Circuit board impedance calibration method and system

Abstract

The invention relates to the technical field of manufacturing process optimization, and discloses a circuit board impedance calibration method and system, and the method comprises the steps: obtaining circuit board design parameters; establishing an initial impedance model according to the circuit board design parameters; performing parameter adjustment on the initial impedance model to obtain a corrected impedance model; performing error analysis on the corrected impedance model to obtain an initial impedance predicted value; performing iterative compensation on the initial impedance predicted value to obtain an optimized impedance predicted value; judging the optimized impedance predicted value and a preset value to obtain a final impedance predicted value; testing the final impedance predicted value, calculating a test variance, and judging the variance and a preset threshold value to obtain a test result; judging according to a test result and a preset condition, and generating an impedance calibration report; according to the impedance calibration report, the circuit board production process parameters are updated, and a new circuit board production guidance file is generated. According to the method, the impedance calibration of the circuit board can be efficiently realized.

Description

Technical Field

[0001] The present invention relates to the technical field of manufacturing process optimization, and in particular to a circuit board impedance calibration method and system. Background Art

[0002] As electronic devices develop towards high performance and miniaturization, the precise control of the impedance characteristics of the circuit board as one of the core components has become particularly important to ensure signal integrity and system stability. The manufacture of circuit boards involves complex process flows, including the design and implementation of parameters such as trace width, copper foil thickness, dielectric materials, vias and blind and buried vias. Slight changes in these factors, coupled with production process fluctuations such as differences in etching and immersion gold processes, and systematic errors in test instruments, will cause the impedance value of the final product to deviate from the design expectations.

[0003] In one prior art, an accurate mathematical model is established to simulate the impedance characteristics of a circuit board, and a compensation algorithm is used to adjust the impedance deviation caused by unpredictable changes in the production process.

[0004] Although the existing technology can improve the accuracy of impedance calibration to a certain extent, it has problems of high algorithm complexity and slow calculation speed, which makes circuit board impedance calibration not only time-consuming and labor-intensive, but also difficult to meet the rapid response and high quality requirements of large-scale production, thereby reducing production efficiency. Summary of the invention

[0005] The present invention provides a circuit board impedance calibration method and system, aiming to solve the problems of high complexity and slow operation speed of circuit board impedance calibration algorithm in the prior art. The circuit board impedance calibration in the prior art is not only time-consuming and labor-intensive, but also difficult to meet the rapid response and high quality requirements of large-scale production, thereby reducing production efficiency.

[0006] In a first aspect, in order to solve the above technical problem, the present invention provides a circuit board impedance calibration method, which is executed by a computer and includes: Acquire circuit board design parameters, wherein the circuit board design parameters include trace width, copper foil thickness, dielectric material characteristic data, contact failure probability, and fluctuation range data of etching process and gold immersion process; According to the circuit board design parameters, a parameter optimization operation is performed to obtain optimized parameters, and an initial impedance model is established according to the optimized parameters; According to the fluctuation range data, adjusting the parameters of the dielectric layer thickness and the copper foil surface roughness in the initial impedance model to obtain a modified impedance model; Performing error compensation on the modified impedance model and calculating an impedance prediction value, performing error judgment between the impedance prediction value and the actual impedance value to obtain an initial impedance prediction value; Based on the gradient descent optimization algorithm, the initial impedance prediction value is iteratively compensated, and the optimized impedance prediction value is obtained by conditional judgment; Performing a judgment operation according to the optimized impedance prediction value and the preset impedance threshold to obtain a final impedance prediction value; According to the final impedance prediction value, a test operation is performed, and a rolling variance of the test is calculated, and the rolling variance is compared with a preset stability threshold value to obtain a stability test result; According to the stability test results and preset conditions, a judgment operation is performed to generate a final impedance calibration report; According to the impedance calibration report, the circuit board production process parameters are updated, a new circuit board production guidance file is generated, and the circuit board impedance calibration is completed.

[0007] As an optional implementation manner, performing a parameter optimization operation according to the circuit board design parameters to obtain optimized parameters, and establishing an initial impedance model according to the optimized parameters, includes: Obtaining trace width, copper foil thickness and dielectric material properties in the circuit board design parameters; Calculating the impedance value of the circuit board signal transmission path according to the trace width, the copper foil thickness and the dielectric material properties; If the impedance value exceeds the preset impedance range, the trace width or copper foil thickness is adjusted, and the impedance value is recalculated until the preset impedance range is met and the adjusted impedance value is output, and the adjusted trace width or copper foil thickness is used as optimization parameter 1; According to the adjusted impedance value, in combination with geometric parameters of via holes and blind and buried via holes, the impedance matching of the signal transmission path is optimized, and according to the optimized impedance matching result, an impedance distribution diagram of the circuit board layer is generated; The impedance consistency of the signal transmission path is determined by the impedance distribution diagram. If the impedance consistency does not meet the preset requirements, the dielectric material properties or the geometric parameters are continuously adjusted to regenerate the impedance distribution diagram until the impedance consistency meets the preset requirements, and the adjusted dielectric material properties or the geometric parameters are used as optimization parameters 2; If the impedance consistency meets the preset requirements, an initial impedance model is established according to the optimization parameter 1 and the optimization parameter 2 in combination with the circuit board design parameters.

[0008] As an optional implementation, the parameters of the dielectric layer thickness and the copper foil surface roughness in the initial impedance model are adjusted according to the fluctuation range data to obtain a modified impedance model, including: Determining the adjustment range of the dielectric layer thickness and the copper foil surface roughness according to the maximum value and the minimum value in the fluctuation range data; Extracting initial parameter values ​​of the dielectric layer thickness and the copper foil surface roughness from the initial impedance model as reference values ​​for adjustment; According to the adjustment interval and the reference value, if the dielectric layer thickness is within the adjustment interval, a linear interpolation method is used to calculate the corrected dielectric layer thickness; if it is not within the adjustment interval, a boundary value is used as the corrected dielectric layer thickness; According to the adjustment interval and the reference value, if the surface roughness of the copper foil is within the adjustment interval, the corrected surface roughness of the copper foil is calculated by using the quadratic interpolation method; if it is not within the adjustment interval, the boundary value is used as the corrected surface roughness of the copper foil; The corrected dielectric layer thickness and the corrected copper foil surface roughness are input into the initial impedance model as correction parameters to generate a corrected impedance model, and the corrected impedance model parameters are saved; By using the modified impedance model, the impedance values ​​under different process parameter combinations are calculated, and a corresponding relationship table between the impedance values ​​and the process parameters is generated; According to the corresponding relationship table, the relationship curve between the impedance value and the process parameter is fitted by the least square method to obtain the final modified impedance model.

