Screen protective film damage detection method and system

Abstract

The present invention relates to the field of damage detection technology, and discloses a damage detection method and system for a screen protective film. The method comprises: performing laser interference thickness scanning on the screen protective film to obtain three-dimensional thickness distribution data and thickness gradient vector field data; performing multi-layer polarization interference detection on a circularly polarized light beam based on the three-dimensional thickness distribution data to obtain polarization phase difference distribution data; performing non-periodic phase de-envelopment processing on the polarization phase difference distribution data according to the thickness gradient vector field data to obtain continuous polarization phase distribution data; performing stress optical coefficient tensor calculation and dynamic elliptical polarization modulation based on the continuous polarization phase distribution data to obtain stress damage spatial positioning data; and performing damage imaging reconstruction on the edge cutting area and the central bending area of ​​the screen protective film to obtain three-dimensional stress damage imaging results. The present invention realizes full-chain detection from geometric thickness change to stress distribution to damage positioning.

Description

Technical Field

[0001] The present invention relates to the technical field of damage detection, and in particular to a method and system for detecting damage to a screen protective film. Background Art

[0002] Screen protectors typically utilize a glass-PVB-glass composite structure. During use, complex stress distribution occurs in the cut edge areas and central curved areas. These stress concentrations often serve as starting points for microcrack initiation and propagation, ultimately leading to film failure. Therefore, accurately detecting and evaluating stress damage within screen protectors is crucial for product quality control, lifespan prediction, and failure analysis.

[0003] Traditional methods for detecting damage to screen protectors rely primarily on surface observation, acoustic emission testing, and simple photoelastic methods. These methods have significant limitations in detection accuracy, spatial resolution, and depth information acquisition. While existing photoelastic testing techniques can detect stress distribution within materials, most employ single-layer detection modes and fixed polarization state scanning, making it difficult to accurately account for optical interface effects and polarization phase jumps in multilayer composite materials. Summary of the Invention

[0004] The present invention provides a method and system for detecting damage of a screen protective film, which realizes full-chain detection from geometric thickness change to stress distribution to damage location.

[0005] In a first aspect, the present invention provides a method for detecting damage to a screen protective film, the method comprising:

[0006] Perform laser interferometry thickness scanning on the screen protective film to obtain three-dimensional thickness distribution data and thickness gradient vector field data;

[0007] Performing multi-layer polarization interference detection on the circularly polarized light beam based on the three-dimensional thickness distribution data to obtain polarization phase difference distribution data;

[0008] performing a non-periodic phase de-envelope processing on the polarization phase difference distribution data according to the thickness gradient vector field data to obtain continuous polarization phase distribution data;

[0009] Performing stress optical coefficient tensor calculation and dynamic elliptical polarization modulation based on the continuous polarization phase distribution data to obtain stress damage spatial positioning data;

[0010] Damage imaging reconstruction is performed on the edge cutting area and the central bending area of ​​the screen protective film according to the stress damage spatial positioning data to obtain a three-dimensional stress damage imaging result.

[0011] In combination with the first aspect, in a first implementation of the first aspect of the present invention, performing laser interferometry thickness scanning on the screen protective film to obtain three-dimensional thickness distribution data and thickness gradient vector field data includes:

[0012] Perform laser interferometry scanning on the screen protective film point by point to obtain the original thickness measurement data;

[0013] Performing three-dimensional coordinate mapping based on the original thickness measurement data to obtain three-dimensional thickness distribution data;

[0014] Partial differential gradient calculation is performed on the three-dimensional thickness distribution data to obtain thickness gradient vector field data.

[0015] In combination with the first aspect, in a second implementation of the first aspect of the present invention, performing multi-layer polarization interferometry detection on the circularly polarized light beam based on the three-dimensional thickness distribution data to obtain polarization phase difference distribution data includes:

[0016] creating circularly polarized beam configuration parameters of a multilayer polarization interference optical system based on the three-dimensional thickness distribution data;

[0017] Performing a multi-layer depth scan on the screen protective film according to the circularly polarized beam configuration parameters to obtain four-quadrant polarization intensity data;

[0018] Polarization phase difference calculation is performed on the four-quadrant polarization intensity data to obtain initial phase difference distribution data, and polarization stability constraint is performed on the initial phase difference distribution data to obtain polarization phase difference distribution data.

[0019] In combination with the first aspect, in a third implementation of the first aspect of the present invention, performing non-periodic phase de-envelope processing on the polarization phase difference distribution data according to the thickness gradient vector field data to obtain continuous polarization phase distribution data includes:

[0020] Performing depth correlation based on the thickness gradient vector field data and the polarization phase difference distribution data to obtain a thickness compensation factor;

[0021] performing phase jump discrimination on the thickness gradient vector field data according to the thickness compensation factor to obtain true phase jump identification data;

[0022] Dynamically adjusting the window size of the real phase jump identification data to obtain an adaptive window parameter;

[0023] A non-periodic de-envelope algorithm is performed on the polarization phase difference distribution data based on the adaptive window parameters to obtain continuous polarization phase distribution data.

[0024] In combination with the first aspect, in a fourth implementation of the first aspect of the present invention, performing phase jump discrimination on the thickness gradient vector field data according to the thickness compensation factor to obtain true phase jump identification data includes:

[0025] constructing a phase jump discriminant function based on the thickness compensation factor;

[0026] performing gradient amplitude comparison on the thickness gradient vector field data according to the phase jump discriminant function to obtain thickness gradient threshold screening data;

[0027] performing phase difference amplitude calculation on the thickness gradient threshold screening data and the polarization phase difference distribution data to obtain phase mutation candidate point data;

[0028] Based on the phase mutation candidate point data, dual conditional logic judgment is performed to obtain true phase jump identification data.

[0029] In combination with the first aspect, in a fifth implementation of the first aspect of the present invention, the calculation of the stress optical coefficient tensor and dynamic elliptical polarization modulation based on the continuous polarization phase distribution data to obtain stress damage spatial positioning data includes:

[0030] A modified Müller matrix is ​​constructed based on the continuous polarization phase distribution data to obtain Müller matrix transformation parameters corresponding to the glass-PVB-glass composite structure;

[0031] Performing stress-optical coefficient tensor calibration on the continuous polarization phase distribution data according to the Müller matrix transformation parameters to obtain a stress-optical coefficient tensor;

[0032] Performing elliptical polarization parameter modulation based on the stress-optical coefficient tensor to obtain elliptical polarization modulation parameters;

[0033] Performing three-dimensional stress tensor reconstruction on the continuous polarization phase distribution data based on the elliptical polarization modulation parameters to obtain three-dimensional stress tensor component data;

[0034] Dynamic elliptical polarization modulation scanning is performed based on the three-dimensional stress tensor component data to obtain stress damage spatial positioning data.

[0035] In combination with the first aspect, in a sixth implementation of the first aspect of the present invention, performing elliptical polarization parameter modulation based on the stress-optical coefficient tensor to obtain elliptical polarization modulation parameters includes:

[0036] Calculating an ellipsometric parameter vector based on the stress-optical coefficient tensor to obtain ellipticity distribution data;

[0037] Calculating a stress gradient response coefficient based on the ellipticity distribution data and the three-dimensional stress tensor component data to obtain an adaptive modulation depth parameter;

[0038] Inputting the adaptive modulation depth parameter into the dual-frequency drive configurator to perform frequency separation calculation to obtain the dual-frequency drive parameter;

[0039] Elliptical polarization dynamic tracking is performed based on the dual-frequency driving parameters and the thickness compensation factor to obtain elliptical polarization modulation parameters.

