A copper strip performance detection device and detection method

Abstract

The present application relates to copper strip performance on-line detection technical field, it is a kind of copper strip performance detection device and detection method, specific method includes: through the temperature, thickness and the multi-frequency eddy current response of synchronous acquisition copper strip each detection section, after aligning according to material position, whether it is in limited thickness influence area is judged according to real-time temperature calculation eddy current penetration depth and combined with measured thickness;For non-influence area, conductivity is calculated according to temperature compensation, and the conductivity of influence area is calculated by using multi-frequency eddy current response inversion and consistency check;Then combine the lift-off distance to calculate the thickness coupling correction amount, export conductivity or mark isolation zone after double criterion of conductivity accuracy and detection confidence level.The scheme effectively strips the interference of thickness fluctuation on conductivity detection, improves detection accuracy and confidence.The present application solves the problem that the eddy current detection misjudges the conductivity due to the coupling of temperature and thickness fluctuation of finish rolling copper strip in the prior art.

Description

Technical Field

[0001] This invention relates to the field of online copper strip performance testing technology, and is a copper strip performance testing device and testing method. Background Technology

[0002] After finishing rolling, copper strip needs to undergo conductivity testing to determine whether the product performance is up to standard. Industrially, the eddy current method is commonly used for online conductivity testing. This method utilizes an excitation coil to induce eddy currents on the surface of the copper strip, and the conductivity information is indirectly obtained by receiving changes in the secondary magnetic field through a detection coil. During finishing rolling, the temperature of the copper strip is not constant along its length, but is affected by factors such as changes in rolling speed, fluctuations in coolant flow, and the accumulation of deformation heat, resulting in a continuously fluctuating temperature distribution. The conductivity of copper decreases as the temperature increases and increases as the temperature decreases; therefore, the eddy current signal itself already includes the conductivity fluctuations caused by temperature. Simultaneously, the thickness of the finished copper strip is affected by factors such as roll eccentricity, bearing wear, tension fluctuations, and roll thermal expansion, exhibiting micron-level fluctuations along its length. The eddy current penetration depth is directly related to the material's conductivity; temperature changes the conductivity... The penetration depth is also altered by the conductivity. When the copper strip thickness and penetration depth are comparable, the eddy current reaches the back of the copper strip before it has fully decayed and is reflected. The reflected signal is superimposed on the signal received by the probe, causing the measurement result to include both conductivity and thickness components. Existing detection methods typically assume that the thickness is large enough and only perform temperature compensation, or statically judge whether the detection conditions are met based on the target thickness, without considering the dynamic changes in penetration depth caused by different temperatures in different sections of the same roll of copper strip. This makes the degree of interference of thickness fluctuations on conductivity detection vary with temperature fluctuations. As a result, it is impossible to distinguish whether the impedance change is caused by a real change in conductivity or by thickness fluctuations, and it is easy to mistakenly attribute the signal response caused by thickness fluctuations to conductivity anomalies, leading to misjudgment. The above problems are particularly prominent in the high-speed continuous production of precision rolled copper strip. Summary of the Invention

[0003] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0004] The technical problem to be solved by the present invention is that the conductivity of fine-rolled copper strip is misjudged by eddy current testing due to the coupling of temperature and thickness fluctuations in the prior art. The present invention proposes a copper strip performance testing device and testing method.

[0005] To achieve the above objectives, the present invention provides a method for testing the performance of copper strips, comprising the following specific steps: Based on the material location, the temperature, thickness, lift-off distance and multi-frequency eddy current response of each detection section of the copper strip are collected simultaneously to obtain the detection data with position alignment; The eddy current penetration depth is calculated based on the detection data and combined with the measured thickness to determine whether the detection section is in the finite thickness influence zone. Based on the judgment result, the real-time conductivity is calculated for the non-influence zone according to the correspondence between temperature and conductivity. For the influence zone, the conductivity is jointly inverted using the eddy current response under at least two excitation frequencies. The consistency of the inversion results is verified to obtain the real-time conductivity and detection status mark of each detection section. The thickness coupling conductivity correction is calculated based on the real-time conductivity, measured thickness, and lift-off distance to obtain the correction data for each detection section. Based on real-time conductivity, correction data, and detection status markers, conductivity accuracy criteria and detection confidence criteria are executed. When a detection segment meets both criteria, conductivity is output; when a detection segment does not meet both criteria, it is marked as an isolation area. Finally, the conductivity detection results for each detection segment of the copper strip are obtained.

[0006] Furthermore, before determining whether the detection section is in the finite thickness influence zone, the penetration depth is corrected based on the deviation between the real-time lift-off distance and the reference lift-off distance. Then, the corrected penetration depth is combined with the measured thickness to determine whether the detection section is in the finite thickness influence zone.

[0007] Furthermore, based on the deviation rate between the measured thickness and the target thickness of each detection section, thick strips, thin strips, or normal thickness sections are marked to form thickness distribution labels; a first excitation frequency and a second excitation frequency are selected based on the differences in thickness distribution labels, with lower frequency combinations used for thin strips and normal thickness sections, and higher frequency combinations used for thick strips; the excitation frequency corresponding to the thickness distribution label is used when calculating the eddy current penetration depth.

[0008] Furthermore, the joint inversion is achieved through a pre-established joint calibration model of standard copper sheets. Establishing the joint calibration model includes: preparing a set of standard copper sheets covering the conductivity range, thickness range, and temperature range of the copper strip to be tested; stabilizing the standard copper sheets at multiple temperature points while maintaining a constant lift-off distance; collecting the eddy current amplitude and phase at at least two excitation frequencies to form a calibration data point set; establishing a multidimensional lookup table based on the calibration data; and solving for the conductivity during online inversion using temperature, thickness, amplitude, and phase as inputs through an iterative approximation-residual minimization algorithm.

[0009] Furthermore, the consistency verification includes: independently inverting conductivity using each excitation frequency and calculating the deviation of the inversion results for each frequency; when the deviation is less than the calibrated allowable deviation, taking the average value of the inversion results for each frequency as the real-time conductivity; when the deviation is greater than or equal to the calibrated allowable deviation, marking the detection segment as an inversion inconsistency area and not outputting conductivity.

[0010] Furthermore, when calculating the thickness coupling conductivity correction, the dynamic penetration depth is first calculated based on the real-time conductivity, and the finite thickness influence index is calculated in combination with the measured thickness; then the thickness coupling conductivity correction is calculated based on the finite thickness influence index, the real-time lift-off distance, and the thickness of the detection section.

[0011] Furthermore, before executing the conductivity accuracy criterion and the detection confidence criterion, adjacent detection segments with consistent thickness distribution labels are merged into a detection interval; the average real-time conductivity of the detection interval and the maximum thickness coupling conductivity correction are used as inputs to execute the conductivity accuracy criterion and the detection confidence criterion; the detection interval that meets both criteria outputs the conductivity, otherwise it is marked as an isolation area.

[0012] Furthermore, the generation method of the detection status mark includes: marking the detection section as a detection condition unmet area or a normal detection area based on the comparison results of real-time conductivity and conductivity qualified threshold, real-time temperature and temperature calibration threshold, and inversion consistency status.