[0009] As an optional implementation, performing error compensation on the modified impedance model and calculating an impedance prediction value, performing error judgment between the impedance prediction value and the actual impedance value to obtain an initial impedance prediction value, includes: According to the preset test probe wear coefficient and the contact failure probability, the error distribution of the test data is calculated, the parameters of the modified impedance model are adjusted according to the error distribution, the compensation value of the system error is determined and the error compensation is performed to obtain the compensated modified impedance model; Calculating the predicted impedance value using the compensated modified impedance model, and calculating the degree of deviation between the predicted impedance value and the actual impedance value to obtain the prediction accuracy, and performing error judgment based on the prediction accuracy; If the prediction accuracy is higher than a preset accuracy threshold, the impedance prediction value is used as an initial impedance prediction value; If the prediction accuracy is lower than the preset accuracy threshold, the parameters of the modified impedance model are re-adjusted, and an initial impedance prediction value that meets the accuracy requirement is finally obtained through iterative optimization.

[0010] As an optional implementation, the initial impedance prediction value is iteratively compensated according to the gradient descent optimization algorithm, and the optimized impedance prediction value is obtained by conditional judgment, including: Obtaining the initial impedance prediction value, and determining the initial parameters of the gradient descent algorithm in combination with preset compensation accuracy and operation speed constraints; Calculating the current gradient value according to the initial impedance prediction value and the gradient descent algorithm, and determining whether the gradient value meets the preset convergence condition; If the gradient value does not meet the convergence condition, the initial impedance prediction value is updated, and the iteration step is adjusted in combination with the compensation accuracy to generate a new impedance prediction value; if the gradient value meets the convergence condition, the next step of condition judgment is entered; Recalculate the gradient value according to the new impedance prediction value, record it as the updated gradient value, and judge whether the updated gradient value satisfies the operation speed constraint condition, if so, continue to iterate, otherwise adjust the algorithm parameters until the operation speed constraint condition is satisfied; After a preset number of iterative operations, an iterative impedance prediction value is obtained to determine whether it satisfies the preset compensation accuracy and operation speed constraints at the same time; If the iterative impedance prediction value meets the constraints, the final optimized value is output, otherwise the parameters of the gradient descent algorithm are readjusted and a new round of iteration is performed; According to the final optimized value, an optimized impedance prediction value is generated to complete the impedance prediction value compensation process based on gradient descent.

[0011] As an optional implementation manner, the determining operation is performed according to the optimized impedance prediction value and the preset impedance threshold to obtain the final impedance prediction value, including: Obtaining the optimized impedance prediction value, comparing it with a preset impedance threshold, and determining whether it is within the preset impedance threshold range; If the optimized impedance prediction value is within the preset impedance threshold range, the current optimized impedance prediction value is the final impedance prediction value and is used as the design result of the circuit board impedance; If the optimized impedance prediction value is not within the preset impedance threshold range, the current model parameters are obtained and readjusted, and the optimized impedance prediction value is recalculated according to the adjusted model parameters; The recalculated optimized impedance prediction value is compared with the preset impedance threshold until the preset impedance threshold is met, and a final impedance prediction value is output.

[0012] As an optional implementation, the test operation is performed according to the final impedance prediction value, and the rolling variance of the test is calculated, and the rolling variance is compared with a preset stability threshold to obtain a stability test result, including: Starting a computer test system, performing multiple test operations on the final impedance prediction value, and recording each test result; According to each test result, the rolling variance of the test is calculated in real time to determine whether the rolling variance is less than a preset stability threshold; If the rolling variance is less than a preset stability threshold, the system stability is determined to meet the requirements, and the test results and stability report are output; If the rolling variance is greater than a preset stability threshold, the number of tests or the interval time is adjusted, and the test and rolling variance calculation are performed again until it is less than the preset stability threshold, and the test results and stability report are output; According to the final test results and the final stability report, the confidence interval and error range of the optimized impedance value are generated to obtain the stability test results.

[0013] As an optional implementation manner, the determination operation is performed according to the stability test result and the preset conditions to generate a final impedance calibration report, including: According to the stability test result of the system, judging whether the test result meets the preset conditions; If the stability test result meets the preset conditions, a final impedance calibration report is generated and the calibration data is stored; If the stability test result does not meet the preset conditions, adjust the relevant parameters and re-execute the system stability test until the system stability test result meets the preset conditions, generate a final impedance calibration report and store the calibration data.

[0014] In a second aspect, the present invention provides a circuit board impedance calibration system, which is configured in a computer and includes: A data acquisition module is used to acquire circuit board design parameters, wherein the circuit board design parameters include trace width, copper foil thickness, dielectric material characteristic data, contact failure probability, and fluctuation range data of etching process and gold immersion process; An initial impedance model establishment module is used to perform parameter optimization operations according to the circuit board design parameters to obtain optimized parameters, and establish an initial impedance model according to the optimized parameters; A modified impedance model establishment module is used to adjust the parameters of the dielectric layer thickness and the copper foil surface roughness in the initial impedance model according to the fluctuation range data to obtain a modified impedance model; An initial impedance prediction value acquisition module is used to perform error compensation on the modified impedance model and calculate an impedance prediction value, and perform error judgment between the impedance prediction value and the actual impedance value to obtain an initial impedance prediction value; An optimized impedance prediction value acquisition module is used to iteratively compensate the initial impedance prediction value based on a gradient descent optimization algorithm, and obtain an optimized impedance prediction value by conditional judgment; A final impedance prediction value acquisition module is used to perform a judgment operation based on the optimized impedance prediction value and a preset impedance threshold to obtain a final impedance prediction value; An impedance calibration report acquisition module is used to perform a test operation according to the final impedance prediction value, calculate the rolling variance of the test, compare the rolling variance with a preset stability threshold, and obtain a stability test result; perform a judgment operation according to the stability test result and preset conditions to generate a final impedance calibration report; The circuit board impedance calibration module is used to update the circuit board production process parameters according to the impedance calibration report, generate a new circuit board production guidance file, and complete the calibration of the circuit board impedance.

