High-frequency PCB signal integrity simulation method and system and storage medium

Abstract

The invention relates to the technical field of signal simulation, in particular to a high-frequency PCB signal integrity simulation method and system and a storage medium. Comprising the following steps: constructing a multilayer dielectric model of a high-frequency circuit board, and extracting electrical characteristic data to obtain signal waveform distribution; determining a reference time sequence based on signal waveform distribution, performing Monte Carlo simulation in combination with environmental factors, generating a plurality of signal distortion scenes, analyzing waveform distortion, and identifying a high-risk propagation path; extracting high-risk path segment feature data, constructing a signal integrity evaluation matrix, and analyzing a signal distortion root; adjusting multi-layer medium parameters according to a classification result, and generating optimized path configuration; extracting a signal integrity index, verifying the effectiveness of an optimized path, generating a comprehensive report, predicting the signal distortion probability, and providing a basis for the design of a high-frequency circuit board. According to the method, the problems of signal integrity analysis and optimization of the high-frequency PCB are solved, and accurate optimization of the signal propagation path and effective prediction of the signal distortion probability are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of signal simulation, and in particular to a high-frequency PCB board signal integrity simulation method and system and a storage medium. BACKGROUND

[0002] High-frequency PCB (Printed Circuit Board) signal integrity is a crucial part of electronic product design. With the high-frequency and high-speed of electronic devices, the requirements for circuit board design are becoming increasingly high. When signals propagate on PCB boards, they are affected by factors such as timing skew, signal distortion, crosstalk, reflection, etc., which can significantly affect signal quality and cause signal integrity problems. Therefore, how to effectively simulate and optimize the propagation behavior of signals on PCB boards to ensure signal integrity is the key to improving the performance of high-frequency PCB boards.

[0003] Currently, many existing technologies attempt to optimize signal transmission by analyzing the physical structure and electromagnetic characteristics of the circuit board. Traditional design methods rely on static electromagnetic field simulation and simple signal transmission models, however, in practical applications, the multi-layer medium of the circuit board, complex signal paths, and environmental factors such as temperature, humidity, etc., often result in more complex signal propagation behavior, and existing technologies often fail to fully consider these factors.

[0004] The technical solution of the present application is based on a multi-layer medium model, which extracts the electrical characteristics data of high-frequency circuit boards, uses advanced simulation technology, and combines the influence of environmental factors to accurately simulate the propagation behavior of signals in PCB boards. In this simulation process, the accurate determination of signal waveform distribution and timing skew position helps to identify potential signal distortion areas. By generating different environmental factor combinations through Monte Carlo simulation, the signal distortion scenarios can be predicted and optimized in the design stage to ensure the integrity of high-frequency signals. In addition, combined with the analysis of coupling effects and the identification of high-risk path segments, different distortion sources can be classified and optimized for adjustment to ensure the stability of signals in high-frequency environments, effectively reduce signal distortion, and provide design optimization suggestions to help designers accurately design circuit boards in complex working environments. SUMMARY

[0005] The present application provides a high-frequency PCB board signal integrity simulation method, system and storage medium, which is used to accurately simulate the propagation behavior of signals in high-frequency circuit boards through a multi-layer medium model, and combines the influence of environmental factors to optimize the transmission path of signals, ensure signal quality, and ultimately provide stable and reliable design reference.

[0006] In a first aspect, the present application provides a high-frequency PCB board signal integrity simulation method, the method comprising: Step S1: constructing a multi-layer medium model of the high-frequency circuit board, extracting electrical characteristic data of the high-frequency circuit board from the multi-layer medium model, simulating signal propagation behavior in the multi-layer medium, and obtaining signal waveform distribution; Step S2: determining a reference timing of signal propagation according to the signal waveform distribution, generating a plurality of signal distortion scenarios through Monte Carlo simulation by combining random variables of environmental factors, analyzing waveform distortion under different combinations of environmental factors, and determining a timing deviation position; for the timing deviation position, analyzing and obtaining interaction response data based on coupling effect, judging a high-risk propagation path segment based on the interaction response data, and obtaining a risk path set; Step S3: extracting feature data of the high-risk propagation path segment through the risk path set, constructing a signal integrity evaluation matrix based on the feature data, and obtaining a classification result of the signal distortion source through pattern recognition; Step S4: extracting a dominant factor according to the classification result, adjusting multi-layer medium parameters using an iterative optimization algorithm, generating an optimized propagation path configuration, simulating signal behavior according to the optimized propagation path configuration, obtaining waveform data, and if the waveform data and the measured deviation are less than a preset threshold, confirming that the reproduction is successful, and obtaining a debugging path; Step S5: extracting a signal integrity index through the debugging path, verifying the degree of reduction of coupling effect, verifying the effectiveness of the optimized path, and determining a stable range of environmental factor influence; generating comprehensive report data through the stable range, predicting signal distortion probability, and obtaining a reference basis for high-frequency circuit board design.

[0007] As a preferred technical solution of the present application, step S1 comprises: constructing a multi-layer medium model of the high-frequency circuit board, the model including dielectric constant, medium thickness, and conductor geometric parameters; extracting electrical characteristic data from the multi-layer medium model, the electrical characteristic data including resistance, inductance, capacitance, and admittance parameters; simulating signal propagation behavior in the multi-layer medium according to the electrical characteristic data through a finite element method, calculating electromagnetic field distribution of the high-frequency circuit board; determining signal propagation delay and attenuation characteristics in each layer of medium according to the electromagnetic field distribution, and generating a preliminary signal waveform distribution including time-domain waveform and amplitude variation data.

[0008] As a preferred technical solution of the present application, step S2 comprises: According to the signal waveform distribution, a reference timing of signal propagation is determined; a random variable of environmental factors is introduced, the random variable including temperature variation, humidity fluctuation and drift of dielectric constant caused by material aging; a plurality of signal distortion scenarios are generated through Monte Carlo simulation, the signal distortion scenarios including waveform distortion under different combinations of environmental factors; according to the signal distortion scenarios, deviation of waveform distortion from the reference timing is analyzed, and a potential timing deviation position is determined, the timing deviation position including offset points of rising and falling edges of signals; For the timing deviation position, coupling effects of the via and the adjacent trace are determined; through frequency domain analysis, interactive response data of the via and the adjacent trace are calculated, the interactive response data including crosstalk strength and reflection coefficient; it is judged whether the interactive response data exceeds a preset threshold; if the interactive response data exceeds the preset threshold, a path segment corresponding to the timing deviation position is marked as a high-risk propagation path segment; according to the marking result, a risk path set containing all high-risk propagation path segments is generated.

