Pulse electroplating detection method, pulse electroplating device and equipment

Abstract

The invention discloses a pulse electroplating detection method, a pulse electroplating device and equipment, and the method comprises the steps: synchronously collecting transient current density data of a three-pole assembly in a pulse switching time window, and calculating a time derivative of a current density ratio to obtain electrochemical stress gradient data; performing space-time correlation analysis on the stress gradient data of the continuous pulse period, and tracking a spatial propagation trajectory of stress anomaly; a key monitoring area is determined according to the propagation trajectory, and ion migration impedance sensitivity distribution is detected through micro-amplitude current modulation; performing multi-dimensional coupling analysis on the stress gradient, the propagation trajectory and the impedance sensitivity data, and identifying time sequence correlation characteristics of stress evolution and ion anomaly; and performing quantitative evaluation and grade division on the electrochemical state of the avoidance area based on the coupling correlation characteristics. According to the scheme, early recognition and predictive evaluation of the ion migration abnormity of the boundary layer of the avoidance area can be realized in the pulse electroplating process, and the electroplating quality control precision and the process stability are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of electroplating detection technology, and in particular to a pulse electroplating detection method, a pulse electroplating device and equipment. Background Art

[0002] Pulse plating technology is an electroplating process that uses a periodically varying current to deposit metal. By alternating between forward and reverse currents in a rectifier, precise control of the plating process is achieved. Compared to traditional DC plating, pulse plating significantly improves the density, smoothness, and adhesion of the coating, leading to its widespread application in electronic component processing.

[0003] In the related art (Chinese patent document with application number 202311655960.7), the pulse electroplating device adopts a three-pole configuration structure of an anode assembly, a cathode assembly and a shunt assembly, wherein the anode assembly is arranged on one side of the carrier plate, and the shunt assembly is located between the anode assembly and the cathode assembly. In the forward pulse stage, the anode assembly acts as the positive electrode and the cathode assembly acts as the negative electrode, forming a normal electroplating circuit to deposit metal on the workpiece to be electroplated; in the reverse pulse stage, the cathode assembly is converted to the positive electrode and the shunt assembly becomes the negative electrode, thereby avoiding hydrogen evolution corrosion caused by the reverse current on the anode assembly. In order to optimize the uniformity of current distribution during forward electroplating, the shunt assembly adopts a unique avoidance zone design, that is, specific areas are hollowed out in the shunt assembly, so that the metal ions released by the anode assembly can directly pass through these vacant areas to reach the surface of the workpiece to be electroplated without being blocked by the shunt assembly.

[0004] However, while this avoidance zone design solves the current distribution problem, it also produces complex electrochemical phenomena at the boundary of the avoidance zone. Due to the sudden change in the geometric shape of the edge of the avoidance zone and the periodic switching of the pulse current, a discontinuous distribution of electric field strength will appear in the boundary area, causing the migration path of metal ions to deflect and the concentration gradient to be dynamically reconstructed when crossing the boundary area. Moreover, during the transient process of each pulse switching, the boundary area becomes a buffer zone for the re-equilibrium of ion concentration. The recovery time of its concentration distribution does not match the start time of the next pulse cycle, resulting in a cumulative memory effect on the electroplating effect of subsequent pulses. Traditional ion concentration monitoring methods mainly rely on offline chemical analysis or single-point electrochemical detection. Their time resolution is usually in the second to minute level, which is far from enough to track the millisecond-level dynamic reconstruction process of the boundary layer. As a result, this memory effect gradually accumulates during multiple batches of electroplating, ultimately causing a significant deterioration in the uniformity of the coating thickness. Summary of the Invention

[0005] The main purpose of the present invention is to solve the technical problem that in the existing pulse electroplating device, the ion migration abnormality at the avoidance zone boundary of the shunt component is difficult to detect and predict in real time, resulting in unstable electroplating quality.

[0006] In a first aspect, in order to solve the above technical problems, the present invention provides a detection method for pulse plating, comprising: During the time window from the forward pulse to the reverse pulse of the pulse plating process, the transient current density data between the anode component, the shunt component, and the cathode component are synchronously collected. The first-order time derivative and the second-order time derivative of the current density ratio between the three components are calculated to obtain the electrochemical stress gradient data. Performing spatiotemporal correlation analysis on the electrochemical stress gradient data of multiple consecutive pulse cycles to track the spatial position change and evolution trend of stress gradient anomalies and obtain stress anomaly propagation trajectory data; Based on the key monitoring area determined by the stress anomaly propagation trajectory data, the current density is slightly modulated in the steady-state section of the forward pulse, the potential response change of the three-electrode system is synchronously monitored, the ion migration impedance sensitivity coefficient is calculated, and the impedance sensitivity distribution data is obtained; Performing multi-dimensional coupling analysis on the electrochemical stress gradient data, stress anomaly propagation trajectory data, and impedance sensitivity distribution data to identify the temporal correlation characteristics between stress evolution and ion migration anomalies, and obtain coupling correlation characteristic data; Based on the coupling correlation characteristic data, the electrochemical state of the avoidance zone of the shunt component is quantitatively evaluated, the abnormality level is determined, and the avoidance zone state diagnosis result is obtained.

[0007] In an optional embodiment, the transient current density data between the anode component, the shunt component, and the cathode component are synchronously collected within the time window when the forward pulse of the pulse electroplating is switched to the reverse pulse, and the first-order time derivative and the second-order time derivative of the current density ratio between the three components are calculated to obtain the electrochemical stress gradient data, including: During the period when the forward pulse switches to the reverse pulse, the transient current density data of the anode assembly, the shunt assembly and the cathode assembly are synchronously acquired, and the current density ratios between the anode assembly and the shunt assembly, the anode assembly and the cathode assembly, and the shunt assembly and the cathode assembly are calculated to obtain the three-electrode current density ratio data; Calculating the first-order time derivative and the second-order time derivative of the three-pole current density ratio data respectively, judging the validity of each derivative data based on the geometric symmetry of the avoidance zone, and screening out the effective derivative data reflecting the stress change; According to the stress change rate represented by the first-order derivative and the stress change acceleration represented by the second-order derivative in the effective derivative data, the spatial distribution parameters of the stress gradient at the boundary of the avoidance zone are calculated to obtain electrochemical stress gradient data.

[0008] In an optional embodiment, the first-order time derivative and the second-order time derivative of the three-pole current density ratio data are calculated respectively, the validity of each derivative data is judged based on the geometric symmetry of the avoidance zone, and the valid derivative data reflecting the stress change is screened out, including: Performing numerical differentiation operations on each ratio sequence in the three-pole current density ratio data, calculating the first-order time derivative and the second-order time derivative of the anode-shunt component ratio, the anode-cathode component ratio, and the shunt-cathode component ratio, to obtain a derivative data matrix; A symmetry evaluation benchmark is established based on the central symmetry axis and mirror symmetry plane of the avoidance zone's geometric boundary. The degree of deviation of each derivative data relative to the symmetry benchmark is calculated, and abnormal derivative values ​​that violate the geometric symmetry constraints are identified to obtain a symmetry screening mark. According to the symmetry screening identifier, derivative data that meets the geometric symmetry requirements are retained, and non-physical derivative values ​​generated by current noise or system disturbances are eliminated to obtain effective derivative data reflecting stress changes.

[0009] In an optional embodiment, performing spatiotemporal correlation analysis on the electrochemical stress gradient data of a plurality of consecutive pulse cycles, tracking the spatial position change and evolution trend of the stress gradient anomaly, and obtaining stress anomaly propagation trajectory data includes: The electrochemical stress gradient data of a plurality of consecutive pulse cycles are arranged in a time series, the deviation degree of the stress gradient of each cycle is calculated based on the symmetry benchmark of the geometric boundary of the avoidance zone, and the stress gradient abnormal points whose deviation degree exceeds a preset range are identified to obtain time series stress abnormality identification data; According to the spatial distribution position of the abnormal points in the time series stress anomaly identification data, combined with the geometric constraints of the avoidance zone boundary, the spatial displacement law of the abnormal points between adjacent pulse cycles is analyzed, the direction vector and propagation speed of the abnormal propagation are calculated, and the stress anomaly spatial propagation parameters are obtained; Based on the stress anomaly spatial propagation parameters, the movement path of the anomaly point in the avoidance zone is tracked, the residence phenomenon of the stress anomaly at the geometric corner and the acceleration phenomenon at the straight line boundary are identified, and the geometric constraint propagation characteristic data is obtained; The geometric constraint propagation characteristic data is combined with the pulse time beat to reconstruct the complete motion trajectory of the stress anomaly in the time-space two-dimensional coordinate system, predict the propagation trend and arrival area of ​​the stress anomaly, and obtain the stress anomaly propagation trajectory data.

[0010] In an optional embodiment, the tracking of the movement path of the abnormal point within the avoidance zone based on the stress anomaly spatial propagation parameter, identifying the residence phenomenon of the stress anomaly at the geometric corner and the acceleration phenomenon at the straight line boundary, and obtaining the geometric constraint propagation characteristic data include: According to the direction vector and propagation velocity data in the stress anomaly spatial propagation parameter, the motion trajectory and velocity distribution of the abnormal point at each spatial position in the avoidance zone are calculated, the geometric path characteristics of the trajectory are identified, and the motion trajectory data of the abnormal point is obtained; Performing geometric partition analysis on the motion trajectory data of the outlier point to distinguish the difference in motion characteristics when the outlier point is located in the geometric corner area and the straight boundary area of ​​the avoidance zone, calculating the speed attenuation coefficient of the corner area and the speed growth coefficient of the straight area, and obtaining the partition motion characteristic parameters; Based on the partitioned motion characteristic parameters, the residence accumulation effect of stress anomalies in the corner area and the propagation acceleration effect in the straight area are identified, the residence time and the acceleration multiple are quantified, and the geometric constraint propagation characteristic data are obtained.