[0015] In a third aspect, the present invention further provides a computer-readable storage medium, the computer-readable storage medium comprising a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned circuit board impedance calibration methods.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a circuit board impedance calibration method, the method comprising: obtaining circuit board design parameters, the circuit board design parameters comprising routing width, copper foil thickness, dielectric material characteristic data, contact failure probability, and fluctuation range data of etching process and gold immersion process; performing parameter optimization operation according to the circuit board design parameters to obtain optimized parameters, and establishing an initial impedance model according to the optimized parameters; performing parameter adjustment on dielectric layer thickness and copper foil surface roughness in the initial impedance model according to the fluctuation range data to obtain a modified impedance model; performing error compensation on the modified impedance model and calculating an impedance prediction value, performing error judgment between the impedance prediction value and the actual impedance value, and obtaining an initial impedance model. Impedance prediction value; based on the gradient descent optimization algorithm, the initial impedance prediction value is iteratively compensated, and the optimized impedance prediction value is obtained by conditional judgment; according to the optimized impedance prediction value and the preset impedance threshold, a judgment operation is performed to obtain a final impedance prediction value; according to the final impedance prediction value, a test operation is performed, and the rolling variance of the test is calculated, and the rolling variance is compared with the preset stability threshold for judgment to obtain a stability test result; according to the stability test result and the preset conditions, a judgment operation is performed to generate a final impedance calibration report; according to the impedance calibration report, the circuit board production process parameters are updated, a new circuit board production guidance file is generated, and the circuit board impedance calibration is completed.

[0017] This method uses a computer system to collect and process circuit board design parameters, establishes an initial impedance model and corrects it in combination with manufacturing process fluctuations, thereby achieving precise control of impedance prediction. This method uses a gradient descent algorithm to iteratively compensate the impedance prediction value, and verifies the stability of the system through multiple tests. The innovation lies in the close integration of impedance optimization with production process parameters, and the accuracy of impedance calibration is ensured by real-time adjustment of test probe parameters and contact pressure. Finally, based on the optimized impedance calibration report, this method updates the circuit board production process parameters and generates a new production guidance document, which effectively improves the accuracy and consistency of circuit board manufacturing and provides a reliable guarantee for the performance optimization of high-frequency and high-speed circuit boards. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic flow chart of a circuit board impedance calibration method provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of the final impedance prediction value adjustment and output process provided by an embodiment of the present invention; Figure 3 It is a flowchart of initial impedance model establishment and parameter adjustment provided by an embodiment of the present invention.

[0019] Figure 4 It is a schematic diagram of the structure of a circuit board impedance calibration system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] To solve the above problems, refer to Figure 1 The first embodiment of the present invention provides a circuit board impedance calibration method, comprising the following steps: S1, obtaining circuit board design parameters, wherein the circuit board design parameters include trace width, copper foil thickness, dielectric material characteristic data, contact failure probability, and fluctuation range data of etching process and gold immersion process; S2, performing a parameter optimization operation according to the circuit board design parameters to obtain optimized parameters, and establishing an initial impedance model according to the optimized parameters; S3, adjusting the parameters of the dielectric layer thickness and the copper foil surface roughness in the initial impedance model according to the fluctuation range data to obtain a modified impedance model; S4, performing error compensation on the modified impedance model and calculating an impedance prediction value, performing error judgment between the impedance prediction value and the actual impedance value to obtain an initial impedance prediction value; S5, based on the gradient descent optimization algorithm, iteratively compensate the initial impedance prediction value, and obtain the optimized impedance prediction value by conditional judgment; S6, performing a judgment operation according to the optimized impedance prediction value and the preset impedance threshold to obtain a final impedance prediction value; S7, performing a test operation according to the final impedance prediction value, calculating the rolling variance of the test, comparing the rolling variance with a preset stability threshold, and obtaining a stability test result; performing a judgment operation according to the stability test result and preset conditions, and generating a final impedance calibration report; S8, updating the circuit board production process parameters according to the impedance calibration report, generating a new circuit board production guidance file, and completing the circuit board impedance calibration; In step S1, circuit board design parameters are obtained, wherein the circuit board design parameters include trace width, copper foil thickness, dielectric material characteristic data, contact failure probability, and fluctuation range data of etching process and gold immersion process.

[0022] In one implementation, circuit board design parameters are obtained, where the circuit board design parameters include trace width, copper foil thickness, dielectric material characteristic data, contact failure probability, and fluctuation range data of etching process and gold immersion process, including: Trace width: Get the width of each trace according to the circuit board design or CAD file. These designs or files are usually generated by PCB design software and can be directly extracted through the design tool; Copper foil thickness: provided by the PCB manufacturer, selected according to standard specifications or specific requirements during the production process. In the design, the thickness of the copper foil can also be determined according to the number of layers and application requirements; Dielectric material characteristic data: Obtain characteristic data of dielectric materials from circuit board manufacturers, including dielectric constant, loss factor and other relevant physical properties. These data are usually used to calculate the characteristic impedance of transmission lines and will affect the signal transmission performance of circuit boards. Probability of poor contact: The probability of poor contact is evaluated by analyzing the manufacturing process of the circuit board, combining historical failure data or statistical analysis methods. This data usually comes from electrical testing and failure analysis. Fluctuation range data of etching process and immersion gold process: obtained through communication with manufacturers, analysis of historical production data, experimental verification, or tracking and adjusting key parameters in the production process through a real-time monitoring system.

[0023] In step S2, a parameter optimization operation is performed according to the circuit board design parameters to obtain optimized parameters, and an initial impedance model is established according to the optimized parameters.

