Calibration Method and System for Circuit Board Impedance

Abstract

The present invention relates to the technical field of manufacturing process optimization, and discloses a method and a system for calibrating the impedance of a circuit board. The method includes: obtaining circuit board design parameters; establishing an initial impedance model according to the circuit board design parameters; adjusting the parameters of the initial impedance model to obtain a corrected impedance model; performing error analysis on the corrected impedance model to obtain an initial impedance prediction value; performing iterative compensation on the initial impedance prediction value to obtain an optimized impedance prediction value; judging the optimized impedance prediction value and a preset value to obtain a final impedance prediction value; testing the final impedance prediction value and calculating the test variance, and judging the variance and a preset threshold to obtain a test result; judging according to the test result and a preset condition to generate an impedance calibration report; updating the circuit board production process parameters according to the impedance calibration report to generate a new circuit board production guidance document. This method can efficiently calibrate the impedance of the circuit board.

Description

Technical Field

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

[0002] With the development of electronic devices towards high performance and miniaturization, as one of the core components, the precise control of the impedance characteristics of the circuit board becomes particularly important for ensuring signal integrity and system stability. The manufacturing of the circuit board involves complex process flows, including the design and implementation of parameters such as trace width, copper foil thickness, dielectric material, vias, and buried blind vias. Minor changes in these factors, combined with production process fluctuations such as differences in etching and immersion gold processes, as well as systematic errors of test instruments, will cause the impedance value of the final product to deviate from the design expectation.

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

[0004] Although the existing technology can improve the accuracy of impedance calibration to a certain extent, there are problems of high algorithm complexity and slow operation speed, resulting in not only time-consuming and laborious impedance calibration of the circuit board, but also difficulty in meeting the rapid response and high-quality requirements of large-scale production, reducing production efficiency. Summary of the Invention

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

[0006] In a first aspect, to solve the above technical problems, the present invention provides a method for calibrating the impedance of a circuit board, which is executed by a computer and includes:

[0007] Obtain circuit board design parameters, 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 immersion gold process;

[0008] Perform parameter optimization operations based on the circuit board design parameters to obtain optimized parameters, and establish an initial impedance model based on the optimized parameters;

[0009] Adjust the parameters of the dielectric layer thickness and copper foil surface roughness in the initial impedance model according to the fluctuation range data to obtain a corrected impedance model;

[0010] Perform error compensation on the corrected impedance model and calculate the impedance prediction value. Compare the impedance prediction value with the actual impedance value to obtain the initial impedance prediction value;

[0011] Based on the gradient descent optimization algorithm, perform iterative compensation on the initial impedance prediction value and obtain the optimized impedance prediction value through conditional judgment;

[0012] According to the optimized impedance prediction value and the preset impedance threshold, perform a judgment operation to obtain the final impedance prediction value;

[0013] According to the final impedance prediction value, perform a test operation and calculate the rolling variance of the test. Compare the rolling variance with the preset stability threshold to obtain the stability test result;

[0014] According to the stability test result and the preset conditions, perform a judgment operation to generate the final impedance calibration report;

[0015] According to the impedance calibration report, update the circuit board production process parameters to generate a new circuit board production guidance document, completing the calibration of the circuit board impedance.

[0016] As an optional implementation manner, the step of 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 includes:

[0017] Obtain the trace width, copper foil thickness, and dielectric material characteristics in the circuit board design parameters;

[0018] According to the trace width, the copper foil thickness, and the dielectric material characteristics, calculate the impedance value of the circuit board signal transmission path;

[0019] If the impedance value exceeds the preset impedance range, adjust the trace width or copper foil thickness, recalculate the impedance value until it meets the preset impedance range and output the adjusted impedance value, and use the adjusted trace width or copper foil thickness as the optimized parameter 1;

[0020] According to the adjusted impedance value and in combination with the geometric parameters of vias and blind buried vias, optimize the impedance matching of the signal transmission path, and generate an impedance distribution map of the circuit board layer according to the optimized impedance matching result;

[0021] Through the impedance distribution map, judge the impedance consistency of the signal transmission path. If the impedance consistency does not meet the preset requirements, continue to adjust the dielectric material characteristics or the geometric parameters, regenerate the impedance distribution map until the impedance consistency meets the preset requirements, and use the adjusted dielectric material characteristics or geometric parameters as the optimized parameter 2;

[0022] After 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.

