step-by-step trial-and-error quantization acquisition, and parameter approximation analysis of equivalent circuits. The specific steps are as follows:

[0074] Methods for outputting multi-frequency electrochemical response sequences include:

[0075] The composite detection sequence is converted into an analog voltage disturbance signal through digital-to-analog conversion; the analog voltage disturbance signal is coupled to the electroplating DC power supply using a superposition circuit to inject it into the electroplating tank, thereby stimulating the electrolytic interface to generate inductive feedback.

[0076] It should be noted that the digital-to-analog conversion is performed using a reference voltage source (5V in this example) that provides a constant level reference, along with a weighted resistor network. Specifically, based on binary weighted logic, a set of resistance values ​​is preset to... The resistor branches are distributed proportionally, where the resistance of the branch corresponding to the most significant bit is the base value (1kΩ in the example), the resistance of the branch corresponding to the second most significant bit is twice the base value (2kΩ in the example), and so on until the least significant bit branch; by connecting each digital logic level in the composite detection sequence to the electronic switch of the corresponding branch resistor, the on / off state of each branch resistor is controlled; the current flowing through each branch is converged to the summing node according to the binary weight ratio, and using Ohm's law and the principle of current superposition, the composite detection sequence is converted into an analog voltage perturbation signal with continuously changing level according to the bit weight;

[0077] By using a superimposed circuit containing an operational amplifier and a magnetically coupled induction coil, the analog voltage disturbance signal is linearly coupled to the output of the electroplating DC power supply. While realizing signal transmission, the DC high current component is isolated, so that a small fluctuation with an amplitude not exceeding the effective value of the output voltage (5% in the example) is superimposed on the originally constant DC output.

[0078] The superimposed mixed current is injected into the electroplating tank. Since the simulated voltage disturbance signal contains frequency characteristics (such as a frequency of 10Hz and a frequency of 1kHz), the charge will charge and discharge and electrochemical reaction will occur on the electrode surface, thereby stimulating the electrolytic interface to generate inductive feedback containing interface impedance information.

[0079] The induced current and induced voltage signals at the electrolysis interface are collected and converted from analog to digital. The converted induced current and induced voltage signals are then truncated in the time domain and frequency aligned and packaged to output a multi-frequency electrochemical response sequence.

[0080] Specifically, the principle of electromagnetic induction is used to sense changes in the magnetic field around the high-current busbar to obtain the induced current signal at the electrolysis interface without contact, and a voltage divider sampling circuit is used to obtain the induced voltage signal. During the analog-to-digital conversion of the induced current and induced voltage signals, internal voltage comparison logic is used to compare the acquired analog voltage with the controlled, generated stepped reference voltage step by step.

[0081] Starting from the most significant bit of the register, each bit is set to logic level 1 in sequence from high to low, so that the controlled generated step reference voltage produces a corresponding step increment, and is aligned with the current analog amplitude of the induced current signal or induced voltage signal in real time.

[0082] During each comparison process, if the analog voltage is higher than the current step reference voltage, the logic level of that bit in the register is retained to 1; if the analog voltage is lower than the step reference voltage, the bit in the register is corrected and reset to logic level 0.

[0083] Through this bit-by-bit probing and feedback from high to low, the binary value in the register is continuously corrected until the voltage corresponding to the register value is infinitely close to the analog voltage. Thus, the analog voltage is quantized by continuously approximating the quantization process to complete the analog-to-digital conversion.

[0084] For the digital sequence after analog-to-digital conversion, time-domain truncation is performed based on the high-precision timestamp of the starting pulse to remove the non-steady-state part at the beginning of the waveform. Then, spectrum alignment and data encapsulation are performed according to the period length of each frequency component (e.g., 10Hz and 1kHz). Redundant data other than the sampling period (1ms in the example) are removed, and a multi-frequency electrochemical response sequence is output.

[0085] The methods for obtaining the real and imaginary components include:

[0086] The multi-frequency electrochemical response sequence is multiplied and integrated with the orthogonal reference signal to obtain the complex impedance value corresponding to each frequency point, which is used as the impedance response characteristic.

[0087] Specifically, a standard sine numerical sequence containing the initial phase of the excitation signal is generated in real time by directly using a digital sequence that is phase-synchronized with each frequency component in the composite detection sequence, and a cosine numerical sequence obtained by shifting the phase (90° in the example) on the same frequency axis, thereby forming an orthogonal reference signal.

