Copper foil electric signal loss evaluation method based on wavelet transform multi-scale analysis

Abstract

The application discloses a copper foil electric signal loss evaluation method based on wavelet transform multi-scale analysis, and belongs to the technical field of electronic material performance evaluation, and comprises the following steps: obtaining a copper foil surface topography image and a height matrix; adaptively determining a wavelet decomposition layer number based on the geometric features of a power spectrum density curve; performing multi-scale decomposition and reconstruction on the topography image by using wavelet transform to obtain surface height matrices of different scales; calculating multi-scale statistical parameters; generating a virtual surface with specific spatial correlation and non-Gaussian statistical characteristics by Fourier transform and Johnson conversion system based on the multi-scale statistical parameters; applying the virtual surface to a transmission line model to perform electromagnetic field full-wave simulation, calculating scattering parameters to evaluate electric signal loss. The application realizes physical decoupling and accurate quantification of surface topography, and can accurately predict the high-frequency signal transmission performance of an extremely thin copper foil without manufacturing an entity circuit board.

Description

Technical Field

[0001] This invention belongs to the field of electronic material performance evaluation technology, specifically relating to a method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis. Background Technology

[0002] As communication technologies evolve towards 5G millimeter wave and even 6G, the trend towards higher frequencies and smaller sizes in electronic devices is becoming increasingly prominent. As a key conductive material in PCBs, copper foil faces severe challenges: at high frequencies, the skin effect intensifies, and current concentrates within a few micrometers of the surface, making the microstructure of the copper foil a core factor determining conductor loss and signal integrity. However, existing evaluation techniques have the following shortcomings: First, the surface of copper foil is a complex superposition of macroscopic contours and microscopic roughness, with different scale features contributing differently to frequency-varying losses. Traditional methods rely on single statistical parameters such as Ra and Rz, which cannot effectively decouple multi-scale features, leading to deviations in the loss prediction model at different frequencies. Second, existing electromagnetic simulations often assume that the surface height follows an ideal Gaussian distribution. However, due to the crystal growth characteristics, the actual copper foil surface exhibits significant non-Gaussian characteristics (such as skewness and kurtosis). Using the Gaussian assumption will distort the microscopic electromagnetic environment and reduce the physical accuracy of the simulation results. Third, currently, measurement data is mostly used only for substituting into empirical formulas, lacking an effective means of converting from the actual morphology to full-wave electromagnetic simulation. Directly processing the complex measurement data is computationally too intensive, while simplifying the model results in severe distortion, making it difficult to predict electrical signal losses (S-parameters) with low cost and high accuracy during the R&D stage.

[0003] Therefore, there is an urgent need for a new evaluation method that can accurately decouple multi-scale features, reproduce the real morphology with high fidelity, and connect the link from morphology measurement to performance simulation. Summary of the Invention

[0004] The purpose of this invention is to provide a method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis, so as to overcome the shortcomings of existing technologies such as feature scale aliasing, deviation between Gaussian surface assumption and actual morphology, and separation between measurement and simulation.

[0005] To achieve the above objectives, the present invention provides the following technical solutions: In a first aspect, the present invention provides a method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis, comprising the following steps: Obtain the topographic image and height matrix information of the copper foil surface; The power spectral density curve is calculated based on the height matrix information, and the number of multi-scale decomposition layers is determined according to the geometric characteristics of the power spectral density curve. The topography image is decomposed into multi-scale components using wavelet transform to obtain the decomposed image components. Multi-scale reconstruction is performed on the decomposed image components to obtain surface height matrix information corresponding to different scales; Statistical parameters are calculated on the surface height matrix information at different scales to obtain multi-scale statistical parameters of the copper foil surface morphology. Based on the statistical parameters, a virtual surface with specific spatial correlation and non-Gaussian statistical characteristics is generated; The virtual surface is applied to the transmission line model for electromagnetic field simulation, scattering parameters are calculated, and the electrical signal loss of the copper foil is evaluated based on the scattering parameters.

[0006] Furthermore, the acquisition of the morphology image and height matrix information of the copper foil surface specifically includes: Multi-level scanning of the copper foil surface is performed using atomic force microscopy, laser scanning confocal microscopy, or white light interferometer to obtain its microscopic morphology images and corresponding three-dimensional height matrix information.