[0009] As a preferred technical solution of the present application, in step S3, the classification result of the signal distortion source is obtained, including: According to the risk path set, feature data of the high-risk propagation path segment is extracted, the feature data including path length, coupling strength and timing deviation amplitude; through the feature data, a signal integrity evaluation matrix of the high-frequency circuit board is constructed, the matrix including multi-dimensional path features and distortion parameters; through a neural network model, pattern recognition is performed on the signal integrity evaluation matrix, the neural network model including a convolution layer and a full connection layer; through the neural network model, a classification result of the signal distortion source is output, the classification result including distortion types caused by crosstalk, reflection and environmental factors.

[0010] As a preferred technical solution of the present application, in step S4, an optimized propagation path configuration is generated, including: According to the classification result, a dominant factor of signal distortion is determined, the dominant factor including temperature variation, material characteristics and geometric structure influence; for the dominant factor, an iterative optimization algorithm is adopted to adjust multi-layer medium parameters, the multi-layer medium parameters including dielectric constant and medium thickness; through the iterative optimization algorithm, an optimized propagation path configuration is generated, the propagation path configuration including adjusted conductor spacing and interlayer thickness; according to the optimized propagation path configuration, a simulation condition for problem reproduction is determined, the simulation condition including temperature range and signal frequency range.

[0011] As a preferred technical solution of the present application, in step S4, a debugging path is obtained, including: According to the optimized propagation path configuration, actual test environment parameters are set, the test environment parameters including working temperature and signal input condition; through electromagnetic simulation, propagation behavior of the signal in the optimized propagation path configuration is simulated, waveform data is generated, the waveform data including time domain waveform and frequency domain response; according to the waveform data, deviation from the actually measured signal is calculated, the deviation including amplitude difference and phase difference; if the deviation is less than a preset threshold, it is confirmed that the signal quality problem is successfully reproduced, a debugging path is generated, the debugging path including optimized path parameters.

[0012] As a preferred technical solution of the present application, in step S5, the stable range of the influence of environmental factors is determined, including: According to the debugging path, signal integrity indicators are extracted, the signal integrity indicators including eye height, jitter and bit error rate; through a finite element method, coupling effects in the debugging path are simulated, adjusted crosstalk and reflection data are calculated; according to the crosstalk and reflection data, the degree of reduction of the coupling effects is verified; through the signal integrity indicators and the degree of reduction of the coupling effects, the stable range of the influence of environmental factors is determined, the stable range including acceptable fluctuation intervals of temperature and humidity.

[0013] As a preferred technical solution of the present application, through the stable range, comprehensive report data is generated, signal distortion probability is predicted, and reference basis for high-frequency circuit board design is obtained, including: According to the stable range, comprehensive report data is generated, the comprehensive report data including signal integrity indicators, coupling effect data and environmental factor influence range; Through Monte Carlo simulation, based on the comprehensive report data, signal distortion probability is predicted, the signal distortion probability including distortion occurrence rate under different environmental conditions; According to the signal distortion probability, reference basis for high-frequency circuit board design is generated, the reference basis including optimized path parameters and environmental adaptability suggestions.

[0014] In a second aspect, the present application further provides a high-frequency PCB signal integrity simulation system for implementing the above method, the system including: A model construction unit is configured to construct a multi-layer dielectric model of a high-frequency circuit board, extract electrical characteristic data of the high-frequency circuit board from the multi-layer dielectric model, simulate propagation behavior of a signal in the multi-layer dielectric, and obtain signal waveform distribution. a distortion analysis unit configured to determine a reference timing of signal propagation according to the signal waveform distribution, generate a plurality of signal distortion scenarios by Monte Carlo simulation in combination with random variables of environmental factors, analyze waveform distortion under different combinations of environmental factors to determine a timing deviation position, analyze and obtain interaction response data based on coupling effects for the timing deviation position, determine a high-risk propagation path segment based on the interaction response data, and obtain a risk path set; a path evaluation unit configured to extract feature data of the high-risk propagation path segment from the risk path set, construct a signal integrity evaluation matrix based on the feature data, and obtain a classification result of a signal distortion source by pattern recognition; a path optimization unit configured to extract a dominant factor according to the classification result, adjust multi-layer medium parameters by using an iterative optimization algorithm, generate an optimized propagation path configuration, simulate signal behavior according to the optimized propagation path configuration, obtain waveform data, and confirm reproduction success if the waveform data has a deviation less than a preset threshold from actual measurement, and obtain a debugging path; a result generation unit configured to extract a signal integrity index from the debugging path, verify a coupling effect reduction degree, verify effectiveness of the optimized path, determine a stable range of environmental factor influence, generate comprehensive report data through the stable range, predict a signal distortion probability, and obtain a reference basis for high-frequency circuit board design.

[0015] In a third aspect, the present application further provides a computer readable storage medium, wherein the computer readable storage medium stores instructions, and the instructions are executed by a processor to implement the above method.

[0016] The present application has the following beneficial effects: The application extracts the electrical characteristic data of the circuit board, such as the dielectric constant, the conductor geometric parameter, the medium thickness and the like, by constructing a multi-layer medium model of the high-frequency circuit board, thereby accurately simulating the propagation behavior of the signal in the multi-layer medium, simulating the electromagnetic field distribution of the signal by using the finite element method, obtaining the time-domain waveform and amplitude variation data of the signal, and ensuring the accurate generation of the signal waveform, thereby laying a foundation for subsequent distortion analysis; based on the signal waveform distribution, the reference timing of signal propagation is determined, and the random variables of environmental factors, such as temperature, humidity, material aging and the like, are introduced, a plurality of signal distortion scenarios are generated by Monte Carlo simulation, thereby being able to consider the waveform distortion under different environmental conditions and identify the timing deviation position. By analyzing the coupling effect, the high-risk propagation path is identified, and a risk path set is generated, thereby providing a basis for subsequent signal optimization; by extracting the characteristic data of the high-risk propagation path segment, such as the path length, the coupling strength and the timing deviation amplitude, a signal integrity evaluation matrix is constructed, the matrix is analyzed by pattern recognition combined with a neural network model, and the signal distortion sources, such as crosstalk, reflection and the like, are classified, thereby providing a clear direction for the subsequent optimization step; based on the classification result, the multi-layer medium parameters, such as the dielectric constant, the medium thickness and the like, are adjusted by an iterative optimization algorithm, and an optimized propagation path configuration is generated; the optimized path configuration generates new waveform data by simulating the signal behavior, and the new waveform data is compared with the measured data, if the waveform data deviation from the measured data is less than a preset threshold, it is confirmed that the reproduction is successful, and the effectiveness of the optimization is further verified; by optimizing the path configuration, the signal integrity index is extracted, the reduction degree of the coupling effect is verified, the stable range of the environmental factors on the signal propagation is determined, and a comprehensive report data is generated, thereby predicting the signal distortion probability, providing a reliable reference basis for the high-frequency circuit board design; the above comprehensive report provides stable design guidance for engineers, thereby ensuring the signal stability and efficient transmission of the high-frequency circuit board in the actual environment; through the mutual cooperation between the above technical solutions, a comprehensive simulation and optimization means is provided for the signal integrity of the high-frequency PCB board, thereby greatly improving the design accuracy and signal stability, and being suitable for the actual needs in the design and development of the high-frequency circuit board. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creating labor based on these drawings.