[0023] As an alternative implementation, based on the fluctuation range data, parameter adjustment is performed on the dielectric layer thickness and the copper foil surface roughness in the initial impedance model to obtain a corrected impedance model, including:

[0024] According to the maximum value and the minimum value in the fluctuation range data, the adjustment intervals of the dielectric layer thickness and the copper foil surface roughness are determined;

[0025] The initial parameter values of the dielectric layer thickness and the copper foil surface roughness are extracted from the initial impedance model as the reference values for adjustment;

[0026] According to the adjustment interval and the reference value, if the dielectric layer thickness is within the adjustment interval, the linear interpolation method is used to calculate the corrected dielectric layer thickness; if it is not within the adjustment interval, the boundary value is used as the corrected dielectric layer thickness;

[0027] According to the adjustment interval and the reference value, if the copper foil surface roughness is within the adjustment interval, the quadratic interpolation method is used to calculate the corrected copper foil surface roughness; if it is not within the adjustment interval, the boundary value is used as the corrected copper foil surface roughness;

[0028] 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, and the corrected impedance model parameters are saved;

[0029] Through the corrected impedance model, the impedance values under different process parameter combinations are calculated to generate a correspondence table between the impedance values and the process parameters;

[0030] According to the correspondence table, the least squares method is used to fit the relationship curve between the impedance value and the process parameters to obtain the final corrected impedance model.

[0031] As an alternative implementation, error compensation is performed on the corrected impedance model and the impedance prediction value is calculated, and the error between the impedance prediction value and the actual impedance value is judged to obtain the initial impedance prediction value, including:

[0032] According to the preset test probe wear coefficient and the probability of poor contact, the error distribution of the test data is calculated, and the corrected impedance model is adjusted through the error distribution to determine the compensation value of the systematic error and perform error compensation to obtain the compensated corrected impedance model;

[0033] Calculate the impedance prediction value using the corrected impedance model after compensation, calculate the deviation degree between the impedance prediction value and the actual impedance value to obtain the prediction accuracy, and perform error judgment based on the prediction accuracy;

[0034] If the prediction accuracy is higher than the preset accuracy threshold, use the impedance prediction value as the initial impedance prediction value;

[0035] If the prediction accuracy is lower than the preset accuracy threshold, re-adjust the parameters of the corrected impedance model, and finally obtain the initial impedance prediction value that meets the accuracy requirements through iterative optimization.

[0036] As an alternative implementation, the iterative compensation of the initial impedance prediction value according to the gradient descent optimization algorithm and the conditional judgment to obtain the optimized impedance prediction value include:

[0037] Obtain the initial impedance prediction value, and determine the initial parameters of the gradient descent algorithm in combination with the preset compensation accuracy and operation speed constraint conditions;

[0038] Calculate the current gradient value according to the initial impedance prediction value and the gradient descent algorithm, and judge whether the gradient value meets the preset convergence condition;

[0039] If the gradient value does not meet the convergence condition, update the initial impedance prediction value, adjust the iteration step size in combination with the compensation accuracy, and generate a new impedance prediction value; if the gradient value meets the convergence condition, proceed to the next conditional judgment;

[0040] According to the new impedance prediction value, recalculate the gradient value, denoted as the updated gradient value, and judge whether the updated gradient value meets the operation speed constraint condition. If it meets, continue the iteration; otherwise, adjust the algorithm parameters until the operation speed constraint condition is met;

[0041] After a preset number of iterative operations, obtain the iterative impedance prediction value and judge whether it meets the preset compensation accuracy and operation speed constraint conditions at the same time;

[0042] If the iterative impedance prediction value meets the constraint conditions, output the final optimized value; otherwise, readjust the parameters of the gradient descent algorithm and perform a new round of iteration;

[0043] Generate the optimized impedance prediction value after optimization according to the final optimized value, and complete the compensation process of the impedance prediction value based on the gradient descent.

[0044] As an alternative implementation, the judgment operation based on the optimized impedance prediction value and the preset impedance threshold to obtain the final impedance prediction value includes:

[0045] Obtain the optimized impedance prediction value, compare it with the preset impedance threshold, and determine whether it is within the preset impedance threshold range;

[0046] If the optimized impedance prediction value is within the preset impedance threshold range, then the current optimized impedance prediction value is the final impedance prediction value and is used as the design result of the circuit board impedance;

[0047] If the optimized impedance prediction value is not within the preset impedance threshold range, then obtain the current model parameters and readjust them, and recalculate the optimized impedance prediction value according to the adjusted model parameters;

[0048] Compare the recalculated optimized impedance prediction value with the preset impedance threshold until the preset impedance threshold is satisfied, and output the final impedance prediction value.

[0049] As an alternative implementation, based on the final impedance prediction value, perform a test operation, calculate the rolling variance of the test, and compare the rolling variance with a preset stability threshold to obtain a stability test result, including:

[0050] Start the computer test system, perform multiple test operations on the final impedance prediction value, and record each test result;

[0051] According to each test result, calculate the rolling variance of the test in real time, and determine whether the rolling variance is less than the preset stability threshold;

[0052] If the rolling variance is less than the preset stability threshold, it is determined that the system stability meets the requirements, and the test result and stability report are output;

[0053] If the rolling variance is greater than the preset stability threshold, adjust the number of tests or the interval time, re-perform the test and calculate the rolling variance until it is less than the preset stability threshold, and output the test result and stability report;

[0054] Generate a confidence interval and an error range for the optimized impedance value based on the final test result and the final stability report to obtain the stability test result.