[0007] Furthermore, determining the number of multi-scale decomposition layers based on the geometric characteristics of the power spectral density curve specifically involves: Using the inflection points or feature points in the power spectral density curve as physical criteria, the number of decomposition layers for subsequent wavelet transforms is adaptively determined.

[0008] Furthermore, the step of using wavelet transform to perform multi-scale decomposition on the topography image to obtain decomposed image components specifically includes: Selective combination and reconstruction processing of wavelet coefficients in the decomposed image components are performed to preserve detail components, and surface height matrix information corresponding to different physical scale ranges is reconstructed using inverse wavelet transform. The surface height matrix information includes a low-frequency reconstructed surface characterizing the macroscopic geometric contour, and one or more high-frequency reconstructed surfaces characterizing the microscopic texture features.

[0009] Furthermore, the multi-scale reconstruction of the decomposed image components to obtain surface height matrix information corresponding to different scales specifically involves: The decomposed image components are reconstructed at multiple scales to obtain surface height matrix information corresponding to multiple scales.

[0010] Furthermore, the generation of a virtual surface with specific spatial correlation and non-Gaussian statistical characteristics based on the statistical parameters specifically includes: Gaussian surfaces with specific spatial correlations are generated using Fourier transform and power spectral density methods; The statistical parameters are applied to the Gaussian surface using the Johnson transformation system to generate a virtual surface with non-Gaussian statistical characteristics.

[0011] Furthermore, the statistical parameters include, but are not limited to, spatial parameters, hybrid parameters, functional parameters, and morphological parameters as defined in the ISO 25178 standard.

[0012] Furthermore, the step of applying the virtual surface to the transmission line model for electromagnetic field simulation and calculating scattering parameters specifically involves: Using the non-Gaussian virtual surface and material parameters, a transmission line structure is constructed, and full-wave electromagnetic field simulation is performed to calculate its scattering parameters.

[0013] Furthermore, the transmission line structure includes, but is not limited to, stripline, microstrip, or coplanar waveguide structures.

[0014] Secondly, the present invention also provides a system for evaluating the electrical signal loss of copper foil, implementing a method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis, comprising: The measurement module is used to acquire topographic images and height matrix information of the copper foil surface; The decomposition layer number determination module is used to calculate the power spectral density curve based on the height matrix information, and determine the number of multi-scale decomposition layers according to the geometric characteristics of the power spectral density curve. The wavelet decomposition module is used to perform multi-scale decomposition of the topography image using wavelet transform to obtain decomposed image components. A multi-scale reconstruction module is used to perform multi-scale reconstruction on the decomposed image components to obtain surface height matrix information corresponding to different scales. The statistical parameter calculation module is used to perform statistical parameter calculations on the surface height matrix information at different scales to obtain multi-scale statistical parameters of the copper foil surface morphology. A virtual surface generation module is used to generate a virtual surface with specific spatial correlation and non-Gaussian statistical characteristics based on the statistical parameters. The electrical signal loss evaluation module is used to apply the virtual surface to the transmission line model for electromagnetic field simulation, calculate scattering parameters, and evaluate the electrical signal loss of the copper foil based on the scattering parameters.

[0015] Compared with the prior art, the present invention has the following beneficial technical effects: This invention provides a method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis. It adaptively determines the number of wavelet decomposition levels using the geometric features of the power spectral density curve, and performs multi-scale decomposition and reconstruction of the morphology image through wavelet transform, effectively separating the morphology image and height matrix information of the copper foil surface in a physical sense. By extracting multi-scale statistical parameters of the copper foil surface and generating a virtual surface with specific spatial correlation and non-Gaussian statistical characteristics based on these parameters, the virtual surface is directly applied to a transmission line model for electromagnetic field simulation. Scattering parameters are calculated to evaluate the electrical signal loss, enabling accurate prediction of the high-frequency electrical signal transmission performance of copper foil during the design phase without the need for physical test circuit boards, significantly reducing R&D costs and time. In generating the virtual surface, this invention not only preserves the spatial correlation of the surface morphology but also accurately reconstructs the non-Gaussian morphology, such as nodular accumulations, formed on the actual electrolytic copper foil surface due to crystal growth characteristics by introducing realistically extracted non-Gaussian statistical features.