[0013] Furthermore, when determining the optimal detection window, the inflection point of the rate of change of conductivity and the finite thickness influence index is monitored. The moment when the rate of change of conductivity changes from negative to positive and the finite thickness influence index changes from decreasing to stabilizing is determined as the optimal detection window; the conductivity output within the optimal detection window has the highest reliability.

[0014] In addition, the copper strip performance testing device of the present invention includes the following components: Data acquisition component, penetration detection component, calculation component, and judgment component; The acquisition component is used to synchronously acquire the temperature, thickness, lift-off distance and multi-frequency eddy current response of each detection section of the copper strip based on the material position, so as to obtain position-aligned detection data; The penetration judgment component is used to calculate the eddy current penetration depth based on the detection data and combine it with the measured thickness to determine whether the detection section is in the finite thickness influence zone. Based on the judgment result, the real-time conductivity of the non-influence zone is calculated according to the correspondence between temperature and conductivity. For the influence zone, the conductivity is jointly inverted using the eddy current response under at least two excitation frequencies. The consistency of the inversion results is verified to obtain the real-time conductivity and detection status mark of each detection section. The calculation component is used to calculate the thickness coupling conductivity correction amount based on the real-time conductivity, measured thickness and lift-off distance, and obtain the correction amount data for each detection section; The determination component is used to perform conductivity accuracy criteria and detection confidence criteria based on real-time conductivity, correction data and detection status markers. When the detection segment meets both criteria, the conductivity is output. When the detection segment does not meet both criteria, it is marked as an isolation area. Finally, the conductivity detection results of each detection segment of the copper strip are obtained.

[0015] Compared with existing technologies, this invention simultaneously acquires the measured temperature and thickness of the same material location in the copper strip, dynamically calculates the eddy current penetration depth and determines the finite thickness influence zone, performs temperature compensation for the non-influence zone, and uses multi-frequency joint inversion for the influence zone. This effectively eliminates the interference of thickness fluctuations on conductivity detection and avoids the problem of misjudging thickness changes as conductivity anomalies. At the same time, the joint calibration model and multi-frequency consistency verification ensure the reliability of the inversion results, and the dual criteria and isolation mechanism further avoid the output of unreliable data. This improves the accuracy and confidence of online conductivity detection of precision rolled copper strip, and reduces the misjudgment rate and offline re-inspection cost. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a schematic diagram illustrating the steps of a copper strip performance testing method according to the present invention; Figure 2 This is a schematic diagram of the overall process of a copper strip performance testing method according to the present invention; Figure 3 This is a schematic diagram of the functional components of a copper strip performance testing device according to the present invention. Detailed Implementation

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0018] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0019] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0020] Example 1: like Figure 1 , 2As shown, an embodiment of the present invention provides a method for testing the performance of copper strips, comprising the following steps: S1. Collect temperature signals, eddy current multi-frequency response signals, online thickness signals, and lift-off distance signals along the length of the copper strip to obtain basic parameters of the copper strip material and generate thickness distribution labels; S110. Based on the material location of the copper strip production line, the unit is divided into detection sections, and the temperature signal timing data, eddy current multi-frequency response signal timing data, online thickness timing data and lift-off distance timing data of each section are collected simultaneously. In this embodiment, the copper strip is first divided into equal-length detection sections along the direction of copper strip movement, based on the material position determination unit (encoder cumulative length). It should be noted that, in this embodiment, the length of each detection segment is set to be... The division of the detection zone is triggered by the cumulative number of encoder pulses, which is independent of the rolling speed, ensuring that the data of the same material position under different sensors are strictly aligned. Then upstream of the eddy current conductivity detection unit A non-contact infrared temperature sensing unit is installed at one location to collect the surface temperature of the copper strip; upstream of the eddy current conductivity detection unit... An online thickness detection unit is installed, using an X-ray thickness gauge or a laser thickness gauge to collect the actual thickness of the copper strip; the eddy current conductivity detection unit includes a multi-frequency eddy current probe, which simultaneously collects the amplitude and phase response at at least two excitation frequencies; a non-contact laser displacement sensor is installed directly below the eddy current probe and coaxially with the probe axis to directly measure the real-time lift-off distance between the probe end face and the copper strip surface; if coaxial installation is not possible, the difference between the side and the direct below must be compensated through calibration.

[0021] It should be noted that in this embodiment, all sensing units synchronously sample via a high-speed data acquisition device, and the sampling frequency is set to: temperature ,thickness eddy current response RMS value Lifting distance The original sampling frequency for thickness is... Before subsequent processing, samples were uniformly downsampled to... The downsampling method uses an arithmetic mean within a 20ms time window to keep the time synchronized with the temperature, eddy current response and lift-off distance signals.

[0022] S120. Obtain the basic material parameters of the target copper strip, including grade, reference conductivity, temperature coefficient of resistance, magnetic permeability, and reference lift-off distance. For example, in this embodiment, the grade is specified by the production plan, such as T2 copper, H62 brass, etc.; the reference conductivity For this brand name in The standard conductivity can be obtained by actual measurement using the four-probe method according to GB / T32791 or ASTM E1004 standards, or an industry-standard value can be used; the temperature coefficient of resistance... For this grade of copper material The temperature coefficient of resistance in the vicinity; the permeability Take the approximate permeability of copper, and for nonferromagnetic materials take... .

[0023] It should be noted that, in this embodiment, the reference conductivity... The value is (Corresponding to T2 copper, IACS 100%); Temperature coefficient of resistance The value is ; Baseline lift-off distance The standard lift-off distance for eddy current probe installation and calibration is taken in this embodiment. The value is set based on the following: In online eddy current testing of copper strips, the typical working distance between the probe and the surface of the copper strip is usually within [a certain range]. Between, take As an intermediate benchmark, it can cover lift fluctuations under normal operating conditions and is easy to calibrate and correct.

[0024] S130. Based on the deviation rate of the actual thickness of each detection section relative to the target thickness, mark the detection section as a thick strip section, a thin strip section, or a normal thickness section to form a thickness distribution label. First, based on the online thickness time-series data of each detection segment, the arithmetic mean of the thickness data within each detection segment is taken as the average thickness of that segment. Target thickness This refers to the target thickness value specified in the process card for this batch of copper strip products. (Based on the target thickness...) Based on this, define the thickness deviation rate: ; When setting the thickness deviation rate threshold, the standard deviation of the thickness deviation rate sample of all tested sections in the historical qualified batches of the same process is taken. ,Pick As a base threshold, and setting the absolute value of the threshold. Upper and lower limit constraints.

[0025] It should be noted that the method for determining this thickness deviation rate threshold is as follows: when The value is less than (Right now When the final threshold is taken, ;when The value is greater than (Right now When the final threshold is taken, In other cases, take If no historical data is available, the threshold will be set to the default value. This embodiment sets the thickness deviation rate threshold based on the following criteria: In the precision rolling copper strip process, the thickness deviation is within... Within a certain range, fluctuations are considered normal and require no special marking; deviations exceeding a certain range are considered normal. When the thickness fluctuation is too high, it means that the condition of the rolls or the tension control may have deviated significantly from the normal range. The interference of thickness fluctuation on eddy current detection cannot be ignored and needs to be marked and processed separately. The intermediate range is adaptively determined based on the statistical fluctuation range of the historical data of the production line.