[0055] As an alternative implementation, based on the stability test result and preset conditions, perform a judgment operation to generate a final impedance calibration report, including:

[0056] According to the stability test result of the system, determine whether the test result meets the preset conditions;

[0057] If the stability test result meets the preset conditions, generate a final impedance calibration report and store the calibration data;

[0058] If the stability test result does not meet the preset conditions, adjust the relevant parameters and re-perform the system stability test until the system stability test result meets the preset conditions, generate the final impedance calibration report and store the calibration data.

[0059] In a second aspect, the present invention provides a calibration system for the impedance of a circuit board, configured in a computer, including:

[0060] A data acquisition module for acquiring circuit board design parameters, where the circuit board design parameters include trace width, copper foil thickness, dielectric material characteristic data, contact failure probability, and fluctuation range data of the etching process and immersion gold process;

[0061] An initial impedance model establishment module for performing parameter optimization operations on the circuit board design parameters to obtain optimized parameters, and establishing an initial impedance model based on the optimized parameters;

[0062] A corrected impedance model establishment module for performing parameter adjustments on the dielectric layer thickness and copper foil surface roughness in the initial impedance model according to the fluctuation range data to obtain a corrected impedance model;

[0063] An initial impedance prediction value acquisition module for performing error compensation on the corrected impedance model and calculating an impedance prediction value, and performing error judgment on the impedance prediction value and the actual impedance value to obtain an initial impedance prediction value;

[0064] An optimized impedance prediction value acquisition module for performing iterative compensation on the initial impedance prediction value based on the gradient descent optimization algorithm, and obtaining an optimized impedance prediction value through condition judgment;

[0065] A final impedance prediction value acquisition module for performing judgment operations based on the optimized impedance prediction value and a preset impedance threshold to obtain a final impedance prediction value;

[0066] An impedance calibration report acquisition module for performing test operations based on the final impedance prediction value, calculating the rolling variance of the test, comparing the rolling variance with a preset stability threshold for judgment to obtain a stability test result; and performing judgment operations based on the stability test result and preset conditions to generate a final impedance calibration report;

[0067] A circuit board impedance calibration module for updating the circuit board production process parameters according to the impedance calibration report, generating a new circuit board production guidance document, and completing the calibration of the circuit board impedance.

[0068] In a third aspect, the present invention also provides a computer-readable storage medium, which includes a stored computer program. When the computer program runs, it controls the device where the computer-readable storage medium is located to execute the calibration method for the circuit board impedance described in any one of the above.

[0069] Compared with the prior art, the present invention has the following beneficial effects:

[0070] The present invention provides a calibration method for circuit board impedance. The method includes: obtaining circuit board design parameters, where the circuit board design parameters include trace width, copper foil thickness, dielectric material characteristic data, contact bad probability, and fluctuation range data of etching process and immersion gold process; performing parameter optimization operations according to the circuit board design parameters to obtain optimized parameters, and establishing an initial impedance model according to the optimized parameters; adjusting parameters of the dielectric layer thickness and copper foil surface roughness in the initial impedance model according to the fluctuation range data to obtain a corrected impedance model; performing error compensation on the corrected impedance model and calculating an impedance prediction value, making an error judgment between the impedance prediction value and the actual impedance value to obtain an initial impedance prediction value; performing iterative compensation on the initial impedance prediction value based on the gradient descent optimization algorithm, and making a conditional judgment to obtain an optimized impedance prediction value; making a judgment operation according to the optimized impedance prediction value and a preset impedance threshold to obtain a final impedance prediction value; performing a test operation according to the final impedance prediction value and calculating the rolling variance of the test, comparing the rolling variance with a preset stability threshold to make a judgment to obtain a stability test result; making a judgment operation according to the stability test result and a preset condition to generate a final impedance calibration report; updating the circuit board production process parameters according to the impedance calibration report to generate a new circuit board production guidance document, and completing the calibration of the circuit board impedance.

[0071] This method uses a computer system to collect and process circuit board design parameters. By establishing an initial impedance model and making corrections in combination with manufacturing process fluctuations, precise control of impedance prediction is achieved. This method uses the gradient descent algorithm to perform iterative compensation on the impedance prediction value and verifies the system stability through multiple tests. The innovation lies in closely combining impedance optimization with production process parameters, and ensuring the accuracy of impedance calibration by adjusting the test probe parameters and contact pressure in real time. Finally, based on the optimized impedance calibration report, this method updates the circuit board production process parameters to generate a new production guidance document, effectively improving the accuracy and consistency of circuit board manufacturing, and providing a reliable guarantee for the performance optimization of high-frequency and high-speed circuit boards. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 is a schematic flow chart of the calibration method for circuit board impedance provided by an embodiment of the present invention;

[0073] Figure 2 It is a schematic diagram of the process of adjusting and outputting the final impedance prediction value provided by an embodiment of the present invention;

[0074] Figure 3 It is a schematic flowchart of establishing an initial impedance model and adjusting parameters provided by an embodiment of the present invention.