[0016] This invention abandons the blind reliance on manually setting the cutoff wavelength in traditional filtering methods, instead using the geometric inflection point of the power spectral density (PSD) curve as the physical basis for determining the number of wavelet decomposition levels. Production personnel can not only determine product quality based on predicted S-parameters, but also identify the specific causes of abnormal losses by tracing back the multi-scale decomposition results. This allows for targeted adjustments to electrolyte formulations, current densities, or cathode roller polishing processes, significantly improving the yield of high-end high-frequency copper foil. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of a copper foil electrical signal loss evaluation method based on wavelet transform multi-scale analysis in an embodiment of the present invention.

[0018] Figure 2 This is a schematic diagram of the S-parameter prediction results of the stripline model based on the present invention in Example 1. Detailed Implementation

[0019] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0020] This paper addresses existing technologies for high-frequency signal integrity analysis of copper foil, which suffer from problems such as feature scale aliasing, deviation between Gaussian surface assumptions and actual morphology, and the disconnect between measurement and simulation. With the rapid development of 5G and future 6G mobile communication technologies, electronic devices are evolving towards higher frequencies, higher speeds, and smaller sizes, placing increasingly stringent electrical performance requirements on copper foil, a key material for printed circuit boards (PCBs). In high-frequency signal transmission, conductor losses, particularly signal integrity issues caused by the microstructure of the copper foil surface, have become a critical bottleneck restricting circuit performance improvement. Traditional methods for characterizing copper foil surface morphology, such as roughness parameters based on specific cutoff wavelengths (e.g., root mean square roughness Rq, ten-point height Rz), not only fail to comprehensively describe complex multi-scale surface features but also lead to misjudgments of high-frequency signal transmission mechanisms due to feature scale aliasing. Furthermore, in simulation analysis, there is a significant discrepancy between the simplified Gaussian surface assumption and the actual non-Gaussian, anisotropic morphology of copper foil. In addition, the disconnect between measurement data and electromagnetic simulation models makes it difficult for existing evaluation systems to accurately predict and optimize the electrical performance of copper foil at high frequencies.

[0021] See Figure 1 This invention provides a method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis, and a method for correlating this evaluation with high-frequency signal transmission loss. The aim is to achieve accurate, comprehensive, and efficient quantitative characterization of the microstructure of the copper foil surface and establish an accurate mapping relationship between it and high-frequency electrical signal transmission loss. The method includes the following steps: Obtain the topographic image and height matrix information of the copper foil surface; In a more specific embodiment of the present invention, the surface of the copper foil is scanned in multiple levels (e.g., the scanning range is from 0.5×0.5 µm² to 512×512 µm²) using high-precision surface measurement equipment such as atomic force microscope, laser scanning confocal microscope or white light interferometer, to obtain the morphological image and height matrix information of the copper foil surface. By stitching and fusing these multi-level scanning data, a full-scale, high-fidelity height matrix information containing all features from micro-grains and grain boundaries to macro-rolling marks or burrs is finally generated. The power spectral density curve is calculated based on the height matrix information, and the number of multi-scale decomposition layers is determined according to the geometric characteristics of the power spectral density curve. Power spectral density analysis is a bridge connecting the spatial domain and the frequency domain. It can decompose the surface height information into the power contribution of different spatial frequency (or wavelength) components, and intuitively reveal the law of energy distribution of surface morphology changing with scale. In a more specific embodiment of the present invention, the number of multi-scale decomposition layers is determined based on the geometric characteristics of the power spectral density curve. Specifically, the inflection points (or feature points) in the power spectral density (PSD) curve are used as physical criteria to determine whether the surface morphology of the copper foil has multi-scale characteristics, and the number of decomposition layers for subsequent wavelet transform is adaptively determined. Unlike traditional methods, this process no longer relies on a manually set cutoff wavelength, but is entirely based on the inherent properties of the sample itself. Each inflection point on the curve typically corresponds to a scale at which the surface morphology image generation mechanism changes. For example, high-frequency bands may correspond to fine structures formed by grain refinement or surface treatment, while low-frequency bands may reflect macroscopic fluctuations caused by the rolling process. By identifying these inflection points, the surface can be decomposed into several physically independent scale levels, thus providing a scientific and objective basis for the number of layers in subsequent wavelet decomposition, fundamentally overcoming the blindness of manually setting the cutoff wavelength in traditional filtering methods.