[0088] The multi-frequency electrochemical response sequence is multiplied point by point with a sinusoidal reference signal of the same frequency and phase and a cosine reference signal with a phase offset (90° in the example) to complete the component projection of the response signal in an orthogonal coordinate system.

[0089] For the discrete product sequence after dot product, numerical integration is performed within the complete period of the corresponding frequency (1ms in the example). The low-pass filtering characteristic of integration is used to filter out high-frequency noise, and the amplitude of the in-phase component that is in the same direction as the reference signal and the amplitude of the quadrature component that is out of phase (90° in the example) are extracted from the response signal.

[0090] Next, using the complex form of Ohm's law, the ratio of the induced voltage signal component to the induced current signal component is calculated to obtain the complex impedance value corresponding to each frequency point, and the complex impedance value is used as the impedance response characteristic that can characterize the state of the electrolytic interface.

[0091] The complex impedance values ​​are projected onto the complex plane coordinate system, and the real part of the impedance corresponding to the horizontal axis and the imaginary part of the impedance corresponding to the vertical axis are separated. They are then classified into real and imaginary components under different time constants according to frequency.

[0092] It should be noted that, using the mathematical rule of rectangular coordinate projection, the complex impedance value is projected onto a complex plane coordinate system with the real part of the impedance as the horizontal axis and the imaginary part of the impedance as the vertical axis.

[0093] In the complex plane coordinate system, the real part of the impedance is determined by its projection position on the horizontal axis, and the imaginary part is determined by its projection position on the vertical axis. Based on the physical correspondence that the response at a frequency (10Hz in the example) is mainly controlled by the diffusion process of mass transfer, while the response at a frequency (1kHz in the example) is mainly controlled by the electrochemical polarization process of charge transfer, the real and imaginary impedance data are classified by frequency as real and imaginary components characterizing different dynamic response processes.

[0094] For example, the real part of the impedance data at a frequency (example value is 10Hz) is classified as a real component characterizing the low-frequency diffusion process, and the real part of the impedance data at a frequency (example value is 1kHz) is classified as a real component characterizing the high-frequency charge transfer process. Thus, the characteristic separation of the electrochemical interface at different time constants is completed by dividing it according to the frequency dimension.

[0095] Methods for resolving real-time electrochemical state parameter sets include:

[0096] The theoretical trajectory is generated by pre-setting the electrochemical equivalent circuit structure and assigning initial physical quantity values ​​to the components.

[0097] Specifically, based on the physical characteristics of the electrolytic interface of the electroplating tank, an electrochemical equivalent circuit structure consisting of a resistor connected in series and a resistor-capacitor connected in parallel is selected, and each component is assigned initial physical values ​​including the electrolyte body resistance (0.5Ω in the example), polarization resistance (2.0Ω in the example), and double-layer capacitance (0.01F in the example).

[0098] Using the complex formula for calculating AC impedance: ( );

[0099] in, It is the value of complex impedance. It is the resistance of the electrolyte itself. It is a polarization resistor. It is a double-layer capacitor. It is an angular frequency and satisfies , It is the frequency point of the sine wave;

[0100] Substituting various frequency points, such as 10Hz (example value) and 1kHz (example value), into the transfer function of the electrochemical equivalent circuit structure, the theoretical complex impedance values ​​corresponding to different frequencies are calculated. These values ​​are then mapped to the impedance complex plane coordinate system and connected to form a line, generating a theoretical trajectory for characterizing the ideal electrochemical response characteristics.

[0101] Based on the positional deviation between the theoretical trajectory and the measured trajectory composed of the real and imaginary components, the physical quantity values ​​of each component in the electrochemical equivalent circuit structure are adjusted to make the theoretical trajectory approximate the measured trajectory until the residual meets the preset threshold.

[0102] It should be noted that the impedance coordinate points formed by the theoretical trajectory are compared one by one with the measured trajectory coordinate points formed by the separated real and imaginary components, and the Euclidean distance between the two coordinate points at the same frequency is calculated as the position deviation.

[0103] The least squares iterative logic is adopted. An objective function is constructed for the physical quantities of the components. The objective function is the sum of squares of the positional deviations between the theoretical trajectory and the measured trajectory at all sampling frequency points. In each iteration, the gradient descent algorithm is used to calculate the partial derivatives of the objective function with respect to the physical quantities of each component, such as electrolyte bulk resistance, polarization resistance and double layer capacitance. The values ​​of each component are then finely adjusted in the reverse direction according to the gradient direction indicated by the partial derivatives.