[0075] Figure 4 It is a schematic structural diagram of a calibration system for the impedance of a circuit board provided by an embodiment of the present invention. Detailed implementation manners

[0076] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0077] To solve the above problems, referring to Figure 1 , the first embodiment of the present invention provides a method for calibrating the impedance of a circuit board, including the following steps:

[0078] S1. Obtain circuit board design parameters, 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 immersion gold process;

[0079] S2. According to the circuit board design parameters, perform parameter optimization operations to obtain optimized parameters, and establish an initial impedance model according to the optimized parameters;

[0080] S3. According to the fluctuation range data, adjust the parameters of the dielectric layer thickness and copper foil surface roughness in the initial impedance model to obtain a corrected impedance model;

[0081] S4. Perform error compensation on the corrected impedance model and calculate an impedance prediction value, and perform an error judgment on the impedance prediction value and the actual impedance value to obtain an initial impedance prediction value;

[0082] S5. Based on the gradient descent optimization algorithm, perform iterative compensation on the initial impedance prediction value, and perform conditional judgment to obtain an optimized impedance prediction value;

[0083] S6. According to the optimized impedance prediction value and a preset impedance threshold, perform a judgment operation to obtain a final impedance prediction value;

[0084] S7. Based on the predicted final impedance value, perform a test operation, calculate the rolling variance of the test, compare the rolling variance with a preset stability threshold for judgment, and obtain a stability test result; according to the stability test result and preset conditions, perform a judgment operation to generate a final impedance calibration report;

[0085] S8. According to the impedance calibration report, perform an update operation on the circuit board production process parameters to generate a new circuit board production guidance document, and complete the calibration of the circuit board impedance;

[0086] In step S1, obtain circuit board design parameters, where the circuit board design parameters include trace width, copper foil thickness, dielectric material characteristic data, contact bad probability, and fluctuation range data of etching process and immersion gold process.

[0087] In one implementation, obtaining circuit board design parameters, where the circuit board design parameters include trace width, copper foil thickness, dielectric material characteristic data, contact bad probability, and fluctuation range data of etching process and immersion gold process, includes:

[0088] Trace width: Obtain the width of each trace according to the circuit board design drawing or CAD file. These design drawings or files are usually generated by PCB design software and can be directly extracted through design tools;

[0089] 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;

[0090] Dielectric material characteristic data: Obtain the characteristic data of the dielectric material from the circuit board manufacturer, including dielectric constant, loss factor, and other related physical characteristics. These data are usually used to calculate the characteristic impedance of the transmission line and will affect the signal transmission performance of the circuit board;

[0091] Contact bad probability: Evaluate the contact bad probability through the analysis of the circuit board manufacturing process, combined with historical failure data or statistical analysis methods. This data usually comes from electrical tests and failure analysis;

[0092] Fluctuation range data of etching process and immersion gold process: Obtained by communicating with the manufacturer, analyzing historical production data, conducting experimental verification, or tracking and adjusting key parameters in the production process through a real-time monitoring system.

[0093] In step S2, according to the circuit board design parameters, perform a parameter optimization operation to obtain optimized parameters, and establish an initial impedance model according to the optimized parameters.

[0094] In one implementation, according to the circuit board design parameters, parameter optimization operations are performed to obtain optimized parameters, and an initial impedance model is established based on the optimized parameters, including:

[0095] Obtain the trace width, copper foil thickness, and dielectric material properties in the circuit board design parameters;

[0096] According to the trace width, the copper foil thickness, and the dielectric material properties, calculate the impedance value of the circuit board signal transmission path;

[0097] If the impedance value exceeds the preset impedance range, adjust the trace width or copper foil thickness, recalculate the impedance value until it meets the preset impedance range, output the adjusted impedance value, and use the adjusted trace width or copper foil thickness as optimization parameter 1;

[0098] According to the adjusted impedance value, combined with the geometric parameters of vias and buried vias, optimize the impedance matching of the signal transmission path, and generate an impedance distribution map of the circuit board layer according to the optimized impedance matching result;

[0099] Through the impedance distribution map, judge the impedance consistency of the signal transmission path. If the impedance consistency does not meet the preset requirements, continue to adjust the dielectric material properties or the geometric parameters, regenerate the impedance distribution map until the impedance consistency meets the preset requirements, and use the adjusted dielectric material properties or the geometric parameters as optimization parameter 2;

[0100] After the impedance consistency meets the preset requirements, establish an initial impedance model according to the optimization parameter 1 and the optimization parameter 2, combined with the circuit board design parameters;

[0101] Further, the calculation formula for calculating the impedance value of the circuit board signal transmission path can be expressed as:

[0102]

[0103] Among them, represents the impedance value of the transmission path, represents the relative dielectric constant of the dielectric material, represents the dielectric thickness, represents the trace width, represents the copper foil thickness;

[0104] It should be noted that the impedance distribution map helps to judge the impedance consistency of the signal transmission path. If it is found that the impedance consistency does not meet the requirements, for example, the impedance mutation around the via exceeds 5%, further adjustment is required. It can be considered to change 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 ground copper foil area around the via.