[0026] After determining the thickness deviation rate threshold, segments with an average thickness deviation rate greater than the positive threshold are marked as thick segments; segments with an average thickness deviation rate less than the negative threshold are marked as thin segments; and the remaining segments are marked as normal thickness segments. Finally, the thickness distribution label for each detection segment is output, and this label corresponds one-to-one with the position bound in S110.

[0027] It should be noted that this step statically classifies the thickness fluctuations of the copper strip along its length, and the thickness distribution label reflects the direction and degree of deviation of the thickness of this section from the target thickness.

[0028] S2. Based on real-time temperature and measured thickness, the penetration state is dynamically calculated. Combined with the thickness distribution label, the detection strategy is selected to obtain the real-time conductivity of each section and perform multi-frequency consistency verification and detection condition determination.

[0029] S210. Calculate the initial value of current conductivity and initial value of penetration depth based on the real-time temperature of each detection section, and calculate the thickness penetration ratio in combination with the measured thickness to dynamically determine whether it is in the limited thickness influence zone. For example, in this embodiment, for each detection segment, the measured temperature at the current moment of the temperature signal time series data is taken. Using reference conductivity and temperature coefficient of resistance Calculate the initial value of conductivity at the current temperature: ; in, The initial conductivity; Real-time temperature; Next, the first excitation frequency is calculated from the initial conductivity. Initial penetration depth below: ;in, This represents the initial penetration depth. This is the first excitation frequency; For magnetic permeability; it should be noted that in this formula, conductivity is... International System of Units Substituting into the calculation, if... If expressed, then it needs to be multiplied by Convert and then substitute.

[0030] In this embodiment, the first excitation frequency The value is determined based on the differences in thickness distribution labels, specifically: for thick strip segments, the first excitation frequency... Pick For thin strip segments and normal thickness segments, the first excitation frequency... Pick The value of the first excitation frequency is determined based on the following settings: [The text abruptly shifts to a different topic] ...the thickness of the precision-rolled copper strip... Within the range, The penetration depth of the lower copper material is approximately Between these thicknesses, the thickness is comparable to that of copper strips, effectively distinguishing between the affected and unaffected areas of limited thickness; for thicker strip sections, [the following is used]. It can improve the detection sensitivity of changes in conductivity of thick bands, and at the same time increase the initial thickness penetration ratio to a certain extent. However, if Still smaller If the thickness is too small, it will still be treated as a finite thickness influence zone, which will not affect the applicability of subsequent multi-frequency joint inversion.

[0031] Then, take the measured thickness at the same time. Calculate the initial thickness penetration ratio This indicates that the current detection segment is at time [time]. The ratio of the measured thickness to the initial penetration depth is used to determine whether the section is within the finite thickness influence zone. ; Finally, a judgment is made, specifically as follows: when the initial thickness penetration ratio... If the value is greater than or equal to the judgment threshold, the detection segment is determined to be in the non-affected zone at the current moment; when the initial thickness penetration ratio If the depth is less than the threshold, the detection segment is determined to be in the finite thickness influence zone at the current moment. Output the initial penetration depth, initial thickness penetration ratio, and finite thickness influence zone determination result (finite thickness influence zone / non-influence zone) for each detection segment.

[0032] It should be noted that the judgment threshold in this embodiment is 2.6, which is set based on the following criteria: when the thickness of the copper strip reaches the penetration depth... At times, the eddy current attenuates to the surface amplitude before reaching the back of the copper strip. The contribution of the back-reflection signal to the probe impedance is lower than the noise level that the detection system can resolve, and can be considered as thickness fluctuation having no effect on the detection signal. Therefore, we take... This serves as the threshold for determining the influence zone of finite thickness.

[0033] This step dynamically determines whether each detection segment is currently within the finite thickness influence zone by using real-time temperature and measured thickness, overcoming the shortcomings of traditional methods that rely solely on static thickness judgment while ignoring the dynamic influence of temperature. Simultaneously, thickness distribution labels are used in this step to differentiate the excitation frequency, ensuring that the classification results truly participate in the calculation of the penetration state.

[0034] S220. Select the detection strategy based on the determination result of the finite thickness influence zone: For the non-influence zone, use the temperature compensation model to output the real-time conductivity; for the finite thickness influence zone, use multi-frequency response joint inversion to solve the real-time conductivity through iteration. The multi-frequency response joint inversion includes a joint inversion model, which in this embodiment is established through joint calibration using standard copper sheets; For example, in this embodiment, the selection logic of the detection strategy is as follows: for non-affected areas ( The eddy currents completely decay before reaching the back side, and thickness fluctuations have no effect on the eddy current response. The measured values ​​only reflect the conductivity of the copper strip itself, so the real-time conductivity is directly calculated using a temperature compensation model. ; For the finite thickness influence zone ( If the eddy current touches the air boundary before it has fully decayed, it will cause back reflection. The probe impedance contains both conductivity and thickness components, which cannot be distinguished by a single frequency. Therefore, at least two excitation frequencies are used. The amplitude and phase response of the eddy current under the given conditions are jointly inverted.

[0035] In this embodiment, the second excitation frequency The value is also determined based on the thickness distribution label differences, specifically: for thick strip segments, the second excitation frequency... Pick For thin strip segments and normal thickness segments, the second excitation frequency Pick The value of the second excitation frequency is determined as follows: the second frequency is selected as the first frequency. The penetration depth differs significantly between the two frequencies, and the sensitivity to thickness and conductivity also differs significantly, which is beneficial for multi-frequency response joint inversion to distinguish the two components. Furthermore, the aforementioned frequency values ​​are all within the conventional frequency range for copper strip eddy current detection, the probe design is mature, and the detection sensitivity is high. For thick strip sections, [the following applies]. The combination is because the thicker band has a larger thickness and a relatively smaller penetration depth. Using a higher frequency can improve the conductivity resolution and will not introduce back reflection interference.

[0036] The method for establishing the joint calibration model is as follows: (1) Preparation of standard copper sheet set: Specifically, select several standard copper sheets with metrologically confirmed conductivity to cover the conductivity range (e.g., IACS 90%–110%), thickness range (e.g., 0.05–0.20 mm, with at least 5 thickness points) and normal production temperature range (e.g., 20–80°C) of the copper strip to be tested. The surface condition of the standard copper sheets is consistent with that of the online copper strip, and the surface roughness is controlled within the specified range. .

[0037] (2) Calibration data acquisition, specifically: the standard copper sheet is stabilized at multiple calibration temperature points (e.g., 20, 30, 40, 50, 60, 70, 80°C). During calibration, the probe is raised and lowered using a precision micro-motion stage, and real-time closed-loop feedback adjustment is achieved using a laser displacement sensor to ensure that the distance between the probe and the surface of the standard copper sheet remains constant. And the deviation does not exceed Collect at least two excitation frequencies respectively , eddy amplitude and phase And record the known conductivity of the standard copper sheet. ,thickness and temperature Form a set of calibration data points: ; (3) Establish joint calibration relationships, specifically: establish an inversion model based on calibration data: ; This embodiment uses a multidimensional lookup table combined with linear interpolation to achieve positive response prediction. The calibration data is divided into grids according to three dimensions: temperature, thickness, and conductivity. Each grid node stores the corresponding amplitude and phase response.