[0018] Figure 1 A high-frequency PCB signal integrity simulation method flowchart in the embodiment; Figure 2 A risk path set acquisition flowchart in the embodiment; Figure 3 This is a structural diagram of a high-frequency PCB board signal integrity simulation system in an embodiment. Detailed Implementation

[0019] This invention provides a method, system, and storage medium for simulating signal integrity on a high-frequency PCB board. The terms "first," "second," "third," "fourth," etc. (if present)," in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" or "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0020] For ease of understanding, the specific process of the embodiments of the present invention will be described below, such as... Figure 1 As shown in the figure, a high-frequency PCB board signal integrity simulation method in an embodiment of the present invention includes: Step S1: Construct a multilayer dielectric model of the high-frequency circuit board, extract the electrical characteristic data of the high-frequency circuit board from the multilayer dielectric model, simulate the signal propagation behavior in the multilayer dielectric, and obtain the signal waveform distribution; specifically including: A multilayer dielectric model of a high-frequency circuit board is constructed, the model including dielectric constant, dielectric thickness, and conductor geometric parameters. Electrical characteristic data, including resistance, inductance, capacitance, and admittance parameters, are extracted from the multilayer dielectric model. Using the finite element method, the propagation behavior of signals in the multilayer dielectric is simulated based on the electrical characteristic data, and the electromagnetic field distribution of the high-frequency circuit board is calculated. Based on the electromagnetic field distribution, the propagation delay and attenuation characteristics of signals in each dielectric layer are determined, and a preliminary signal waveform distribution is generated, including time-domain waveform and amplitude variation data.

[0021] Specifically, in the present embodiment, firstly, the high-frequency circuit board and the modeling tool are scanned by the scanning device to construct a multi-layer medium model of the high-frequency circuit board, the model including dielectric constant, medium thickness and conductor geometric parameters related to the circuit board material, the parameters being key physical properties describing the circuit board structure, wherein the model is constructed to accurately reflect the actual situation of the multi-layer medium structure by obtaining the above-mentioned layer structure data and combining specific requirements in the actual working environment of the circuit board; the electric characteristic data is extracted from the constructed multi-layer medium model, including resistance, inductance, capacitance and admittance parameters, which are important physical quantities describing signal propagation characteristics, wherein the resistance parameter is calculated based on the conductor geometric parameter, i.e. the circuit board trace geometric parameter, such as the width and thickness of the conductor, while the inductance and capacitance are derived from the structure characteristics through standard formulas, and the admittance parameter is extracted according to the medium thickness and other influencing factors, the extracted electric characteristic data providing basic data support for the signal propagation behavior; the signal propagation behavior in the multi-layer medium is also simulated by the finite element method, wherein the finite element method is a numerical simulation technique, which discretizes the multi-layer medium model of the circuit board into a plurality of finite elements, and solves the electromagnetic field of each element, i.e. by converting the Maxwell equation set into a matrix form, the electromagnetic field intensity and direction of each grid element are iteratively calculated by numerical calculation, so as to obtain the overall electromagnetic field distribution, in order to improve the accuracy, the grid density of different regions is also optimized, especially in the high-frequency region, the grid is refined to capture the rapid change of the field distribution, the distribution of the above-mentioned electromagnetic field directly affects the signal propagation delay and attenuation characteristics, and provides an important basis for subsequent signal waveform analysis.

[0022] Based on the above electromagnetic field distribution, the signal propagation delay and attenuation characteristics in each layer of medium are determined, specifically by integrating the phase information in the electromagnetic field distribution, the signal propagation delay can be calculated; at the same time, based on the dielectric constant and thickness of the medium, combined with the change of electric field intensity, the signal attenuation characteristics are analyzed, wherein the signal propagation delay and attenuation characteristics are key factors in signal integrity evaluation, which determine the timing and amplitude characteristics of the signal; the frequency domain data is also converted into time domain waveform by Fourier transform to generate preliminary signal waveform distribution, including time domain waveform and amplitude change data, so as to ensure the accurate generation of signal waveform and provide basic data for subsequent signal integrity analysis; through the above technical solution, not only the signal propagation characteristics are accurately modeled, but also the signal propagation path configuration in the circuit board design is optimized, providing necessary signal waveform data for signal distortion analysis.

[0023] Step S2: According to the signal waveform distribution, determine the reference timing of signal propagation, combine the random variables of environmental factors, generate multiple signal distortion scenarios through Monte Carlo simulation, analyze the waveform distortion under different environmental factor combinations, and determine the timing deviation position; for the timing deviation position, analyze and obtain the interactive response data based on the coupling effect, judge the high-risk propagation path segment based on the interactive response data, and obtain the risk path set; as shown in Figure 2 Specifically, it includes: According to the signal waveform distribution, determine the reference timing of signal propagation; introduce random variables of environmental factors, including temperature changes, humidity fluctuations, and material aging drifts of dielectric constant; generate multiple signal distortion scenarios through Monte Carlo simulation, including waveform distortion under different environmental factor combinations; according to the signal distortion scenario, analyze the waveform distortion and the deviation of the reference timing, and determine the potential timing deviation position, including the shift point of signal rising edge and falling edge; For the timing deviation position, determine the coupling effect of the via and the adjacent trace; through frequency domain analysis, calculate the interactive response data of the via and the adjacent trace, including crosstalk strength and reflection coefficient; judge whether the interactive response data exceeds the preset threshold; if the interactive response data exceeds the preset threshold, mark the path segment corresponding to the timing deviation position as a high-risk propagation path segment; according to the marking result, generate a risk path set containing all high-risk propagation path segments.