[0104] For example, if the partial derivative in the direction of the polarization resistance is positive, then the current physical value of the polarization resistance is decreased (in the example, the value is decreased by 0.01Ω); if the partial derivative is negative, then the current physical value of the polarization resistance is increased (in the example, the value is increased by 0.01Ω).

[0105] Each time the physical quantity value is adjusted, it is re-substituted into the complex calculation formula of AC impedance to calculate and generate a new theoretical trajectory. This makes the value of the objective function continuously decrease during the iteration process, so that the theoretical trajectory continuously approaches the measured trajectory in the coordinate plane. The residual value composed of the sum of squares of the deviations at each frequency point is continuously monitored until the residual value decreases to below the preset threshold (0.001 in the example), at which point it is determined that the current theoretical trajectory can accurately simulate the actual electrolytic interface state.

[0106] When the residual meets the preset threshold, the parameter values ​​of each component in the current electrochemical equivalent circuit structure are extracted to identify the physical quantity values ​​corresponding to the electrolyte bulk resistance, polarization resistance and double layer capacitance, and output the real-time electrochemical state parameter set.

[0107] It should be noted that when the residual meets the preset threshold (0.001 in the example), the state of the electrochemical equivalent circuit structure after the iteration stops is locked, and the final parameter values ​​corresponding to each component in the current electrochemical equivalent circuit structure are directly extracted.

[0108] By reading the corresponding values, the physical quantities of electrolyte bulk resistance, polarization resistance, and double-layer capacitance that reflect the conductivity of the electrolyte, polarization resistance, polarization resistance, and double-layer capacitance that reflect the charge distribution characteristics of the electrode interface are identified. These physical quantities are then summarized and packaged to output a set of real-time electrochemical state parameters that can characterize the real physical state of the electrolytic interface during the electroplating process.

[0109] This invention achieves precise conversion from macroscopic signals to microscopic parameters. By utilizing the synergistic iteration of gradient descent and least squares, the residual between the theoretical and measured trajectories is controlled within a very small threshold, thereby eliminating interference from process noise and accurately extracting core physical quantities such as electrolyte bulk resistance, polarization resistance, and double-layer capacitance. This "digital twin" parameter identification not only improves the sensitivity of sensing the state of the electrolysis interface but also, due to its component quantification based on clear physical meaning, provides a decision-making benchmark with strong causal relationships for subsequent sensor failure identification and logic compensation.

[0110] In electroplating industrial production, traditional control systems heavily rely on real-time feedback from physical sensors (such as conductivity meters and thermometers). However, the electroplating tank environment is highly corrosive and subject to complex electromagnetic interference, making physical sensor probes prone to chemical contamination, zero-point drift, or even complete failure. This can lead to erroneous signals from the control system and process accidents. Furthermore, existing technologies lack effective online self-calibration methods for sensors, and when sensors fail, emergency shutdowns or a switch to coarse open-loop control are often the only options, making it difficult to ensure production continuity. Therefore, this invention constructs an intelligent evaluation system with self-diagnostic and logical compensation capabilities by aligning mechanistic electrochemical impedance parameters with macroscopic monitoring data over time and using Euclidean distance evaluation. The specific steps are as follows:

[0111] Methods for outputting sensor condition assessment results include:

[0112] Based on timestamp information, the real-time electrochemical state parameter set is time-aligned with the macroscopic environmental data collected by physical sensors.

[0113] It should be noted that the sampling time information recorded during packaging is extracted from the real-time electrochemical state parameter set, and macroscopic environmental data collected and tagged by physical sensors such as conductivity sensors and temperature sensors under the same clock reference is also obtained.

[0114] Retrieve data records from the macroscopic environmental data collected by physical sensors that are completely consistent with the sampling time of the real-time electrochemical state parameter set (example values ​​are 2021 / 01-11 / 14:00:00). By aligning the two sets of data on the same time axis, it is ensured that the subsequent benchmarking analysis is for the operating state of the electroplating tank at the same physical moment, thereby eliminating phase deviations caused by data transmission delays or different acquisition frequencies.

[0115] The electrolyte bulk resistance from the real-time electrochemical state parameter set is mapped and converted into a theoretical conductivity value, which is then compared with the measured conductivity value in the macroscopic environmental data to obtain the Euclidean distance between the two.

[0116] Specifically, it utilizes the reciprocal relationship between conductivity and resistivity, combined with the geometric constants of the electrodes in the electroplating tank (example values). The physical quantity of electrolyte bulk resistance (0.5Ω in the example) identified by real-time electrochemical state parameters is converted into a theoretical conductivity value (2000mS / cm in the example) that characterizes the actual conductivity of the electrolyte through algebraic operations.