[0040] In combination with the first aspect, in a seventh implementation of the first aspect of the present invention, performing dynamic elliptical polarization modulation scanning based on the three-dimensional stress tensor component data to obtain stress damage spatial positioning data includes:

[0041] performing stress-photoelasticity coupling response variable calculation based on the three-dimensional stress tensor component data and the three-dimensional thickness distribution data to obtain coupling response variable distribution data;

[0042] performing adaptive modulation analysis on the elliptical polarization modulation parameters according to the coupling response variable distribution data to obtain dynamic modulation configuration data;

[0043] Performing scan path planning based on the dynamic modulation configuration data to obtain target scan path data;

[0044] Dynamic tracking of polarization ellipse parameters is performed based on the target scanning path data and the thickness compensation factor to obtain stress damage spatial positioning data.

[0045] In combination with the first aspect, in an eighth implementation of the first aspect of the present invention, performing damage imaging reconstruction on the edge cut area and the central curved area of ​​the screen protective film based on the stress damage spatial positioning data to obtain a three-dimensional stress damage imaging result includes:

[0046] Constructing damage imaging model parameters based on the stress damage spatial positioning data, the thickness gradient vector field data, the continuous polarization phase distribution data, and the coupled response variable distribution data;

[0047] performing dual-region differential detection on the edge cut region and the central curved region of the screen protective film according to the damage imaging model parameters to obtain region detection configuration data;

[0048] A damage assessment is performed based on the regional detection configuration data to obtain damage assessment index data, and voxelized three-dimensional imaging reconstruction is performed based on the damage assessment index data to obtain a three-dimensional stress damage imaging result.

[0049] In a second aspect, the present invention provides a damage detection system for a screen protective film, the damage detection system for the screen protective film comprising:

[0050] A scanning module is used to perform laser interference thickness scanning on the screen protective film to obtain three-dimensional thickness distribution data and thickness gradient vector field data;

[0051] a detection module, configured to perform multi-layer polarization interference detection on the circularly polarized light beam based on the three-dimensional thickness distribution data to obtain polarization phase difference distribution data;

[0052] a processing module, configured to perform a non-periodic phase de-envelope processing on the polarization phase difference distribution data according to the thickness gradient vector field data to obtain continuous polarization phase distribution data;

[0053] A modulation module, configured to perform stress optical coefficient tensor calculation and dynamic elliptical polarization modulation based on the continuous polarization phase distribution data to obtain stress damage spatial positioning data;

[0054] The reconstruction module is used to reconstruct damage imaging of the edge cutting area and the central bending area of ​​the screen protective film according to the stress damage spatial positioning data to obtain a three-dimensional stress damage imaging result.

[0055] In the technical solution provided by the present invention, by establishing thickness gradient vector field data to guide the non-periodic unwrapping processing of polarization phase difference distribution data, the cumulative error problem of the traditional 2π phase jump processing method in thin film materials is effectively solved, and the high-precision acquisition of continuous polarization phase distribution data is achieved. A multi-layer configuration of four-quadrant polarization detectors is adopted at different z-axis depth levels. Compared with the traditional single-layer polarization detection technology, it can better handle the interlayer interface effects of the glass-PVB-glass composite structure, and improve the detection accuracy and stability of the polarization phase difference distribution data. A modified Müller matrix transformation parameter suitable for the glass-PVB-glass composite structure is established, taking into account the anisotropic characteristics and interlayer interface effects of the screen protective film, and can more accurately realize the numerical conversion of polarization phase to stress component than the standard Müller matrix. Based on the adaptive modulation technology driven by the stress-photoelastic coupling response variable, the dual-frequency driving scheme and the spiral path algorithm realize the preferential scanning and precise positioning of the stress concentration area, which significantly improves the detection sensitivity of the microcrack initiation position. A dual-region differentiated detection strategy was established to address the different stress characteristics of the screen protector's edge cut region and central curved region. The edge region focuses on detecting shear stress distribution, while the central region primarily detects normal stress distribution, achieving targeted and efficient detection. By integrating stress tensor component data, thickness gradient information, polarization phase distribution, and coupled response variables, a multi-parameter fusion damage imaging model was established, enabling full-chain detection from geometric thickness changes to stress distribution and damage localization. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0057] Figure 1 Schematic diagram of the steps of a method for detecting damage to a screen protective film according to an embodiment of the present invention;

[0058] Figure 2 Schematic diagram of the structure of the damage detection system of the screen protective film in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] Embodiments of the present invention provide a method and system for detecting damage to a screen protective film. The terms "first," "second," "third," "fourth," and so on (if any) in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way are interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to these processes, methods, products, or apparatus.

[0060] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 An embodiment of a method for detecting damage to a screen protective film according to an embodiment of the present invention includes:

[0061] Step S1, performing laser interferometry thickness scanning on the screen protective film to obtain three-dimensional thickness distribution data and thickness gradient vector field data;

[0062] It is understandable that the execution subject of the present invention can be a damage detection system for a screen protector, or a terminal or a server, which is not limited here. The embodiment of the present invention is described by taking a server as the execution subject as an example.

[0063] Specifically, a high-precision laser interferometry measurement system was built, which was equipped with a laser with stable wavelength output and a scanning platform with high-precision displacement control function. The screen protective film was scanned point by point through laser interferometry technology, and the intra-volume multi-layer interference imaging method was used to analyze the thickness of the glass-PVB-glass composite structure of the protective film layer by layer, and obtain the original thickness measurement data at different spatial coordinates (x, y, z). The scanning range covers the entire protective film area, and the scanning step length is refined to a plane resolution of 10 microns × 10 microns and a vertical resolution of 2 microns, ensuring sufficient spatial sampling density within the thickness range of 0.3 to 0.8 mm, capable of capturing tiny thickness variation characteristics, and the detection accuracy reaches ±0.5 microns. Based on the original thickness measurement data, three-dimensional coordinate mapping processing is performed, and the scanning position information is corresponded to the thickness data point by point to form a three-dimensional thickness distribution map T(x, y, z). During the coordinate mapping process, interpolation correction methods are used to correct spatial coordinate errors caused by slight deviations in the scanning path. Polynomial fitting or 3D spline interpolation algorithms are used to ensure the continuity and smoothness of the spatial distribution of the thickness data, resulting in high-fidelity 3D thickness distribution data. To extract the thickness variation trends of the protective film in different regions, partial differentiation is performed on the 3D thickness distribution data. First-order differential operations are performed in the x, y, and z directions to obtain the rate of change of thickness in each direction, forming a thickness gradient vector field. The partial differentiation calculation uses a central difference method or a five-point difference method for numerical approximation. The difference step size is dynamically adjusted based on the local variation characteristics of the data. In particular, in the edge cut region and the central bend region of the protective film, where the thickness variation rate is large due to stress concentration, a denser mesh is used to improve resolution. To improve the thickness gradient vector field's ability to reflect depth information, a thickness compensation factor is introduced to compensate for the optical attenuation characteristics of the protective film material. This factor applies an exponential correction to the thickness distribution in the depth direction. This allows the thickness variation to not only depict surface features but also deeply reflect the thickness variations at internal multilayer interfaces. The thickness gradient vector field extracted in this way can effectively capture the thickness mutation characteristics of the screen protective film at the multi-layer interface and reflect the local stress concentration area.