[0038] (3a) The iterative approximation algorithm for conductivity inversion is as follows: The above multidimensional lookup table is only used for positive response prediction, by... Interpolation Online inversion of conductivity At that time, an iterative approximation-residual minimization algorithm is used. Specifically, with the initial conductivity... as initial value for iteration Substitute the values ​​into the lookup table and perform three-dimensional linear interpolation to obtain the result. Positive Predicted Response Define the residual objective function: ; in, This is the measured amplitude; This is the positive prediction amplitude; The full-range range of amplitude in the calibration data; This is the measured phase; Positive prediction phase; To determine the full-range range of phase in the calibration data, the Brent one-dimensional search algorithm is used. Perform iterative updates, when The iteration may terminate when the number of iterations exceeds 100, and the result at that point should be output. As a result of the joint inversion, the forward interpolation in this iterative process must ensure... All values ​​must be within the calibration grid boundary; otherwise, they will be directly judged as exceeding the calibration range, and the inversion will not be performed.

[0039] (4) Calibration area verification, specifically: using a verification copper sheet not included in the table construction, testing is performed under different temperature and thickness conditions, and the corrected conductivity is compared with the standard value. Only when the error meets the product testing requirements is the corresponding temperature-thickness-frequency region determined as a valid calibration area; areas that fail verification cannot be used for online automatic judgment, and the corresponding segments will be marked as exceeding the calibration range. It should be noted that, in this embodiment, the relative error threshold for calibration area verification is... The relative error threshold is set based on the following criteria: the industrial accuracy requirements for conductivity testing of precision-rolled copper strip are typically within... Within this range, the validation error of the calibration model is taken as... This is to allow for margins to accommodate other error sources in online inspection (such as temperature measurement error, thickness measurement error, lift-off fluctuation, etc.).

[0040] After establishing the joint calibration model, for the finite thickness influence zone, the inversion process employs iterative calculations: The first step is to calculate using S210. As the initial value of conductivity; The second step is to determine the thickness based on online measurements. Current temperature eddy current amplitude at two frequencies and phase The conductivity is solved using the iterative approximation-residual minimization algorithm in step (3a): ; The third step is to calculate the relative deviation between the results of two adjacent iterations. : ; when When the iteration converges, the output is... Otherwise, Then return to step two and continue iterating, with a maximum of 20 iterations.

[0041] It should be noted that this embodiment uses relative deviation. As the primary criterion for iterative convergence, the residual objective function This is used only as an internal search termination condition. If convergence is not achieved after the maximum number of iterations, the detection segment is marked as an inversion non-convergence region, and no conductivity value is output.

[0042] It should be noted that the joint calibration model It also supports a reduced-dimensional single-frequency query mode; when querying... At that time, the second frequency response parameter is fixed. The mean value in the grid is calibrated for the corresponding temperature and thickness, using only... Four-dimensional interpolation inversion. In this case, the objective function in the iterative approximation-residual minimization algorithm is replaced by a residual function containing only the first frequency component: ;in, This is the measured amplitude at the first frequency; This represents the positive predicted amplitude at the first frequency. The full-range range of the first frequency amplitude in the calibration data; The measured phase at the first frequency; This is the positive predicted phase at the first frequency; This is the full-range range of the first frequency phase in the calibration data. (Query) Similarly, the objective function contains only the second frequency component. The calibration region verification error of this dimensionality reduction query must also satisfy... This is a requirement; otherwise, no single-frequency consistency verification result will be provided for this region.

[0043] Output real-time conductivity time-series data for each detection segment. .

[0044] Based on the penetration status judgment results and thickness distribution labels, this step provides a low-complexity, high-real-time temperature compensation scheme for the non-affected area, and a multi-frequency joint inversion scheme for the affected area that can simultaneously distinguish the contributions of both conductivity and thickness components.

[0045] S230. Perform multi-frequency consistency verification on the inversion results of the affected area, and determine the testing conditions according to the effective range of the joint calibration table and the product standard, and mark the areas where the testing conditions are not met. In this embodiment, for the finite thickness influence region using multi-frequency joint inversion, the consistency of the inversion results at the two frequencies is verified; firstly, the multi-frequency consistency deviation is defined. : ; in, The conductivity obtained by inversion using only the first frequency, The conductivity is obtained by inversion using only the second frequency.

[0046] when Less than the calibration tolerance When the two frequency results are considered to be consistent, their average value is taken as the real-time conductivity output; when If the current detection state is determined to be outside the calibration range or the thickness data does not correspond correctly with the eddy current response, the detection section is marked as an inversion inconsistency zone and no conductivity value is output.

[0047] It should be noted that, in this embodiment, the allowable calibration deviation is... The value is The allowable deviation for this calibration is set based on the following criteria: conductivity. Within the acceptable range, Approximate correspondence The relative deviation should be consistent with the calibration area verification threshold. When the deviation between the inversion results of two frequencies exceeds this value, it indicates that the inversion result of at least one frequency is unreliable and should not be forced to output.

[0048] After completing the multi-frequency consistency verification, for each detection segment, if the real-time conductivity is less than the lower limit of the conductivity qualification threshold, or greater than the upper limit of the conductivity qualification threshold, or the real-time temperature exceeds the temperature calibration threshold range, or is marked as an inversion inconsistency area, inversion non-convergence area, or area exceeding the calibration range, the detection segment is uniformly marked as a detection condition non-compliance area, and the specific reason is noted in the status label; otherwise, it is marked as a normal detection area.

[0049] It should be noted that the conductivity qualification threshold is determined according to the target copper strip product standard, and its value range is as follows: to The temperature calibration threshold is determined based on the temperature range of the standard copper sheet established when the joint calibration table is created, and its value range is as follows: to Additionally, the acceptable conductivity threshold... The corresponding IACS for T2 copper is 95%–105%, which is a common conductivity qualification range in the product standards for precision-rolled copper strip; temperature calibration threshold. The temperature range is consistent with the calibration data acquisition range in S220. When the temperature exceeds this range, the calibration model does not have effective extrapolation capability.

[0050] Output the real-time conductivity time series data for each detection segment and the corresponding detection status markers (detection condition not met, inversion inconsistency, normal detection).

[0051] This step ensures that the output conductivity results are within the effective range of the calibration model and that the inversion results at each frequency are self-consistent through multi-frequency consistency verification and detection condition determination. This avoids erroneous output of inversion results that exceed the calibration range or have internal contradictions, thereby guaranteeing the credibility of the final output conductivity data.