[0105] In step S3, according to the fluctuation range data, the thickness of the dielectric layer and the surface roughness of the copper foil in the initial impedance model are adjusted for parameters to obtain a corrected impedance model.

[0106] In one implementation, 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 corrected impedance model includes:

[0107] According to the maximum and minimum values in the fluctuation range data, determine the adjustment intervals for the dielectric layer thickness and the copper foil surface roughness;

[0108] Extract the initial parameter values of the dielectric layer thickness and the copper foil surface roughness from the initial impedance model as the reference values for adjustment;

[0109] According to the adjustment interval and the reference value, if the dielectric layer thickness is within the adjustment interval, use the linear interpolation method to calculate the corrected dielectric layer thickness; if it is not within the adjustment interval, use the boundary value as the corrected dielectric layer thickness;

[0110] According to the adjustment interval and the reference value, if the copper foil surface roughness is within the adjustment interval, use the quadratic interpolation method to calculate the corrected copper foil surface roughness; if it is not within the adjustment interval, use the boundary value as the corrected copper foil surface roughness;

[0111] Take the corrected dielectric layer thickness and the corrected copper foil surface roughness as correction parameters, input them into the initial impedance model, generate a corrected impedance model, and save the corrected impedance model parameters;

[0112] Through the corrected impedance model, calculate the impedance values under different process parameter combinations, and generate a correspondence table between the impedance values and the process parameters;

[0113] According to the correspondence table, use the least squares method to fit the relationship curve between the impedance values and the process parameters to obtain the final corrected impedance model.

[0114] Furthermore, taking the corrected dielectric layer thickness and the corrected copper foil surface roughness as correction parameters and inputting them into the initial impedance model to generate a corrected impedance model includes:

[0115] Input the corrected parameters into the initial impedance model to generate a corrected impedance model. For example, the corrected model may show that at the same line width, the actual impedance value is 2% higher than the theoretical value;

[0116] Next, calculate the impedance values under different combinations of process parameters using the corrected model. This step can generate a detailed correspondence table. For example, when the line width is 50μm, the copper thickness is 35μm, and the dielectric thickness is 100μm, the impedance value is 52Ω. Such tabular data helps designers quickly select appropriate parameter combinations.

[0117] In step S4, perform error compensation on the corrected impedance model and calculate the impedance prediction value. Compare the impedance prediction value with the actual impedance value to make an error judgment and obtain the initial impedance prediction value.

[0118] In one implementation, the step of performing error compensation on the corrected impedance model, calculating the impedance prediction value, comparing the impedance prediction value with the actual impedance value, and obtaining the initial impedance prediction value includes:

[0119] According to the preset test probe wear coefficient and the probability of poor contact, calculate the error distribution of the test data. Adjust the parameters of the corrected impedance model through the error distribution, determine the compensation value for the systematic error, and perform error compensation to obtain the compensated corrected impedance model.

[0120] Use the compensated corrected impedance model to calculate the impedance prediction value, calculate the deviation degree between the impedance prediction value and the actual impedance value to obtain the prediction accuracy, and make an error judgment based on the prediction accuracy.

[0121] If the prediction accuracy is higher than the preset accuracy threshold, use the impedance prediction value as the initial impedance prediction value.

[0122] If the prediction accuracy is lower than the preset accuracy threshold, readjust the parameters of the corrected impedance model. Through iterative optimization, finally obtain the initial impedance prediction value that meets the accuracy requirements.

[0123] Furthermore, after adjusting the parameters of the corrected model, it includes:

[0124] For the random error caused by poor contact, reduce its impact by increasing the number of tests and taking the average value. Use the compensated corrected model to calculate the impedance prediction value. Suppose the impedance prediction value of the model before compensation for a certain PCB structure is 75Ω, and the compensated prediction value may be adjusted to 74.8Ω.

[0125] Compare the prediction value with the actual measured value to determine whether the prediction accuracy meets the preset threshold. If the set threshold is ±0.5Ω and the actual measured value is 74.6Ω, it is considered that the prediction result meets the accuracy requirements; if the deviation exceeds the threshold, the error distribution parameters need to be readjusted.

[0126] 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 through conditional judgment.