[0011] In an optional embodiment, the key monitoring area determined according to the stress anomaly propagation trajectory data is subjected to slight modulation of the current density in the steady-state section of the forward pulse, the potential response change of the three-electrode system is synchronously monitored, and the ion migration impedance sensitivity coefficient is calculated to obtain impedance sensitivity distribution data, including: Based on the predicted arrival position and residence area distribution of the stress anomaly in the stress anomaly propagation trajectory data, combined with the curvature distribution characteristics of the geometric boundary of the avoidance zone, the high probability area of ​​stress concentration is identified, the spatial position of the key monitoring area is determined, and the monitoring area positioning data is obtained; In the middle time window of the forward pulse steady-state segment, a modulation strategy is determined according to the positioning data of the monitoring area, the overall current density is periodically slightly modulated, and the modulation amplitude and frequency parameters are adjusted to enhance the response sensitivity of the target area to obtain optimized modulation parameters; Based on the optimized modulation parameters, the potential response data of the anode component, the shunt component and the cathode component in the modulation state are synchronously collected, and the ratio of the potential response amplitude of each component to the modulation amplitude and the phase difference between the response and the modulation are calculated to obtain the three-electrode potential response characteristic data; The regional difference analysis of the three-pole potential response characteristic data is performed, and the response amplitude ratio of each monitoring area is weighted according to the geometric curvature distribution of the avoidance zone to obtain the sensitivity coefficient distribution reflecting the change of local ion migration impedance, thereby forming impedance sensitivity distribution data.

[0012] In an optional embodiment, the electrochemical stress gradient data, stress anomaly propagation trajectory data, and impedance sensitivity distribution data are subjected to multi-dimensional coupling analysis to identify the temporal correlation characteristics between stress evolution and ion migration anomalies, thereby obtaining coupling correlation characteristic data, including: The electrochemical stress gradient data, stress anomaly propagation trajectory data, and impedance sensitivity distribution data are time-series aligned according to the pulse cycle time scale, and a corresponding relationship between the three types of data under the same time reference is established to obtain a time-series synchronized data matrix; Performing a correlation analysis on the stress gradient change and the impedance sensitivity change in the time-series synchronization data matrix, calculating the time delay parameter and correlation strength coefficient between the two, identifying the phase difference characteristics of the stress evolution leading the ion migration anomaly, and obtaining the phase correlation parameter; According to the phase correlation parameters combined with the spatial information of the stress anomaly propagation trajectory, the spatial distribution law of the phase difference at each key node on the stress propagation path is analyzed, the distribution pattern of the phase difference changing with the geometric position is identified, and the spatiotemporal coupling characteristic data is obtained; Based on the spatiotemporal coupling characteristic data, a comprehensive coupling strength index between stress evolution and ion migration anomaly is calculated, and the system stability state is divided according to the numerical range of the coupling strength to obtain coupling correlation characteristic data.

[0013] In an optional embodiment, the quantitative evaluation of the electrochemical state of the avoidance zone of the shunt component based on the coupling correlation characteristic data, determining the abnormality level, and obtaining the avoidance zone state diagnosis result includes: Based on the comprehensive coupling strength index and phase correlation parameter in the coupling correlation characteristic data, the geometric symmetry deviation and temporal stability index of the electrochemical system in the avoidance zone are calculated to obtain a quantitative index of the system state; Based on the system state quantitative index combined with the symmetry benchmark characteristics of the avoidance zone geometric boundary, the abnormality degree grading judgment standard is determined by dividing the numerical interval of the quantitative index, and the electrochemical state of the avoidance zone is divided into four levels: normal stability, slight deviation, moderate imbalance and severe instability, and the state grading result is obtained; Performing trend analysis on the state level classification results, calculating the transition probability and expected transition time from the current state level to the next level, identifying early warning signals of the system approaching a critical instability state, and obtaining state evolution prediction data; The state level classification results and state evolution prediction data are comprehensively processed to generate a complete diagnosis report including the current abnormality level, stability evaluation and development trend prediction, and obtain the avoidance zone state diagnosis result.

[0014] A second aspect of the present invention provides a pulse plating device, comprising: The electrochemical stress gradient detection module is used to synchronously collect transient current density data between the anode component, the shunt component, and the cathode component within the time window when the forward pulse switches to the reverse pulse of the pulse electroplating, calculate the first-order time derivative and the second-order time derivative of the current density ratio between the three components, and obtain electrochemical stress gradient data; A stress anomaly propagation trajectory tracking module is used to perform spatiotemporal correlation analysis on the electrochemical stress gradient data of multiple consecutive pulse cycles, track the spatial position change and evolution trend of the stress gradient anomaly, and obtain stress anomaly propagation trajectory data; An impedance sensitivity distribution detection module is used to slightly modulate the current density in the forward pulse steady-state section according to the key monitoring area determined by the stress anomaly propagation trajectory data, synchronously monitor the potential response changes of the three-electrode system, calculate the ion migration impedance sensitivity coefficient, and obtain impedance sensitivity distribution data; a multi-dimensional coupling analysis module for performing multi-dimensional coupling analysis on the electrochemical stress gradient data, stress anomaly propagation trajectory data, and impedance sensitivity distribution data, identifying the temporal correlation characteristics between stress evolution and ion migration anomalies, and obtaining coupling correlation characteristic data; The state diagnosis and evaluation module is used to quantitatively evaluate the electrochemical state of the avoidance zone of the shunt component based on the coupling correlation characteristic data, determine the abnormality level, and obtain the avoidance zone state diagnosis result.

[0015] The third aspect of the present invention provides a pulse electroplating device, comprising: a memory and at least one processor, wherein instructions are stored in the memory, and the memory and the at least one processor are interconnected through lines; the at least one processor calls the instructions in the memory so that the pulse electroplating device performs the steps of the above-mentioned pulse electroplating detection method.

[0016] The technical solution provided by the embodiments of the present application can accurately capture the electrochemical information at the moment of the most intense electric field reconstruction by synchronously collecting transient current density data between the anode assembly, shunt assembly, and cathode assembly within the time window when the forward pulse switches to the reverse pulse. The avoidance zone is a specially hollowed-out area in the shunt assembly, and its boundary refers to the intersection of these hollowed-out areas and the solid part of the shunt. When the ion concentration distribution begins to be uneven near the boundary of the avoidance zone, it will directly affect the conduction path and distribution state of the current in the three-pole system. Specifically, under normal circumstances, the current density ratio between the anode assembly, shunt assembly, and cathode assembly should maintain a relatively stable numerical relationship. However, when ion anomalies occur at the boundary of the avoidance zone, this stable ratio relationship will deviate. For example, the original current density ratio of the anode to the shunt assembly is 2:1, which may become 2.1:1 or 1.9:1. This slight deviation in the value is a specific manifestation of the subtle change. By calculating the first-order time derivative and second-order time derivative of the current density ratio between the three components, this subtle ratio deviation can be amplified into a significant stress gradient feature. The first-order derivative shows how quickly this ratio changes, while the second-order derivative shows the trend of the change rate itself. The combination of the two can fully describe the instantaneous change process of the stress state at the boundary of the avoidance zone, thereby converting the ion behavior that cannot be observed by the naked eye into electrochemical stress distribution data that can be expressed numerically.

[0017] By performing spatiotemporal correlation analysis on electrochemical stress gradient data from multiple consecutive pulse cycles, it is possible to identify the changing patterns and development trends of stress gradient anomalies at different spatial locations within the avoidance zone, enabling dynamic tracking of the stress anomaly propagation path. This tracking process is similar to tracking a heat source moving across a room: the heat source's trajectory is determined by continuously monitoring temperature changes at different locations. Similarly, stress anomalies propagate along a specific path within the avoidance zone. By analyzing this propagation trajectory, it is possible to predict which areas the anomaly will affect next. Within a designated key monitoring area, by making small adjustments to the current density during the stable phase of the forward pulse and simultaneously monitoring the potential responses of the anode, shunt, and cathode components, the sensitivity of the local area to these small adjustments can be determined. Normal areas respond gently to small current adjustments, while areas with ion migration issues exhibit a more pronounced potential response to the same adjustments. This difference in sensitivity directly reflects the stability of the ionic environment in that area. Subsequently, a comprehensive analysis of the previously acquired stress gradient data, propagation trajectory data, and sensitivity data revealed a temporal relationship between stress anomalies and ion migration anomalies. Stress anomalies typically occur 2-3 pulse cycles before ion anomalies, providing a window for early warning. Finally, based on this temporal correlation, a comprehensive assessment of the electrochemical state of the avoidance zone was conducted, categorizing the state into varying degrees of anomaly severity. This shift from passive problem detection to proactive problem prediction enables accurate diagnosis and early warning information before ion migration anomalies fully manifest. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Schematic diagram of an embodiment of a detection method for pulse plating in an embodiment of the present invention; Figure 2 A schematic diagram of a pulse plating device according to an embodiment of the present invention; Figure 3 A schematic diagram of a pulse plating device according to an embodiment of the present invention; Figure 4 It is a schematic diagram of the structure of the pulse plating system; Figure 5 for Figure 4 Schematic diagram of the decomposition after omitting some structures.

[0019] Description of Figure Numbers: 1. Anode assembly; 11. Anode part; 12. First conductive part; 2. Cathode assembly; 21. Carrier plate; 22. Second conductive part; 3. Shunt assembly; 31. Shunt part; 32. Third conductive part; 33. Avoidance area; 4. Electroplating tank; 41. Accommodating cavity. DETAILED DESCRIPTION

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0021] The pulse plating detection method involved in this solution is applied to the pulse plating system in the example shown in the figure. This system belongs to the public technology. Here we briefly introduce some structures and specific usage processes of the pulse plating system to facilitate the understanding of the subsequent method solution. Please refer to the attached Figure 4 and Figure 5 For understanding, the system includes: an anode assembly 1, a cathode assembly 2, a shunt assembly 3 and an electroplating tank 4, wherein the anode assembly 1 includes an anode member 11 and a first conductive member 12, the first conductive member 12 is used to conduct current, and the anode member 11 is electrically connected to the first conductive member 12; the cathode assembly 2 includes a carrier plate 21 and a second conductive member 22, the second conductive member 22 is used to conduct current, and the carrier plate 21 is electrically connected to the second conductive member 22; at least one anode member 11 is relatively arranged on one side of the carrier plate 21, and in the conductive state, the carrier plate 21 can form a current loop with the anode member 11; the shunt assembly 3 includes a shunt member 31 and a third conductive member 3 2. The third conductive member 32 is used to conduct current. The shunt member 31 is arranged opposite to the anode member 11 and is electrically connected to the third conductive member 32. The shunt member 31 is arranged between the anode member 11 and the carrier plate 21, and in the conductive state, the shunt member 31 can form a current loop with the carrier plate 21. The first conductive member 12, the second conductive member 22, and the third conductive member 32 are not conductive to each other. The electroplating tank 4 has a accommodating chamber 41 with an opening on one side, which is usually opened upward and is used to load the electroplating solution and accommodate the anode member 11, the shunt member 31, and the carrier plate 21, so that the electroplating operation can be performed on the electroplated part in the electroplating solution in the accommodating chamber 41 in the conductive state.