[0022] The topography image is decomposed into multi-scale components using wavelet transform to obtain the decomposed image components. In a more specific embodiment of the present invention, the shape image is decomposed into decomposed image components using wavelet transform at multiple scales, specifically including: Selective combination and reconstruction processing of wavelet coefficients in the decomposed image components are performed to preserve detail components, and surface height matrix information corresponding to different physical scale ranges is reconstructed using inverse wavelet transform. The surface height matrix information includes a low-frequency reconstructed surface characterizing the macroscopic geometric contour, and one or more high-frequency reconstructed surfaces characterizing the microscopic texture features.

[0023] To achieve the decoupling of the macroscopic contour and microscopic texture of the copper foil surface morphology in physical terms.

[0024] This invention utilizes inflection points in the power spectral density (PSD) curve to assist wavelet transform. Based on the number of decomposition layers determined by the PSD curve, and by selecting appropriate wavelet basis functions (such as Daubechies, Symlets, etc.), the morphology image of the copper foil surface is decomposed into a series of decomposed image components with different resolutions at multiple scales. These decomposed image components include a low-frequency approximation component representing the macroscopic trend of the surface, and multiple high-frequency detail components representing detailed information at different scales (such as textures in the horizontal, vertical, and diagonal directions). In this way, the macroscopic contours and microscopic textures, which were originally complexly entangled in the spatial domain, are physically decoupled perfectly, forming independent components, thus effectively solving the mismatch problem in subsequent mechanism analysis and model construction caused by feature aliasing. For the decoupled decomposed image components, a comprehensive parameter set covering amplitude, space, function, extrema, and non-Gaussian morphology can be further constructed for targeted and independent evaluation. This greatly compensates for the shortcomings of existing single statistical parameter evaluations and lays a solid foundation for achieving comprehensive and accurate quantitative characterization of the copper foil surface morphology.

[0025] Multi-scale reconstruction of the decomposed image components yields surface height matrix information corresponding to different scales. This allows for independent analysis of morphological image features at different scales. Selective reconstruction of the decomposed wavelet coefficients—retaining detail components at a specific scale or in a specific direction while setting other components to zero—followed by inverse wavelet transform, reconstructs a surface height matrix containing only features at that specific scale. For example, it can reconstruct a low-frequency surface reflecting only macroscopic contours, or a high-frequency surface reflecting only microscopic textures of a specific size. This step facilitates independent and in-depth analysis and research of morphological image features at different scales, providing a clear understanding of the impact of different manufacturing processes (such as roughening and passivation) on surface structures at different scales. Statistical parameters are calculated on the surface height matrix information at different scales to obtain multi-scale statistical parameters of the copper foil surface morphology. In a more specific embodiment provided by the present invention, based on the statistical parameters, a virtual surface with specific spatial correlation and non-Gaussian statistical characteristics is generated, specifically including: Gaussian surfaces with specific spatial correlations are generated using Fourier transform and power spectral density methods; The statistical parameters are applied to the Gaussian surface using the Johnson transformation system to generate a virtual surface with non-Gaussian statistical characteristics. The statistical parameters include, but are not limited to, spatial parameters, hybrid parameters, functional parameters, and morphological parameters defined in ISO 25178, such as root mean square roughness (Sq), maximum peak-to-valley difference (Sz), kurtosis (Sku), skewness (Ssk), root mean square (RMS), and maximum height difference (ΔZ).

[0026] This invention introduces the Johnson transformation system and utilizes multi-scale statistical parameters extracted after multi-scale decomposition to construct a virtual surface with specific spatial correlation and non-Gaussian statistical characteristics. This method accurately reconstructs the microscopic geometric details of the real surface in an electromagnetic simulation environment, significantly improving the physical realism of electromagnetic wave surface scattering and conductor loss calculations, making the simulation results closer to reality.

[0027] The virtual surface is applied to the transmission line model for electromagnetic field simulation, and the scattering parameters are calculated, specifically as follows: Using the non-Gaussian virtual surface and material parameters, a transmission line structure is constructed, and full-wave electromagnetic field simulation is performed to calculate scattering parameters.

[0028] This invention conducts correlation assessment and prediction of the surface morphology characteristics and high-frequency transmission performance of various ultra-thin copper foils, including but not limited to HVLP copper foil, thereby guiding the preparation of various ultra-thin copper foils with specific micromorphological characteristics and excellent high-frequency transmission performance.