[0117] Next, the theoretical conductivity value and the measured conductivity value (1980 mS / cm in the example) in the time-aligned macroscopic environmental data are extracted. The absolute value of the difference between the theoretical conductivity value and the measured conductivity value is calculated in the numerical space. This value is defined as the Euclidean distance between the two and is used to quantify the consistency between the virtual mapping parameters and the measured parameters of the physical sensor.

[0118] The Euclidean distance is used as the fault confidence score and compared with a preset confidence threshold. If the Euclidean distance is less than the preset confidence threshold, the physical sensor is determined to be effective; if the Euclidean distance is greater than the preset confidence threshold, the physical sensor is determined to be ineffective, and the sensor status evaluation result is output.

[0119] Specifically, based on the historical operating records of the corresponding target plating type under standard working conditions, the historical measured conductivity values ​​collected by the physical sensor under calibrated conditions are extracted, as well as the historical theoretical conductivity values ​​generated by the electrochemical equivalent circuit structure inversion.

[0120] For each set of historical data at the same time stamp, the Euclidean distance between the historical theoretical conductivity value and the historical measured conductivity value is calculated to form a discrete numerical sequence that characterizes the inherent measurement bias of the system. By performing statistical analysis on the discrete numerical sequence, the arithmetic mean (20 in the example) and standard deviation (10 in the example) of the discrete numerical sequence are calculated, and the sum of the arithmetic mean and three times the standard deviation is defined as the preset reliability threshold (50 in the example).

[0121] The Euclidean distance is defined as a fault confidence score that measures the reliability of physical sensor performance, and it is compared with a stored pre-set confidence threshold (50 in the example) in real time.

[0122] If the calculated fault confidence score (example value 20) is less than the preset confidence threshold, it indicates that the measurement results of the physical sensor are in high agreement with the physical state calculated by the electrochemical mechanism. In this case, the physical sensor is deemed to be effective and the current confidence status of the monitoring data is maintained.

[0123] If the fault confidence score (example value 80) is greater than the preset confidence threshold, it indicates that the measured value deviates significantly from the theoretical range mapped by the electrolyte body resistance, and the physical sensor is determined to be invalid (possibly due to probe contamination or zero-point drift fault). Finally, the sensor status evaluation result is output to remind the device to be maintained.

[0124] Methods for optimizing instruction sets using output control laws include:

[0125] When the sensor status evaluation result determines that the physical sensor is invalid, that is, the physical sensor data is abnormal; the input path of the macroscopic environmental data collected by the physical sensor is blocked.

[0126] Specifically, when the fault confidence score is greater than the preset confidence threshold, it is confirmed that the measured conductivity value output by the physical sensor has an abnormal deviation or failure. At this time, a physical link disconnection operation is performed using a logic switching switch to stop receiving and intercept macroscopic environmental data from the physical sensor data acquisition channel, so that it no longer enters the subsequent control feedback loop.

[0127] This shielding process prevents macroscopic environmental data containing erroneous information from interfering with the stability of the production process, providing a clean instruction logic space for subsequent virtual parameter compensation.

[0128] The polarization resistance physical quantity value in the real-time electrochemical state parameter set is converted into a compensatory feedback signal with physical dimensions, and the compensatory feedback signal is used to replace the failed physical signal.

[0129] It should be noted that, taking advantage of the negative correlation between polarization resistance and the interfacial electrochemical reaction rate, the polarization resistance physical quantity value (2.0Ω in the example) identified by the real-time electrochemical state parameters is substituted into the linear mapping formula through a preset sensitivity coefficient (0.05 in the example). By calculating the product of the sensitivity coefficient and the reciprocal of the polarization resistance physical quantity value, a value with physical dimensions is obtained. This value is then superimposed on the reference level, thereby transforming the abstract resistance value into a compensatory feedback signal with physical dimensions that can reflect the dynamics of the real reaction.

[0130] Subsequently, the compensatory feedback signal is connected to the signal input port that was originally occupied by the physical sensor, and injected into the logic control core as a virtual feedback data stream. In the event of physical hardware failure, the physical quantity value extracted from the impedance characteristics is used to complete the equivalent replacement of the failed physical signal.

[0131] The compensation feedback signal is compared with the preset expected value in the initial control benchmark of the target plating type to obtain the instantaneous deviation of the physical parameters and retrieve the corresponding basic control gain.