[0022] When in use, the electroplating solution is poured into the opening of the accommodating cavity 41 of the electroplating tank 4, the anode component 11, the carrier plate 21 and the diverter 31 are immersed in the electroplating solution, the workpiece to be electroplated is loaded on the carrier plate 21, and the current is turned on. When the output current is a positive current, the current is conducted to the anode component 11 through the first conducting component 12, the anode component 1 conducts the current as the positive electrode, the current is conducted to the carrier plate 21 through the second conducting component 22, and the cathode component 2 conducts the current as the negative electrode, so that the carrier plate 21 can form a current loop with the anode component 11, thereby electroplating the workpiece to be electroplated; when the output current is a reverse current, the current is conducted through the second conducting component 22. To the carrier plate 21, the cathode assembly 2 conducts current as the positive electrode, and the current is conducted to the shunt member 31 through the third conductive member 32. The shunt assembly 3 conducts current as the negative electrode, so that the carrier plate 21 can form a current loop with the shunt member 31; furthermore, based on the periodic output of the forward current and reverse current, an electroplating loop can be formed respectively in the above manner, so that when the electroplated part is pulse-plated, the forward current is output, and the current distribution in the anode member 11 is uniform, thereby improving the electroplating uniformity of the electroplated part; the reverse current is output without passing through the anode member 11, thereby avoiding hydrogen evolution on the surface of the anode member 11, causing surface erosion, and accelerating the loss rate of the electroplating equipment. During normal pulse plating, in order to improve the electroplating efficiency and electroplating uniformity, the output time of the forward current is greater than the output time of the reverse current.

[0023] Furthermore, a clearance zone 33 is formed between adjacent shunt members 31 on the same third conductive member 32. The clearance zone 33 is disposed opposite the anode member 11 and opposite the carrier plate 21. During the pulse electroplating process, batch electroplating is performed. The parts to be plated are loaded onto the carrier plate 21, and the process is conducted and a forward current is output. When the anode member 11 serves as the positive electrode and the carrier plate 21 serves as the negative electrode, the clearance zone 33 corresponds to the area between the anode member 11 and the parts to be plated. As a result, a large amount of metal ions oxidized at the anode member 11 can be attracted by the negative electrode and adhere to the surface of the parts to be plated without being blocked by the shunt member 31, thereby improving electroplating efficiency and coating uniformity.

[0024] In this scenario, while the avoidance zone 33 solves the current distribution problem, it also produces complex electrochemical phenomena at the boundary of the avoidance zone 33. Due to the sudden change in the geometric shape of the edge of the avoidance zone 33 and the periodic switching of the pulse current, a discontinuous distribution of electric field strength will appear in the boundary area, causing the metal ions to deflect their migration path and dynamically reconstruct the concentration gradient when crossing the boundary area. Moreover, in the transient process of each pulse switching, the boundary area becomes a buffer zone for the re-balance of ion concentration, and the recovery time of its concentration distribution does not match the start time of the next pulse cycle, thereby producing a cumulative memory effect on the electroplating effect of subsequent pulses. Traditional ion concentration monitoring methods mainly rely on offline chemical analysis or single-point electrochemical detection, and their time resolution is usually in the second to minute level, which is far from being able to track the millisecond-level dynamic reconstruction process of the boundary layer. As a result, this memory effect gradually accumulates during multiple batches of electroplating, ultimately causing a significant deterioration in the uniformity of the coating thickness.

[0025] To this end, this application proposes a pulse plating detection method, please refer to Figure 1 The method of this embodiment may specifically include: During the time window from the forward pulse to the reverse pulse of the pulse plating process, the transient current density data between the anode component, the shunt component, and the cathode component are synchronously collected. The first-order time derivative and the second-order time derivative of the current density ratio between the three components are calculated to obtain the electrochemical stress gradient data. Performing spatiotemporal correlation analysis on the electrochemical stress gradient data of multiple consecutive pulse cycles to track the spatial position change and evolution trend of stress gradient anomalies and obtain stress anomaly propagation trajectory data; Based on the key monitoring area determined by the stress anomaly propagation trajectory data, the current density is slightly modulated in the steady-state section of the forward pulse, the potential response change of the three-electrode system is synchronously monitored, the ion migration impedance sensitivity coefficient is calculated, and the impedance sensitivity distribution data is obtained; Performing multi-dimensional coupling analysis on the electrochemical stress gradient data, stress anomaly propagation trajectory data, and impedance sensitivity distribution data to identify the temporal correlation characteristics between stress evolution and ion migration anomalies, and obtain coupling correlation characteristic data; Based on the coupling correlation characteristic data, the electrochemical state of the avoidance zone of the shunt component is quantitatively evaluated, the abnormality level is determined, and the avoidance zone state diagnosis result is obtained.

[0026] In one embodiment of the present invention, the transient current density data between the anode component, the shunt component, and the cathode component are synchronously collected within the time window when the forward pulse of the pulse electroplating is switched to the reverse pulse, and the first-order time derivative and the second-order time derivative of the current density ratio between the three components are calculated to obtain the electrochemical stress gradient data, including: During the period when the forward pulse switches to the reverse pulse, the transient current density data of the anode assembly, the shunt assembly and the cathode assembly are synchronously acquired, and the current density ratios between the anode assembly and the shunt assembly, the anode assembly and the cathode assembly, and the shunt assembly and the cathode assembly are calculated to obtain the three-electrode current density ratio data; Calculating the first-order time derivative and the second-order time derivative of the three-pole current density ratio data respectively, judging the validity of each derivative data based on the geometric symmetry of the avoidance zone, and screening out the effective derivative data reflecting the stress change; According to the stress change rate represented by the first-order derivative and the stress change acceleration represented by the second-order derivative in the effective derivative data, the spatial distribution parameters of the stress gradient at the boundary of the avoidance zone are calculated to obtain electrochemical stress gradient data.

[0027] The following is a detailed description of the steps involved in the above embodiment: During the transition from forward pulse to reverse pulse, the entire process from the peak current drop to the completion of the transition is selected as the data acquisition window. Current sensors are installed on the conductive components of the anode, shunt, and cathode assemblies to simultaneously record the current density changes in all three assemblies. The acquisition frequency is set to 100kHz to ensure that microsecond-level current changes can be captured. The acquired raw current density data is filtered and three sets of current density ratios are calculated: the ratio of the anode assembly to the shunt assembly, the ratio of the anode assembly to the cathode assembly, and the ratio of the shunt assembly to the cathode assembly. For example, if the current density of the anode assembly is 120A / dm² and that of the shunt assembly is 60A / dm² at a certain moment, the ratio is 2.0. This continuous calculation generates time series ratio data. This ratio calculation method eliminates the influence of absolute current fluctuations and highlights the relative changes between the three-electrode systems, providing sensitive data for detecting subtle anomalies at the boundaries of the avoidance zone.

[0028] The first- and second-order time derivatives of the obtained tripolar current density ratio data were calculated using a numerical difference method. The first-order derivative was obtained by dividing the difference between the ratios at adjacent moments by the time interval, while the second-order derivative was calculated by dividing the difference between the first-order derivatives at adjacent moments by the time interval. The specific process for determining validity based on the geometric symmetry of the avoidance zone involves utilizing the mirror symmetry of the avoidance zone design to divide the avoidance zone into two symmetrical regions, one on the left and one on the right. Under normal circumstances, the derivative values ​​of the two regions should be similar in value and have the same sign. If a derivative value differs from the derivative value at its symmetrical position by more than 30% of the average value, the data is considered to be potentially affected by noise and is eliminated. Geometric symmetry refers to the spatial geometric symmetry of the avoidance zone due to its hollow design. This symmetry should be maintained during normal electrochemical processes. This symmetry-constrained screening effectively identifies and retains valid derivative data that truly reflects electrochemical stress changes, while eliminating anomalous data caused by external factors such as equipment noise and power grid fluctuations.

[0029] The spatial distribution parameters of the stress gradient at the avoidance zone boundary are calculated based on the selected valid derivative data. The specific implementation process is as follows: the first-order derivative value is used as an indicator of the stress change intensity at each measurement point, and the second-order derivative value is used as an indicator of the change trend. The time series data is converted into spatial position data through coordinate mapping. The electrochemical stress gradient refers to the rate of change of the electrochemical stress at different spatial locations within the avoidance zone, similar to how a temperature gradient describes the speed of temperature change in space. The spatial distribution parameters are calculated using an interpolation method. A grid coordinate system is established at the avoidance zone boundary. The derivative values ​​of each measurement point are assigned to the corresponding grid locations, forming a data matrix describing the stress distribution at the entire avoidance zone boundary. This spatial processing transforms the previously abstract time-varying information into an intuitive spatial distribution image, making the electrochemical stress evolution process at the avoidance zone boundary visual and quantifiable, providing accurate data support for the subsequent identification of the spatial location and propagation path of stress anomalies.

[0030] In one embodiment of the present invention, the first-order time derivative and the second-order time derivative of the three-pole current density ratio data are calculated respectively, the validity of each derivative data is judged based on the geometric symmetry of the avoidance zone, and the valid derivative data reflecting the stress change is screened out, including: Performing numerical differentiation operations on each ratio sequence in the three-pole current density ratio data, calculating the first-order time derivative and the second-order time derivative of the anode-shunt component ratio, the anode-cathode component ratio, and the shunt-cathode component ratio, to obtain a derivative data matrix; A symmetry evaluation benchmark is established based on the central symmetry axis and mirror symmetry plane of the avoidance zone's geometric boundary. The degree of deviation of each derivative data relative to the symmetry benchmark is calculated, and abnormal derivative values ​​that violate the geometric symmetry constraints are identified to obtain a symmetry screening mark. According to the symmetry screening identifier, derivative data that meets the geometric symmetry requirements are retained, and non-physical derivative values ​​generated by current noise or system disturbances are eliminated to obtain effective derivative data reflecting stress changes.