[0024] Specifically, in the present embodiment, according to the signal waveform distribution, the reference timing of signal propagation is first determined; specifically, by analyzing the peak and valley positions in the preliminary signal waveform distribution, the standard propagation time of the signal from the source end to the receiving end is calculated, thereby determining the reference timing, wherein the key time points in the signal waveform are extracted first, including the starting point and the ending point of the signal, the average propagation delay is calculated based on these time points, and the reference timing value is further formed; a random variable of environmental factors is also introduced, the above random variable includes the drift of dielectric constant caused by temperature change, humidity fluctuation and material aging, so as to ensure the accurate simulation of signal propagation characteristics under different environmental conditions, wherein the influence of temperature change, humidity fluctuation and material aging is modeled by setting a reasonable probability distribution, temperature change is described by normal distribution, and humidity fluctuation and material aging adopt a distribution function consistent with the actual environmental conditions; on the basis of the above random variable, a variable sample set is generated, which will be used as the input of subsequent signal propagation simulation; by using the Monte Carlo simulation method, a plurality of signal distortion scenarios are generated by repeatedly iterating and calculating the samples extracted from the random variable distribution, the above scenarios cover waveform distortion under different combinations of environmental factors, and in the simulation process, the distortion degree of each waveform in the scene is compared with the deviation of the reference timing, the behavior change of the signal under various environments is analyzed; and the distortion of the signal waveform is calculated through multiple iterations and random sampling, and a distortion scenario set is generated, by collecting the waveform data generated by the above iterations, a distortion scenario set is formed, and according to the above data, the waveform distortion and the deviation of the reference timing are further analyzed, especially the shift points of the rising edge and the falling edge of the signal, these timing deviation points provide a basis for subsequent optimization design.

[0025] In the analysis process, by calculating the timing difference between the signal waveform and the reference timing in each distortion scenario, those deviation points whose difference exceeds the preset threshold are identified and marked as potential timing deviation positions, by further classifying the above timing deviation positions, combining factors such as temperature change and humidity fluctuation, the dominant factor of the distortion scenario is determined, and then guiding the subsequent signal integrity optimization; for example, temperature change may cause the shift of the signal rising edge, while humidity fluctuation may affect the timing stability of the signal falling edge; based on the above analysis results, the dielectric parameters are adjusted specifically, the signal propagation path configuration is optimized, thereby effectively reducing the timing deviation and ensuring the integrity of the signal and the stable propagation of the signal in complex environment, providing a scientific basis for the design and optimization of high-frequency PCB circuit board.

[0026] For the above timing skew positions, the coupling effect of the via and the adjacent trace is determined, that is, after extracting the timing skew positions, the via structure and the adjacent trace path existing in these positions are identified, and the electromagnetic coupling relationship between them is evaluated, based on the electrical characteristic data in the multi-layer medium model, the geometric distance between the via and the adjacent trace and the dielectric constant of the medium are further positioned, so as to preliminarily determine the existence form of the coupling effect; the interactive response data of the above via and adjacent trace is calculated through frequency domain analysis, the interactive response data includes crosstalk strength and reflection coefficient, wherein the crosstalk strength reflects the signal interference degree between adjacent traces, and the reflection coefficient measures the reflection of the signal at the via, by converting the time domain signal into the frequency domain, the frequency spectrum distribution is calculated by using Fourier transform, and the crosstalk strength and the reflection coefficient are further quantified, which provides accurate data for identifying possible signal distortion paths, wherein the crosstalk strength can be obtained by calculating the power spectral density ratio, and the reflection coefficient is calculated by the impedance mismatch formula, to ensure the accuracy of the data.

[0027] In order to better simulate the influence of environmental changes, Monte Carlo simulation is introduced to model the drift of dielectric constant caused by temperature change, so as to adjust the frequency domain analysis parameters and generate interactive response data under different combinations of environmental factors, the calculated crosstalk strength and reflection coefficient are compared with the corresponding preset threshold, if any one of the crosstalk strength and the reflection coefficient exceeds the corresponding preset threshold, these path segments will be marked as high-risk propagation paths, so that the potential signal distortion area can be effectively identified, and timely path adjustment can be made to avoid unnecessary errors in design; the timing skew positions marked as high-risk path segments are added to the risk path set, and all marked paths are summarized to form a risk path set, ensuring that the integrity of the signal is fully guaranteed. In addition, through parallel processing of different scenarios, the analysis efficiency is further improved, especially for complex multi-layer circuit board layout, when parallel processing the frequency domain data of multiple pairs of vias and traces, the evaluation efficiency of crosstalk strength can be significantly improved, and the signal integrity is further optimized; through the above technical scheme, the propagation behavior of the signal under different environments can be comprehensively captured, and the high-risk propagation path can be accurately identified and marked, which provides reliable data support and optimization basis for signal integrity simulation of high-frequency PCB board.

[0028] Step S3: extracting feature data of high-risk propagation path segments through the risk path set, constructing a signal integrity evaluation matrix based on the feature data, and obtaining a classification result of the signal distortion source through pattern recognition; specifically including: extracting feature data of high-risk propagation path segments according to the risk path set, the feature data including path length, coupling strength and timing deviation amplitude; constructing a signal integrity evaluation matrix of the high-frequency circuit board through the feature data, the matrix including multi-dimensional path features and distortion parameters; performing pattern recognition on the signal integrity evaluation matrix through a neural network model, the neural network model including a convolution layer and a full connection layer; outputting a classification result of the signal distortion source through the neural network model, the classification result including distortion types caused by crosstalk, reflection and environmental factors.

[0029] Specifically, in the present embodiment, by selecting the propagation path segments marked as high-risk from the above risk path set, the path length, i.e. the physical distance from the starting point to the ending point, is calculated for each segment, wherein the above physical distance can be measured by a geometric modeling tool to ensure the accuracy of the feature data and provide reliable basis for subsequent matrix construction, the degree of interaction is determined by measuring the capacitance and inductance values between adjacent traces to evaluate the electromagnetic coupling relationship between the above traces; at the same time, based on the preliminary signal waveform distribution, the difference between the actual propagation time and the ideal time is calculated, thereby obtaining the timing deviation amplitude of each high-risk path segment; through the above feature data, a signal integrity evaluation matrix of the high-frequency circuit board is constructed, the matrix contains multi-dimensional path features and distortion parameters, wherein the path length, coupling strength and timing deviation amplitude are combined as the row vectors of the matrix and are integrated into distortion parameters such as signal amplitude attenuation and phase shift to form a multi-dimensional matrix structure, the above matrix not only can quantify the correlation between paths, but also provides data support for subsequent pattern recognition.