[0064] Step S2, performing multi-layer polarization interferometry detection on the circularly polarized light beam based on the three-dimensional thickness distribution data to obtain polarization phase difference distribution data;

[0065] Specifically, based on the three-dimensional thickness distribution data, the circularly polarized beam configuration parameters of the multi-layer polarization interference optical system are created. According to the thickness changes and interface characteristics of the various layers of materials such as glass-PVB-glass inside the screen protective film, the incident angle, wavelength selection and depth scanning strategy of the circularly polarized beam are designed. A helium-neon laser with a wavelength of 632.8 nanometers is selected as the light source. The linearly polarized light is converted into circularly polarized light through a quarter-wave plate, and the incident angle is set to 15° to minimize surface reflection interference while ensuring that the incident light can penetrate the multi-layer structure of the protective film and generate interference signals at different depths. Combined with the local thickness mutation characteristics in the three-dimensional thickness distribution data, the energy density distribution of the circularly polarized beam is optimized to have higher light intensity uniformity in the interface area where the thickness of the protective film changes significantly, thereby improving the stability and signal-to-noise ratio of the interference imaging. According to the circularly polarized beam configuration parameters, the screen protective film is subjected to multi-layer depth scanning. During the scanning process, a four-quadrant polarization detector collects intensity data for the polarized light beam at polarization states of 0°, 45°, 90°, and 135°. Spatially layered sampling ensures 80-layer deep layered scans within a thickness range of 0.3 to 0.8 mm. The acquisition of the four-quadrant polarization intensity data requires maintaining the coherence and polarization stability of the laser light source to avoid polarization state changes caused by environmental factors such as vibration and temperature drift, thereby ensuring accurate acquisition of intensity responses in different polarization directions during each layer scan. The four-quadrant polarization intensity data is then subjected to polarization phase difference calculations, and initial phase difference distribution data is derived based on the intensity differences in each polarization direction. The initial phase difference data extracted through intensity difference analysis can reflect the local optical delay differences at different depth levels of the screen protector, indirectly revealing the stress distribution within the material. Considering the inherent birefringence of the screen protector material and the polarization state instability caused by the external environment, a polarization stability constraint is introduced based on the initial phase difference distribution data. A polarization stability constraint function is established. By normalizing the polarization intensity data and setting the phase drift threshold to 0.02 radians, the initial phase difference distribution is corrected to eliminate abnormal polarization drift caused by random noise, systematic errors, or local defects. The resulting polarization phase difference distribution data has good spatial continuity and physical consistency.

[0066] Step S3, performing non-periodic phase de-envelopment processing on the polarization phase difference distribution data according to the thickness gradient vector field data to obtain continuous polarization phase distribution data;

[0067] Specifically, a deep correlation is performed based on thickness gradient vector field data and polarization phase difference distribution data. By establishing a three-dimensional coordinate correspondence, the thickness gradient information at each spatial location is jointly analyzed with the polarization phase difference value at the corresponding location to identify the spatial consistency characteristics of thickness and phase jump points. Based on this, a thickness compensation factor is calculated. This factor takes into account the differences in optical properties between the material layers within the screen protector and the impact of thickness variation on the light propagation path length. This compensation factor quantitatively corrects phase variations at different depth levels, effectively eliminating phase inhomogeneity errors caused by material birefringence variations and thickness variations, and improving the stability and accuracy of subsequent phase de-envelopment. The thickness gradient vector field data is analyzed based on the thickness compensation factor and combined with the polarization phase difference distribution data for phase jump identification. Leveraging the simultaneous occurrence of thickness gradient and phase difference jumps, a joint threshold judgment criterion for the thickness change rate and phase difference change rate is established. Points where the thickness gradient exceeds a certain threshold and the phase change exceeds the standard range are identified as true phase jump points, thereby generating true phase jump identification data. Compared to traditional periodic de-envelopment methods based on the 2π jump assumption, a method based on physical thickness variation can effectively distinguish true phase jumps caused by material interfaces from pseudo-phase jumps caused by interference fringe folding, avoiding the cumulative error diffusion problem inherent in traditional methods. This method can more accurately restore the continuity of stress distribution, especially in multi-layer composite structures such as glass-PVB-glass. After identifying true phase jumps, the de-envelopment algorithm dynamically adjusts the local processing window to account for the varying thickness variations and complex stress distribution in different regions of the screen protector. By analyzing the local rate of change of the thickness gradient field, the window size is dynamically adjusted based on the local thickness gradient. The adaptive window size parameter is reduced in regions of drastic thickness variations to improve jump detection sensitivity and phase reconstruction detail, while the window is appropriately expanded in regions of gentle thickness variation to enhance de-envelopment stability and processing speed. This adaptive window adjustment strategy, through the introduction of a dynamic adjustment coefficient, adjusts the base window size in real time based on the local thickness gradient during the de-envelopment calculation, ensuring higher spatial resolution and phase reconstruction accuracy in critical locations such as microcrack initiation zones. Based on the above-mentioned adaptive window parameters, a non-periodic unwrapping algorithm is performed on the polarization phase difference distribution data. The polarization phase change trend is analyzed layer by layer, the jump points are continuously connected and the mutation correction is performed, and the non-jump areas are kept naturally extended, gradually constructing the continuous polarization phase distribution data.

[0068] A phase jump discriminant function is constructed based on the thickness compensation factor. This discriminant function combines thickness gradient changes with phase difference changes to comprehensively analyze the physical characteristics of material interfaces in multilayer screen protector structures. The thickness compensation factor accounts for material optical attenuation characteristics, correcting for thickness variations at different depths. This allows the discriminant function to automatically adjust its sensitivity at different locations, effectively identifying subtle changes in the superficial layer while capturing abrupt changes at deeper interfaces, thereby improving the accuracy and stability of jump detection. Based on the phase jump discriminant function, the thickness gradient vector field data is compared for gradient amplitude. The thickness change rate in the x, y, and z directions is calculated for each scan point, and the spatial gradient amplitude is compared with a preset thickness gradient threshold for screening. The thickness gradient threshold is set at 50 microns per millimeter to distinguish normal thickness variations from potential interface abrupt changes. The resulting thickness gradient threshold screening data includes points with significant spatial thickness variations, which are highly correlated with physical interface variations. The thickness gradient threshold screening data is then combined with the polarization phase difference distribution data to calculate the phase difference amplitude change at each screening point. By comparing phase difference data between spatially adjacent layers, calculating the phase change rate and extracting the change amplitude, candidate phase jump point data is obtained. During this process, a phase change amplitude threshold is set to determine whether there is a significant phase jump between adjacent depth layers. The phase jump judgment threshold is set near π or an integer multiple of π. A dual-conditional logical judgment is performed based on the phase jump candidate point data to obtain true phase jump identification data. This judgment process considers both the thickness gradient amplitude and the phase difference amplitude. Only points that meet both the thickness gradient mutation and phase difference mutation conditions at the same location are judged as true phase jump points.