[0132] Specifically, the compensation feedback signal is subtracted from the preset expected value (the dimension value corresponding to the example value of 2.1Ω) in the initial control reference of the target plating type in real time to calculate the instantaneous deviation representing the deviation of the current reaction intensity from the set target.

[0133] Based on the obtained instantaneous deviation, the corresponding proportional coefficient is retrieved from the proportional-integral-derivative control parameter table stored in the process memory, and the basic control gain that matches the magnitude of the current instantaneous deviation is retrieved (example value is 1.5).

[0134] It should be noted that the construction process of the proportional-integral-derivative control parameter table is as follows: Using a trial-and-error method, during the commissioning phase of the actual electroplating production line, a small initial proportional coefficient is manually set, and the current recovery stability at the electrolytic interface when small instantaneous deviations occur is observed. By successively increasing the proportional coefficient and recording the empirical values ​​when the system does not oscillate and the adjustment time is shortest, different instantaneous deviation ranges are mapped one-to-one with the corresponding empirical proportional values. Finally, these empirical data, verified as effective in actual commissioning, are arranged according to the deviation gradient from small to large, forming a structured data table, which is pre-stored in the process memory.

[0135] By using this benchmarking comparison, the degree of state fluctuation caused by changes in polarization characteristics at the electrolytic interface can be quantified, providing a numerical benchmark for the fine adjustment of control law optimization instructions.

[0136] The control gain is corrected based on the instantaneous deviation and the physical value of the double-layer capacitance in the real-time electrochemical state parameter set, and the control law optimization instruction set is output.

[0137] It should be noted that, based on the instantaneous deviation, combined with the physical quantity value corresponding to the double-layer capacitance extracted from the real-time electrochemical state parameter set (the example value is 0.01F), the hysteresis correction effect of the capacitance value on the interface charge response is used to perform a product weighting operation on the retrieved basic control gain, and adjust the response damping coefficient of the control loop, thereby obtaining the final control parameters after correction.

[0138] The corrected final control parameters are converted into digital control pulses that can be recognized by the electroplating power supply, and the output includes a control law optimization instruction set including voltage regulation amplitude, pumping frequency variable and dosing pump pulse width. Thus, even when physical sensors fail, the macroscopic production output can still be dynamically adjusted based on the microscopic parameters of the electrochemical interface.

[0139] Through this closed-loop design encompassing the entire chain from physical fault diagnosis to virtual parameter compensation, this invention achieves deep redundancy and self-healing in the "sensing layer" of the production system. By quantifying sensor confidence using Euclidean distance, the system can identify probe faults within seconds and decisively shield against abnormal interference. More importantly, through cross-dimensional mapping of polarization resistance and double-layer capacitance, "equivalent logic reconstruction" of the failed physical signal is achieved. This approach not only eliminates the production fluctuation risks caused by sensor failures but also ensures high-precision closed-loop regulation based on the microscopic reaction kinetics parameters of the electrode interface even under extreme conditions without physical sensor support, greatly improving the intelligence level and resilience of the electroplating process line.

[0140] Methods for driving actuators to coordinate and adjust the electroplating process include:

[0141] The control law optimization instruction set is parsed into the underlying control codes corresponding to the voltage regulation amplitude, pumping frequency variable, and dosing pump pulse width.

[0142] It should be noted that, using instruction decoding logic, the generated control law optimization instruction set is decomposed into orthogonal instruction components for different hardware actuators; specifically, the instruction for current density adjustment is converted into the corresponding voltage adjustment amplitude (the example value is a decrease of 0.2V), the instruction for tank liquid disturbance balance is converted into the pumping frequency variable of the circulating filter pump (the example value is an increase of 5Hz), and the instruction for chemical component compensation is converted into the dosing pump pulse width of the automatic dosing machine stepper motor (the example value is 200ms).

[0143] Through logical mapping, physical control variables are encoded into hexadecimal low-level control codes conforming to industrial communication protocols (example value: Modbus-RTU). This parsing method ensures that high-level logic instructions can be converted into electrical signal instructions to drive motors, frequency converters, and rectifiers, achieving precise transmission from electrochemical micro-parameters to macroscopic execution actions.

[0144] The underlying control code is sent to the electroplating DC power supply, the circulating filter pump, and the automatic dosing machine respectively, so as to drive the electroplating DC power supply to adjust the output potential, drive the circulating filter pump to change the flow rate of the tank liquid, and drive the automatic dosing machine to perform additive replenishment.

[0145] It should be noted that the underlying control code corresponding to the voltage regulation is sent to the digital control port of the electroplating DC power supply, which drives the electroplating DC power supply to adjust the output potential by adjusting the thyristor firing angle.