[0024] In one implementation, performing a parameter optimization operation according to the circuit board design parameters to obtain optimized parameters, and establishing an initial impedance model according to the optimized parameters includes: Obtaining trace width, copper foil thickness and dielectric material properties in the circuit board design parameters; Calculating the impedance value of the circuit board signal transmission path according to the trace width, the copper foil thickness and the dielectric material properties; If the impedance value exceeds the preset impedance range, the trace width or copper foil thickness is adjusted, and the impedance value is recalculated until the preset impedance range is met and the adjusted impedance value is output, and the adjusted trace width or copper foil thickness is used as optimization parameter 1; According to the adjusted impedance value, in combination with geometric parameters of via holes and blind and buried via holes, the impedance matching of the signal transmission path is optimized, and according to the optimized impedance matching result, an impedance distribution diagram of the circuit board layer is generated; The impedance consistency of the signal transmission path is determined by the impedance distribution diagram. If the impedance consistency does not meet the preset requirements, the dielectric material properties or the geometric parameters are continuously adjusted to regenerate the impedance distribution diagram until the impedance consistency meets the preset requirements, and the adjusted dielectric material properties or the geometric parameters are used as optimization parameters 2; If the impedance consistency meets the preset requirements, an initial impedance model is established according to the optimization parameter 1 and the optimization parameter 2 in combination with the circuit board design parameters; Furthermore, the calculation formula for calculating the impedance value of the circuit board signal transmission path can be expressed as: in, Indicates the impedance value of the transmission path, represents the relative dielectric constant of the dielectric material, Indicates the thickness of the medium, Indicates the trace width, Indicates the thickness of copper foil; It should be noted that the impedance distribution diagram helps to determine the impedance consistency of the signal transmission path. If the impedance consistency is found to be unsatisfactory, such as the impedance mutation around the via exceeds 5%, further adjustments are required. You can consider changing the dielectric material properties, such as selecting a material with a dielectric constant of 4.0, or fine-tuning the geometric parameters, such as increasing the grounding copper foil area around the via.

[0025] In step S3, according to the fluctuation range data, the parameters of the dielectric layer thickness and the copper foil surface roughness in the initial impedance model are adjusted to obtain a modified impedance model.

[0026] In one implementation, according to the fluctuation range data, the dielectric layer thickness and the copper foil surface roughness in the initial impedance model are adjusted to obtain a modified impedance model, including: Determining the adjustment range of the dielectric layer thickness and the copper foil surface roughness according to the maximum value and the minimum value in the fluctuation range data; Extracting initial parameter values ​​of the dielectric layer thickness and the copper foil surface roughness from the initial impedance model as reference values ​​for adjustment; According to the adjustment interval and the reference value, if the dielectric layer thickness is within the adjustment interval, a linear interpolation method is used to calculate the corrected dielectric layer thickness; if it is not within the adjustment interval, a boundary value is used as the corrected dielectric layer thickness; According to the adjustment interval and the reference value, if the surface roughness of the copper foil is within the adjustment interval, the corrected surface roughness of the copper foil is calculated by using the quadratic interpolation method; if it is not within the adjustment interval, the boundary value is used as the corrected surface roughness of the copper foil; The corrected dielectric layer thickness and the corrected copper foil surface roughness are input into the initial impedance model as correction parameters to generate a corrected impedance model, and the corrected impedance model parameters are saved; By using the modified impedance model, the impedance values ​​under different process parameter combinations are calculated, and a corresponding relationship table between the impedance values ​​and the process parameters is generated; According to the corresponding relationship table, the relationship curve between the impedance value and the process parameter is fitted by the least square method to obtain the final modified impedance model.

[0027] Furthermore, the corrected dielectric layer thickness and the corrected copper foil surface roughness are used as correction parameters and input into the initial impedance model to generate a corrected impedance model, including: The corrected parameters are input into the initial impedance model to generate a corrected impedance model. For example, the corrected model may show that the actual impedance value is 2% higher than the theoretical value at the same line width. Next, the impedance values ​​under different process parameter combinations are calculated using the modified model. This step can generate a detailed correspondence table. For example, the impedance value is 52Ω when the line width is 50μm, the copper thickness is 35μm, and the dielectric thickness is 100μm. This tabular data helps designers quickly select the appropriate parameter combination.

[0028] In step S4, error compensation is performed on the modified impedance model and an impedance prediction value is calculated. Error judgment is performed between the impedance prediction value and the actual impedance value to obtain an initial impedance prediction value.

[0029] In one implementation, performing error compensation on the modified impedance model and calculating an impedance prediction value, performing error judgment between the impedance prediction value and an actual impedance value to obtain an initial impedance prediction value, includes: According to the preset test probe wear coefficient and the contact failure probability, the error distribution of the test data is calculated, the parameters of the modified impedance model are adjusted according to the error distribution, the compensation value of the system error is determined and the error compensation is performed to obtain the compensated modified impedance model; Calculating the predicted impedance value using the compensated modified impedance model, and calculating the degree of deviation between the predicted impedance value and the actual impedance value to obtain the prediction accuracy, and performing error judgment based on the prediction accuracy; If the prediction accuracy is higher than a preset accuracy threshold, the impedance prediction value is used as an initial impedance prediction value; If the prediction accuracy is lower than the preset accuracy threshold, the parameters of the modified impedance model are re-adjusted, and an initial impedance prediction value that meets the accuracy requirement is finally obtained through iterative optimization.

[0030] Furthermore, after adjusting the parameters of the correction model, it includes: For random errors caused by poor contact, the impact is reduced by increasing the number of tests and taking the average value. The impedance prediction value is calculated using the compensated correction model. Assuming that the impedance prediction value of a certain PCB structure is 75Ω before correction, the predicted value after compensation may be adjusted to 74.8Ω. Compare the predicted value with the actual measured value to determine whether the prediction accuracy meets the preset threshold. If the threshold is set to ±0.5Ω and the actual measured value is 74.6Ω, the prediction result is considered to meet the accuracy requirements; if the deviation exceeds the threshold, the error distribution parameters need to be readjusted.

[0031] In step S5, based on the gradient descent optimization algorithm, the initial impedance prediction value is iteratively compensated, and the optimized impedance prediction value is obtained by conditional judgment.