[0031] The following is a detailed description of the steps involved in the above embodiment: Numerical differentiation is performed on each ratio series in the three-electrode current density ratio data, using the forward difference method. Taking the anode-shunt component ratio series as an example, assuming the ratios corresponding to consecutive times t1, t2, and t3 are R1, R2, and R3, respectively, the first-order time derivative is calculated as (R2-R1) / (t2-t1), and the second-order time derivative is calculated as [(R3-R2) / (t3-t2)-(R2-R1) / (t2-t1)] / (t2-t1). The same method is used to calculate the first- and second-order time derivatives of the anode-cathode component ratio series and the shunt-cathode component ratio series. The derivative data matrix is ​​a two-dimensional data table formed by arranging all the derivative values ​​of the three ratio series in chronological order and by group type. Rows represent time sampling points, and columns represent different derivative types. For example, if the anode-to-shunt ratio changes from 2.0 to 2.1 at a given moment, with a time interval of 0.01 seconds, the first-order derivative is 10s⁻¹, representing the rate of change of the ratio. This numerical differentiation operation quantifies the time course of the ratio into specific rate and acceleration values, making subtle changes in the electrochemical process precisely measurable and analyzable.

[0032] The specific process for establishing a symmetry evaluation benchmark based on the central symmetry axis and mirror symmetry plane of the avoidance zone's geometric boundary is as follows: first, the geometric center of the avoidance zone is determined as the intersection of the central symmetry axes. Then, two symmetry axes are established along the vertical and horizontal directions to divide the avoidance zone into four quadrants. The mirror symmetry plane is an imaginary plane passing through the center of the avoidance zone and perpendicular to the surface of the diverter component, dividing the avoidance zone into two bilaterally symmetrical parts. The central symmetry axis is a straight line passing through the geometric center of the avoidance zone and is used to determine the symmetry of each measurement point relative to the center. The symmetry evaluation benchmark is established by pairing and comparing the derivative values ​​of corresponding positions in each quadrant and calculating the relative deviation between the paired derivative values. For example, if a derivative value of 5 at a point in the upper left quadrant is compared to a derivative value of 4.8 at the corresponding point in the lower right quadrant, the deviation is |(5-4.8) / 4.65|×100%=4.3%. When the deviation exceeds a preset threshold of 15%, the derivative value is flagged as an abnormal violation of the geometric symmetry constraint. This evaluation benchmark based on the inherent geometric characteristics of the avoidance zone can effectively identify asymmetric phenomena caused by local electrochemical anomalies and provide a judgment criterion with sufficient physical basis for data screening.

[0033] Data screening is performed based on symmetry screening flags. Specifically, a screening flag table is established, marking each derivative data point as "retained" or "rejected." Derivative data that meets geometric symmetry requirements refers to data with deviations within a 15% threshold. These data reflect the true electrochemical stress variations at the avoidance zone boundary. Non-physical derivative values ​​are anomalous data generated by external factors such as current noise, power grid fluctuations, and sensor drift. Such data do not conform to the physical symmetry constraints of the avoidance zone. The elimination process uses a point-by-point verification approach, removing anomalous derivative values ​​marked "rejected" from the derivative data matrix and retaining valid data marked "retained." For example, if 8 out of 100 derivative data points have deviations exceeding the threshold, these 8 outliers are eliminated, leaving 92 valid data points as the final valid derivative data set. The 15% threshold is selected based on a comprehensive consideration of the avoidance zone's geometric machining accuracy and the plating bath environment. This ensures sensitive detection of true anomalies while avoiding misjudgments due to minor geometric deviations. This data screening method based on physical constraints ensures the reliability of subsequent stress analysis and avoids the interference of noise data on the electrochemical stress evolution detection results.

[0034] In one embodiment of the present invention, the temporal and spatial correlation analysis of the electrochemical stress gradient data of a plurality of consecutive pulse cycles is performed to track the spatial position change and evolution trend of the stress gradient anomaly to obtain the stress anomaly propagation trajectory data, including: The electrochemical stress gradient data of a plurality of consecutive pulse cycles are arranged in a time series, the deviation degree of the stress gradient of each cycle is calculated based on the symmetry benchmark of the geometric boundary of the avoidance zone, and the stress gradient abnormal points whose deviation degree exceeds a preset range are identified to obtain time series stress abnormality identification data; According to the spatial distribution position of the abnormal points in the time series stress anomaly identification data, combined with the geometric constraints of the avoidance zone boundary, the spatial displacement law of the abnormal points between adjacent pulse cycles is analyzed, the direction vector and propagation speed of the abnormal propagation are calculated, and the stress anomaly spatial propagation parameters are obtained; Based on the stress anomaly spatial propagation parameters, the movement path of the anomaly point in the avoidance zone is tracked, the residence phenomenon of the stress anomaly at the geometric corner and the acceleration phenomenon at the straight line boundary are identified, and the geometric constraint propagation characteristic data is obtained; The geometric constraint propagation characteristic data is combined with the pulse time beat to reconstruct the complete motion trajectory of the stress anomaly in the time-space two-dimensional coordinate system, predict the propagation trend and arrival area of ​​the stress anomaly, and obtain the stress anomaly propagation trajectory data.

[0035] The following is a detailed description of the steps involved in the above embodiment: The electrochemical stress gradient data from multiple consecutive pulse cycles are arranged in a time series. Specifically, each pulse cycle is labeled 1, 2, 3, and the corresponding stress gradient data are arranged in sequence into a time series table. The symmetry benchmark is determined by measuring the geometric parameters of symmetrical locations on the left and right sides of the avoidance zone in a static state without electroplating. The average value is used as the ideal symmetry benchmark. The degree of deviation is calculated using the percentage deviation method: the difference between the measured stress gradient and the symmetry benchmark is divided by the benchmark value and multiplied by 100%. For example, if the baseline stress gradient at a point on the left side of the avoidance zone is 8 Pa / m, and the measured value at that point during the third pulse cycle is 10.4 Pa / m, the degree of deviation is |(10.4-8) / 8| × 100% = 30%. The default range is set to ±20%, a value determined based on a comprehensive consideration of the geometric machining error of the avoidance zone (approximately 5%) and the influence of electroplating environment fluctuations (approximately 15%). When the deviation exceeds 20%, the data point is marked as an anomaly. Information about the anomaly point, including the pulse cycle number, spatial coordinates (x, y), and specific deviation value, forms an anomaly identification table. This anomaly identification method based on symmetry deviation leverages the inherent symmetry of the avoidance zone's geometric design to sensitively detect local anomalies caused by electrochemical imbalance, avoiding the limitations of traditional methods that rely on absolute numerical judgment.

[0036] Propagation analysis is performed based on the spatial coordinates of the anomaly points recorded in the anomaly identification table. Specifically, the coordinate changes of the same anomaly point during consecutive pulse cycles are extracted. Geometric constraints specifically refer to three typical shapes of avoidance zone boundaries: straight line segments (straight line boundaries), corner regions (the sharp angle formed by the intersection of two straight lines), and transition regions (the connecting portion between a straight line and a corner). Anomaly propagation analysis utilizes the coordinate difference method: if the coordinates of an anomaly point in the nth cycle are (x1, y1) and the coordinates in the (n+1)th cycle are (x2, y2), then the displacement vector is (x2-x1, y2-y1), the propagation direction angle θ = arctan[(y2-y1) / (x2-x1)], and the propagation velocity v = √[(x2-x1)²+(y2-y1)²] / Δt, where Δt is the pulse cycle interval. Spatial propagation parameters for stress anomalies include the propagation direction angle, propagation velocity, and cumulative propagation distance for each anomaly point. These parameters are recorded and stored in a data table. The pulse cycle interval is a fixed parameter in the pulse electroplating system, providing a unified time base for velocity calculations. This propagation analysis method based on coordinate geometry transforms the abstract electrochemical propagation process into a concrete description of spatial motion, making the anomalous diffusion pattern precisely quantifiable and predictable.

[0037] The movement path of anomalies is continuously tracked based on propagation parameter data. The specific method is to connect the coordinate points of the same anomaly in each pulse cycle with straight lines to form a motion trajectory diagram. The identification criteria for the dwell phenomenon are: the displacement of the anomaly in the corner region is less than 0.5 mm for three or more consecutive pulse cycles, and the propagation velocity is reduced to less than 50% of the normal velocity. The identification criteria for the acceleration phenomenon are: the propagation velocity of the anomaly in the straight boundary segment is more than twice its propagation velocity in the corner region. For example, the average propagation velocity of an anomaly in the corner region is 1.2 mm / cycle. When entering the straight boundary segment, the velocity increases to 3.0 mm / cycle, and the velocity ratio is 2.5, which meets the identification criteria for the acceleration phenomenon. Geometrically constrained propagation feature data is a dataset that records the differences in anomaly propagation behavior within different geometric regions. It includes the dwell duration (the number of consecutive pulse cycles of dwell), the acceleration factor (the ratio of the velocity of the straight segment to the velocity of the corner region), and the path deflection angle (the angle by which the anomaly's motion direction changes when entering different geometric regions). These quantitative geometric constraint effect data reveal the specific influence mechanism of the avoidance zone boundary shape on the propagation of electrochemical stress, providing important physical parameter support for predicting abnormal development trends.

[0038] Trajectory reconstruction is achieved by combining geometrically constrained propagation feature data with pulse time cadence. This involves creating a two-dimensional graph with pulse cycles as the abscissa and spatial position coordinates as the ordinate. Trajectory reconstruction utilizes piecewise linear interpolation: intermediate points are interpolated at equal intervals between known discrete time points (pulse cycles). The coordinates of these intermediate points are calculated by linear interpolation of adjacent known points. Propagation trend prediction is based on a linear extension of the trajectory slope change over the last five pulse cycles, using the formula: predicted coordinate = current coordinate + average moving vector × predicted number of cycles. Arrival zone prediction is achieved by calculating the intersection of the extended trajectory with the avoidance zone boundary, using a simultaneous solution of linear equations to determine the intersection coordinates. Stress anomaly propagation trajectory data is a complete dataset containing the anomaly's historical location, current state, and predicted location for the next three to five cycles. The data is formatted as a sequence of time-space coordinate pairs. This time-cadence-based trajectory reconstruction method transforms discrete detection data into a continuous motion image, enabling intuitive visualization and accurate prediction of the electrochemical stress evolution process at the avoidance zone boundary.