[0052] S3. Based on the real-time conductivity, measured thickness, lift-off distance, and influence zone determination results of each section, a dynamic penetration depth is constructed through lift-off correction and thickness penetration weighting, and a finite thickness influence index is calculated. The optimal detection window is determined by monitoring the inflection point of conductivity change rate and the inflection point of finite thickness influence index. Then, combined with the finite thickness influence index and thickness distribution label, the thickness coupling conductivity correction amount of each section is calculated based on the physical characteristics of eddy current back reflection. S310. The lift-off correction adjusts the penetration depth according to the deviation between the real-time lift-off distance and the benchmark lift-off distance of each section. The larger the lift-off, the slightly smaller the penetration depth. The thickness penetration weighting determines the weighting factor according to the difference between the finite thickness influence zone and the non-influence zone. The influence zone amplifies the dynamic penetration depth. The two corrections are coupled to obtain the dynamic penetration depth and calculate the finite thickness influence index of each section. For example, in another embodiment, a dynamic penetration depth model for each detection segment is constructed using real-time conductivity time-series data, lift-off distance time-series data, and a reference lift-off distance as inputs. First, a correction based on the liftoff distance is performed, specifically including: defining the liftoff correction factor. This is used to reflect the effect of changes in the distance between the probe and the copper strip surface on the effective penetration depth of the eddy current. Increasing the lift-off distance slightly weakens the equivalent eddy current field and slightly reduces the effective penetration depth; decreasing the lift-off distance slightly increases the penetration depth. This embodiment uses a linear model: ; in, To remove the correction factor; For real-time distance lifting; The reference lift-off distance is set to a value in this embodiment. ; The preferred value for the sensitivity coefficient is [value to be filled in]. .

[0053] Then, a weighted correction based on the thickness penetration state is performed, specifically including: defining the thickness penetration weighting factor. This is used to reflect the difference in eddy current penetration behavior between the finite thickness affected zone and the unaffected zone. Finite thickness affected zone ( Because back reflection compresses the effective penetration depth, it is necessary to amplify and weight the penetration depth; non-affected areas ( Since the eddy currents do not reach the back side, the penetration depth is entirely determined by the electromagnetic properties of the material, and the weighting factor is set to 1. It should be noted that within the finite thickness influence zone, after the eddy currents reach the back side, due to changes in boundary conditions, the eddy current density at the back side no longer decays exponentially according to the infinite thickness of the material. Instead, due to reflection superposition, the equivalent attenuation constant decreases, resulting in an increased penetration depth. Therefore, an amplification factor greater than 1 is applied to the influence zone to restore the true equivalent penetration depth. In this embodiment: ; in, This is the thickness penetration weighting factor; The initial thickness penetration ratio calculated for S210; The magnification factor for the finite thickness influence zone is preferably set to a value of [value to be filled in]. .

[0054] Combining the two corrections mentioned above, the dynamic penetration depth is obtained by multiplying the initial penetration depth, the lift-off correction factor, and the thickness penetration weighting factor. ; After obtaining the dynamic penetration depth, the finite thickness influence index is calculated. , defined as the ratio of the current measured thickness to the dynamic penetration depth: ; in, The effect index is limited by thickness; For real-time thickness; This represents the dynamic penetration depth. The smaller the value, the thinner the thickness relative to the penetration depth, and the stronger the back reflection effect. The larger the value, the greater the thickness relative to the penetration depth, and the weaker the effect of back reflection.

[0055] This step corrects the initial penetration depth to a dynamic penetration depth that is closer to the actual detection conditions by lifting correction and thickness penetration weighting, thereby obtaining the finite thickness influence index and realizing the real-time quantification of the thickness coupling interference intensity.

[0056] S320: Real-time monitoring of the inflection point of the rate of change of conductivity in each section from negative to positive and the inflection point of the finite thickness influence index from decreasing to stabilizing. Combined with the conductivity qualification threshold, the optimal detection window is determined and the optimal detection time is recorded. In a preferred embodiment, the time-series data of the conductivity change rate and the time-series data of the finite thickness influence index for each detection segment are monitored in real time to identify the following two physical inflection points: The first inflection point is the moment when the conductivity change rate changes from a negative value to a positive value, indicating that the copper strip temperature changes from rising to falling, and the conductivity changes from falling to rising again, entering a relatively stable thermal state; the second inflection point is the moment when the finite thickness influence index changes from a continuous decrease to a stable state, indicating that the coupling degree between thickness and penetration depth no longer intensifies, entering a relatively stable state.

[0057] Rate of change of conductivity It is obtained from the first derivative of real-time conductivity with respect to time: ; in, For the first Rate of change of conductivity at each sampling point; In this embodiment, the sampling time interval is... The sampling frequency corresponding to the effective value of the eddy current response in S110 .

[0058] For the inflection point where the rate of change of conductivity changes from negative to positive, the following quantitative criterion is used: when continuous The inner value passes through zero from a negative value, and subsequently... When the value remains positive, this moment is considered the inflection point where the rate of change of conductivity changes from negative to positive. It should be noted that if this inflection point does not occur, an alternative stability criterion is used: when the absolute value of the rate of change of conductivity is below a certain value for 2 consecutive seconds... And the absolute value of the rate of temperature change is lower than 2 seconds for 2 consecutive seconds. When the temperature reaches a certain point, the thermal state is considered to have stabilized, equivalent to the appearance of an inflection point. This criterion is based on the following assumptions: the temperature change of the copper strip has thermal inertia, and the rate of change of conductivity does not change abruptly but is continuous. The process of penetrating zero and its aftermath A stable positive value can effectively filter out signal noise and instantaneous fluctuations.

[0059] For determining the inflection point of the influence index of finite thickness from decreasing to stabilizing, the sliding window method is used: taking the time when the target is to be determined as the node, the values ​​before that node are calculated. The average value of the finite thickness influence index (mean of the preceding descending window), and the value after this node. The average value of the influence index of the inner finite thickness (mean value of the subsequent stable value window); when the relative deviation of the two sets of means is less than If the following quantitative descent criteria are met, then the node is determined to be an inflection point of the finite thickness influence index. (The preceding data is taken as an example.) All inside Sampling points (500 points in total, corresponding to a 100Hz sampling rate), these points are analyzed with respect to time. A univariate linear regression yields the regression slope. .like (i.e., a relative slope decreasing by at least 0.1% per second) and the coefficient of determination for linear regression. (Indicating that the downward trend is statistically significant), then it is determined that the node before this point... The trend is continuously downward; otherwise, the prerequisite for an inflection point is not met.

[0060] When determining the optimal detection window, three conditions must be met simultaneously: The conductivity change rate of this section has reached an inflection point from negative to positive; the finite thickness influence index of this section has reached an inflection point from decreasing to stabilizing; and the real-time conductivity of this section is within the acceptable conductivity threshold range. When all three conditions are met, the detection section is determined to have entered the optimal detection window, and this moment is recorded as the optimal detection moment.

[0061] This step uses a dual inflection point determination to identify a time window in which the thermal state and coupling strength of the copper strip tend to be relatively stable. The conductivity results output within this window have the highest reliability, avoiding unstable data output during periods of drastic temperature changes or continuous increase in coupling strength.