[0030] The neural network model includes a convolutional layer and a fully connected layer, wherein the convolutional layer is used to extract local features, such as the spatial correlation of path length and coupling strength, and the size and stride of the convolutional kernel are adjusted according to specific requirements to ensure effective processing of multi-dimensional path features and distortion parameters in the matrix. The feature data output by the convolutional layer is transmitted to the fully connected layer, which calculates the global pattern through a weight matrix, processes the nonlinear relationship using a ReLU activation function, and finally outputs the distortion type through a softmax function. The neural network model is trained using multiple signal distortion scenarios generated from Monte Carlo simulation as a dataset to optimize parameters to identify patterns such as crosstalk. The convolutional layer of the neural network model can handle distortions dominated by temperature changes, reducing classification errors through iterative training to provide more accurate root cause identification and optimize propagation path configuration. In addition, for different high-frequency circuit board scenarios, the fully connected layer of the neural network model can expand hidden units to enhance the ability to identify timing deviation amplitudes, thereby reducing the error of signal distortion probability prediction. During processing, the convolutional layer extracts features that reveal crosstalk patterns when coupling strength exceeds a threshold, while the fully connected layer integrates and outputs classification results, thereby improving the efficiency of the evaluation matrix and achieving more stable signal behavior simulation. Through the neural network model, the classification results of the signal distortion root cause are output, including distortion types caused by crosstalk, reflection, and environmental factors. The classification results are directly used to generate optimized propagation path configurations, providing a reference for high-frequency circuit board design. For example, in a multi-layer dielectric model of a high-frequency circuit board, if the classification result is a crosstalk type, the path length is adjusted to reduce coupling strength and improve signal integrity indicators. If the distortion is caused by reflection, the classification result guides the iterative optimization algorithm to modify the medium parameters, verify the degree of coupling effect reduction, and predict future signal distortion probability. For distortion caused by environmental factors, the classification result can analyze the impact of temperature drift on the dielectric constant, generate comprehensive report data, support signal behavior simulation in actual test environments, and determine the simulation conditions for problem reproduction, thereby providing a stable range of debugging paths and ensuring the reliability and optimization effect of circuit board design.

[0031] Step S4: According to the classification result, extract the dominant factor, use the iterative optimization algorithm to adjust the multi-layer medium parameters, and generate the optimized propagation path configuration; according to the optimized propagation path configuration, simulate the signal behavior, obtain the waveform data, if the waveform data and the measured deviation are less than the preset threshold, it is confirmed that the reproduction is successful, and the debugging path is obtained; In step S4, the optimized propagation path configuration is generated, including: According to the classification result, a dominant factor of signal distortion is determined, the dominant factor including temperature variation, material property and geometric structure influence; for the dominant factor, an iterative optimization algorithm is adopted to adjust multi-layer medium parameters, the multi-layer medium parameters including dielectric constant and medium thickness; through the iterative optimization algorithm, an optimized propagation path configuration is generated, the propagation path configuration including adjusted conductor spacing and interlayer thickness; according to the optimized propagation path configuration, a simulation condition of problem reproduction is determined, the simulation condition including temperature range and signal frequency range.

[0032] Specifically, in the embodiment, by analyzing the classification result, the weight value of each dominant factor is extracted, and the weight value is sorted to ensure that the factor with the greatest impact is processed first, thereby improving the optimization efficiency. The dominant factors include temperature variation, material property and geometric structure influence. For the above dominant factors, an iterative optimization algorithm is used to adjust the multi-layer medium parameters, including dielectric constant and medium thickness. Specifically, based on the initial value, the dielectric constant and thickness are continuously adjusted by algorithms such as gradient descent to simulate the influence of temperature variation on dielectric constant, evaluate the influence of material property on signal propagation path, and adjust the coupling effect of geometry on signal, thereby achieving the purpose of optimizing signal propagation. In the optimization process, one or more parameters are adjusted each time. After multiple iterations, the optimization algorithm can gradually approach the minimum signal distortion point, ensuring that the propagation path of the signal is as stable and reliable as possible under actual use conditions. Through the above iterative process, the generated optimized propagation path configuration includes adjusted conductor spacing and interlayer thickness. The above configuration can effectively reduce signal distortion and improve the stability and reliability of the circuit board. After completing the path configuration optimization, the simulation conditions of problem reproduction are determined according to the generated optimization configuration. The simulation conditions include temperature range and signal frequency range. The above conditions can cover typical application scenarios of high-frequency circuit boards and verify the reproducibility of signal behavior through simulation. For example, after optimizing the propagation path configuration, the changes in temperature range and different signal frequencies are simulated to analyze their influence on signal waveform, ensuring the effectiveness of the optimized configuration in the actual test environment. Through the above simulation conditions, the performance of the optimized design under different environments, such as waveform deviation of signal frequency within the set range, can be verified, thereby confirming the effectiveness of the optimized path and providing a basis for subsequent design adjustment. The above technical solution, by combining the above iterative optimization algorithm and simulation verification, generates an optimized propagation path configuration that provides a stable signal integrity foundation for high-frequency circuit board design and effectively reduces the probability of signal distortion, enhancing the robustness and reliability of the circuit board. It can ensure the stable propagation of signals under complex environmental conditions, provide a targeted solution, and improve the accuracy and practicality of circuit board design.

[0033] Further, in step S4, the debug path is obtained, including: According to the optimized propagation path configuration, actual test environment parameters are set, the test environment parameters including working temperature and signal input condition; through electromagnetic simulation, propagation behavior of the signal in the optimized propagation path configuration is simulated, waveform data is generated, the waveform data including time domain waveform and frequency domain response; according to the waveform data, deviation from the actually measured signal is calculated, the deviation including amplitude difference and phase difference; if the deviation is less than a preset threshold, it is confirmed that the signal quality problem is successfully reproduced, a debugging path is generated, the debugging path including the optimized path parameters.

[0034] Specifically, in the embodiment, according to the optimized propagation path configuration described above, actual test environment parameters are first set, the test environment parameters including working temperature and signal input condition, wherein the working temperature is set to a specific value within a certain range, and the signal input condition is defined, for example, input voltage amplitude and frequency, etc., to match the actual high-frequency circuit board test scene, through electromagnetic simulation, propagation behavior of the signal in the optimized propagation path configuration is simulated, the generated waveform data including time domain waveform and frequency domain response, specifically, a multi-layer medium model is constructed by using finite element method, the optimized propagation path parameters such as dielectric constant and medium thickness are applied to the model, so as to simulate the propagation characteristics of the signal in the configuration, and generate preliminary waveform distribution; through frequency domain analysis, via hole interaction response data is obtained, and time sequence deviation position of signal propagation is analyzed in detail; if the calculation result shows that the interaction response exceeds the preset threshold, such as the crosstalk intensity or the reflection coefficient exceeding the set threshold, these paths are marked as high-risk paths, and then the frequency domain response part of the waveform data is expanded, so as to help identify the potential distortion source and further optimize the design; further, through Monte Carlo simulation, random variables such as temperature drift are introduced, to generate multiple distortion scenes, which helps to expand the coverage of the waveform data generation process, and ensures the reliability of the signal under different environmental conditions.