[0069] Step S4, performing stress optical coefficient tensor calculation and dynamic elliptical polarization modulation based on the continuous polarization phase distribution data to obtain stress damage spatial positioning data;

[0070] Specifically, a modified Müller matrix is ​​constructed based on continuous polarization phase distribution data. Considering that screen protectors are composed of a three-layer composite material of glass, PVB, and glass, and that different materials vary in optical anisotropy and stress response, the Müller matrix is ​​corrected based on the material anisotropy, interlayer interface effects, and the measured polarization phase distribution. This allows the derivation of Müller matrix transformation parameters applicable to the composite structure. By introducing the stress-optical coupling coefficient and the optical rotation parameters of each layer, a set of correction matrices is formed that accurately reflects the internal polarization response characteristics of the composite structure. Based on the Müller matrix transformation parameters, the continuous polarization phase distribution data is calibrated to a stress-optical coefficient tensor. The relationship between the continuous phase change rate and the depth-directed gradient is used to derive the correspondence between stress components and polarization phase changes. Combined with the anisotropy compensation factor in the modified Müller matrix, the stress-optical coefficient tensor parameters within the screen protector are extracted. The stress-optical coefficient tensor contains both normal and shear stress components, thus describing the material's stress response characteristics in different directions. To ensure the accuracy of tensor calculations, an optimization algorithm based on least-squares fitting is employed to eliminate random errors and noise interference during the measurement process, resulting in the stress-optical coefficient tensor. Elliptical polarization parameters are modulated based on the stress-optical coefficient tensor. The elliptical polarization parameters primarily consist of ellipticity and azimuth, corresponding to the major-minor axis ratio and principal axis direction of the light wave ellipse under stress, respectively. By analyzing the relationship between the principal stress directions in the stress tensor and the polarization phase change, the elliptical polarization modulation parameters are dynamically adjusted to maximize the response of polarized light to local stress changes when penetrating the material. During the modulation parameter setting process, dynamic modulation depth and frequency related to the local stress gradient are introduced, allowing the elliptical polarization state to be fine-tuned in real time to follow changes in the stress distribution, thereby improving the sensitivity and response speed of the polarization scan to subtle stress anomalies. Based on the elliptical polarization modulation parameters, a three-dimensional stress tensor is reconstructed from the continuous polarization phase distribution data. By mapping the elliptical polarization response to the stress components in each direction, the stress tensor components in each direction are solved using an inverse transformation method, generating three-dimensional stress tensor component data. To improve the stability and spatial continuity of tensor component calculations, a multi-scale iterative optimization algorithm was used to smooth local data. A thickness compensation factor was then incorporated to fine-tune the depth-direction data, ensuring that the stress tensor components truly reflected the microscopic stress distribution characteristics within the protective film, particularly the stress concentration phenomena at microcrack initiation regions and material interfaces. Based on the three-dimensional stress tensor component data, dynamic elliptical polarization modulation scanning was implemented. By setting a scanning path to prioritize areas of stress concentration and dynamically adjusting the scanning step size and modulation frequency based on the local stress gradient, high-precision spatial localization of stress-damaged areas within the protective film was achieved.During dynamic scanning, the use of spiral or grid-like path strategies, coupled with real-time adjustment of elliptical polarization parameters, effectively improves spatial resolution and reduces missed detections. This is particularly true within the 0.3 to 0.8 mm thickness range, where the system demonstrates high sensitivity and accuracy in detecting stress anomalies at the initial stages of microcrack initiation. By comprehensively analyzing the polarization response data obtained from dynamic scanning, stress damage spatial localization data is generated and output as a high-resolution pseudo-color image, highlighting potential damage locations, stress concentration levels, and risk level assessments.

[0071] Ellipsometric parameters are calculated vectorially based on the stress-optical coefficient tensor. Ellipsometric parameters are important quantities that describe the properties of elliptically polarized light. They primarily include ellipticity and the direction of the principal polarization axis. Ellipsometric parameters, reflecting the ratio of the major axis to the minor axis, directly reflect the birefringence response of light propagating through stressed materials. By vector mapping the principal direction components of the stress tensor with the polarization phase distribution, the ellipticity changes corresponding to the local stress state are extracted. Ellipsometric distribution data is generated, depicting the polarization state variation trends caused by stress changes at different locations and depths of the screen protector. The stress gradient response coefficient is calculated based on the ellipticity distribution data and the three-dimensional stress tensor component data. The stress gradient response coefficient is an important indicator for evaluating the rate of local stress change. By taking the spatial gradient of the ellipticity distribution and combining it with the rate of change of the stress tensor components at the corresponding locations, the severity of stress changes within the local region of the material is quantified. Based on this analysis, an adaptive modulation depth parameter is derived, allowing the modulation depth to be adaptively adjusted according to stress changes. In areas with drastic stress variations, stress concentrations, or microcrack initiation, the adaptive modulation depth parameter is increased to improve the elliptically polarized light's sensitivity to local stress anomalies. In areas with gentle stress variations, the modulation depth is appropriately reduced to ensure overall system stability and scanning efficiency. The adaptive modulation depth parameter is input into the dual-frequency drive configurator for frequency separation calculations. The dual-frequency drive configurator dynamically allocates horizontal and vertical modulation frequencies based on the modulation depth, with the horizontal modulation frequency set at 1.2 kHz and the vertical modulation frequency set at 0.8 kHz. This frequency separation calculation ensures that stress responses in different directions are effectively separated and independently modulated during the scanning process, avoiding frequency aliasing. During the frequency separation calculation, the base frequency is fine-tuned based on the severity of the local stress gradient, resulting in a denser modulation frequency in areas of drastic stress variations. This improves the accuracy of detecting subtle stress anomalies and microcrack initiation locations. This results in a set of dual-frequency drive parameters that dynamically match the local stress variation characteristics. Elliptical polarization dynamic tracking is performed based on the dual-frequency drive parameters and a thickness compensation factor. The thickness compensation factor effectively corrects for optical path differences caused by material thickness variations, ensuring the continuity and accuracy of the elliptical polarization modulation parameters at different depth levels. During dynamic tracking, the elliptical polarization's ellipticity and principal axis orientation parameters are updated in real time, dynamically adjusting the polarization state as the local stress state changes. This allows the polarized beam to flexibly respond to the complex and variable stress field distribution within the screen protector. Through these steps, the elliptical polarization modulation parameters are ultimately obtained.

[0072] The stress-photoelastic coupling response variables are calculated based on three-dimensional stress tensor component data and three-dimensional thickness distribution data. These variables are crucial for linking a material's internal stress state with its polarization response characteristics. Specifically, by combining the stress components with local thickness variations and the material's photoelastic properties, the response intensity of each spatial point to elliptically polarized light under a specific stress environment is quantified. The distribution of the coupled response variables reveals areas of stress concentration and dramatic stress gradient variations, as well as optical path variations caused by thickness non-uniformity, thereby generating coupled response variable distribution data. Adaptive modulation analysis of the elliptical polarization modulation parameters is performed based on the coupled response variable distribution data. By normalizing the coupled response variables, the optimal polarization modulation parameter combination for each local region is determined, including the ellipticity adjustment amplitude, the rate of change of the polarization principal axis direction, and the dynamic matching of the modulation frequency. Dynamic modulation configuration data is generated. These data, indexed by spatial position, provide the optimal modulation strategy parameters for each region. Scanning path planning is performed based on the dynamic modulation configuration data, generating target scanning path data. During path planning, priority is given to areas with large stress gradients and high coupled response variables. Scanning strategies using spiral, grid, or adaptive grid density adjustment are employed to ensure high scan point density and resolution in critical areas. The scanning step size is reduced to 2 μm × 2 μm × 1 μm in high-stress regions, ensuring high-precision coverage of microcrack initiation areas. In areas with gentle stress variations, the step size is appropriately increased to accelerate overall scanning speed. The scanning path is not only optimized in the plane but also layered in the thickness direction. Tomographic scanning, combined with 3D thickness distribution data, ensures uniform coverage within the 0.3 to 0.8 mm thickness range while also accounting for fine local features. This generates the target scanning path data. Dynamic tracking of polarization ellipse parameters is performed based on the target scanning path data and a thickness compensation factor. The introduction of the thickness compensation factor effectively corrects for optical path deviations caused by internal material thickness variations, ensuring the continuity and accuracy of polarization ellipse parameters at different depth levels. During dynamic tracking, various ellipse parameters, including ellipticity, principal axis orientation, and modulation depth, are updated in real time as the scanning path and local stress environment change, enabling the scanning beam to sensitively respond to spatial variations in the stress distribution within the protective film. By combining dynamic tracking with path planning, the spatial positioning data of stress damage is finally obtained. This data is output in the form of a high-spatial-resolution three-dimensional grid, which can calibrate the potential microcrack initiation location, stress abnormality area and damage risk level.