[0029] Example Multi-region sampling and characterization of the HVLP copper foil surface were performed to obtain the morphology image and height matrix information of the HVLP copper foil surface; The power spectral density curve is calculated based on the height matrix information of the HVLP copper foil surface, and the number of multi-scale decomposition layers is determined according to the geometric characteristics of the power spectral density curve; wavelet transform is used to perform multi-scale decomposition on the topography image of the HVLP copper foil surface to obtain decomposed image components. Multi-scale reconstruction is performed on the decomposed image components to obtain surface height matrix information corresponding to different scales; Statistical parameters were calculated on the surface height matrix information at different scales to obtain multi-scale statistical parameters of the surface morphology of the HVLP copper foil. Calculations showed that the surface profile Rz of the HVLP copper foil was approximately 1.8 µm. The extracted modeling parameters included root mean square height Sq = 0.261 µm, skewness SSsk = 0.035, and kurtosis Sku = 3.578. Next, based on the actual PCB design, a stripline structure was fabricated: dielectric layer 1 thickness was 107.56 µm, dielectric layer 2 thickness was 141.47 µm, upper trace width was 134.56 µm, lower trace width was 137.99 µm, trace spacing was 218.77 µm, and trace thickness was 15.15 µm.

[0030] Based on the aforementioned statistical parameters, a virtual surface with specific spatial correlation and non-Gaussian statistical characteristics is generated; and based on this virtual surface, the aforementioned stripline structure is constructed, and full-wave electromagnetic field simulation is performed. Through simulation calculation, its high-frequency electrical signal loss is predicted and output in the form of S-parameters (S21), as shown below. Figure 2 As shown in the figure, simulation prediction results show that S21 is -0.57 dB at 14 GHz and -1.13 dB at 40 GHz. These results can be directly used to evaluate the signal transmission performance of the copper foil in the target frequency band, providing a basis for material selection or process optimization. This invention establishes a complete evaluation system from "microscopic morphology decoupling" to "macroscopic electrical performance prediction." Production personnel can not only judge whether the product is qualified based on the predicted S-parameters, but also identify the specific causes of abnormal losses by tracing back the multi-scale decomposition results. This allows for targeted adjustments to the electrolyte formulation, current density, or cathode roller polishing process, which has significant industrial application value for improving the yield of high-end high-frequency copper foil. This invention transforms the quantified multi-scale parameters into a transmission line simulation model, enabling direct simulation calculation of the S-parameters reflecting the quality of electrical signal transmission. This means that the high-frequency electrical signal transmission performance of ultra-thin copper foil can be quickly evaluated during the design phase without the need for expensive and time-consuming physical test circuit boards, significantly shortening the development cycle of new products and reducing testing costs.

[0031] In another embodiment of the present invention, the present invention also provides a system for evaluating the electrical signal loss of copper foil, implementing a method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis, comprising: The measurement module is used to acquire topographic images and height matrix information of the copper foil surface; The decomposition layer number determination module is used to calculate the power spectral density curve based on the height matrix information, and determine the number of multi-scale decomposition layers according to the geometric characteristics of the power spectral density curve. The wavelet decomposition module is used to perform multi-scale decomposition of the topography image using wavelet transform to obtain decomposed image components. A multi-scale reconstruction module is used to perform multi-scale reconstruction on the decomposed image components to obtain surface height matrix information corresponding to different scales. The statistical parameter calculation module is used to perform statistical parameter calculations on the surface height matrix information at different scales to obtain multi-scale statistical parameters of the copper foil surface morphology. A virtual surface generation module is used to generate a virtual surface with specific spatial correlation and non-Gaussian statistical characteristics based on the statistical parameters. The electrical signal loss evaluation module is used to apply the virtual surface to the transmission line model for electromagnetic field simulation, calculate scattering parameters, and evaluate the electrical signal loss of the copper foil based on the scattering parameters.