[0035] According to the generated waveform data, the deviation between the measured signal is calculated, including amplitude difference and phase difference, if the deviation is less than the preset threshold, it is confirmed that the signal quality problem has reappeared, and then a debugging path is generated, the above debugging path includes optimized path parameters, the above debugging path reflects the parameters adjusted in the optimization process, such as dielectric constant, medium thickness, conductor spacing, etc., the above adjustment helps to improve signal integrity, reduce distortion, and improve the stability of the design; further extract the dominant factors from the classification results, such as temperature change dominated distortion, which can adjust the medium parameters through iterative optimization algorithm to ensure that the optimized configuration can effectively reduce signal distortion and achieve ideal signal quality. When the deviation meets the requirements through simulation verification, the debugging path can be used as the final design basis to ensure that the signal propagation path of the high-frequency circuit board reaches the best configuration; the above technical scheme, through multiple iterations and verification, the optimized propagation path can significantly reduce the interference of environmental factors, not only ensures the reproduction of signal quality, but also provides a stable reference basis for the design in the actual test environment.

[0036] Step S5: Extract signal integrity indicators through the debugging path, verify the reduction degree of coupling effect, verify the effectiveness of the optimized path, and determine the stable range of environmental factor influence; generate comprehensive report data through the stable range, predict signal distortion probability, and obtain a reference basis for high-frequency circuit board design.

[0037] Among them, in step S5, the stable range of environmental factor influence is determined, including: According to the debugging path, the signal integrity indicators are extracted, including eye height, jitter and bit error rate; the coupling effect in the debugging path is simulated by the finite element method, and the adjusted crosstalk and reflection data are calculated; according to the crosstalk and reflection data, the reduction degree of coupling effect is verified; through the signal integrity indicators and the reduction degree of coupling effect, the stable range of environmental factor influence is determined, and the stable range includes the acceptable fluctuation range of temperature and humidity.

[0038] Specifically, in the present embodiment, according to the above debugging path, first, the signal integrity indicators are extracted, including eye height, jitter and bit error rate, wherein the eye height of the signal is obtained through the eye diagram analysis tool, the eye height reflects the vertical opening size of the signal amplitude in the eye diagram, and generally a larger eye height indicates good signal transmission; the jitter, i.e. the fluctuation of the signal timing, is measured, and generally its peak-to-peak value is calculated, and the bit error rate, indicating the error probability of each transmission bit, is estimated; the signal integrity indicators are directly extracted from the optimized propagation path configuration, providing basic data for subsequent signal quality verification; the coupling effect in the debugging path is also simulated by the finite element method, and the adjusted crosstalk and reflection data are calculated, specifically, a finite element grid model is first constructed, the optimized propagation path configuration is applied to the model, and electrical property data such as dielectric constant and conductor geometry are input, the Maxwell equations are solved by the finite element method to obtain the electromagnetic field distribution, so that the interaction response of the via and the adjacent trace can be accurately captured, and the crosstalk and reflection data are calculated, wherein the crosstalk data are solved by the integral path method, and the reflection data are obtained by time domain reflectometry simulation to ensure the accuracy of the calculation results.

[0039] According to the calculated crosstalk and reflection data, the degree of reduction of the coupling effect is further verified. For example, by comparing the crosstalk values before and after optimization, if it is reduced by more than a certain threshold, the effectiveness of the optimization can be confirmed, and this step can ensure the effectiveness and accuracy of the signal integrity optimization path; after obtaining the crosstalk and reflection data, the influence range of environmental factors on signal propagation is determined by combining the signal integrity indicators and the degree of reduction of the coupling effect, the stable range includes the acceptable fluctuation interval of temperature and humidity, and aims to determine whether the signal can maintain its stability and reliability under specific environmental conditions; for example, by Monte Carlo simulation, the temperature and humidity parameters are randomly varied to simulate multiple different environmental scenarios, and the parameter interval that remains stable under specific environments is identified; in combination with the above analysis results, it is determined that when the temperature fluctuation and humidity fluctuation are within the acceptable range, the signal integrity indicators can be maintained within the predetermined threshold, thereby providing a reliable stable range for the actual application of the circuit board; the above technical solution realizes comprehensive evaluation of signal integrity and coupling effect, determines the signal stability of high-frequency PCB under different working conditions in combination with the influence of environmental factors, not only improves the accuracy of signal integrity evaluation, but also provides a solid foundation for subsequent design optimization and actual application.

[0040] Further, in step S5, reference basis for high-frequency circuit board design is obtained, including: According to the stable range, comprehensive report data is generated, including signal integrity indicators, coupling effect data and environmental factor influence range; predicting, by Monte Carlo simulation, signal distortion probability based on the comprehensive report data, the signal distortion probability including distortion occurrence rates under different environmental conditions; generating, according to the signal distortion probability, a reference basis for high-frequency circuit board design, the reference basis including optimization path parameters and environmental adaptability suggestions.

[0041] Specifically, the comprehensive report data is generated according to the above-mentioned stable range. The report data includes signal integrity indicators such as eye width, jitter value, etc. The indicators reflect the transmission quality of the signal after optimization of the propagation path. At the same time, the report data also integrates the coupling effect data verified by the finite element method, especially the via interaction response level, to further analyze the electromagnetic interference between different dielectric layers and circuit paths. In addition, the report also summarizes the environmental factor influence range, such as the dielectric constant change interval caused by temperature change, humidity fluctuation, etc. to provide comprehensive basic data for subsequent signal integrity analysis. The above process effectively integrates various data to ensure the accuracy and consistency of subsequent signal simulation. After generating the comprehensive report data, the signal distortion probability is predicted by the Monte Carlo simulation method. Monte Carlo simulation is a statistical sampling technique that simulates the distortion degree of signal waveform by randomly sampling different environmental factors such as temperature and humidity, and calculates the distortion probability through multiple iterations. During the simulation process, multiple possible distortion scenarios are generated based on the key signal integrity indicators and environmental factor influence range in the comprehensive report data. The distortion occurrence rate is estimated based on the calculation results of each sampling point. Through a large number of random sampling and calculation, the change trend of signal distortion probability under different environmental conditions can be effectively captured, improving the prediction accuracy of signal behavior under complex environments.