[0146] The underlying control code corresponding to the pumping frequency variable is sent to the frequency converter of the circulating filter pump, which drives the circulating filter pump to change the impeller speed to change the flow rate of the tank liquid.

[0147] At the same time, the underlying control code corresponding to the pulse width of the dosing pump is sent to the solenoid valve driver of the automatic dosing machine to drive the automatic dosing machine to perform additive replenishment;

[0148] Through the coordinated operation of various actuators, the electrolytic environment in the electroplating tank can still be repaired and balanced in real time based on compensatory feedback signals even when physical sensors fail.

[0149] The system acquires the hardware status parameters after the actuator completes its action, compares these parameters with the control law optimization instruction set, and determines the controlled adjustment state of the electroplating process. It also maintains the operating state of the actuator after the linkage adjustment and acquires the adjusted process feedback.

[0150] It should be noted that after the actuator completes the adjustment command, the hardware status parameters of the actuator after completing the action are obtained in real time using the Hall sensor, flow meter and liquid level sensor installed on the equipment (such as the real-time output voltage of the electroplating DC power supply, the real-time speed of the circulating filter pump, etc.).

[0151] The acquired hardware status parameters are compared with the original control law optimization instruction set using a difference verification. If the deviation is within a preset range (3% in the example), the electroplating process is determined to be in a controlled adjustment state. The operating state of the actuator after linkage adjustment is maintained, and the adjusted process feedback is obtained by collecting the induced current and induced voltage signals at the electrolytic interface. This closed-loop confirmation step ensures that the actuator has accurately responded to the adjustment requirements derived from the microscopic characteristics of the electrochemical interface.

[0152] Methods for updating the initial control baseline of the target plating type include:

[0153] Extract the hardware status parameters after the linkage adjustment is completed, as well as the physical quantity values ​​of each component in the real-time electrochemical status parameter set; use the hardware status parameters and the physical quantity values ​​of each component to overwrite the corresponding stored values ​​in the initial control benchmark of the target plating type.

[0154] It should be noted that the hardware status parameters after the linkage adjustment is completed are extracted, as well as the physical quantity values ​​of each component, including electrolyte body resistance, polarization resistance and double layer capacitance, are extracted from the latest real-time electrochemical status parameter set.

[0155] By utilizing these hardware state parameters that reflect the current steady-state equilibrium point and the physical values ​​of each component, the corresponding stored values ​​in the initial control benchmark of the target plating type in the process formula database are overwritten through numerical rewriting.

[0156] The entire dataset, including the updated electrode reference, resistance reference, and current limit, is packaged and output as the updated target plating initial control reference. The updated target plating initial control reference is then sent to the beginning of the next cycle as a starting reference, thereby realizing a self-optimizing cycle in which the control reference dynamically evolves with the production conditions.

[0157] This embodiment also provides a multi-parameter closed-loop management method for an integrated electroplating control module, including:

[0158] The initial control benchmark of the target plating type is obtained, a composite detection sequence is generated and injected into the electroplating tank to stimulate the electrolytic interface to generate inductive feedback, and a multi-frequency electrochemical response sequence is output.

[0159] The impedance response characteristics of the multi-frequency electrochemical response sequence are extracted, decomposed into real and imaginary components under different time constants, and the real-time electrochemical state parameter set is analyzed.

[0160] The real-time electrochemical state parameter set is logically compared with the macroscopic environmental data collected by physical sensors, and the sensor state evaluation results are output.

[0161] Based on the sensor status evaluation results, when the physical sensor data is determined to be abnormal, the failed physical signal is replaced by the real-time electrochemical state parameter set, and the control law optimization instruction set is output.

[0162] Based on the control law optimization instruction set, the actuator is driven to adjust the electroplating process in a coordinated manner, while updating the initial control reference of the target plating type, and using the updated initial control reference of the target plating type as the starting reference for the next cycle.

[0163] This embodiment also provides a computer device suitable for the integrated electroplating control module multi-parameter closed-loop management system, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the integrated electroplating control module multi-parameter closed-loop management system as proposed in the above embodiment.

[0164] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0165] This embodiment also provides a storage medium storing a computer program. When executed by a processor, the program implements the multi-parameter closed-loop management system for the integrated electroplating control module as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0166] In summary, this invention achieves dynamic adaptation between the excitation signal and the instantaneous physical limits of the electroplating tank interface by extracting the boundary of the electrochemical stability envelope as the coordinates of the safe region and generating a composite detection sequence accordingly. Under the premise of ensuring that no side reactions such as hydrogen evolution reaction or abnormal decomposition of additives are triggered, it can more specifically obtain multi-frequency electrochemical responses, thereby improving the reliability and security of monitoring data while maintaining the stability of the production environment.