[0032] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis, characterized in that, Includes the following steps: Obtain the topographic image and height matrix information of the copper foil surface; The power spectral density curve is calculated based on the height matrix information, and the number of multi-scale decomposition layers is determined according to the geometric characteristics of the power spectral density curve. The topography image is decomposed into multi-scale components using wavelet transform to obtain the decomposed image components. Multi-scale reconstruction is performed on the decomposed image components to obtain surface height matrix information corresponding to different scales; Statistical parameters are calculated on the surface height matrix information at different scales to obtain multi-scale statistical parameters of the copper foil surface morphology. Based on the statistical parameters, a virtual surface with specific spatial correlation and non-Gaussian statistical characteristics is generated; The virtual surface is applied to the transmission line model for electromagnetic field simulation, scattering parameters are calculated, and the electrical signal loss of the copper foil is evaluated based on the scattering parameters.

2. The method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis according to claim 1, characterized in that, The acquisition of the morphology image and height matrix information of the copper foil surface specifically includes: Multi-level scanning of the copper foil surface is performed using atomic force microscopy, laser scanning confocal microscopy, or white light interferometer to obtain microscopic morphology images and three-dimensional height matrix information.

3. The method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis according to claim 1, characterized in that, The determination of the number of multi-scale decomposition layers based on the geometric characteristics of the power spectral density curve specifically involves: Using the inflection points or feature points in the power spectral density curve as physical criteria, the number of decomposition layers for subsequent wavelet transforms is adaptively determined.

4. The method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis according to claim 1, characterized in that, The step of performing multi-scale decomposition of the topography image using wavelet transform to obtain decomposed image components specifically includes: The topography image is decomposed into multiple scales using wavelet transform to obtain multiple decomposed image components with different resolutions.

5. The method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis according to claim 1, characterized in that, The process of reconstructing the decomposed image components at multiple scales to obtain surface height matrix information corresponding to different scales specifically involves: Selective combination and reconstruction processing of wavelet coefficients in the decomposed image components are performed to preserve detail components, and surface height matrix information corresponding to different physical scale ranges is reconstructed using inverse wavelet transform. The surface height matrix information includes a low-frequency reconstructed surface characterizing the macroscopic geometric contour, and one or more high-frequency reconstructed surfaces characterizing the microscopic texture features.

6. The method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis according to claim 1, characterized in that, The process of generating a virtual surface with specific spatial correlation and non-Gaussian statistical characteristics based on the statistical parameters specifically includes: Gaussian surfaces with specific spatial correlations are generated using Fourier transform and power spectral density methods; The statistical parameters are applied to the Gaussian surface using the Johnson transformation system to generate a virtual surface with non-Gaussian statistical characteristics.

7. A method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis according to claim 6, characterized in that, The statistical parameters include, but are not limited to, spatial parameters, hybrid parameters, functional parameters, and morphological parameters as defined in ISO 25178.

8. The method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis according to claim 1, characterized in that, The step of applying the virtual surface to the transmission line model for electromagnetic field simulation and calculating scattering parameters specifically involves: Using the non-Gaussian virtual surface and material parameters, a transmission line structure is constructed, and full-wave electromagnetic field simulation is performed to calculate scattering parameters.

9. The method for evaluating the electrical signal loss of copper foil based on wavelet transform multi-scale analysis according to claim 8, characterized in that, The transmission line structure includes, but is not limited to, stripline, microstrip, or coplanar waveguide structures.

10. A system for evaluating the electrical signal loss of copper foil, characterized in that, Implementing the copper foil electrical signal loss evaluation method based on wavelet transform multi-scale analysis as described in any one of claims 1-9, comprising: The measurement module is used to acquire topographic images and height matrix information of the copper foil surface; The decomposition layer number determination module is used to calculate the power spectral density curve based on the height matrix information, and determine the number of multi-scale decomposition layers according to the geometric characteristics of the power spectral density curve. The wavelet decomposition module is used to perform multi-scale decomposition of the topography image using wavelet transform to obtain decomposed image components. A multi-scale reconstruction module is used to perform multi-scale reconstruction on the decomposed image components to obtain surface height matrix information corresponding to different scales. The statistical parameter calculation module is used to perform statistical parameter calculations on the surface height matrix information at different scales to obtain multi-scale statistical parameters of the copper foil surface morphology. A virtual surface generation module is used to generate a virtual surface with specific spatial correlation and non-Gaussian statistical characteristics based on the statistical parameters. The electrical signal loss evaluation module is used to apply the virtual surface to the transmission line model for electromagnetic field simulation, calculate scattering parameters, and evaluate the electrical signal loss of the copper foil based on the scattering parameters.

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