[0073] Step S5: reconstruct damage imaging of the edge cut area and the central curved area of ​​the screen protective film according to the stress damage spatial positioning data to obtain a three-dimensional stress damage imaging result.

[0074] Specifically, the stress damage spatial positioning data, thickness gradient vector field data, continuous polarization phase distribution data and coupling response variable distribution data are integrated to construct a damage imaging model parameter system based on these multi-source information. This system forms a multi-dimensional feature space that can reflect the stress distribution characteristics, thickness change trend, polarization response characteristics and photoelastic coupling effect of the multi-layer composite structure of the screen protective film by standardizing and spatially registering various physical quantities. The damage imaging model parameters include not only the local stress maximum value, stress gradient change rate, phase continuity index and coupling response strength, but also the thickness mutation characteristics and high-order statistical characteristics of each parameter in the spatial distribution, to ensure that the potential damage risk characteristics of different regions can be described. Based on the damage imaging model parameters, the edge cutting area and the central bending area of ​​the screen protective film are subjected to dual-region differential detection to generate regional detection configuration data. Taking into account that the edge cutting area is more prone to microcrack initiation caused by shear stress due to the mechanical stress concentration effect during the processing process, a higher spatial resolution and a more intensive scanning strategy are adopted in the detection configuration, and the scanning accuracy is set to 1 micron × 1 micron × 0.5 micron, with a focus on detecting the shear stress τ xy Distribution and its local gradient changes. The central bending area is affected by the bending load during use and mainly produces positive stress σ xx , σ yyBecause the stresses are primarily tensile and compressive, a fast scanning mode with a slightly larger step size is used in the central region, with scanning accuracy controlled within a 5 μm × 5 μm × 2 μm range. This focuses on detecting the normal stress distribution and its uniformity. A dual-region differentiated detection strategy, combining stress component type, thickness variation characteristics, and areas of polarization response anomalies, effectively improves detection efficiency and spatial resolution, while avoiding the resolution loss and detection blind spots associated with traditional imaging methods due to uniform configurations. Damage assessment is performed based on regional detection configuration data, generating a damage assessment index data system. Key indicators such as the stress concentration factor, gradient concentration factor, and interface debonding risk index are introduced during the damage assessment process. The stress concentration factor reflects the degree of local stress anomaly by calculating the ratio of the local maximum stress to the nominal stress; the gradient concentration factor reflects the inhomogeneity of the stress distribution by calculating the ratio of the local stress gradient peak to the global average gradient; and the interface debonding risk index assesses interlayer bonding risk based on the integral of the shear stress over the interface area. These indicators integrate multidimensional data such as stress, phase, thickness, and polarization response to form a systematic quantitative damage risk assessment system. Voxelized 3D imaging reconstruction is performed based on damage assessment index data to produce 3D stress damage imaging results. During the voxelized reconstruction process, the entire inspection area is divided into tiny voxel units, each sized at 2 cubic microns. Each voxel is assigned corresponding stress magnitude, gradient intensity, and damage risk level data. An interpolation algorithm is used to smooth transitions at voxel boundaries, ensuring visual continuity and data-based physical meaning in the 3D imaging results. The imaging results are presented in pseudo-color format, with low-stress areas indicated in blue, medium-stress areas in green, high-stress areas with potential damage risk in red, and areas with a high risk of microcrack initiation highlighted in yellow. The final output includes a 3D stress distribution cloud map, microcrack initiation location coordinates, damage level assessments for each area, and a complete inspection report.

[0075] In an embodiment of the present invention, by establishing thickness gradient vector field data to guide the non-periodic unwrapping processing of polarization phase difference distribution data, the cumulative error problem of the traditional 2π phase jump processing method in thin film materials is effectively solved, and high-precision acquisition of continuous polarization phase distribution data is achieved. A multi-layer configuration with four-quadrant polarization detectors set at different z-axis depth levels is adopted. Compared with the traditional single-layer polarization detection technology, it can better handle the interlayer interface effects of the glass-PVB-glass composite structure, and improve the detection accuracy and stability of the polarization phase difference distribution data. A modified Müller matrix transformation parameter suitable for the glass-PVB-glass composite structure is established, taking into account the anisotropic characteristics and interlayer interface effects of the screen protective film. Compared with the standard Müller matrix, it can more accurately realize the numerical conversion of polarization phase to stress component. Based on the adaptive modulation technology driven by the stress-photoelastic coupling response variable, through the dual-frequency driving scheme and the spiral path algorithm, the preferential scanning and precise positioning of the stress concentration area are achieved, which significantly improves the detection sensitivity of the microcrack initiation position. A dual-region differentiated detection strategy was established to address the different stress characteristics of the screen protector's edge cut region and central curved region. The edge region focuses on detecting shear stress distribution, while the central region primarily detects normal stress distribution, achieving targeted and efficient detection. By integrating stress tensor component data, thickness gradient information, polarization phase distribution, and coupled response variables, a multi-parameter fusion damage imaging model was established, enabling full-chain detection from geometric thickness changes to stress distribution and damage localization.

[0076] In a specific embodiment, the process of executing step S1 may specifically include the following steps:

[0077] Perform laser interferometry scanning on the screen protective film point by point to obtain the original thickness measurement data;

[0078] Performing three-dimensional coordinate mapping based on the original thickness measurement data to obtain three-dimensional thickness distribution data;

[0079] Partial differential gradient calculation is performed on the three-dimensional thickness distribution data to obtain thickness gradient vector field data.