[0032] In one implementation, the initial impedance prediction value is iteratively compensated according to the gradient descent optimization algorithm, and the optimized impedance prediction value is obtained by conditional judgment, including: Obtaining the initial impedance prediction value, and determining the initial parameters of the gradient descent algorithm in combination with preset compensation accuracy and operation speed constraints; Calculating the current gradient value according to the initial impedance prediction value and the gradient descent algorithm, and determining whether the gradient value meets the preset convergence condition; If the gradient value does not meet the convergence condition, the initial impedance prediction value is updated, and the iteration step is adjusted in combination with the compensation accuracy to generate a new impedance prediction value; if the gradient value meets the convergence condition, the next step of condition judgment is entered; Recalculate the gradient value according to the new impedance prediction value, record it as the updated gradient value, and judge whether the updated gradient value satisfies the operation speed constraint condition, if so, continue to iterate, otherwise adjust the algorithm parameters until the operation speed constraint condition is satisfied; After a preset number of iterative operations, an iterative impedance prediction value is obtained to determine whether it satisfies the preset compensation accuracy and operation speed constraints at the same time; If the iterative impedance prediction value meets the constraints, the final optimized value is output, otherwise the parameters of the gradient descent algorithm are readjusted and a new round of iteration is performed; According to the final optimized value, an optimized impedance prediction value is generated to complete the impedance prediction value compensation process based on gradient descent; It should be noted that when updating the impedance prediction value, the compensation accuracy constraint needs to be considered, and the adaptive learning rate method is used to dynamically adjust the step size according to the current gradient. The judgment of the operation speed constraint can be achieved through timing. If the single iteration time exceeds the preset limit (such as 1 millisecond), it can be considered to simplify the calculation process or adjust the algorithm parameters.

[0033] In step S6, a judgment operation is performed based on the optimized impedance prediction value and the preset impedance threshold to obtain a final impedance prediction value.

[0034] In one implementation, the step of performing a judgment operation based on the optimized impedance prediction value and the preset impedance threshold to obtain a final impedance prediction value includes: Obtaining the optimized impedance prediction value, comparing it with a preset impedance threshold, and determining whether it is within the preset impedance threshold range; If the optimized impedance prediction value is within the preset impedance threshold range, the current optimized impedance prediction value is the final impedance prediction value and is used as the design result of the circuit board impedance; If the optimized impedance prediction value is not within the preset impedance threshold range, the current model parameters are obtained and readjusted, and the optimized impedance prediction value is recalculated according to the adjusted model parameters; Compare the recalculated optimized impedance prediction value with the preset impedance threshold until the preset impedance threshold is met, and output a final impedance prediction value; It should be noted that the adjustment direction includes replacing the conductor material or increasing the conductor cross-sectional area, re-adjusting the model parameters, and recalculating the optimized impedance value.

[0035] In step S7, a test operation is performed according to the final impedance prediction value, and the rolling variance of the test is calculated, and the rolling variance is compared with a preset stability threshold to obtain a stability test result; a judgment operation is performed according to the stability test result and preset conditions to generate a final impedance calibration report.

[0036] In one implementation, a test operation is performed according to the final impedance prediction value, and a rolling variance of the test is calculated, and the rolling variance is compared with a preset stability threshold to obtain a stability test result; a judgment operation is performed according to the stability test result and a preset condition to generate a final impedance calibration report, including: According to the stability test result of the system, judging whether the test result meets the preset conditions; If the stability test result meets the preset conditions, a final impedance calibration report is generated and the calibration data is stored; If the stability test result does not meet the preset conditions, adjust the relevant parameters and re-execute the system stability test until the system stability test result meets the preset conditions, generate a final impedance calibration report and store the calibration data; Further, the test operation is performed according to the final impedance prediction value, and the rolling variance of the test is calculated, and the rolling variance is compared and judged with a preset stability threshold to obtain a stability test result, including: Starting a computer test system, performing multiple test operations on the final impedance prediction value, and recording each test result; According to each test result, the rolling variance of the test is calculated in real time to determine whether the rolling variance is less than a preset stability threshold; If the rolling variance is less than a preset stability threshold, the system stability is determined to meet the requirements, and the test results and stability report are output; If the rolling variance is greater than a preset stability threshold, the number of tests or the interval time is adjusted, and the test and rolling variance calculation are performed again until it is less than the preset stability threshold, and the test results and stability report are output; According to the final test results and the final stability report, the confidence interval and error range of the optimized impedance value are generated to obtain the stability test results.

[0037] In step S8, according to the impedance calibration report, the circuit board production process parameters are updated to generate a new circuit board production guidance file, thereby completing the calibration of the circuit board impedance.

[0038] In one implementation, the updating operation of the circuit board production process parameters according to the impedance calibration report, generating a new circuit board production guidance file, and completing the calibration of the circuit board impedance includes: Obtain the optimized impedance calibration report, extract the impedance calibration data in the report, and establish a mapping relationship between the impedance calibration data and process parameters; Obtain the current process parameter values ​​of etching solution concentration, etching solution temperature, immersion gold solution flow rate, immersion gold solution pH value, exposure time, light intensity, pressing pressure, pressing time, drilling speed, and feed speed from the production database; A multivariate regression algorithm was used to establish a process parameter optimization model with impedance calibration data as the dependent variable and process parameters as the independent variables. According to the process parameter optimization model, the optimized values ​​of etching solution concentration, etching solution temperature, immersion gold solution flow rate, immersion gold solution pH value, exposure time, light intensity, pressing pressure, pressing time, drilling speed and feed speed are calculated; If the optimized value of the process parameter exceeds the preset safety range, the boundary value replacement algorithm is used to adjust the optimized value that exceeds the range to the boundary value within the safety range; Import the optimized process parameter values ​​into the production instruction file template, generate a new production instruction file, transmit the new production instruction file to the production control system, update the production process parameter configuration, and complete the calibration of the circuit board impedance.