[0127] In one implementation, the iterative compensation of the initial impedance prediction value based on the gradient descent optimization algorithm and the conditional judgment to obtain the optimized impedance prediction value include:

[0128] Obtain the initial impedance prediction value, and determine the initial parameters of the gradient descent algorithm in combination with the preset compensation accuracy and operation speed constraint conditions;

[0129] Calculate the current gradient value according to the initial impedance prediction value and the gradient descent algorithm, and judge whether the gradient value meets the preset convergence condition;

[0130] If the gradient value does not meet the convergence condition, update the initial impedance prediction value, adjust the iteration step size in combination with the compensation accuracy, and generate a new impedance prediction value; if the gradient value meets the convergence condition, proceed to the next conditional judgment;

[0131] According to the new impedance prediction value, recalculate the gradient value, denoted as the updated gradient value, and judge whether the updated gradient value meets the operation speed constraint condition. If it meets, continue the iteration; otherwise, adjust the algorithm parameters until the operation speed constraint condition is met;

[0132] After a preset number of iterative operations, obtain the iterative impedance prediction value, and judge whether it meets the preset compensation accuracy and operation speed constraint conditions at the same time;

[0133] If the iterative impedance prediction value meets the constraint conditions, output the final optimized value; otherwise, readjust the parameters of the gradient descent algorithm and perform a new round of iteration;

[0134] Generate the optimized impedance prediction value according to the final optimized value, and complete the compensation process of the impedance prediction value based on the gradient descent;

[0135] It should be noted that when updating the impedance prediction value, the compensation accuracy constraint condition needs to be considered, and the method of adaptive learning rate is adopted to dynamically adjust the step size according to the magnitude of the current gradient. The judgment of the operation speed constraint condition can be realized by timing. If the single iteration time exceeds the preset limit (such as 1 millisecond), the calculation process can be considered to be simplified or the algorithm parameters can be adjusted.

[0136] In step S6, according to the optimized impedance prediction value and the preset impedance threshold, a judgment operation is performed to obtain the final impedance prediction value.

[0137] In one implementation, the judgment operation according to the optimized impedance prediction value and the preset impedance threshold to obtain the final impedance prediction value includes:

[0138] Obtain the optimized impedance prediction value, compare it with a preset impedance threshold, and determine whether it is within the preset impedance threshold range;

[0139] If the optimized impedance prediction value is within the preset impedance threshold range, then the current optimized impedance prediction value is the final impedance prediction value and is used as the design result of the circuit board impedance;

[0140] If the optimized impedance prediction value is not within the preset impedance threshold range, then obtain the current model parameters and readjust them. According to the adjusted model parameters, recalculate the optimized impedance prediction value;

[0141] Compare the recalculated optimized impedance prediction value with the preset impedance threshold until the preset impedance threshold is satisfied, and output the final impedance prediction value;

[0142] It should be noted that the adjustment directions include replacing the wire material or increasing the wire cross-sectional area. After readjusting the model parameters, recalculate the optimized impedance value.

[0143] In step S7, according to the final impedance prediction value, perform a test operation, calculate the rolling variance of the test, compare the rolling variance with a preset stability threshold to make a judgment, and obtain a stability test result; according to the stability test result and preset conditions, perform a judgment operation to generate a final impedance calibration report.

[0144] In one implementation, according to the final impedance prediction value, perform a test operation, calculate the rolling variance of the test, compare the rolling variance with a preset stability threshold to make a judgment, and obtain a stability test result; according to the stability test result and preset conditions, perform a judgment operation to generate a final impedance calibration report, including:

[0145] According to the stability test result of the system, judge whether the test result meets the preset conditions;

[0146] If the stability test result meets the preset conditions, then generate a final impedance calibration report and store the calibration data;

[0147] If the stability test result does not meet the preset conditions, adjust the relevant parameters and re-perform 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;

[0148] Furthermore, the 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 to make a judgment, and obtaining a stability test result includes:

[0149] Start the computer test system, perform multiple test operations on the final impedance prediction value, and record the test results each time;

[0150] According to each test result, calculate the rolling variance of the test in real time, and determine whether the rolling variance is less than the preset stability threshold;

[0151] If the rolling variance is less than the preset stability threshold, it is determined that the system stability meets the requirements, and the test results and stability report are output;

[0152] If the rolling variance is greater than the preset stability threshold, adjust the number of tests or the interval time, re - perform the test and calculate the rolling variance until it is less than the preset stability threshold, and output the test results and stability report;

[0153] Generate the confidence interval and error range of the optimized impedance value based on the final test results and the final stability report to obtain the stability test results.

[0154] In step S8, according to the impedance calibration report, perform an update operation on the circuit board production process parameters, generate a new circuit board production guidance document, and complete the calibration of the circuit board impedance.