[0080] Specifically, a laser interferometry system with high spatial resolution and high stability was constructed. The system consists of an interferometric laser with a stable wavelength output, a precision motion control platform, an interferometric probe, and a high-sensitivity detector. The light source uses a helium-neon laser with a wavelength of 632.8 nanometers to ensure strong coherence, effectively guaranteeing the clarity of the interference fringes and the resolution of the measurement system. The motion control platform utilizes a high-precision three-axis stepper motor or linear servo system, providing sub-micron displacement control accuracy, ensuring uniform scanning according to the set step size. The scanning path utilizes a point-by-point scanning method, with the control platform advancing the x- and y-directions at a spatial resolution of 10 microns by 10 microns. Simultaneously, a 2-micron step is used in the z-direction to achieve fine vertical tomographic sampling, covering a protective film thickness range of 0.3 mm to 0.8 mm. Throughout the scanning process, the principle of laser interferometry is used to calculate the local optical path length change of the film material from the phase change of the interference fringes, thereby inferring the actual thickness value corresponding to each scanning point. Because screen protectors are transparent, multi-layer structures, internal interface reflections introduce multiple interference signals. Therefore, the system is equipped with a multi-channel interference signal processing module. This module employs a Fourier transform-based signal separation algorithm to distinguish primary reflections from multiple reflections, ensuring the accuracy and reliability of the raw thickness measurement data. After completing point-by-point scanning and obtaining raw thickness measurement data, these data are mapped to a three-dimensional coordinate system to establish a spatial distribution model. The plane coordinates (x, y) of each scan point are mapped to the corresponding thickness value z, and the two-dimensional plane scan results are expanded into a three-dimensional point cloud dataset by adding z-axis depth information. To ensure the accuracy of the mapping process, mechanical errors of the scanning platform are compensated to correct for spatial distortion caused by accumulated errors in the motion system or laser beam tilt. Using a standard target-based planar correction method and a self-calibration algorithm, the scanning coordinate system is adjusted in real time, ensuring that the spatial position of each point reflects the actual surface and internal geometric characteristics of the film material. In order to enhance the continuity and smoothness of the three-dimensional thickness data and avoid data noise caused by surface micro-roughness or local measurement errors during the scanning process, a three-dimensional interpolation algorithm is introduced, such as cubic spline interpolation or Kriging interpolation method, to perform spatial fitting on the discrete thickness data, thereby generating a three-dimensional thickness distribution map T(x, y, z) with higher smoothness and spatial consistency. Partial differential gradient calculation is performed on the three-dimensional thickness distribution data to extract the thickness change rate information of the protective film in all directions in space and construct a thickness gradient vector field. The first-order partial differential operation is performed on the thickness distribution function T(x, y, z) in the x, y, and z directions respectively to obtain the thickness change rate components in each direction. The partial differential calculation uses the central difference method or the five-point difference method to improve the stability and accuracy of the numerical calculation. For the central difference method, at each node in the spatial grid, the local thickness gradient at the point is obtained by taking the thickness difference of the adjacent points and dividing it by the corresponding coordinate step size. For example, The thickness difference between two adjacent points in the x direction is divided by the step size of 10 microns. and The calculation method is similar to that of . The three-dimensional thickness gradient vector field consists of gradient components in these three directions and can describe the thickness variation trend of the protective film in all directions in space. In the actual calculation process, attention is paid to the influence of boundary conditions and local noise. In the edge area of ​​the scan, the lack of neighboring points leads to a decrease in the accuracy of traditional differential calculations. First-order forward or backward difference methods are introduced to compensate for this. For areas with local data noise, local weighted smoothing is used to filter the local thickness data before calculating the gradient to suppress the interference of high-frequency noise on the gradient results. To improve the physical interpretability of the gradient vector field, normalization is introduced to unify the amplitude of the gradient vector to a standard scale range, facilitating the subsequent identification of stress concentration areas and damage risk assessment. Considering that the screen protective film is a multi-layer composite structure with different optical properties and thickness change rates of materials in different layers, the construction of the thickness gradient vector field is corrected by a thickness compensation factor. The thickness compensation factor is set to decrease exponentially with depth z to reflect the optical attenuation characteristics within the material and the influence of thickness changes at the interlayer interface on light propagation. By performing thickness compensation correction on the three-dimensional thickness gradient vector field, the detection sensitivity of interface mutations is effectively enhanced, and the response capability to tiny thickness changes at the interface of multilayer structures such as glass-PVB-glass is improved.

[0081] In a specific embodiment, the process of executing step S2 may specifically include the following steps:

[0082] creating circularly polarized beam configuration parameters of a multilayer polarization interference optical system based on the three-dimensional thickness distribution data;

[0083] Performing a multi-layer depth scan on the screen protective film according to the circularly polarized beam configuration parameters to obtain four-quadrant polarization intensity data;

[0084] Polarization phase difference calculation is performed on the four-quadrant polarization intensity data to obtain initial phase difference distribution data, and polarization stability constraint is performed on the initial phase difference distribution data to obtain polarization phase difference distribution data.

[0085] Specifically, screen protectors have a multi-layer composite structure consisting of glass, PVB, and glass. The thickness and refractive index variations of the different layers significantly affect the propagation path and phase delay characteristics of light within the material. Therefore, before performing polarization interferometry testing, optical system parameters are constructed based on the thickness distribution. Combined with the spatial distribution of the thickness of each layer, the incident angle, wavelength, beam diameter, focal length configuration, and incident energy density of the circularly polarized beam are determined to ensure optimal interference effects at each thickness level. To reduce surface reflection interference and maximize the signal-to-noise ratio, a helium-neon laser with a wavelength of 632.8 nanometers is used as the light source. A high-precision quarter-wave plate converts linearly polarized light into circularly polarized light, and an incident angle of 15° is set to optimize the transmission and reflection conditions of the beam at the multi-layer interface, ensuring that thickness variations of each layer fully respond to the interference signal. Based on the three-dimensional thickness distribution data, the focal depth and energy density distribution of the circularly polarized beam are optimized to meet the requirements of tomographic scanning of screen protectors with a thickness range of 0.3 to 0.8 mm. By adjusting the beam diameter to adapt to the area with the largest local thickness variation of the protective film and performing energy homogenization through a collimating lens system, signal drift or distortion caused by local overexposure or underexposure is avoided. At the same time, according to the reflection characteristics of the multi-layer interface of the film material, a low-reflectivity coating is configured to suppress the interference fringe aliasing caused by multiple reflections, thereby improving the measurement accuracy. Through the above series of optical system parameter optimizations based on thickness distribution, a circularly polarized beam configuration is established. A multi-layer depth scan of the screen protective film is performed according to the circularly polarized beam configuration parameters. During the scanning process, a four-quadrant polarization detector is used to synchronously collect the polarization state intensity of the polarized light in the directions of 0°, 45°, 90°, and 135°, which are recorded as I0, I1, and I2, respectively. 45 , I 90 , I 135 . In order to adapt to the spatial characteristics of thickness changes, the scanning adopts a layered encryption strategy, increasing the number of scanning layers in the interface area where the thickness changes drastically (such as near the interface between glass and PVB), and optimizing the layer density in the z-axis direction from 200 layers of the traditional method to 80 layers, while reducing the scanning time, it still ensures that the important layers in the thickness range of 0.3 to 0.8 mm have sufficient depth resolution. The spatial step size is set to 10 microns × 10 microns in the x and y directions, and 2 microns in the z direction to ensure uniform sampling in all directions of space, thereby capturing the interference characteristics of polarized light in each layer thickness. Through the four-quadrant detection mode, the intensity changes in different polarization directions are obtained simultaneously. The polarization phase difference is calculated for the four-quadrant polarization intensity data. By comparing I0, I 45 , I 90 , I 135The four sets of polarization intensity data are differentially processed to calculate the initial phase difference distribution data. The phase difference is extracted using the inverse tangent expression, and the phase offset between different polarization states is calculated based on the intensity difference, thus constructing a preliminary polarization phase difference map in three-dimensional space. This initial phase difference data can reveal the birefringence variation characteristics of the material inside the screen protector at different depths and locations, indirectly reflecting the local stress state. However, the initial phase difference distribution is easily affected by factors such as light source instability, detector noise, and interface reflection interference, and has a certain degree of random drift and systematic error. To improve the stability and physical consistency of the phase difference distribution data, the initial phase difference data is subjected to polarization stability constraints. The core of the polarization stability constraint lies in constructing a stability constraint function. By analyzing the spatial consistency of the four-quadrant intensity data, it screens out physically reasonable phase variation patterns and corrects areas with abnormal offsets. In the specific operation, the normalized polarization stability factor of the four-quadrant intensity data is calculated, and the phase drift threshold is set to 0.02 radians. Anomalous points with polarization state changes exceeding the threshold are eliminated. At the same time, local mean filtering and Gaussian smoothing are performed within the spatial neighborhood to suppress isolated noise points and enhance the continuity of the phase distribution. This polarization stability constraint effectively eliminates the interference of random noise and system drift during the measurement process on the phase difference distribution. The resulting polarization phase difference distribution data has excellent spatial smoothness, continuity, and physical consistency.