[0062] S330. The interference intensity of thickness coupling on conductivity detection is quantified by the peak value of the finite thickness influence index, the contribution of lift-off fluctuation is quantified by the real-time lift-off distance, and the physical boundary of back reflection is quantified by the thickness of the detection section. Combined with the electromagnetic properties of the copper strip material, and based on the positive correlation between the peak value of the finite thickness influence index, the lift-off distance, the thickness of the detection section and the thickness coupling interference, the thickness coupling conductivity correction amount of the detection section is calculated. For example, in this embodiment, a thickness coupling conductivity correction amount is provided. The calculation strategy is as follows: ; in, This is a correction factor for the thickness-coupled conductivity. The coupling coefficient of the copper base; The minimum coupling value of the finite thickness influence index is the minimum value extracted from the time series data of the finite thickness influence index of this detection section (representing the moment of strongest coupling). To reference the finite thickness influence index, in this embodiment, its value is taken as 2.6; To determine the real-time lift-off distance, the average value of the time-series lift-off distance data within the detection section is taken. For reference, the lift-off distance is set to a value in this embodiment. ; The average thickness of the detection section; For reference thickness, in this embodiment, its value is [value to be filled in]. , which is the median value of the thickness of the precision-rolled copper strip.

[0063] It should be noted that the coupling coefficient of the copper foundation... This study characterizes the sensitivity of different copper alloys to eddy current back-side reflection interference with conductivity detection under the influence of finite thickness. The underlying physical principle is that higher material conductivity and lower magnetic permeability result in a larger proportion of back-side reflection signals and stronger coupling interference. This coefficient is determined using an industry-standard value method, preferentially obtained through eddy current response calibration experiments on standard copper sheets at different thicknesses and temperatures. When no actual measurement conditions are available, the industry-standard value for T2 copper is used in this embodiment. H62 brass The coupling coefficient of other grades of copper materials is calculated using the following formula: ; in, (Reference conductivity of T2 copper); .

[0064] For thick and thin strip segments, the thickness value By directly substituting the actual measured values, the thickness inverse factor in the formula for thickness-coupled conductivity correction automatically reflects the physical law that back-side reflection interference is stronger in thinner strips than in thicker strips. The calculated... If it exceeds Then take This serves as an upper limit; the basis for setting this upper limit is the physical limit of the interference of copper strip thickness fluctuations on conductivity detection. When the correction amount exceeds... At this point, it means that the test results for that section have deviated significantly from the true value, and further quantitative correction is no longer meaningful; the section should be isolated. It should be noted that this step, by comprehensively quantifying the three coupling factors of finite thickness influence index, lift-off distance, and thickness, provides a conductivity correction for thickness coupling interference, enabling subsequent conductivity accuracy criteria to be evaluated after correction, thus avoiding a coarse judgment based solely on the original inversion results.

[0065] S4. Using conductivity detection accuracy and detection confidence as dual criteria, combined with thickness distribution labels, optimal detection window judgment results and detection condition non-compliance area markers, a segmented dynamic judgment strategy for copper strip performance testing is generated.

[0066] S410. Merge adjacent detection segments with consistent thickness distribution labels into a detection interval. Use the arithmetic mean of the real-time conductivity of each segment constituting the detection interval as the average conductivity of the detection interval. Use the maximum value of the thickness coupling conductivity correction of each segment constituting the detection interval as the maximum correction amount of the detection interval. Use the correction of the average conductivity of the detection interval to be within the qualified range and the maximum correction amount of the detection interval to be lower than the allowable upper limit as dual criteria. Force isolation is required for areas that do not meet the detection conditions. Output effective conductivity results for detection intervals that meet the dual criteria. In a preferred embodiment, adjacent detection segments with the same thickness distribution label are first merged to obtain several detection intervals. Each detection interval contains only segments with the same thickness distribution label and serves as the smallest unit for subsequent judgment output. The finite thickness influence zone state of each detection segment is taken as the finite thickness influence zone judgment result of that segment at the optimal detection time (or the end time of that segment if no optimal detection time has been determined), which serves as the representative finite thickness influence zone state of that segment. The thickness distribution label and the representative finite thickness influence zone state together constitute a complete detection state label for differentiated judgment.

[0067] After merging the detection intervals, for each detection interval, the arithmetic mean of the real-time conductivity of all segments within the detection interval is calculated as the average real-time conductivity of that detection interval; the maximum value of the thickness coupling conductivity correction of all segments within the detection interval is taken as the maximum correction of that detection interval.

[0068] Next, the conductivity accuracy criterion is defined as follows: the average real-time conductivity of the detection interval, after subtracting the maximum correction amount of that detection interval, still falls within the conductivity qualification threshold range set in S230. That is: ; in, To detect the average real-time conductivity of the detection interval; This is the maximum correction amount for the detection interval; This is the lower limit of the acceptable conductivity threshold. This represents the upper limit of the acceptable conductivity threshold.

[0069] Simultaneously, a detection confidence criterion is defined: the percentage of segments marked as not meeting the detection conditions within the detection interval is less than [a certain percentage]. Furthermore, the correction amount for the maximum thickness coupling conductivity within the detection range is lower than the allowable upper limit. It should be noted that, in this embodiment, the allowable upper limit is... The upper limit for this allowed value is set based on the following: when the thickness coupling correction exceeds... If the thickness coupling interference within the detection range is so severe that it affects the conductivity determination, even if the average conductivity falls within the acceptable range after correction, its reliability is still insufficient to support automatic determination, and isolation should be given priority.

[0070] After defining the dual criteria, the following decision logic is executed for each detection interval: If the proportion of segments marked as not meeting the detection conditions within the detection interval is greater than or equal to 10%, or the maximum thickness coupling conductivity correction of the detection interval is greater than or equal to 1.0 MS / m, then the entire detection interval is marked as an isolation zone, and no online conductivity value is output; if the proportion is less than 10% and the maximum correction is less than 1.0 MS / m, then only the segments marked as not meeting the detection conditions within the interval are isolated, and the conductivity results of the remaining segments can be output. If any segment within the detection interval is determined to have entered the optimal detection window in S320, then the entire detection interval is considered to have met the effective detection conditions.

[0071] Finally, differentiated output rules are applied based on the thickness distribution labels: For thin strip sections / limited thickness influence zones, where thickness coupling interference is high and conductivity detection confidence is low, both conductivity accuracy and detection confidence criteria must be met simultaneously to output valid conductivity results. For thick strip sections / non-influence zones, conductivity accuracy is the core control objective, prioritizing the satisfaction of conductivity accuracy criteria while simultaneously verifying detection confidence criteria. Zones that do not meet detection conditions are forcibly marked as isolation zones, and no online conductivity values ​​are output. For detection zones where both criteria are met, corrected conductivity results are output. The corrected conductivity result is the average real-time conductivity of that detection zone. Its measurement uncertainty is And this should be noted in the test report; that is, the final output value is... The uncertainty band is .

[0072] This step, through dual criteria and differentiated output rules, ensures that only detection intervals that simultaneously meet the requirements for conductivity accuracy and detection confidence are output as valid conductivity results, thus eliminating the possibility of misjudging thickness coupling interference as conductivity anomalies.

[0073] S420. Generate a detection priority queue based on the earliest and best detection time of each detection interval. After all detection intervals meet the dual criteria, execute the segmented dynamic detection strategy for labels with different thickness distributions.

[0074] First, based on the best detection time of each segment within each detection interval, the earliest best detection time reached within the detection interval is taken as the representative best detection time of that detection interval; then, all detection intervals are sorted in order of their representative best detection times to generate a detection priority queue, with the interval having a higher detection priority the earlier its representative best detection time.