[0155] In one implementation, the performing an update operation on the circuit board production process parameters according to the impedance calibration report, generating a new circuit board production guidance document, and completing the calibration of the circuit board impedance includes:

[0156] Obtain the optimized impedance calibration report, extract the impedance calibration data in the report, and establish the mapping relationship between the impedance calibration data and the process parameters;

[0157] Obtain the current process parameter values of the etching solution concentration, etching solution temperature, immersion gold solution flow rate, immersion gold solution pH value, exposure time, light intensity, lamination pressure, lamination time, drilling speed, and feed rate from the production database;

[0158] Adopt the multiple regression algorithm, use the impedance calibration data as the dependent variable and the process parameters as the independent variables to establish a process parameter optimization model;

[0159] According to the process parameter optimization model, calculate the optimized values of the etching solution concentration, etching solution temperature, immersion gold solution flow rate, immersion gold solution pH value, exposure time, light intensity, lamination pressure, lamination time, drilling speed, and feed rate;

[0160] If the optimized values of the process parameters exceed the preset safety range, use the boundary value substitution algorithm to adjust the optimized values that exceed the range to the boundary values within the safety range;

[0161] Import the optimized process parameter values into the production guidance document template to generate a new production guidance document, transfer the new production guidance document to the production control system, update the production process parameter configuration, and complete the calibration of the circuit board impedance.

[0162] Refer to Figure 2 , this flowchart shows the process of optimizing the impedance prediction value. First, obtain the optimized impedance prediction value and compare it with the preset impedance value to determine whether the requirements are met. If the preset impedance value meets the threshold, output the final impedance prediction value; if it does not meet the threshold, obtain the model parameters and make adjustments, repeating the comparison and adjustment process until the requirements of the preset impedance value are met, and complete the adjustment and output of the final impedance prediction value.

[0163] Refer to Figure 3 , this flowchart describes the process of obtaining the circuit board design parameters and establishing the impedance model. First, obtain the circuit board design parameters, establish an initial impedance model in combination with the geometric parameters, calculate the impedance value of the signal transmission path, and determine whether it exceeds the preset range; if it exceeds the range, adjust the trace width and copper foil thickness, and recalculate the impedance value, optimize the impedance matching using via and buried via parameters, and finally generate an impedance distribution map to judge the consistency of the signal transmission path, and complete the establishment of the initial impedance model and parameter adjustment.

[0164] In summary, the present invention provides a method for calibrating the impedance of a circuit board, the method comprising: obtaining 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 the etching process and immersion gold process; performing parameter optimization operations 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 corrected impedance model; performing error compensation on the corrected impedance model and calculating an impedance prediction value, performing error judgment on the impedance prediction value and the actual impedance value to obtain an initial impedance prediction value; performing iterative compensation on the initial impedance prediction value based on the gradient descent optimization algorithm, and obtaining an optimized impedance prediction value through condition judgment; performing judgment operations according to the optimized impedance prediction value and a preset impedance threshold to obtain a final impedance prediction value; performing test operations according to the final impedance prediction value, and calculating the rolling variance of the test, comparing the rolling variance with a preset stability threshold to obtain a stability test result; performing judgment operations according to the stability test result and preset conditions to generate a final impedance calibration report; and performing an update operation on the circuit board production process parameters according to the impedance calibration report to generate a new circuit board production guidance document, and completing the calibration of the circuit board impedance.

[0165] This method uses a computer system to collect and process circuit board design parameters. By establishing an initial impedance model and correcting it in combination with manufacturing process fluctuations, precise control of impedance prediction is achieved. This method uses the gradient descent algorithm to iteratively compensate the impedance prediction value and verifies the system stability through multiple tests. The innovation lies in closely integrating impedance optimization with production process parameters. By real-time adjusting the test probe parameters and contact pressure, the accuracy of impedance calibration is ensured. Finally, based on the optimized impedance calibration report, this method updates the circuit board production process parameters, generates a new production guidance document, 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.

[0166] Referring to Figure 4 , the second embodiment of the present invention provides a calibration system for the impedance of a circuit board, including:

[0167] A data acquisition module 101, configured to acquire circuit board design parameters, where the circuit board design parameters include trace width, copper foil thickness, dielectric material characteristic data, probability of poor contact, and fluctuation range data of etching process and immersion gold process;

[0168] An initial impedance model establishment module 102, configured to perform parameter optimization operations on the circuit board design parameters to obtain optimized parameters, and establish an initial impedance model according to the optimized parameters;

[0169] A corrected impedance model establishment module 103, configured to perform parameter adjustments on the dielectric layer thickness and copper foil surface roughness in the initial impedance model according to the fluctuation range data to obtain a corrected impedance model;

[0170] An initial impedance prediction value acquisition module 104, configured to perform error compensation on the corrected impedance model and calculate an impedance prediction value, and perform error judgment on the impedance prediction value and the actual impedance value to obtain an initial impedance prediction value;

[0171] An optimized impedance prediction value acquisition module 105, configured to perform iterative compensation on the initial impedance prediction value based on the gradient descent optimization algorithm, and obtain an optimized impedance prediction value through condition judgment;

[0172] A final impedance prediction value acquisition module 106, configured to perform judgment operations according to the optimized impedance prediction value and a preset impedance threshold to obtain a final impedance prediction value;

[0173] An impedance calibration report acquisition module 107, configured to perform test operations according to the final impedance prediction value, calculate the rolling variance of the test, compare the rolling variance with a preset stability threshold for judgment to obtain a stability test result; perform judgment operations according to the stability test result and preset conditions to generate a final impedance calibration report;

[0174] The 108 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 document, and complete the calibration of the circuit board impedance.