[0086] In a specific embodiment, the process of executing step S3 may specifically include the following steps:

[0087] Performing depth correlation based on the thickness gradient vector field data and the polarization phase difference distribution data to obtain a thickness compensation factor;

[0088] performing phase jump discrimination on the thickness gradient vector field data according to the thickness compensation factor to obtain true phase jump identification data;

[0089] Dynamically adjusting the window size of the real phase jump identification data to obtain an adaptive window parameter;

[0090] A non-periodic de-envelope algorithm is performed on the polarization phase difference distribution data based on the adaptive window parameters to obtain continuous polarization phase distribution data.

[0091] Specifically, a spatial correlation is established between the thickness gradient vector field data and the polarization phase difference distribution data. The thickness gradient vector field data provides information on the local rate of thickness variation of the screen protector in the x, y, and z dimensions, while the polarization phase difference distribution data reveals detailed characteristics of the optical delay variations within the material. Although these two types of data originate from different sources, they correspond in spatial coordinate systems. Therefore, spatial registration techniques are used to deeply correlate them. For each 3D spatial location (x, y, z), the corresponding thickness gradient vector and polarization phase difference value are extracted. By analyzing the local synchronization between these two variations, the modulation effect of thickness variation on the polarization phase response is evaluated. Based on this spatial depth correlation, a thickness compensation factor is established to correct for the effect of thickness variation on the optical path length and eliminate the polarization phase error caused by thickness variation. The compensation factor is modeled based on the relationship between the thickness variation amplitude and the rate of polarization phase change. It adopts an exponential decay function that decreases with increasing depth, reflecting the optical attenuation characteristics of the material and multilayer interface effects. The thickness compensation factor not only relies on the local thickness variation rate but also incorporates material optical constants such as refractive index and extinction coefficient for modulation, enabling flexible adaptation between different material layers and avoiding phase anomalies caused by sudden refractive index changes at interfaces. To improve the robustness of the compensation factor, a multi-scale smoothing strategy is introduced during its construction. By averaging or weighted fitting within a local neighborhood, random noise interference with thickness compensation is suppressed, ensuring good spatial continuity and physical consistency of the compensation factor. Phase jump detection is performed on the thickness gradient vector field data based on the thickness compensation factor to identify true phase jump points. Traditional phase jump detection methods, based on the 2π periodicity assumption, are inadequate for true phase jumps within multilayer composite materials like screen protectors. Therefore, an improved detection logic is constructed. By setting a joint threshold for the thickness gradient variation rate and the weighted phase variation rate of the compensation factor, points where the local thickness variation exceeds the threshold and the corresponding phase difference abrupt change amplitude exceeds the expected continuous variation range are identified as true jump points. A spatial neighborhood consistency constraint is introduced during the detection process, requiring that jump points exhibit high consistency of variation within a certain neighborhood to prevent single isolated noise points from being mistakenly identified as jump points. Furthermore, considering that thickness mutations and phase jumps occur simultaneously at the interface layer, an interface sensitivity weight is introduced into the discrimination logic, assigning higher weight to thickness mutation locations near the glass-PVB interface, thereby improving the accuracy and sensitivity of jump recognition. This discrimination strategy effectively eliminates the traditional 2π jump error and identifies the actual physical phase jump points within the screen protector. The window size is dynamically adjusted for the actual phase jump recognition data to obtain the adaptive window parameters.Dynamic adjustment of the window size allows for flexible setting of the processing range during phase de-envelopment based on the characteristics of local thickness and phase variations. This avoids using an overly large window in areas of drastic thickness variations, which can lead to loss of detail, and also avoids using an overly small window in areas of gentle thickness variations, which can lead to inefficient processing. Specifically, the local rate of change is calculated based on the thickness gradient vector field data, and the window size is inferred from the magnitude of the rate of change. The larger the rate of change, the smaller the window size, and the smaller the rate of change, the more appropriate the window size increase. Then, combined with jump identification data, a smaller window is preferentially set at the jump point and its neighborhood to ensure that the phase mutation boundary can be accurately captured during de-envelopment. At the same time, a larger window is used in areas without jumps to improve the de-envelopment efficiency and stability of phase-continuous regions. Spatial transition smoothness is considered during dynamic window adjustment to avoid sudden changes in the window size, which can affect the continuity and consistency of the de-envelopment results. Based on the adaptive window parameters, a non-periodic de-envelopment algorithm is applied to the polarization phase difference distribution data to obtain continuous polarization phase distribution data. Compared with the traditional method based on 2π periodic jump correction, the non-periodic de-envelope algorithm can better adapt to the non-periodic phase mutations caused by thickness changes, stress concentration or interface effects inside the actual material. Within the adaptive window, the initial phase difference data is locally expanded, and the jump point is constrained as a boundary condition. The minimum jump cost path search or the shortest path algorithm based on graph optimization is used to connect the continuous phase areas in sequence and correct the phase misalignment at the jump position. By dynamically adjusting the window sliding range and step size, the entire three-dimensional phase difference distribution data is expanded layer by layer to eliminate the phase discontinuity problem caused by multi-layer interfaces and local thickness mutations. In order to further improve the de-envelope accuracy, phase smoothing constraints and polarization stability constraints are introduced in the processing process. By fitting the phase change trend in the local neighborhood, the interference of isolated noise points on the de-envelope results is eliminated, ensuring that the phase change remains physically continuous and reasonable. Through the above steps, continuous polarization phase distribution data is finally obtained.

[0092] In a specific embodiment, the step of performing phase jump discrimination on the thickness gradient vector field data according to the thickness compensation factor to obtain true phase jump identification data may specifically include the following steps:

[0093] constructing a phase jump discriminant function based on the thickness compensation factor;

[0094] performing gradient amplitude comparison on the thickness gradient vector field data according to the phase jump discriminant function to obtain thickness gradient threshold screening data;

[0095] performing phase difference amplitude calculation on the thickness gradient threshold screening data and the polarization phase difference distribution data to obtain phase mutation candidate point data;

[0096] Based on the phase mutation candidate point data, dual conditional logic judgment is performed to obtain true phase jump identification data.