[0167] By logically calibrating the real-time electrochemical state parameter set with physical sensor data, and using polarization resistance and double-layer capacitance for signal compensation and control law correction when anomalies are detected, a deep verification mechanism for the macroscopic physical environment and microscopic electrochemical mechanism is constructed. This enables the continuous operation of the process based on microscopic characteristic quantities even under complex conditions such as physical sensor drift or failure, enhancing the system's fault tolerance and the level of intelligence in closed-loop control. It ensures production continuity under extreme conditions and significantly improves the precision management capability of the electroplating process through complementary data dimensions.

[0168] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An integrated electroplating control module multi-parameter closed-loop management system, characterized in that, include: The excitation unit acquires the initial control reference of the target plating type, generates a composite detection sequence, injects it into the electroplating tank to excite the electrolytic interface to generate induction feedback, and outputs a multi-frequency electrochemical response sequence. The analytical unit extracts the impedance response characteristics of the multi-frequency electrochemical response sequence, decomposes them into real and imaginary components under different time constants, and analyzes the real-time electrochemical state parameter set. The evaluation unit logically compares the real-time electrochemical state parameter set with the macroscopic environmental data collected by the physical sensors and outputs the sensor state evaluation results. The decision-making unit, based on the sensor status evaluation results, when it determines that the physical sensor data is abnormal, replaces the failed physical signal with the real-time electrochemical state parameter set and outputs a control law optimization instruction set. The execution unit, based on the control law optimization instruction set, drives the actuator to perform linkage adjustment of the electroplating process, and at the same time updates the initial control reference of the target plating type, using the updated initial control reference of the target plating type as the starting reference for the next cycle.

2. The integrated electroplating control module multi-parameter closed-loop management system as described in claim 1, characterized in that, The method for generating the composite detector sequence includes: After receiving the production task instruction, the process formula database is searched to obtain the initial control benchmark of the target plating type. Based on the upper limit of current density and the rated value of electrolyte temperature in the initial control benchmark of the target plating type, the corresponding electrochemical stability envelope boundary is extracted as the coordinate of the safe region of the impedance complex plane. The phase step value is determined based on the coordinates of the safe region of the impedance complex plane. The phase step value is accumulated to obtain the address index. The instantaneous amplitude value of the sine wave is retrieved from the storage area where the instantaneous amplitude value of the sine wave is stored, and a specific sine wave frequency point is generated. The instantaneous amplitude values ​​of the sine wave corresponding to each specific sine wave frequency point are accumulated and summarized to generate a composite detection sequence.

3. The integrated electroplating control module multi-parameter closed-loop management system as described in claim 2, characterized in that, The method for outputting a multi-frequency electrochemical response sequence includes: The composite detection sequence is converted into an analog voltage disturbance signal through digital-to-analog conversion; the analog voltage disturbance signal is coupled to the electroplating DC power supply using a superposition circuit to inject it into the electroplating tank, thereby stimulating the electrolytic interface to generate inductive feedback. The induced current and induced voltage signals at the electrolysis interface are collected and converted from analog to digital. The converted induced current and induced voltage signals are then truncated in the time domain and frequency aligned and packaged to output a multi-frequency electrochemical response sequence.

4. The integrated electroplating control module multi-parameter closed-loop management system as described in claim 3, characterized in that, The methods for obtaining the real and imaginary components include: The multi-frequency electrochemical response sequence is multiplied and integrated with the orthogonal reference signal to obtain the complex impedance value corresponding to each frequency point as the impedance response characteristic. The complex impedance values ​​are projected onto the complex plane coordinate system, and the real part of the impedance corresponding to the horizontal axis and the imaginary part of the impedance corresponding to the vertical axis are separated. They are then classified into real and imaginary components under different time constants according to frequency.

5. The integrated electroplating control module multi-parameter closed-loop management system as described in claim 4, characterized in that, The method for resolving the real-time electrochemical state parameter set includes: Pre-determine the electrochemical equivalent circuit structure and assign initial physical quantity values ​​to the components to generate a theoretical trajectory; Based on the positional deviation between the theoretical trajectory and the measured trajectory composed of the real and imaginary components, the physical quantity values ​​of each component in the electrochemical equivalent circuit structure are adjusted to make the theoretical trajectory approach the measured trajectory until the residual meets the preset threshold. When the residual meets the preset threshold, the parameter values ​​of each component in the current electrochemical equivalent circuit structure are extracted to identify the physical quantity values ​​corresponding to the electrolyte bulk resistance, polarization resistance and double layer capacitance, and output the real-time electrochemical state parameter set.