[0039] In one embodiment of the present invention, the tracking of the movement path of the abnormal point within the avoidance zone based on the stress anomaly spatial propagation parameter, identifying the residence phenomenon of the stress anomaly at the geometric corner and the acceleration phenomenon at the straight line boundary, and obtaining the geometric constraint propagation characteristic data include: According to the direction vector and propagation velocity data in the stress anomaly spatial propagation parameter, the motion trajectory and velocity distribution of the abnormal point at each spatial position in the avoidance zone are calculated, the geometric path characteristics of the trajectory are identified, and the motion trajectory data of the abnormal point is obtained; Performing geometric partition analysis on the motion trajectory data of the outlier point to distinguish the difference in motion characteristics when the outlier point is located in the geometric corner area and the straight boundary area of ​​the avoidance zone, calculating the speed attenuation coefficient of the corner area and the speed growth coefficient of the straight area, and obtaining the partition motion characteristic parameters; Based on the partitioned motion characteristic parameters, the residence accumulation effect of stress anomalies in the corner area and the propagation acceleration effect in the straight area are identified, the residence time and the acceleration multiple are quantified, and the geometric constraint propagation characteristic data are obtained.

[0040] The following is a detailed description of the steps involved in the above embodiment: The motion trajectory is calculated based on the direction vector and propagation velocity data from the stress anomaly's spatial propagation parameters. Specifically, the directional angle and velocity values ​​of each anomaly point during successive pulse cycles are extracted and the trajectory path is calculated using a coordinate recursion method. The directional vector is expressed as an angle, with 0° representing horizontal rightward and 90° representing vertical upward. The propagation velocity is recorded in millimeters per pulse cycle. The motion trajectory is calculated using a point-by-point approach: assuming the current position of the anomaly point is (x0, y0), the direction angle is θ, and the propagation velocity is v, then the position at the next moment is (x0 + v × cosθ, y0 + v × sinθ). Velocity distribution is generated by statistically analyzing the velocity values ​​of the anomaly point at each spatial location to form a velocity distribution map. Geometric path feature recognition is achieved by analyzing the trajectory's shape characteristics. These include three types of paths: straight paths (trajectory deflection angles less than 15°), curved paths (deflection angles 15°-45°), and sharp paths (deflection angles greater than 45°). The anomaly point trajectory data is a comprehensive dataset containing the complete spatial motion path of each anomaly point, the geometric feature types of each path segment, and the corresponding velocity values. For example, an outlier point moves from coordinates (2, 5) at a 30° angle and a speed of 2 mm / cycle for three cycles to coordinates (7.2, 8.5), resulting in a straight-line trajectory. This vector-based trajectory reconstruction method converts discrete propagation parameters into a continuous spatial motion description, making the complex stress propagation process within the avoidance zone intuitive and visual.

[0041] The specific method for geometric partitioning analysis of outlier trajectory data is to divide the avoidance zone into two types: corner regions and straight boundary regions based on the geometric shape of the avoidance zone. Corner regions refer to the sharp angles formed by the intersection of two straight lines within the avoidance zone boundary, with angles ranging from 30° to 150°. Straight boundary regions refer to the straight segments within the avoidance zone boundary, with angles less than 5°. Motion feature difference analysis is achieved by comparing the motion parameters of the same outlier in different regions. The velocity decay coefficient is calculated by dividing the average velocity in the corner region by the average velocity of the outlier in other regions. A value less than 1 indicates velocity decay. The velocity growth coefficient is calculated by dividing the average velocity in the straight region by the average velocity of the outlier in the corner region. A value greater than 1 indicates velocity growth. For example, if the average velocity of an outlier in the corner region is 1.5 mm / cycle and the average velocity in the straight region is 4.2 mm / cycle, the velocity decay coefficient is 1.5 / 3.0 = 0.5, and the velocity growth coefficient is 4.2 / 1.5 = 2.8. The zoned motion characteristic parameters include the average velocity, dwell time, velocity variation coefficient, and path deflection angle of each anomaly point within different geometric regions. This differentiated analysis method based on geometric partitioning reveals the regulatory effect of the avoidance zone boundary shape on the propagation of stress anomalies and quantifies the specific impact of the geometric constraint effect.

[0042] The specific implementation process for identifying geometric constraint effects based on partitioned motion characteristic parameters includes the identification and quantification of the dwell accumulation effect and the propagation acceleration effect. The dwell accumulation effect refers to the phenomenon in which the propagation velocity of a stress anomaly decreases significantly and its residence time increases in corner regions. Identification criteria include a velocity attenuation coefficient less than 0.7 and a residence time exceeding two pulse cycles. The propagation acceleration effect refers to the phenomenon in which the propagation velocity of a stress anomaly increases significantly in a straight region. Identification criteria include a velocity growth coefficient greater than 1.5. The dwell time is quantified by counting the number of consecutive pulse cycles that the anomaly stays in the corner region. For example, if the anomaly stays in a corner region from the third to the seventh cycle, the residence time is five cycles. The acceleration factor is quantified by calculating the ratio of the maximum velocity of the anomaly after entering the straight region to its velocity before entering. For example, if the velocity before entering is 2 mm / cycle and the maximum velocity after entering reaches 7 mm / cycle, the acceleration factor is 3.5 times. Geometric constraint propagation characteristic data is a data set that records the propagation behavior characteristics of each anomaly under different geometric constraint conditions. It includes quantitative parameters such as residence duration, acceleration factor, velocity variation, and propagation path deflection. The mechanism of the residence effect in corner regions is that the sharp angle of the geometric boundary increases the resistance to stress propagation, while the mechanism of the acceleration effect in straight regions is that the straight boundary provides the path of least resistance for stress propagation. This method of propagation feature identification based on geometric constraints reveals the profound mechanism by which the avoidance zone boundary shape regulates the electrochemical stress evolution process, providing important physical parameter basis for predicting and controlling the development of stress anomalies.

[0043] In one embodiment of the present invention, the key monitoring area determined according to the stress anomaly propagation trajectory data is subjected to slight modulation of the current density in the steady-state section of the forward pulse, the potential response change of the three-electrode system is synchronously monitored, and the ion migration impedance sensitivity coefficient is calculated to obtain the impedance sensitivity distribution data, including: Based on the predicted arrival position and residence area distribution of the stress anomaly in the stress anomaly propagation trajectory data, combined with the curvature distribution characteristics of the geometric boundary of the avoidance zone, the high probability area of ​​stress concentration is identified, the spatial position of the key monitoring area is determined, and the monitoring area positioning data is obtained; In the middle time window of the forward pulse steady-state segment, a modulation strategy is determined according to the positioning data of the monitoring area, the overall current density is periodically slightly modulated, and the modulation amplitude and frequency parameters are adjusted to enhance the response sensitivity of the target area to obtain optimized modulation parameters; Based on the optimized modulation parameters, the potential response data of the anode component, the shunt component and the cathode component in the modulation state are synchronously collected, and the ratio of the potential response amplitude of each component to the modulation amplitude and the phase difference between the response and the modulation are calculated to obtain the three-electrode potential response characteristic data; The regional difference analysis of the three-pole potential response characteristic data is performed, and the response amplitude ratio of each monitoring area is weighted according to the geometric curvature distribution of the avoidance zone to obtain the sensitivity coefficient distribution reflecting the change of local ion migration impedance, thereby forming impedance sensitivity distribution data.

[0044] The following is a detailed description of the steps involved in the above embodiment: Key monitoring areas are identified based on the predicted arrival location and residence area distribution in the stress anomaly propagation trajectory data. This is achieved by extracting the spatial coordinates of the anomaly points marked in the trajectory data, which are expected to arrive within the next 3-5 pulse cycles. The residence area distribution refers to the spatial region where the anomaly points reside for more than two pulse cycles. The curvature distribution characteristic of the avoidance zone's geometric boundary refers to the degree of curvature at each location on the boundary. This is measured using a simplified three-point method: three consecutive points A, B, and C are selected on the boundary with a spacing of 1 mm. The angle ABC is calculated, with smaller angles indicating greater curvature. The curvature value is expressed as the cosine of the angle, with smaller cosθ values ​​indicating sharper curvature. High-probability areas of stress concentration are identified using a spatial overlap method: the predicted arrival location, residence area, and high-curvature locations (cosθ < 0.5) are marked on the avoidance zone plan. The overlapping areas are considered high-probability areas. For example, coordinates (8, 12) are both the predicted arrival point of the anomaly and have a historical residence record. The boundary angle is 60° (cosθ = 0.5), meeting the criteria for a high-probability area. Monitoring area location data is recorded in a coordinate table, including area number, center coordinates, coverage area, and risk level (high, medium, and low). This spatial overlay-based regional screening method concentrates large-scale monitoring tasks on key areas, avoiding resource waste and improving the targeting of anomaly detection.

[0045] A modulation strategy is developed and executed within the middle time window of the forward pulse's steady-state phase. This time window refers to the middle 40% of the forward pulse's total duration, during which the current has reached a steady state and has not yet begun to decay. Modulation parameters are determined based on the risk level of the monitored area: 2% modulation amplitude and 2Hz modulation frequency are used in high-risk areas, 1.5% modulation amplitude and 3Hz modulation frequency are used in medium-risk areas, and 1% modulation amplitude and 4Hz modulation frequency are used in low-risk areas. The modulation amplitude is limited to 2% because larger amplitudes interfere with the normal electroplating process. The frequency range of 2-4Hz is the optimal detection frequency range determined based on the electrochemical response time constant of the avoidance zone (approximately 0.2-0.5 seconds). Periodic micro-amplitude modulation is implemented by superimposing a sinusoidal modulation signal on a baseline current density, with the modulation depth set according to the risk level of the area. For example, in a high-risk area with a baseline current density of 100A / dm², the modulated current density will periodically vary between 98-102A / dm² at a frequency of 2Hz. The optimized modulation parameter record table contains the specific modulation amplitude, frequency, and duration values ​​for each monitored area. The differentiated settings of modulation amplitude and frequency make full use of the differences in sensitivity of different risk areas to current disturbances, and achieve effective stimulation of potential anomalies by precisely controlling the disturbance intensity.