[0175] It should be noted that the circuit board impedance calibration system provided by the embodiments of the present invention is used to execute all the process steps of the circuit board impedance calibration method in the above embodiments. The working principles and beneficial effects of the two correspond one by one, so they will not be elaborated here.

[0176] In summary, the present invention provides a method for calibrating the impedance of a circuit board. The method includes: obtaining circuit board design parameters, 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 immersion gold 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; adjusting the parameters of the dielectric layer thickness and copper foil surface roughness in the initial impedance model according to the fluctuation range data to obtain a corrected impedance model; performing error compensation on the corrected impedance model and calculating an impedance prediction value, and performing an error judgment on the impedance prediction value and the actual impedance value to obtain an initial impedance prediction value; based on the gradient descent optimization algorithm, performing iterative compensation on the initial impedance prediction value, and performing conditional judgment to obtain an optimized impedance prediction value; performing a judgment operation according to the optimized impedance prediction value and a preset impedance threshold to obtain a final impedance prediction value; performing a test operation according to the final impedance prediction value, and calculating the rolling variance of the test, comparing the rolling variance with a preset stability threshold to obtain a stability test result; performing a judgment operation according to the stability test result and a preset condition to generate a final impedance calibration report; updating the circuit board production process parameters according to the impedance calibration report, generating a new circuit board production guidance document, and completing the calibration of the circuit board impedance.

[0177] This method uses a computer system to collect and process circuit board design parameters, and realizes precise control of impedance prediction by establishing an initial impedance model and making corrections in combination with manufacturing process fluctuations. This method uses the gradient descent algorithm to perform iterative compensation on the impedance prediction value, and verifies the system stability through multiple tests. The innovation lies in closely combining impedance optimization with production process parameters, and ensuring the accuracy of impedance calibration by adjusting the test probe parameters and contact pressure in real time. Finally, based on the optimized impedance calibration report, this method updates the circuit board production process parameters, generates a new production guidance document, effectively improves the precision and consistency of circuit board manufacturing, and provides a reliable guarantee for the performance optimization of high-frequency and high-speed circuit boards.

[0178] An embodiment of the present invention also 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 calibration method program for the impedance of a circuit board. When the processor executes the computer program, the steps in the above-described embodiments of the calibration method based on the impedance of the circuit board are implemented, such as Figure 1 the step S1 shown. Alternatively, when the processor executes the computer program, the functions of each module / unit in the above-described device embodiments are implemented, such as the 101 data acquisition module.

[0179] Exemplarily, the computer program may be divided into one or more modules / units, and the one or more modules / units are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device.

[0180] The electronic device may be a computing device such as a desktop computer, a notebook, a palm computer, and a smart tablet. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above components are merely examples of the electronic device and do not constitute a limitation on the electronic device. The electronic device may include more or fewer components than the above, or combine certain components, or different components. For example, the electronic device may further include input / output devices, network access devices, a bus, etc.

[0181] The so-called processor may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the electronic device and connects various parts of the entire electronic device through various interfaces and lines.

[0182] The memory can be used to store the computer programs and / or modules. By running or executing the computer programs and / or modules stored in the memory, and by invoking the data stored in the memory, the processor can implement various functions of the electronic device. The memory mainly includes a program storage area and a data storage area. Among them, the program storage area can store the operating system, application programs required for at least one function (such as the sound playback function, the image playback function, etc.); the data storage area can store the data created according to the use of the mobile phone (such as audio data, phone book, etc.). In addition, the memory can include high-speed random access memory, and can also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices.

[0183] Among them, if the modules / units integrated in the electronic device are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above-mentioned embodiment methods of the present invention, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included 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, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0184] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0185] The specific embodiments described above further elaborate on the purpose, technical solutions, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the protection scope of the present invention. In particular, for those skilled in the art, any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope 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 fluctuation range data of immersion gold 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 of the etching process and the fluctuation range data of the gold immersion process, the thickness of the dielectric layer and the surface roughness of the copper foil in the initial impedance model are adjusted 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: The method adjusts the parameters of the dielectric layer thickness and the copper foil surface roughness in the initial impedance model according to the fluctuation range data of the etching process and the fluctuation range data of the gold plating process to obtain a modified impedance model, including: Determine the adjustment range of the dielectric layer thickness and the copper foil surface roughness according to the maximum and minimum values ​​in the fluctuation range data of the etching process and the fluctuation range data of the gold immersion process; 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 fluctuation range data of 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 of the etching process and the fluctuation range data of the gold immersion process 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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