[0075] During online testing, the dual-criteria status of each testing interval is continuously monitored. For testing intervals that meet the criteria, the corrected conductivity results are output sequentially according to the testing priority queue. For testing intervals that do not meet the criteria, they remain isolated, and no conductivity value is output, but they are continuously marked in the testing report. This eliminates the need to wait for all testing intervals to meet the dual criteria before outputting, thus improving the real-time performance of online testing.

[0076] Output parameters are set differently based on the thickness distribution of the detection range: a lower first excitation frequency is used for the detection range of thin strips / limited thickness influence areas. and a higher second excitation frequency Combination, in this embodiment , To enhance the resolution of thickness coupling; a higher first excitation frequency is used in the detection interval of the thick strip / unaffected area. and a suitable second excitation frequency Combination, in this embodiment , This is to improve the sensitivity to changes in conductivity. It should be noted that the above frequency combination is consistent with the frequency selection rules in S210 and S220, that is, the thick band segment uses [a specific frequency selection rule] during detection. Combination, thin strip segment and normal thickness segment adopted In combination, the S420 only summarizes the output parameters and does not adjust the online frequency separately.

[0077] After all conductivity values ​​are output for all testing intervals, the corrected conductivity data is immediately linked to the material location label to generate a conductivity distribution curve along the length of the copper strip. A test report is then output, marking the location of the isolation zone and suggesting offline retesting methods (such as the four-probe method or the bridge method). Dynamic judgment of copper strip performance testing is completed, outputting a test completion signal and a copper strip qualification mark for subsequent batch process self-learning.

[0078] This step uses a combination of priority queues and differentiated frequency output strategies to ensure a reasonable output order and that the detection parameters match the actual thickness of each interval. Ultimately, it generates a complete conductivity distribution curve and detection report along the length of the copper strip, achieving a closed-loop process for online detection of the conductivity of fine-rolled copper strip.

[0079] Example 2: like Figure 2 As shown, an embodiment of the present invention provides a copper strip performance testing device, which specifically includes: Data acquisition component, penetration detection component, calculation component, and judgment component; The acquisition component is used to synchronously acquire the temperature, thickness, lift-off distance and multi-frequency eddy current response of each detection section of the copper strip based on the material position, so as to obtain position-aligned detection data; The penetration judgment component is used to calculate the eddy current penetration depth based on the detection data and combine it with the measured thickness to determine whether the detection section is in the finite thickness influence zone. Based on the judgment result, the real-time conductivity of the non-influence zone is calculated according to the correspondence between temperature and conductivity. For the influence zone, the conductivity is jointly inverted using the eddy current response under at least two excitation frequencies. The consistency of the inversion results is verified to obtain the real-time conductivity and detection status mark of each detection section. The calculation component is used to calculate the thickness coupling conductivity correction amount based on the real-time conductivity, measured thickness and lift-off distance, and obtain the correction amount data for each detection section; The determination component is used to perform conductivity accuracy criteria and detection confidence criteria based on real-time conductivity, correction data and detection status markers. When the detection segment meets both criteria, the conductivity is output. When the detection segment does not meet both criteria, it is marked as an isolation area. Finally, the conductivity detection results of each detection segment of the copper strip are obtained.

[0080] Example 3: In this embodiment, the T2 standard copper sheet group is selected as an example. Some copper sheets were not included in the establishment of the joint calibration model. This was used to examine the conductivity output accuracy of the multi-frequency joint inversion under actual detection conditions. At the same time, in the online detection of a roll of finely rolled copper strip, the sections marked as isolation areas were counted and these sections were re-inspected offline to evaluate the actual effect of the dual criteria and isolation mechanism.

[0081] In this embodiment, four standard T2 copper sheets are selected, with thicknesses of respectively... , , , None of the aforementioned copper sheets were used to create the multidimensional lookup table in S220. , , Three typical temperature points were used as detection conditions, and the lift-off distance was controlled within... The first excitation frequency was collected under each condition. Second excitation frequency The eddy current amplitude and phase were used to invert the conductivity using the S220 iterative approximation-residual minimization algorithm. Each condition was tested five times, and the average value was taken as the inverted conductivity. The relative error and the consistency deviation between the two independent inversion results at different frequencies were also calculated. The results are shown in Table 1.

[0082] Table 1. Inversion results of the joint calibration model for T2 standard copper sheets As shown in Table 1, when the thickness of the copper sheet is not less than And the temperature is not higher than At that time, the relative error of the inversion was controlled within Within, and consistency deviation Less than This satisfies the conditions for direct output. When the thickness is reduced to... Or the temperature rises to As time progressed, the relative error gradually increased, and in some sections it exceeded the verification range of the calibration area. Accuracy requirements, or consistency deviations exceeding A threshold is set, and such sections are marked as exceeding the calibration range or exhibiting inconsistencies in the inversion, and their conductivity is no longer output. The above data indicates that the joint calibration model possesses high inversion accuracy under normal operating conditions, and the consistency deviation threshold effectively distinguishes whether the inversion results are reliable, avoiding the output of unreliable data.

[0083] Fluctuations in the lift-off distance are a common source of interference in the online inspection of precision-rolled copper strip. To investigate the effect of the lift-off correction method in S310 on suppressing inspection errors, a thickness... ,temperature On the T2 copper standard sheet, the lift-off distance is set as follows: , , After calculating the lift-off correction factor and correcting the penetration depth according to the method described in S310, the joint inversion was then performed. The results are shown in Table 2.

[0084] Table 2 Comparison of inversion errors before and after lift-off correction As shown in Table 2, the greater the deviation of the lift-off distance from the baseline, the greater the uncorrected error. However, after lift-off correction, the errors all converge to the baseline. Within this period, the effectiveness of the S310 lift-off correction method was verified; To confirm the universality of the joint calibration model for different copper grades, H62 brass standard pieces (reference conductivity approximately) were tested under the same conditions. Multi-frequency joint inversion was performed. The results show that the relative inversion error is within... Within [a certain range], the consistency deviation does not exceed [a certain value]. This indicates that the joint calibration model has good inversion accuracy for different bronze grades.

[0085] In this embodiment, the purpose of the dual criteria and isolation mechanism is to prevent untrusted data from being output. To evaluate the actual effect of this mechanism, a roll of high-quality T2 copper strip is selected as the test object, with a target thickness of [missing information]. Rolling speed The total length is approximately The online conductivity of the copper strip was tested according to the method in Example 1, dividing it into 1000 testing sections, of which 52 sections were marked as isolation zones. The reasons for isolation included excessive multi-frequency consistency deviation, real-time temperature exceeding the calibration threshold, and inversion error exceeding the calibration verification range. For the above 52 isolation zones, offline four-probe conductivity retesting was performed after the copper strip was taken offline. The comparison results are shown in Table 3.

[0086] Table 3 Comparison of Offline Re-inspection in Isolation Sections As shown in Table 3, the sections isolated due to excessive multi-frequency consistency deviation and inversion error exceeding the calibration verification range generally exhibited large deviations in offline re-inspection, indicating that the online results were indeed unreliable. Sections isolated due to temperature exceeding the calibration threshold, while passing offline re-inspection, were reasonably isolated, avoiding the risks associated with extrapolation beyond the specified range. In this embodiment, the isolated sections accounted for approximately [percentage missing]. The confidence level is lower than the set value of the detection confidence criterion. The upper limit demonstrates that the solution can complete high-quality online testing without affecting the production schedule, while effectively avoiding the erroneous output of unreliable data.