[0046] Based on optimized modulation parameters, the potential response data of the three-pole component is synchronously acquired. The acquisition method records the potential changes of each component during each modulation cycle at a sampling rate 20 times the modulation frequency. The peak-to-peak measurement method is used to measure the potential response amplitude: the maximum and minimum potential values ​​during the modulation period are recorded, and the difference between the two is the response amplitude. The modulation amplitude refers to the percentage change of the modulation current relative to the standard current. The ratio of the response amplitude to the modulation amplitude reflects the system's amplification characteristics; a larger ratio indicates greater sensitivity to perturbations. The phase difference is measured using the zero-crossing method: the moments when the modulated input signal and the potential response signal pass through zero are recorded. The difference between these two moments is divided by the modulation period and multiplied by 360° to obtain the phase difference angle. For example, if the 2Hz modulation signal period is 0.5 seconds and the response signal lags the input signal by 0.05 seconds, the phase difference is 36°. The three-pole potential response characteristic data includes the response amplitude ratio, phase difference, and response stability indicators for each of the three components and is stored in a data matrix format. Response stability is assessed by calculating the standard deviation of the response amplitude over multiple modulation cycles. A standard deviation less than 10% of the mean is considered a stable response. This multi-parameter synchronous measurement method can comprehensively capture the impact of local anomalies in the avoidance zone on the response characteristics of the entire three-pole system.

[0047] Regional differences in the three-pole potential response characteristic data were analyzed by grouping the response data from each monitoring area and calculating inter-group differences. Regional differences were quantified using the relative standard deviation of the response amplitude ratio. A relative standard deviation greater than 15% indicated significant regional differences. Weighted calculations for the geometric curvature distribution were performed by categorizing the avoidance zone into three levels based on curvature value: high curvature regions (cosθ < 0.5) were assigned a weight of 1.5, medium curvature regions (0.5 ≤ cosθ < 0.8) were assigned a weight of 1.0, and low curvature regions (cosθ ≥ 0.8) were assigned a weight of 0.7. The weighted response value was calculated as the raw response amplitude ratio multiplied by the corresponding curvature weight. The sensitivity coefficient quantifies the sensitivity to changes in local ion migration impedance and is calculated as: sensitivity coefficient = weighted response value × regional anomaly frequency. The anomaly frequency was obtained from historical data statistics: the coefficient for high-frequency regions was 1.2, for medium-frequency regions was 1.0, and for low-frequency regions was 0.8. For example, if the weighted response value in a certain area is 4.5 mV / %, and the frequency of anomalies is high, then the sensitivity coefficient is 4.5 × 1.2 = 5.4. The impedance sensitivity distribution data is presented as a spatial distribution map, containing the sensitivity coefficient values ​​and corresponding spatial coordinate information for each monitoring area. This sensitivity quantification method based on weighted geometric features accurately reflects the impact of the avoidance zone boundary shape on the stability of the local electrochemical environment, enabling the precise location and assessment of the severity of ion migration impedance anomalies.

[0048] In one embodiment of the present invention, the electrochemical stress gradient data, stress anomaly propagation trajectory data, and impedance sensitivity distribution data are subjected to multi-dimensional coupling analysis to identify the temporal correlation characteristics between stress evolution and ion migration anomalies, thereby obtaining coupling correlation feature data, including: The electrochemical stress gradient data, stress anomaly propagation trajectory data, and impedance sensitivity distribution data are time-series aligned according to the pulse cycle time scale, and a corresponding relationship between the three types of data under the same time reference is established to obtain a time-series synchronized data matrix; Performing a correlation analysis on the stress gradient change and the impedance sensitivity change in the time-series synchronization data matrix, calculating the time delay parameter and correlation strength coefficient between the two, identifying the phase difference characteristics of the stress evolution leading the ion migration anomaly, and obtaining the phase correlation parameter; According to the phase correlation parameters combined with the spatial information of the stress anomaly propagation trajectory, the spatial distribution law of the phase difference at each key node on the stress propagation path is analyzed, the distribution pattern of the phase difference changing with the geometric position is identified, and the spatiotemporal coupling characteristic data is obtained; Based on the spatiotemporal coupling characteristic data, a comprehensive coupling strength index between stress evolution and ion migration anomaly is calculated, and the system stability state is divided according to the numerical range of the coupling strength to obtain coupling correlation characteristic data.

[0049] The following is a detailed description of the steps involved in the above embodiment: The electrochemical stress gradient data, stress anomaly propagation trajectory data, and impedance sensitivity distribution data were aligned according to the pulse cycle time scale. Specifically, the pulse number was used as the unified time axis. The pulse cycle time scale refers to numbering each pulse cycle in the order of occurrence (1, 2, 3, etc.), which serves as the scale of the time axis. The alignment was achieved by matching data timestamps: the pulse cycle numbers recorded for each of the three data types were compared, and data with the same number were grouped together. For example, the electrochemical stress gradient data corresponding to the fifth pulse cycle is 8.5 Pa / m, the stress anomaly propagation trajectory data shows an anomaly point at coordinates (6, 8), and the impedance sensitivity distribution data is 3.2 mV / %. These three data sets constitute the data set for the fifth cycle. The corresponding relationships were established using a table matching method: a two-dimensional table was created with pulse cycle numbers as rows and the three data types as columns, and each table cell was filled with the corresponding data value. A time-synchronized data matrix is ​​a data table that contains the complete correspondence between the three data types for all pulse cycles, with rows representing time series and columns representing different data types. Missing data are handled using linear interpolation: if a cycle lacks a specific type of data, the missing data is filled in using the average value of that type of data from the preceding and following cycles. This pulse beat-based timing alignment eliminates temporal deviations between data sources and enables precise, synchronized analysis of multi-dimensional electrochemical information.

[0050] Correlation analysis was performed between stress gradient changes and impedance sensitivity changes in the time-synchronized data matrix. The Pearson correlation coefficient between the two data series was calculated. Stress gradient changes were calculated by interpolating the stress gradient data between adjacent pulse cycles, and impedance sensitivity changes were similarly obtained by interpolating the data between adjacent cycles. The time delay parameter was calculated using a sliding correlation analysis method: the impedance sensitivity change sequence was time-shifted relative to the stress gradient change sequence, and the correlation coefficients were calculated for different shift steps. The shift step corresponding to the maximum correlation coefficient was the time delay parameter. For example, when the impedance sensitivity sequence was shifted backward by two pulse cycles, the correlation coefficient reached a maximum of 0.85, and the time delay parameter was 2 cycles. The correlation strength coefficient is the maximum correlation coefficient value; values ​​closer to 1 indicate stronger correlation. The phase difference characteristic refers to the temporal advance of stress evolution relative to ion migration anomalies. It is calculated by dividing the time delay parameter by the analysis window length and multiplying it by 360°. The analysis window length was set to 20 pulse cycles, based on the complete cycle characteristics of the electrochemical response in the avoidance zone. Phase correlation parameters include three key indicators: time delay value, correlation strength coefficient, and phase difference angle. This time series-based correlation analysis method accurately identifies the causal temporal relationship between stress evolution and ion anomalies, revealing the predictive value of stress changes on ion behavior.

[0051] The spatial distribution pattern of the stress anomaly is analyzed based on the phase correlation parameters combined with the spatial information of the stress anomaly propagation trajectory. The specific implementation method is to extract the coordinates of key nodes on the propagation trajectory and calculate the phase difference value at each node. Key nodes include special locations such as the trajectory starting point, end point, corner points, and velocity change points. The spatial information extraction method uses a coordinate marking method: the spatial coordinates and corresponding phase difference values ​​of each key node are marked on the avoidance zone plan. The spatial distribution pattern of the phase difference is obtained through spatial interpolation analysis, and the phase difference values ​​of unmeasured locations between nodes are calculated using the inverse distance weighted method. The distribution pattern is identified by contour drawing: locations with the same phase difference value are connected into contour lines to form a phase difference distribution map. For example, a 30° phase difference contour line connects all spatial locations with a phase difference of 30° within the avoidance zone, forming a spatial distribution pattern. Geometric position change analysis is achieved by calculating the phase difference gradient: the phase difference gradient is obtained by dividing the difference in phase difference between adjacent key nodes by the spatial distance. Areas with large gradients indicate drastic phase difference changes. The spatiotemporal coupling characteristic data is a comprehensive dataset describing the coupled variation of phase differences in both time and space. It contains information such as spatial coordinates, phase difference values, variation gradients, and distribution patterns. This two-dimensional spatiotemporal analysis method reveals the spatial regulation of stress-ion correlations by the geometry of the avoidance zone, enabling the spatial localization and identification of patterns in complex electrochemical coupling phenomena.

[0052] A comprehensive coupling strength index is calculated based on spatiotemporal coupling feature data. The specific calculation method is a weighted synthesis of three parameters: correlation strength coefficient, phase difference stability, and spatial distribution uniformity. The correlation strength coefficient is weighted at 0.5, reflecting the basic strength of the coupling; the phase difference stability is weighted at 0.3, and is assessed by calculating the standard deviation of the phase difference at each key node; smaller standard deviations indicate better stability; and the spatial distribution uniformity is weighted at 0.2, and is assessed by calculating the coefficient of variation of the phase difference gradient. The formula for calculating the comprehensive coupling strength index is: 0.5 × correlation strength coefficient + 0.3 × (1 - phase difference standard deviation / average phase difference) + 0.2 × (1 - gradient variation coefficient). System stability states are categorized based on the coupling strength range: strong coupling (0.8-1.0) indicates high system stability, moderate coupling (0.5-0.8) indicates basic system stability, weak coupling (0.2-0.5) indicates a risk of system instability, and no coupling (0-0.2) indicates severe system instability. For example, a comprehensive coupling strength of 0.72 calculated for a certain period corresponds to a moderate coupling state. The coupling correlation feature data includes statistical information such as the combined coupling strength value, stability state level, and corresponding confidence intervals. Weighting is determined based on the response characteristics of the electrochemical system in the avoidance zone, with correlation strength, as the dominant factor, receiving the highest weight, while stability and uniformity, as corrective factors, receive lower weights. This multi-parameter comprehensive evaluation method quantitatively describes the overall state of the stress-ion coupling system, providing a reliable basis for stability early warning during the pulse electroplating process.