[0039] Reference Figure 2 ,The flow chart shows the process of optimizing the impedance prediction value. ,First, the optimized impedance prediction value is obtained and ,compared with the preset impedance value to determine whether it meets the ,requirements. If the preset impedance value meets the threshold, the final impedance prediction value is ,output; if the threshold is not met, the model parameters are ,obtained and adjusted. The comparison and adjustment process is repeated ,until the preset impedance value requirements are met, and the final impedance prediction value ,adjustment and output are completed.

[0040] Reference Figure 3 ,This flowchart describes the process of obtaining the circuit board design parameters and establishing the ,impedance model. Firstly, the circuit board design parameters are obtained and ,the initial impedance model is established in combination with the geometric parameters. ,The impedance value of the signal transmission path is calculated and ,determined whether it exceeds the preset range. If it exceeds the range, the ,track width and copper foil thickness are adjusted and the impedance value is recalculated. ,The impedance matching is optimized using the via and blind and buried hole parameters. Finally, an impedance ,distribution diagram is generated to determine the consistency of the signal transmission ,path. The establishment of the initial impedance model and ,parameter adjustment are completed.

[0041] In summary, the present invention provides a circuit board impedance calibration method, the method comprising: obtaining circuit board design parameters, the circuit board design parameters including routing width, copper foil thickness, dielectric material characteristic data, contact failure probability, and fluctuation range data of etching process and gold immersion process; performing parameter optimization operation to obtain optimized parameters according to the circuit board design parameters, and establishing an initial impedance model according to the optimized parameters; performing parameter adjustment on the dielectric layer thickness and copper foil surface roughness in the initial impedance model according to the fluctuation range data to obtain a modified impedance model; performing error compensation on the modified impedance model and calculating an impedance prediction value, performing error judgment between the impedance prediction value and the actual impedance value, and obtaining Initial impedance prediction value; based on the gradient descent optimization algorithm, the initial impedance prediction value is iteratively compensated, and the optimized impedance prediction value is obtained by conditional judgment; according to the optimized impedance prediction value and the preset impedance threshold, a judgment operation is performed to obtain a final impedance prediction value; according to the final impedance prediction value, a test operation is performed, and the rolling variance of the test is calculated, and the rolling variance is compared with the preset stability threshold for judgment to obtain a stability test result; according to the stability test result and the preset conditions, a judgment operation is performed to generate a final impedance calibration report; according to the impedance calibration report, the circuit board production process parameters are updated, a new circuit board production guidance file is generated, and the circuit board impedance calibration is completed.

[0042] This method uses a computer system to collect and process circuit board design parameters, establishes an initial impedance model and corrects it in combination with manufacturing process fluctuations, thereby achieving precise control of impedance prediction. This method uses a gradient descent algorithm to iteratively compensate the impedance prediction value, and verifies the stability of the system through multiple tests. The innovation lies in the close integration of impedance optimization with production process parameters, and the accuracy of impedance calibration is ensured by real-time adjustment of test probe parameters and contact pressure. Finally, based on the optimized impedance calibration report, this method updates the circuit board production process parameters and generates a new production guidance document, which effectively improves the accuracy and consistency of circuit board manufacturing and provides a reliable guarantee for the performance optimization of high-frequency and high-speed circuit boards.

[0043] Reference Figure 4 A second embodiment of the present invention provides a circuit board impedance calibration system, comprising: 101 data acquisition module, used to acquire circuit board design parameters, the circuit board design parameters including trace width, copper foil thickness, dielectric material characteristic data, contact failure probability, and fluctuation range data of etching process and gold immersion process; 102 an initial impedance model establishment module, used to perform parameter optimization operation according to the circuit board design parameters to obtain optimized parameters, and establish an initial impedance model according to the optimized parameters; 103 a modified impedance model establishment module, used to adjust the parameters of the dielectric layer thickness and the copper foil surface roughness in the initial impedance model according to the fluctuation range data to obtain a modified impedance model; 104 an initial impedance prediction value acquisition module, used to perform error compensation on the modified impedance model and calculate an impedance prediction value, perform error judgment between the impedance prediction value and the actual impedance value, and obtain an initial impedance prediction value; 105 an optimized impedance prediction value acquisition module, used to iteratively compensate the initial impedance prediction value based on a gradient descent optimization algorithm, and obtain an optimized impedance prediction value by conditional judgment; 106 a final impedance prediction value acquisition module, used to perform a judgment operation according to the optimized impedance prediction value and a preset impedance threshold to obtain a final impedance prediction value; 107 impedance calibration report acquisition module, used to perform a test operation according to the final impedance prediction value, and calculate the rolling variance of the test, compare the rolling variance with a preset stability threshold, and obtain a stability test result; perform a judgment operation according to the stability test result and a preset condition, and generate a final impedance calibration report; 108 The circuit board impedance calibration module is used to update the circuit board production process parameters according to the impedance calibration report, generate a new circuit board production guidance file, and complete the calibration of the circuit board impedance.

[0044] It should be noted that a circuit board impedance calibration system provided in an embodiment of the present invention is used to execute all process steps of a circuit board impedance calibration method in the above embodiment, and the working principles and beneficial effects of the two correspond one to one, so they will not be repeated here.

[0045] In summary, the present invention provides a circuit board impedance calibration method, the method comprising: obtaining circuit board design parameters, the circuit board design parameters comprising routing width, copper foil thickness, dielectric material characteristic data, contact failure probability, and fluctuation range data of etching process and gold immersion process; performing parameter optimization operation according to the circuit board design parameters to obtain optimized parameters, and establishing an initial impedance model according to the optimized parameters; performing parameter adjustment on the dielectric layer thickness and copper foil surface roughness in the initial impedance model according to the fluctuation range data to obtain a modified impedance model; performing error compensation on the modified impedance model and calculating an impedance prediction value, performing error judgment between the impedance prediction value and the actual impedance value, and obtaining to an initial impedance prediction value; based on a gradient descent optimization algorithm, the initial impedance prediction value is iteratively compensated, and an optimized impedance prediction value is obtained by conditional judgment; a judgment operation is performed according to the optimized impedance prediction value and a preset impedance threshold to obtain a final impedance prediction value; a test operation is performed according to the final impedance prediction value, and a rolling variance of the test is calculated, and the rolling variance is compared with a preset stability threshold to obtain a stability test result; a judgment operation is performed according to the stability test result and preset conditions to generate a final impedance calibration report; according to the impedance calibration report, the circuit board production process parameters are updated to generate a new circuit board production guidance file to complete the circuit board impedance calibration.