[0042] According to the predicted signal distortion probability, a reference basis for high-frequency circuit board design is generated, which includes extracting high-risk environmental conditions such as environmental ranges with distortion occurrence rates exceeding a set threshold by analyzing the distortion probability, and generating corresponding optimization path parameters accordingly, wherein the generation of optimization path parameters generally includes adjusting key design parameters such as trace spacing and dielectric thickness to reduce coupling effects and improve signal transmission quality; at the same time, the reference basis also includes adaptive suggestions for specific temperature, humidity and other environmental conditions, such as increasing the heat dissipation layer or using temperature compensation materials in high temperature environment to reduce the impact of temperature fluctuations on signal quality, the above optimization measures will be used as a reference basis for circuit board design, directly applied to the subsequent circuit board design process, to improve the performance and reliability of the overall design; the above technical solution, through the effective integration of signal integrity indicators, coupling effect data and environmental factor influence range, and through the Monte Carlo simulation method to accurately predict the signal distortion probability, the finally generated reference basis not only improves the accuracy of the design, but also effectively predicts and optimizes the performance of high-frequency circuit boards under different environmental conditions, providing more reliable and efficient design reference.

[0043] The application also provides a high-frequency PCB board signal integrity simulation system for implementing the above method, as shown in Figure 3 The system comprises: A model construction unit is configured to construct a multi-layer dielectric model of a high-frequency circuit board, extract electrical characteristic data of the high-frequency circuit board from the multi-layer dielectric model, simulate the propagation behavior of a signal in the multi-layer dielectric, and obtain signal waveform distribution. A distortion analysis unit is configured to determine a reference timing of signal propagation according to the signal waveform distribution, combine random variables of environmental factors, generate a plurality of signal distortion scenarios through Monte Carlo simulation, analyze waveform distortion under different combinations of environmental factors, and determine timing deviation positions; for the timing deviation positions, analyze and obtain interaction response data based on coupling effects, judge high-risk propagation path segments based on the interaction response data, and obtain a risk path set. A path evaluation unit is configured to extract feature data of high-risk propagation path segments through the risk path set, construct a signal integrity evaluation matrix based on the feature data, and obtain a classification result of signal distortion sources through pattern recognition. A path optimization unit is configured to extract dominant factors according to the classification result, adjust multi-layer dielectric parameters using an iterative optimization algorithm, and generate an optimized propagation path configuration; simulate signal behavior according to the optimized propagation path configuration, obtain waveform data, and if the waveform data and the measured deviation are less than a preset threshold, it is confirmed that the reproduction is successful, and a debugging path is obtained. A result generation unit is configured to extract a signal integrity index through the debugging path, verify a coupling effect reduction degree, verify effectiveness of an optimized path, and determine a stable range of environmental factor influence; generate comprehensive report data through the stable range, predict a signal distortion probability, and obtain a reference basis for high-frequency circuit board design.

[0044] The application further provides a computer readable storage medium, which stores instructions, and the instructions are executed by a processor to implement the method.

[0045] In summary, the application constructs a multi-layer medium model of a high-frequency circuit board, extracts electrical characteristic data of the circuit board, such as dielectric constant, conductor geometric parameters, medium thickness, and the like, thereby accurately simulating signal propagation behavior in the multi-layer medium, simulates electromagnetic field distribution of the signal by using a finite element method, and obtains time-domain waveform and amplitude variation data of the signal, thereby ensuring accurate generation of the signal waveform and laying a foundation for subsequent distortion analysis; based on signal waveform distribution, a reference timing of signal propagation is determined, and random variables of environmental factors, such as temperature, humidity, material aging, and the like, are introduced, a plurality of signal distortion scenarios are generated by Monte Carlo simulation, thereby being able to consider waveform distortion under different environmental conditions and identify timing deviation positions. By analyzing coupling effects, high-risk propagation paths are identified, and a risk path set is generated, thereby providing a basis for subsequent signal optimization; by extracting characteristic data of the high-risk propagation path segment, such as path length, coupling strength, and timing deviation amplitude, a signal integrity evaluation matrix is constructed, the matrix is analyzed by pattern recognition and a neural network model, signal distortion sources, such as crosstalk, reflection, and the like, are classified, and a clear direction is provided for subsequent optimization steps; based on the classification result, multi-layer medium parameters, such as dielectric constant, medium thickness, and the like, are adjusted by an iterative optimization algorithm, and an optimized propagation path configuration is generated; the optimized path configuration generates new waveform data by simulating signal behavior, and the new waveform data is compared with measured data, if waveform data deviation from the measured data is less than a preset threshold, it is confirmed that reproduction is successful, and effectiveness of the optimization is further verified; by the optimized path configuration, a signal integrity index is extracted, a coupling effect reduction degree is verified, a stable range of environmental factors on signal propagation is determined, and comprehensive report data is generated, a signal distortion probability is predicted, and a reliable reference basis is provided for high-frequency circuit board design; the above comprehensive report provides stable design guidance for engineers, thereby ensuring signal stability and efficient transmission of the high-frequency circuit board in an actual environment; through mutual cooperation between the above technical solutions, comprehensive simulation and optimization means are provided for signal integrity of a high-frequency PCB, thereby greatly improving design precision and signal stability, and being suitable for actual needs in high-frequency circuit board design and development.

[0046] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described system, system and unit can refer to the corresponding processes in the foregoing method embodiments, and will not be described here.

[0047] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application or the whole or part of the technical solutions that essentially contribute to the prior art can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0048] The above-described and above-mentioned embodiments are only used to illustrate the technical solutions of the present application, rather than limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some technical features. These modifications or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A high frequency PCB board signal integrity simulation method, characterized in that, Comprise: Step S1: Constructing a multi-layer medium model of the high-frequency circuit board, extracting electrical characteristic data of the high-frequency circuit board from the multi-layer medium model, simulating the propagation behavior of the signal in the multi-layer medium, and obtaining the signal waveform distribution; Step S2: According to the signal waveform distribution, determine the reference timing of signal propagation, combine the random variables of environmental factors, generate multiple signal distortion scenarios through Monte Carlo simulation, analyze the waveform distortion under different environmental factor combinations, and determine the timing deviation position; for the timing deviation position, analyze and obtain the interaction response data based on the coupling effect, judge the high-risk propagation path segment based on the interaction response data, and obtain the risk path set; Step S3: Through the risk path set, extract the feature data of the high-risk propagation path segment, construct a signal integrity evaluation matrix based on the feature data, and obtain the classification result of the signal distortion source through pattern recognition; Step S4: According to the classification result, extract the dominant factor, adjust the multi-layer medium parameters using an iterative optimization algorithm, and generate an optimized propagation path configuration; according to the optimized propagation path configuration, simulate the signal behavior, obtain the waveform data, and if the waveform data and the measured deviation are less than a preset threshold, it is confirmed that the reproduction is successful, and the debugging path is obtained; Step S5: Through the debugging path, extract the signal integrity index, verify the degree of reduction of the coupling effect, verify the effectiveness of the optimized path, and determine the stable range of the influence of environmental factors; through the stable range, generate comprehensive report data, predict the signal distortion probability, and obtain the reference basis for high-frequency circuit board design.