[0053] In one embodiment of the present invention, the quantitative evaluation of the electrochemical state of the avoidance zone of the shunt component based on the coupling correlation characteristic data, determining the abnormality level, and obtaining the avoidance zone state diagnosis result includes: Based on the comprehensive coupling strength index and phase correlation parameter in the coupling correlation characteristic data, the geometric symmetry deviation and temporal stability index of the electrochemical system in the avoidance zone are calculated to obtain a quantitative index of the system state; Based on the system state quantitative index combined with the symmetry benchmark characteristics of the avoidance zone geometric boundary, the abnormality degree grading judgment standard is determined by dividing the numerical interval of the quantitative index, and the electrochemical state of the avoidance zone is divided into four levels: normal stability, slight deviation, moderate imbalance and severe instability, and the state grading result is obtained; Performing trend analysis on the state level classification results, calculating the transition probability and expected transition time from the current state level to the next level, identifying early warning signals of the system approaching a critical instability state, and obtaining state evolution prediction data; The state level classification results and state evolution prediction data are comprehensively processed to generate a complete diagnosis report including the current abnormality level, stability evaluation and development trend prediction, and obtain the avoidance zone state diagnosis result.

[0054] The following is a detailed description of the steps involved in the above embodiment: The system state quantitative indicators are calculated based on the comprehensive coupling strength index and phase correlation parameters in the coupling correlation feature data. The specific implementation process includes two core calculation steps. The geometric symmetry deviation is calculated by dividing the avoidance zone plan into two parts, left and right, using the centerline as the boundary. The comprehensive coupling strength values ​​on the left and right sides at the same coordinate position are extracted and compared. The geometric symmetry deviation refers to the degree of difference between the actual measured symmetry and the ideal symmetry state. The calculation formula is: Deviation = |(left value - right value) / (left value + right value) × 2| × 100%. For example, if the comprehensive coupling strength at a location on the left is 0.8 and the corresponding location on the right is 0.7, the deviation is |(0.8-0.7) / (0.8+0.7) × 2| × 100% = 6.7%. The timing stability index is calculated by analyzing the temporal fluctuation of the phase correlation parameter: the phase difference values ​​of 10 consecutive pulse cycles are selected, and the average and standard deviation of these 10 values ​​are calculated. The standard deviation divided by the average value is the timing stability coefficient. The system status quantification index includes a percentage value for the geometric symmetry deviation and a temporal stability coefficient. Together, these two indicators reflect the health of the electrochemical system in the avoidance zone. This dual-index quantification method transforms complex electrochemical states into concrete numerical descriptions, eliminating the subjectivity of qualitative judgments.

[0055] The system's abnormality classification criteria are determined based on quantitative indicators of the system's status. Specifically, numerical cutoff points are set based on the avoidance zone design specifications and process requirements. Symmetry benchmark characteristics are obtained by measuring the avoidance zone's design drawings. Ideally, the deviation should be 0%. The numerical interval is divided using an arithmetic division method: the deviation range of 0%-60% is evenly divided into four segments: 0%-15% for normal stability, 15%-30% for mild deviation, 30%-45% for moderate imbalance, and 45%-60% for severe instability. The temporal stability coefficient is similarly divided into four levels: 0%-0.1 for high stability, 0.1-0.2 for moderate stability, 0.2-0.3 for low stability, and >0.3 for instability. The final classification is determined using a dual-indicator approach: when either the geometric deviation or the temporal stability indicator reaches a certain level, the system status is determined to be that level. For example, if the geometric deviation at a certain moment is 20% and the temporal stability coefficient is 0.15, the geometric deviation corresponds to a mild deviation level, and the temporal stability corresponds to a moderate stability level, ultimately resulting in a mild deviation level. The cutoff points of 15%, 30%, and 45% are set based on the thickness uniformity requirements of the electroplating industry quality standards. The status grading results are recorded in digital code form, with 1 representing normal stability, 2 representing mild deviation, 3 representing moderate imbalance, and 4 representing severe instability. This grading method based on process requirements ensures consistency between the grading standards and actual production quality requirements.

[0056] Trend analysis of the state classification results is performed using a statistical calculation based on the level change history of the last 20 pulse cycles. Transition probability is calculated using a frequency statistics method: the number of occurrences of the current level in the historical data is counted, and the number of transitions to the next level is then divided by the two to obtain the transition probability. For example, if there were eight occurrences of the mild deviation level in the last 20 cycles, and two of these transitions to the moderate imbalance level in the next cycle, the transition probability is 2 / 8 = 25%. The expected transition time is calculated by averaging the time intervals between all historical transitions from the current level to the next level and calculating the average interval. Warning signals for critical instability are identified based on two criteria: a transition probability exceeding 40% or an expected transition time of less than three pulse cycles. The 40% probability threshold is determined based on a 0.05 confidence level for statistical significance testing, and the three-cycle threshold is based on the minimum response time for pulse plating process adjustments. State evolution prediction data includes specific probability percentages, expected number of cycles, and warning level indicators. The warning levels are divided into three levels: green warning (transition probability less than 20%), yellow warning (transition probability 20%-40%), and red warning (transition probability greater than 40%). This trend prediction method based on historical statistics exploits the regularity of electrochemical system state changes and enables quantitative prediction of future state evolution.

[0057] The state classification results and state evolution prediction data are integrated to generate a diagnostic report. This process involves integrating all analysis results according to a pre-set report template. This integration utilizes an information aggregation method: the current state level, quantitative indicator values, transition probability, expected time, and warning level are arranged and combined in a fixed format. A complete diagnostic report consists of four information modules: the first module provides a current state description, directly displaying the level code and the corresponding geometric deviation and temporal stability values; the second module provides a stability evaluation, generating an evaluation statement based on the values ​​of the two indicators; the third module provides a development trend prediction, displaying the transition probability, expected time, and warning level; and the fourth module provides action recommendations, automatically generating corresponding action recommendations based on the warning level. For example, a red warning level corresponds to "immediately stop the current batch and check the equipment status," a yellow warning corresponds to "increase monitoring frequency and prepare to adjust parameters," and a green warning corresponds to "maintain current process parameters and continue monitoring." The avoidance zone state diagnosis results are output in a standardized table format, with each row corresponding to an information item and each column corresponding to a specific value or description. Report generation utilizes an automated template-filling process to reduce manual intervention and subjective judgment. This standardized report generation approach ensures the integrity and consistency of diagnostic information and provides operators with clear and unambiguous decision-making guidance.

[0058] Reference Figure 2 The present invention provides a pulse plating device, comprising: The electrochemical stress gradient detection module is used to synchronously collect transient current density data between the anode component, the shunt component, and the cathode component within the time window when the forward pulse switches to the reverse pulse of the pulse electroplating, calculate the first-order time derivative and the second-order time derivative of the current density ratio between the three components, and obtain electrochemical stress gradient data; A stress anomaly propagation trajectory tracking module is used to perform spatiotemporal correlation analysis on the electrochemical stress gradient data of multiple consecutive pulse cycles, track the spatial position change and evolution trend of the stress gradient anomaly, and obtain stress anomaly propagation trajectory data; An impedance sensitivity distribution detection module is used to slightly modulate the current density in the forward pulse steady-state section according to the key monitoring area determined by the stress anomaly propagation trajectory data, synchronously monitor the potential response changes of the three-electrode system, calculate the ion migration impedance sensitivity coefficient, and obtain impedance sensitivity distribution data; a multi-dimensional coupling analysis module for performing multi-dimensional coupling analysis on the electrochemical stress gradient data, stress anomaly propagation trajectory data, and impedance sensitivity distribution data, identifying the temporal correlation characteristics between stress evolution and ion migration anomalies, and obtaining coupling correlation characteristic data; The state diagnosis and evaluation module is used to quantitatively evaluate the electrochemical state of the avoidance zone of the shunt component based on the coupling correlation characteristic data, determine the abnormality level, and obtain the avoidance zone state diagnosis result.

[0059] It should be noted that the pulse plating device provided in the embodiment of the present invention is used to execute all the process steps of the pulse plating detection method of the above embodiment. The working principles and beneficial effects of the two correspond one to one, so they will not be repeated here.

[0060] An embodiment of the present invention further provides a schematic structural diagram of a pulse plating device. The pulse plating device 200 may vary significantly due to different configurations or performance, and may include one or more processors 210 (e.g., one or more processors) and a memory 220, and one or more storage media 230 (e.g., one or more mass storage devices) storing application programs 233 or data 232. The memory 220 and storage medium 230 may be either short-term or persistent storage. The program stored in the storage medium 230 may include one or more modules (not shown), each of which may include a series of instruction operations on the pulse plating device 200. Furthermore, the processor 210 may be configured to communicate with the storage medium 230, and execute the series of instruction operations in the storage medium 230 on the pulse plating device 200 to implement the steps of the above-mentioned pulse plating detection method.

[0061] The pulse plating device 200 may further include one or more power supplies 240, one or more wired or wireless network interfaces 250, one or more input and output interfaces 260, and / or one or more operating systems 231, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. It will be understood by those skilled in the art that Figure 3 The structure of the pulse plating equipment shown does not constitute a limitation on the pulse plating equipment provided by the present invention, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0062] The specific embodiments described above further illustrate the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A detection method for pulse plating, characterized in that: include: During the time window from the forward pulse to the reverse pulse of the pulse plating process, the transient current density data between the anode component, the shunt component, and the cathode component are synchronously collected. The first-order time derivative and the second-order time derivative of the current density ratio between the three components are calculated to obtain the electrochemical stress gradient data. Performing spatiotemporal correlation analysis on the electrochemical stress gradient data of multiple consecutive pulse cycles to track the spatial position change and evolution trend of stress gradient anomalies and obtain stress anomaly propagation trajectory data; Based on the key monitoring area determined by the stress anomaly propagation trajectory data, the current density is slightly modulated in the steady-state section of the forward pulse, the potential response change of the three-electrode system is synchronously monitored, the ion migration impedance sensitivity coefficient is calculated, and the impedance sensitivity distribution data is obtained; Performing multi-dimensional coupling analysis on the electrochemical stress gradient data, stress anomaly propagation trajectory data, and impedance sensitivity distribution data to identify the temporal correlation characteristics between stress evolution and ion migration anomalies, and obtain coupling correlation characteristic data; Based on the coupling correlation characteristic data, the electrochemical state of the avoidance zone of the shunt component is quantitatively evaluated, the abnormality level is determined, and the avoidance zone state diagnosis result is obtained.