6. The integrated electroplating control module multi-parameter closed-loop management system as described in claim 5, characterized in that, The method for outputting sensor state evaluation results includes: Based on timestamp information, the real-time electrochemical state parameter set is time-aligned with the macroscopic environmental data collected by physical sensors; The electrolyte bulk resistance in the real-time electrochemical state parameter set is mapped and converted into a theoretical conductivity value, which is then compared with the measured conductivity value in the macroscopic environmental data to obtain the Euclidean distance between the two. The Euclidean distance is used as the fault confidence score and compared with a preset confidence threshold. If the Euclidean distance is less than the preset confidence threshold, the physical sensor is determined to be effective; if the Euclidean distance is greater than the preset confidence threshold, the physical sensor is determined to be ineffective, and the sensor status evaluation result is output.

7. The integrated electroplating control module multi-parameter closed-loop management system as described in claim 6, characterized in that, The method for optimizing the instruction set by the output control law includes: When the sensor status evaluation result determines that the physical sensor is invalid, that is, when the physical sensor data is abnormal, the input path of the macroscopic environmental data collected by the physical sensor is blocked. The polarization resistance physical quantity value in the real-time electrochemical state parameter set is converted into a compensatory feedback signal with physical dimensions, and the compensatory feedback signal is used to replace the failed physical signal. The compensation feedback signal is compared with the preset expected value in the initial control benchmark of the target plating type to obtain the instantaneous deviation of the physical parameters and retrieve the corresponding basic control gain. The control gain is corrected based on the instantaneous deviation and the physical value of the double-layer capacitance in the real-time electrochemical state parameter set, and the control law optimization instruction set is output.

8. The integrated electroplating control module multi-parameter closed-loop management system as described in claim 7, characterized in that, The method for the drive actuator to coordinate and adjust the electroplating process includes: The control law optimization instruction set is parsed into the underlying control code corresponding to the voltage regulation amplitude, pumping frequency variable and dosing pump pulse width. The underlying control code is sent to the electroplating DC power supply, the circulating filter pump and the automatic dosing machine respectively, so as to drive the electroplating DC power supply to adjust the output potential, drive the circulating filter pump to change the flow rate of the tank liquid, and drive the automatic dosing machine to perform additive replenishment. The system acquires the hardware status parameters after the actuator completes its action, compares these parameters with the control law optimization instruction set, and determines the controlled adjustment state of the electroplating process. It also maintains the operating state of the actuator after the linkage adjustment and acquires the adjusted process feedback.

9. The multi-parameter closed-loop management system for the integrated electroplating control module as described in claim 8, characterized in that, The method for updating the initial control benchmark of the target plating type includes: Extract the hardware status parameters after the linkage adjustment is completed, as well as the physical quantity values ​​of each component in the real-time electrochemical status parameter set; use the hardware status parameters and the physical quantity values ​​of each component to overwrite the corresponding stored values ​​in the initial control reference of the target plating type. The updated data packet is used as the initial control reference for the updated target plating type, and the updated initial control reference for the target plating type is sent to the start of the next cycle as a starting reference.

10. A multi-parameter closed-loop management method for an integrated electroplating control module, based on the multi-parameter closed-loop management system for an integrated electroplating control module as described in any one of claims 1 to 9, characterized in that, include: The initial control benchmark of the target plating type is obtained, a composite detection sequence is generated and injected into the electroplating tank to stimulate the electrolytic interface to generate inductive feedback, and a multi-frequency electrochemical response sequence is output. The impedance response characteristics of the multi-frequency electrochemical response sequence are extracted, decomposed into real and imaginary components under different time constants, and the real-time electrochemical state parameter set is analyzed. The real-time electrochemical state parameter set is logically compared with the macroscopic environmental data collected by physical sensors, and the sensor state evaluation results are output. Based on the sensor status evaluation results, when the physical sensor data is determined to be abnormal, the failed physical signal is replaced by the real-time electrochemical state parameter set, and the control law optimization instruction set is output. Based on the control law optimization instruction set, the actuator is driven to adjust the electroplating process in a coordinated manner, while updating the initial control reference of the target plating type, and using the updated initial control reference of the target plating type as the starting reference for the next cycle.

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