[0087] Example 4: This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the aforementioned copper strip performance testing method by calling a computer program stored in memory.

[0088] The electronic device can vary considerably depending on its configuration or performance. It may include one or more processors (Central Processing Units, CPUs) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement the copper strip performance testing method provided in the above-described embodiment. The electronic device may also include other components for implementing its functions; for example, it may have wired or wireless network interfaces and input / output interfaces for data input and output. Further details are omitted here.

[0089] Example 5: This embodiment proposes a computer-readable storage medium on which an erasable and rewritable computer program is stored. When a computer program runs on a computer device, it causes the computer device to perform one of the copper strip performance testing methods described above.

[0090] For example, computer-readable storage media can be read-only memory (ROM), random access memory (RAM), compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage devices.

[0091] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0092] It should be understood that determining B based on A does not mean determining B solely based on A; it also means determining B based on A and / or other information.

[0093] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired network and / or wireless network. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives (SSDs).

[0094] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0095] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0096] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only one method, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0097] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0098] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0099] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0100] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for testing the performance of copper strips, characterized in that, The method includes the following specific steps: Based on the material location, the temperature, thickness, lift-off distance and multi-frequency eddy current response of each detection section of the copper strip are collected simultaneously to obtain the detection data with position alignment; The eddy current penetration depth is calculated based on the detection data and combined with the measured thickness to determine whether the detection section is in the finite thickness influence zone. Based on the judgment result, the real-time conductivity is calculated for the non-influence zone according to the correspondence between temperature and conductivity. For the influence zone, the conductivity is jointly inverted using the eddy current response under at least two excitation frequencies. The consistency of the inversion results is verified to obtain the real-time conductivity and detection status mark of each detection section. The thickness coupling conductivity correction is calculated based on the real-time conductivity, measured thickness, and lift-off distance to obtain the correction data for each detection section. Based on real-time conductivity, correction data, and detection status markers, conductivity accuracy criteria and detection confidence criteria are executed. When a detection segment meets both criteria, conductivity is output; when a detection segment does not meet both criteria, it is marked as an isolation area. Finally, the conductivity detection results for each detection segment of the copper strip are obtained.

2. The method for testing the performance of copper strip according to claim 1, characterized in that, Before determining whether the detection section is in the finite thickness influence zone, the penetration depth is corrected based on the deviation between the real-time lift-off distance and the reference lift-off distance. Then, the corrected penetration depth is combined with the measured thickness to determine whether the detection section is in the finite thickness influence zone.

3. The method for testing the performance of copper strip according to claim 1, characterized in that, Based on the deviation rate between the measured thickness and the target thickness of each detection section, thick strips, thin strips, or normal thickness sections are marked to form thickness distribution labels; the first excitation frequency and the second excitation frequency are selected according to the differences in thickness distribution labels, with lower frequency combinations used for thin strips and normal thickness sections, and higher frequency combinations used for thick strips; the excitation frequency corresponding to the thickness distribution label is used when calculating the eddy current penetration depth.

4. The method for testing the performance of copper strip according to claim 1, characterized in that, The joint inversion is achieved through a pre-established joint calibration model of standard copper sheets. Establishing the joint calibration model includes: preparing a set of standard copper sheets covering the conductivity range, thickness range, and temperature range of the copper strip to be tested; stabilizing the standard copper sheets at multiple temperature points while maintaining a constant lift-off distance; collecting the eddy current amplitude and phase at at least two excitation frequencies to form a calibration data point set; establishing a multidimensional lookup table based on the calibration data; and solving for the conductivity during online inversion using temperature, thickness, amplitude, and phase as inputs through an iterative approximation-residual minimization algorithm.

5. The method for testing the performance of copper strip according to claim 1, characterized in that, The consistency verification includes: independently inverting conductivity at each excitation frequency and calculating the deviation of the inversion results at each frequency; when the deviation is less than the calibrated allowable deviation, taking the average value of the inversion results at each frequency as the real-time conductivity; when the deviation is greater than or equal to the calibrated allowable deviation, marking the detection section as an inconsistent inversion area and not outputting conductivity.

6. The method for testing the performance of copper strip according to claim 1, characterized in that, When calculating the thickness coupling conductivity correction, the dynamic penetration depth is first calculated based on the real-time conductivity, and the finite thickness influence index is calculated in combination with the measured thickness. Then, the thickness coupling conductivity correction is calculated based on the finite thickness influence index, the real-time lift-off distance, and the thickness of the detection section.

7. The method for testing the performance of copper strip according to claim 6, characterized in that, Before applying the conductivity accuracy criterion and the detection confidence criterion, detection segments with adjacent locations and consistent thickness distribution labels are merged into a detection interval; Using the average real-time conductivity and the maximum thickness coupling conductivity correction of the detection interval as inputs, conductivity accuracy criteria and detection confidence criteria are executed; the conductivity of the detection interval that meets both criteria is output, otherwise it is marked as an isolation zone.

8. The method for testing the performance of copper strip according to claim 1, characterized in that, The generation method of the detection status mark includes: marking the detection section as a detection condition not met or a normal detection section based on the comparison results of real-time conductivity and conductivity qualified threshold, real-time temperature and temperature calibration threshold, and inversion consistency status.

9. The method for testing the performance of copper strip according to claim 6, characterized in that, When determining the optimal detection window, the inflection point of the rate of change of conductivity and the finite thickness influence index is monitored. The moment when the rate of change of conductivity changes from negative to positive and the finite thickness influence index changes from decreasing to stabilizing is determined as the optimal detection window. The conductivity output within the optimal detection window has the highest reliability.

10. A copper strip performance testing device, used to implement the copper strip performance testing method as described in any one of claims 1-9, characterized in that, Includes the following components: Data acquisition component, penetration detection component, calculation component, and judgment component; The acquisition component is used to synchronously acquire the temperature, thickness, lift-off distance and multi-frequency eddy current response of each detection section of the copper strip based on the material position, so as to obtain position-aligned detection data; The penetration judgment component is used to calculate the eddy current penetration depth based on the detection data and combine it with the measured thickness to determine whether the detection section is in the finite thickness influence zone. Based on the judgment result, the real-time conductivity of the non-influence zone is calculated according to the correspondence between temperature and conductivity. For the influence zone, the conductivity is jointly inverted using the eddy current response under at least two excitation frequencies. The consistency of the inversion results is verified to obtain the real-time conductivity and detection status mark of each detection section. The calculation component is used to calculate the thickness coupling conductivity correction amount based on the real-time conductivity, measured thickness and lift-off distance, and obtain the correction amount data for each detection section; The determination component is used to perform conductivity accuracy criteria and detection confidence criteria based on real-time conductivity, correction data and detection status markers. When the detection segment meets both criteria, the conductivity is output. When the detection segment does not meet both criteria, it is marked as an isolation area. Finally, the conductivity detection results of each detection segment of the copper strip are obtained.

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