2. The pulse plating detection method according to claim 1, wherein: The method comprises: synchronously collecting transient current density data between the anode component, the shunt component, and the cathode component within the time window when the forward pulse of the pulse electroplating is switched to the reverse pulse, calculating the first-order time derivative and the second-order time derivative of the current density ratio between the three components, and obtaining electrochemical stress gradient data, including: During the period when the forward pulse switches to the reverse pulse, the transient current density data of the anode assembly, the shunt assembly and the cathode assembly are synchronously acquired, and the current density ratios between the anode assembly and the shunt assembly, the anode assembly and the cathode assembly, and the shunt assembly and the cathode assembly are calculated to obtain the three-electrode current density ratio data; Calculating the first-order time derivative and the second-order time derivative of the three-pole current density ratio data respectively, judging the validity of each derivative data based on the geometric symmetry of the avoidance zone, and screening out the effective derivative data reflecting the stress change; According to the stress change rate represented by the first-order derivative and the stress change acceleration represented by the second-order derivative in the effective derivative data, the spatial distribution parameters of the stress gradient at the boundary of the avoidance zone are calculated to obtain electrochemical stress gradient data.

3. The detection method for pulse plating according to claim 2, wherein: The first-order time derivative and the second-order time derivative of the three-pole current density ratio data are calculated respectively, the validity of each derivative data is judged based on the geometric symmetry of the avoidance zone, and the effective derivative data reflecting the stress change are screened out, including: Performing numerical differentiation operations on each ratio sequence in the three-pole current density ratio data, calculating the first-order time derivative and the second-order time derivative of the anode-shunt component ratio, the anode-cathode component ratio, and the shunt-cathode component ratio, to obtain a derivative data matrix; A symmetry evaluation benchmark is established based on the central symmetry axis and mirror symmetry plane of the avoidance zone's geometric boundary. The degree of deviation of each derivative data relative to the symmetry benchmark is calculated, and abnormal derivative values ​​that violate the geometric symmetry constraints are identified to obtain a symmetry screening mark. According to the symmetry screening identifier, derivative data that meets the geometric symmetry requirements are retained, and non-physical derivative values ​​generated by current noise or system disturbances are eliminated to obtain effective derivative data reflecting stress changes.

4. The detection method of pulse plating according to claim 1, characterized in that: The temporal and spatial correlation analysis of the electrochemical stress gradient data of multiple consecutive pulse cycles is performed to track the spatial position change and evolution trend of the stress gradient anomaly to obtain the stress anomaly propagation trajectory data, including: The electrochemical stress gradient data of a plurality of consecutive pulse cycles are arranged in a time series, the deviation degree of the stress gradient of each cycle is calculated based on the symmetry benchmark of the geometric boundary of the avoidance zone, and the stress gradient abnormal points whose deviation degree exceeds a preset range are identified to obtain time series stress abnormality identification data; According to the spatial distribution position of the abnormal points in the time series stress anomaly identification data, combined with the geometric constraints of the avoidance zone boundary, the spatial displacement law of the abnormal points between adjacent pulse cycles is analyzed, the direction vector and propagation speed of the abnormal propagation are calculated, and the stress anomaly spatial propagation parameters are obtained; Based on the stress anomaly spatial propagation parameters, the movement path of the anomaly point in the avoidance zone is tracked, the residence phenomenon of the stress anomaly at the geometric corner and the acceleration phenomenon at the straight line boundary are identified, and the geometric constraint propagation characteristic data is obtained; The geometric constraint propagation characteristic data is combined with the pulse time beat to reconstruct the complete motion trajectory of the stress anomaly in the time-space two-dimensional coordinate system, predict the propagation trend and arrival area of ​​the stress anomaly, and obtain the stress anomaly propagation trajectory data.

5. The detection method of pulse plating according to claim 4, characterized in that: The method of tracking the movement path of the abnormal point in the avoidance zone based on the stress anomaly spatial propagation parameter, identifying the residence phenomenon of the stress anomaly at the geometric corner and the acceleration phenomenon at the straight line boundary, and obtaining geometric constraint propagation feature data includes: According to the direction vector and propagation velocity data in the stress anomaly spatial propagation parameter, the motion trajectory and velocity distribution of the abnormal point at each spatial position in the avoidance zone are calculated, the geometric path characteristics of the trajectory are identified, and the motion trajectory data of the abnormal point is obtained; Performing geometric partition analysis on the motion trajectory data of the outlier point to distinguish the difference in motion characteristics when the outlier point is located in the geometric corner area and the straight boundary area of ​​the avoidance zone, calculating the speed attenuation coefficient of the corner area and the speed growth coefficient of the straight area, and obtaining the partition motion characteristic parameters; Based on the partitioned motion characteristic parameters, the residence accumulation effect of stress anomalies in the corner area and the propagation acceleration effect in the straight area are identified, the residence time and the acceleration multiple are quantified, and the geometric constraint propagation characteristic data are obtained.

6. The detection method of pulse plating according to claim 1, characterized in that: The key monitoring area determined according to the stress anomaly propagation trajectory data is subjected to slight modulation of the current density in the forward pulse steady-state section, the potential response change of the three-electrode system is synchronously monitored, and the ion migration impedance sensitivity coefficient is calculated to obtain impedance sensitivity distribution data, including: Based on the predicted arrival position and residence area distribution of the stress anomaly in the stress anomaly propagation trajectory data, combined with the curvature distribution characteristics of the geometric boundary of the avoidance zone, the high probability area of ​​stress concentration is identified, the spatial position of the key monitoring area is determined, and the monitoring area positioning data is obtained; In the middle time window of the forward pulse steady-state segment, a modulation strategy is determined according to the positioning data of the monitoring area, the overall current density is periodically slightly modulated, and the modulation amplitude and frequency parameters are adjusted to enhance the response sensitivity of the target area to obtain optimized modulation parameters; Based on the optimized modulation parameters, the potential response data of the anode component, the shunt component and the cathode component in the modulation state are synchronously collected, and the ratio of the potential response amplitude of each component to the modulation amplitude and the phase difference between the response and the modulation are calculated to obtain the three-electrode potential response characteristic data; The regional difference analysis of the three-pole potential response characteristic data is performed, and the response amplitude ratio of each monitoring area is weighted according to the geometric curvature distribution of the avoidance zone to obtain the sensitivity coefficient distribution reflecting the change of local ion migration impedance, thereby forming impedance sensitivity distribution data.

7. The detection method of pulse plating according to claim 1, characterized in that: The electrochemical stress gradient data, stress anomaly propagation trajectory data, and impedance sensitivity distribution data are subjected to multi-dimensional coupling analysis to identify the temporal correlation characteristics between stress evolution and ion migration anomalies, and obtain coupling correlation characteristic data, including: The electrochemical stress gradient data, stress anomaly propagation trajectory data, and impedance sensitivity distribution data are time-series aligned according to the pulse cycle time scale, and a corresponding relationship between the three types of data under the same time reference is established to obtain a time-series synchronized data matrix; Performing a correlation analysis on the stress gradient change and the impedance sensitivity change in the time-series synchronization data matrix, calculating the time delay parameter and correlation strength coefficient between the two, identifying the phase difference characteristics of the stress evolution leading the ion migration anomaly, and obtaining the phase correlation parameter; According to the phase correlation parameters combined with the spatial information of the stress anomaly propagation trajectory, the spatial distribution law of the phase difference at each key node on the stress propagation path is analyzed, the distribution pattern of the phase difference changing with the geometric position is identified, and the spatiotemporal coupling characteristic data is obtained; Based on the spatiotemporal coupling characteristic data, a comprehensive coupling strength index between stress evolution and ion migration anomaly is calculated, and the system stability state is divided according to the numerical range of the coupling strength to obtain coupling correlation characteristic data.

8. The pulse plating detection method according to claim 1, wherein: The quantitative evaluation of the electrochemical state of the avoidance zone of the shunt component based on the coupling correlation characteristic data, determining the abnormality level, and obtaining the avoidance zone state diagnosis result includes: Based on the comprehensive coupling strength index and phase correlation parameter in the coupling correlation characteristic data, the geometric symmetry deviation and temporal stability index of the electrochemical system in the avoidance zone are calculated to obtain a quantitative index of the system state; Based on the system state quantitative index combined with the symmetry benchmark characteristics of the avoidance zone geometric boundary, the abnormality degree grading judgment standard is determined by dividing the numerical interval of the quantitative index, and the electrochemical state of the avoidance zone is divided into four levels: normal stability, slight deviation, moderate imbalance and severe instability, and the state grading result is obtained; Performing trend analysis on the state level classification results, calculating the transition probability and expected transition time from the current state level to the next level, identifying early warning signals of the system approaching a critical instability state, and obtaining state evolution prediction data; The state level classification results and state evolution prediction data are comprehensively processed to generate a complete diagnosis report including the current abnormality level, stability evaluation and development trend prediction, and obtain the avoidance zone state diagnosis result.

9. A pulse plating device, characterized in that: The pulse plating device comprises: The electrochemical stress gradient detection module is used to synchronously collect transient current density data between the anode component, the shunt component, and the cathode component within the time window when the forward pulse switches to the reverse pulse of the pulse electroplating, calculate the first-order time derivative and the second-order time derivative of the current density ratio between the three components, and obtain electrochemical stress gradient data; A stress anomaly propagation trajectory tracking module is used to perform spatiotemporal correlation analysis on the electrochemical stress gradient data of multiple consecutive pulse cycles, track the spatial position change and evolution trend of the stress gradient anomaly, and obtain stress anomaly propagation trajectory data; An impedance sensitivity distribution detection module is used to slightly modulate the current density in the forward pulse steady-state section according to the key monitoring area determined by the stress anomaly propagation trajectory data, synchronously monitor the potential response changes of the three-electrode system, calculate the ion migration impedance sensitivity coefficient, and obtain impedance sensitivity distribution data; a multi-dimensional coupling analysis module for performing multi-dimensional coupling analysis on the electrochemical stress gradient data, stress anomaly propagation trajectory data, and impedance sensitivity distribution data, identifying the temporal correlation characteristics between stress evolution and ion migration anomalies, and obtaining coupling correlation characteristic data; The state diagnosis and evaluation module is used to quantitatively evaluate the electrochemical state of the avoidance zone of the shunt component based on the coupling correlation characteristic data, determine the abnormality level, and obtain the avoidance zone state diagnosis result.

10. A pulse plating device, characterized in that, The pulse plating device includes: a memory and at least one processor, wherein instructions are stored in the memory; The at least one processor calls the instructions in the memory to enable the pulse plating equipment to perform the steps of the pulse plating detection method according to any one of claims 1 to 8.

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