[0046] This method uses a computer system to collect and process circuit board design parameters, and achieves precise control of impedance prediction by establishing an initial impedance model and correcting it in combination with manufacturing process fluctuations. This method uses a gradient descent algorithm to iteratively compensate for the impedance prediction value, and verifies the stability of the system through multiple tests. The innovation lies in the close integration of impedance optimization with production process parameters, and the accuracy of impedance calibration is ensured by real-time adjustment of test probe parameters and contact pressure. Finally, based on the optimized impedance calibration report, this method updates the circuit board production process parameters and generates new production guidance documents, which effectively improves the accuracy and consistency of circuit board manufacturing and provides reliable guarantees for the performance optimization of high-frequency and high-speed circuit boards. An embodiment of the present invention further provides an electronic device. The electronic device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a circuit board impedance calibration method program. When the processor executes the computer program, the steps in the above-mentioned circuit board impedance calibration method embodiments are implemented, such as Figure 1 Alternatively, when the processor executes the computer program, the functions of the modules / units in the above-mentioned device embodiments are realized, for example, the data acquisition module 101.

[0047] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the electronic device.

[0048] The electronic device may be a computing device such as a desktop computer, a notebook, a PDA, and a smart tablet. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the above components are merely examples of electronic devices and do not constitute a limitation on the electronic device. The electronic device may include more or fewer components than the above components, or may combine certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0049] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the electronic device, and uses various interfaces and lines to connect various parts of the entire electronic device.

[0050] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the electronic device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0051] Wherein, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0052] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0053] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for calibrating circuit board impedance, characterized in that: include: Acquire circuit board design parameters, wherein the circuit board design parameters include trace width, copper foil thickness, dielectric material characteristic data, contact failure probability, and fluctuation range data of etching process and gold immersion process; According to the circuit board design parameters, a parameter optimization operation is performed to obtain optimized parameters, and an initial impedance model is established according to the optimized parameters; According to the fluctuation range data, adjusting the parameters of the dielectric layer thickness and the copper foil surface roughness in the initial impedance model to obtain a modified impedance model; Performing error compensation on the modified impedance model and calculating an impedance prediction value, performing error judgment between the impedance prediction value and the actual impedance value to obtain an initial impedance prediction value; Based on the gradient descent optimization algorithm, the initial impedance prediction value is iteratively compensated, and the optimized impedance prediction value is obtained by conditional judgment; Performing a judgment operation according to the optimized impedance prediction value and the preset impedance threshold to obtain a final impedance prediction value; According to the final impedance prediction value, a test operation is performed, and a rolling variance of the test is calculated, and the rolling variance is compared with a preset stability threshold value to obtain a stability test result; According to the stability test results and preset conditions, a judgment operation is performed to generate a final impedance calibration report; According to the impedance calibration report, the circuit board production process parameters are updated, a new circuit board production guidance file is generated, and the circuit board impedance calibration is completed.

2. The circuit board impedance calibration method according to claim 1, characterized in that: The step of performing a parameter optimization operation according to the circuit board design parameters to obtain optimized parameters, and establishing an initial impedance model according to the optimized parameters, comprises: Obtaining trace width, copper foil thickness and dielectric material properties in the circuit board design parameters; Calculating the impedance value of the circuit board signal transmission path according to the trace width, the copper foil thickness and the dielectric material properties; If the impedance value exceeds the preset impedance range, the trace width or copper foil thickness is adjusted, and the impedance value is recalculated until the preset impedance range is met and the adjusted impedance value is output, and the adjusted trace width or copper foil thickness is used as optimization parameter 1; According to the adjusted impedance value, in combination with geometric parameters of via holes and blind and buried via holes, the impedance matching of the signal transmission path is optimized, and according to the optimized impedance matching result, an impedance distribution diagram of the circuit board layer is generated; The impedance consistency of the signal transmission path is determined by the impedance distribution diagram. If the impedance consistency does not meet the preset requirements, the dielectric material properties or the geometric parameters are continuously adjusted to regenerate the impedance distribution diagram until the impedance consistency meets the preset requirements, and the adjusted dielectric material properties or the geometric parameters are used as optimization parameters 2; If the impedance consistency meets the preset requirements, an initial impedance model is established according to the optimization parameter 1 and the optimization parameter 2 in combination with the circuit board design parameters.

3. The circuit board impedance calibration method according to claim 2, characterized in that: According to the fluctuation range data, adjusting the parameters of the dielectric layer thickness and the copper foil surface roughness in the initial impedance model to obtain a modified impedance model includes: Determining the adjustment range of the dielectric layer thickness and the copper foil surface roughness according to the maximum value and the minimum value in the fluctuation range data; Extracting initial parameter values ​​of the dielectric layer thickness and the copper foil surface roughness from the initial impedance model as reference values ​​for adjustment; According to the adjustment interval and the reference value, if the dielectric layer thickness is within the adjustment interval, a linear interpolation method is used to calculate the corrected dielectric layer thickness; if it is not within the adjustment interval, a boundary value is used as the corrected dielectric layer thickness; According to the adjustment interval and the reference value, if the surface roughness of the copper foil is within the adjustment interval, the corrected surface roughness of the copper foil is calculated by using the quadratic interpolation method; if it is not within the adjustment interval, the boundary value is used as the corrected surface roughness of the copper foil; The corrected dielectric layer thickness and the corrected copper foil surface roughness are input into the initial impedance model as correction parameters to generate a corrected impedance model, and the corrected impedance model parameters are saved; By using the modified impedance model, the impedance values ​​under different process parameter combinations are calculated, and a corresponding relationship table between the impedance values ​​and the process parameters is generated; According to the corresponding relationship table, the relationship curve between the impedance value and the process parameter is fitted by the least square method to obtain the final modified impedance model.