2. The method of claim 1, wherein, Step S1, comprising: Constructing a multi-layer medium model of the high-frequency circuit board, the model including dielectric constant, medium thickness, and conductor geometric parameters; extracting electrical characteristic data from the multi-layer medium model, the electrical characteristic data including resistance, inductance, capacitance, and admittance parameters; simulating the propagation behavior of the signal in the multi-layer medium according to the electrical characteristic data through the finite element method, calculating the electromagnetic field distribution of the high-frequency circuit board; determining the propagation delay and attenuation characteristics of the signal in each layer of medium according to the electromagnetic field distribution, generating a preliminary signal waveform distribution, the signal waveform distribution including time-domain waveform and amplitude variation data.

3. The method of claim 1, wherein, Step S2, comprising: According to the signal waveform distribution, determine the reference timing of signal propagation; introduce random variables of environmental factors, including temperature variation, humidity fluctuation, and material aging drift of dielectric constant; generate multiple signal distortion scenarios through Monte Carlo simulation, the signal distortion scenarios including waveform distortion under different environmental factor combinations; according to the signal distortion scenarios, analyze the waveform distortion and the deviation of the reference timing, determine the potential timing deviation position, the timing deviation position including the offset points of signal rising edge and falling edge; For the timing skew position, the coupling effect of the via and the adjacent trace is determined; through frequency domain analysis, the interaction response data of the via and the adjacent trace is calculated, the interaction response data including crosstalk strength and reflection coefficient; it is judged whether the interaction response data exceeds a preset threshold; if the interaction response data exceeds the preset threshold, the path segment corresponding to the timing skew position is marked as a high-risk propagation path segment; according to the marking result, a risk path set containing all high-risk propagation path segments is generated.

4. The method of claim 1, wherein, In step S3, the classification result of the signal distortion source is obtained, including: According to the risk path set, the feature data of the high-risk propagation path segment is extracted, the feature data including path length, coupling strength and timing skew amplitude; through the feature data, a signal integrity evaluation matrix of the high-frequency circuit board is constructed, the matrix including multi-dimensional path features and distortion parameters; through the neural network model, pattern recognition is performed on the signal integrity evaluation matrix, the neural network model including convolution layer and full connection layer; through the neural network model, the classification result of the signal distortion source is output, the classification result including distortion types caused by crosstalk, reflection and environmental factors.

5. The method of claim 1, wherein, In step S4, the optimized propagation path configuration is generated, including: According to the classification result, the dominant factor of signal distortion is determined, the dominant factor including temperature change, material characteristics and geometric structure influence; for the dominant factor, an iterative optimization algorithm is used to adjust multi-layer medium parameters, the multi-layer medium parameters including dielectric constant and medium thickness; through the iterative optimization algorithm, an optimized propagation path configuration is generated, the propagation path configuration including adjusted conductor spacing and layer thickness; according to the optimized propagation path configuration, the simulation conditions for problem reproduction are determined, the simulation conditions including temperature range and signal frequency range.

6. The method of claim 5, wherein, In step S4, the debugging path is obtained, including: According to the optimized propagation path configuration, the actual test environment parameters are set, the test environment parameters including working temperature and signal input condition; through electromagnetic simulation, the propagation behavior of the signal in the optimized propagation path configuration is simulated, waveform data is generated, the waveform data including time domain waveform and frequency domain response; according to the waveform data, the deviation from the measured signal is calculated, the deviation including amplitude difference and phase difference; if the deviation is less than a preset threshold, it is confirmed that the signal quality problem reproduction is successful, and a debugging path is generated, the debugging path including optimized path parameters.

7. The method of claim 1, wherein, In step S5, the stable range of environmental factor influence is determined, including: According to the debugging path, the signal integrity index is extracted, the signal integrity index including eye height, jitter and bit error rate; through the finite element method, the coupling effect in the debugging path is simulated, and the adjusted crosstalk and reflection data are calculated; according to the crosstalk and reflection data, the coupling effect reduction degree is verified; through the signal integrity index and the coupling effect reduction degree, the stable range of environmental factor influence is determined, the stable range including acceptable fluctuation intervals of temperature and humidity.

8. The method of claim 1, wherein, The comprehensive report data is generated through the stable range, a signal distortion probability is predicted, and a reference basis for high-frequency circuit board design is obtained, including: According to the stable range, comprehensive report data is generated, including signal integrity indicators, coupling effect data, and environmental factor influence range; Through Monte Carlo simulation, based on the comprehensive report data, the signal distortion probability is predicted, including the distortion occurrence rate under different environmental conditions; According to the signal distortion probability, a reference basis for high-frequency circuit board design is generated, including optimization path parameters and environmental adaptability suggestions.

9. A high frequency PCB board signal integrity simulation system for implementing the method according to any one of claims 1-8, characterized by The system comprises: A model construction unit is configured to construct a multi-layer medium model of a high-frequency circuit board, extract electrical characteristic data of the high-frequency circuit board from the multi-layer medium model, simulate signal propagation behavior in the multi-layer medium, and obtain signal waveform distribution; A distortion analysis unit is configured to determine a reference timing of signal propagation according to the signal waveform distribution, combine random variables of environmental factors, generate multiple signal distortion scenarios through Monte Carlo simulation, analyze waveform distortion under different environmental factor combinations, and determine timing deviation positions; for the timing deviation positions, analyze and obtain interaction response data based on coupling effects, judge high-risk propagation path segments based on the interaction response data, and obtain a risk path set; A path evaluation unit is configured to extract feature data of high-risk propagation path segments through the risk path set, construct a signal integrity evaluation matrix based on the feature data, and obtain a classification result of signal distortion sources through pattern recognition; A path optimization unit is configured to extract dominant factors according to the classification result, adjust multi-layer medium parameters using an iterative optimization algorithm, generate an optimized propagation path configuration, simulate signal behavior according to the optimized propagation path configuration, obtain waveform data, and if the waveform data and actual measurement deviation is less than a preset threshold, it is confirmed that the reproduction is successful, and a debugging path is obtained; A result generation unit is configured to extract signal integrity indicators through the debugging path, verify the degree of coupling effect reduction, verify the effectiveness of the optimized path, determine the stable range of environmental factor influence, generate comprehensive report data through the stable range, predict the signal distortion probability, and obtain a reference basis for high-frequency circuit board design.

10. A computer-readable storage medium having stored thereon instructions, the instructions comprising, The instructions are executed by the processor to implement the method of any one of claims 1-8. The instructions are executed by the processor to implement the method of any one of claims 1-8.

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