4. The circuit board impedance calibration method according to claim 1, characterized in that: The error compensation of the modified impedance model and calculation of the impedance prediction value, and error judgment between the impedance prediction value and the actual impedance value to obtain the initial impedance prediction value include: According to the preset test probe wear coefficient and the contact failure probability, the error distribution of the test data is calculated, the parameters of the modified impedance model are adjusted according to the error distribution, the compensation value of the system error is determined and the error compensation is performed to obtain the compensated modified impedance model; Calculating the predicted impedance value using the compensated modified impedance model, and calculating the degree of deviation between the predicted impedance value and the actual impedance value to obtain the prediction accuracy, and performing error judgment based on the prediction accuracy; If the prediction accuracy is higher than a preset accuracy threshold, the impedance prediction value is used as an initial impedance prediction value; If the prediction accuracy is lower than a preset accuracy threshold, the parameters of the modified impedance model are re-adjusted, and an initial impedance prediction value that meets the accuracy requirement is finally obtained through iterative optimization.

5. The circuit board impedance calibration method according to claim 4, characterized in that: The method of iteratively compensating the initial impedance prediction value based on the gradient descent optimization algorithm and obtaining the optimized impedance prediction value by conditional judgment includes: Obtaining the initial impedance prediction value, and determining the initial parameters of the gradient descent algorithm in combination with preset compensation accuracy and operation speed constraints; Calculating the current gradient value according to the initial impedance prediction value and the gradient descent algorithm, and determining whether the gradient value meets the preset convergence condition; If the gradient value does not meet the convergence condition, the initial impedance prediction value is updated, and the iteration step is adjusted in combination with the compensation accuracy to generate a new impedance prediction value; if the gradient value meets the convergence condition, the next step of condition judgment is entered; Recalculate the gradient value according to the new impedance prediction value, record it as the updated gradient value, and judge whether the updated gradient value satisfies the operation speed constraint condition, if so, continue to iterate, otherwise adjust the algorithm parameters until the operation speed constraint condition is satisfied; After a preset number of iterative operations, an iterative impedance prediction value is obtained to determine whether it satisfies the preset compensation accuracy and operation speed constraints at the same time; If the iterative impedance prediction value meets the constraints, the final optimized value is output, otherwise the parameters of the gradient descent algorithm are readjusted and a new round of iteration is performed; According to the final optimized value, an optimized impedance prediction value is generated to complete the impedance prediction value compensation process based on gradient descent.

6. The circuit board impedance calibration method according to claim 5, characterized in that: The step of performing a judgment operation according to the optimized impedance prediction value and the preset impedance threshold to obtain a final impedance prediction value includes: Obtaining the optimized impedance prediction value, comparing it with a preset impedance threshold, and determining whether it is within the preset impedance threshold range; If the optimized impedance prediction value is within the preset impedance threshold range, the current optimized impedance prediction value is the final impedance prediction value and is used as the design result of the circuit board impedance; If the optimized impedance prediction value is not within the preset impedance threshold range, the current model parameters are obtained and readjusted, and the optimized impedance prediction value is recalculated according to the adjusted model parameters; The recalculated optimized impedance prediction value is compared with the preset impedance threshold until the preset impedance threshold is met, and a final impedance prediction value is output.

7. The circuit board impedance calibration method according to claim 1, characterized in that: The method of performing a test operation according to the final impedance prediction value, calculating a rolling variance of the test, and comparing the rolling variance with a preset stability threshold to obtain a stability test result includes: Starting a computer test system, performing multiple test operations on the final impedance prediction value, and recording each test result; According to each test result, the rolling variance of the test is calculated in real time to determine whether the rolling variance is less than a preset stability threshold; If the rolling variance is less than a preset stability threshold, the system stability is determined to meet the requirements, and the test results and stability report are output; If the rolling variance is greater than a preset stability threshold, the number of tests or the interval time is adjusted, and the test and rolling variance calculation are performed again until it is less than the preset stability threshold, and the test results and stability report are output; According to the final test results and the final stability report, the confidence interval and error range of the optimized impedance value are generated to obtain the stability test results.

8. The circuit board impedance calibration method according to claim 7, characterized in that: The step of performing a judgment operation based on the stability test result and the preset conditions to generate a final impedance calibration report includes: According to the stability test result of the system, judging whether the test result meets the preset conditions; If the stability test result meets the preset conditions, a final impedance calibration report is generated and the calibration data is stored; If the stability test result does not meet the preset conditions, adjust the relevant parameters and re-execute the system stability test until the system stability test result meets the preset conditions, generate a final impedance calibration report and store the calibration data.

9. A circuit board impedance calibration system, characterized in that: Configured in the computer, including: A data acquisition module is used to acquire circuit board design parameters, wherein the circuit board design parameters include trace width, copper foil thickness, dielectric material characteristic data, contact failure probability, and fluctuation range data of etching process and gold immersion process; An initial impedance model establishment module is used to perform parameter optimization operations according to the circuit board design parameters to obtain optimized parameters, and establish an initial impedance model according to the optimized parameters; A modified impedance model establishment module is used to adjust the parameters of the dielectric layer thickness and the copper foil surface roughness in the initial impedance model according to the fluctuation range data to obtain a modified impedance model; An initial impedance prediction value acquisition module is used to perform error compensation on the modified impedance model and calculate an impedance prediction value, and perform error judgment between the impedance prediction value and the actual impedance value to obtain an initial impedance prediction value; An optimized impedance prediction value acquisition module is used to iteratively compensate the initial impedance prediction value based on a gradient descent optimization algorithm, and obtain an optimized impedance prediction value by conditional judgment; A final impedance prediction value acquisition module is used to perform a judgment operation based on the optimized impedance prediction value and a preset impedance threshold to obtain a final impedance prediction value; An impedance calibration report acquisition module is used to perform a test operation according to the final impedance prediction value, calculate the rolling variance of the test, compare the rolling variance with a preset stability threshold, and obtain a stability test result; perform a judgment operation according to the stability test result and preset conditions to generate a final impedance calibration report; The circuit board impedance calibration module is used to update the circuit board production process parameters according to the impedance calibration report, generate a new circuit board production guidance file, and complete the calibration of the circuit board impedance.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the circuit board impedance calibration method according to any one of claims 1 to 8.

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