[0097] Specifically, the thickness compensation factor is derived from the relationship between thickness distribution and optical attenuation characteristics. It is used to correct for the impact of internal material thickness variations on the light propagation path and phase delay, reflecting the actual contribution of materials at different depths to the polarized light interference phase response. When constructing the phase jump discriminant function, the thickness compensation factor is incorporated as a key weight into the discriminant logic, enabling the discrimination process to adapt to phase variation characteristics at different thickness levels and under different optical path conditions. The phase jump discriminant function comprehensively considers the relationship between the thickness gradient change rate and the local polarization phase difference change rate, constructing a detection model capable of dynamically adjusting sensitivity. By extracting the amplitude of the thickness gradient vector field data to obtain the local thickness change rate, and combining this with weighted processing using the thickness compensation factor, the discriminant function appropriately reduces sensitivity in deep regions with long optical paths and severe light intensity attenuation, while improving its responsiveness to subtle changes in shallower regions. The discriminant function employs either linear or exponential weighting, multiplying the thickness gradient amplitude by the thickness compensation factor to form a composite discriminant index, resulting in a weighted gradient field that accounts for both the thickness change rate and optical attenuation characteristics. By setting a reasonable discrimination threshold, regions with abnormally large and physically significant thickness variations are screened from the overall data as potential phase jump candidate regions. Based on the phase jump discrimination function constructed above, gradient amplitude comparison is performed on the thickness gradient vector field data. The thickness gradient amplitude is calculated at each spatial location and compared point by point with a set thickness change rate threshold. Local regions exceeding the threshold are screened to form thickness gradient threshold screening data. This screening data represents regions within the film material with abnormal thickness change rates, corresponding to locations of physical structural abrupt changes such as material interfaces, defect regions, or microcrack initiation points. To improve the stability and physical credibility of the screening results, spatial smoothing is introduced during the thickness gradient amplitude comparison process to avoid misclassification due to local noise or minor measurement errors. Furthermore, the threshold is dynamically adjusted during the discrimination process, and different discrimination criteria are set based on the thickness change amplitude at different material layers. This makes the screening process adaptive and robust, ensuring accurate identification of true thickness abrupt change regions at different depth levels. Phase difference amplitude calculation is performed on the thickness gradient threshold screening data and the polarization phase difference distribution data. By calculating the rate of change of the polarization phase difference between adjacent scanning layers, the phase change amplitude information is extracted and spatially aligned with the thickness gradient threshold screening data, allowing for a detailed analysis of the phase changes in areas of drastic thickness changes. During the phase difference amplitude calculation process, emphasis is placed on points where the phase change exceeds π or other obvious transition features, as these points correspond to physical phenomena such as sudden stress changes within the material, interface delamination, or crack initiation. To avoid random noise interference in the phase data, the phase difference distribution data is preprocessed before amplitude calculation, including Gaussian smoothing and local mean filtering, to improve the smoothness and continuity of the phase data.This method effectively identifies physically meaningful candidate phase jump points, which have a high degree of spatial overlap with thickness jump points. A dual-conditional logical discrimination is performed on the phase jump candidate data to obtain true phase jump identification data. The key to this dual-conditional logical discrimination is that only points that simultaneously meet the requirements of thickness gradient change amplitude exceeding a threshold and polarization phase difference change amplitude exceeding a set limit are considered true phase jump points. The thickness gradient threshold is set at 50 microns per millimeter, and the phase jump amplitude threshold is set between 0.8 and 1.2 times π to ensure that true physical jumps are captured, rather than artifacts caused by measurement noise. In the actual discrimination process, a logical AND operation is used to combine these two conditions. That is, only points that meet both the thickness change and phase change conditions at the same spatial location are retained as true jump points; other points that do not meet both conditions are eliminated. To improve the accuracy and robustness of the discrimination, connectivity analysis is introduced after the logical discrimination to eliminate isolated small jump points and retain jump regions that are spatially continuous and physically plausible.

[0098] In a specific embodiment, the process of executing step S4 may specifically include the following steps:

[0099] A modified Müller matrix is ​​constructed based on the continuous polarization phase distribution data to obtain Müller matrix transformation parameters corresponding to the glass-PVB-glass composite structure;

[0100] Performing stress-optical coefficient tensor calibration on the continuous polarization phase distribution data according to the Müller matrix transformation parameters to obtain a stress-optical coefficient tensor;

[0101] Performing elliptical polarization parameter modulation based on the stress-optical coefficient tensor to obtain elliptical polarization modulation parameters;

[0102] Performing three-dimensional stress tensor reconstruction on the continuous polarization phase distribution data based on the elliptical polarization modulation parameters to obtain three-dimensional stress tensor component data;

[0103] Dynamic elliptical polarization modulation scanning is performed based on the three-dimensional stress tensor component data to obtain stress damage spatial positioning data.

[0104] Specifically, the optical response characteristics within the material are analyzed based on continuous polarization phase distribution data. Screen protectors are composed of a three-layer composite of glass, PVB, and glass, each with distinct optical anisotropy and stress-optical response patterns. To describe the optical behavior of this multilayer composite, a modified version of the traditional Müller matrix is ​​constructed to characterize the polarization characteristics of multiple interfaces within the composite structure. Based on the trends in local phase retardation and light propagation direction reflected in the continuous polarization phase distribution data, combined with the refractive index, birefringence, and thickness ratio of each layer, the composite Müller matrix transformation parameters are derived. The modified Müller matrix not only incorporates traditional terms such as polarization rotation and polarization ellipticity change, but also incorporates interlayer optical path difference compensation terms and local light scattering coefficients. This allows the matrix model to accurately reflect the coupled characteristics of phase shift and polarization state changes at each material interface, thereby avoiding the error accumulation issues associated with traditional single-layer approximations. This modification establishes a Müller matrix transformation system that is more realistic in accord with physical reality. Based on the modified Müller matrix transformation parameters, the continuous polarization phase distribution data are calibrated using the stress-optical coefficient tensor. The stress optical effect describes the phenomenon that the optical properties of a material change under the action of force, which is manifested as a change in birefringence with stress. During the calibration process, a quantitative relationship is established between the continuous phase distribution of each point and its corresponding stress state. Specifically, the stress optical response coefficients in various directions are derived by taking the first-order spatial differential of the phase change rate and combining it with the anisotropy compensation term in the Müller matrix transformation parameters. In order to ensure the calibration accuracy, polynomial fitting or local weighted regression methods are used to fit the relationship between phase gradient and stress, thereby eliminating the interference of local noise and outliers. The obtained stress optical coefficient tensor contains not only the positive stress component σ xx , σ yy , also including the shear stress component τ xy, describing the stress response characteristics of a material in different directions and locations. Elliptical polarization parameters are modulated based on the stress-optical coefficient tensor to obtain the elliptical polarization modulation parameters. The elliptical polarization parameters, consisting of ellipticity and principal axis orientation angle, reflect the changes in the polarization state of light after it is modulated by the internal stress field as it propagates through the material. By analyzing the spatial distribution characteristics of the principal stress direction components and polarization phase changes in the stress-optical coefficient tensor, and using the polarization ellipticity formula, the ellipticity and principal axis orientation angle at each location are derived. These data are then aggregated to form the elliptical polarization modulation parameters. To enhance sensitivity to subtle stress anomalies and localized damage, an adaptive modulation depth mechanism is introduced during elliptical polarization modulation. This mechanism dynamically adjusts the modulation amplitude based on the magnitude of the local stress gradient, ensuring that the polarization modulation amplitude is increased in areas of intense stress variation and appropriately reduced in areas of uniform stress distribution, thereby maximizing scanning sensitivity and imaging accuracy. The modulation parameters are spatially varied continuously to avoid signal instability caused by sudden changes in the polarization state during scanning, ensuring that the elliptically polarized beam can smoothly traverse the complex stress field within the protective film and record local stress state changes. Three-dimensional stress tensors are reconstructed from the continuous polarization phase distribution data based on the elliptical polarization modulation parameters. By matching the polarization phase distribution with the modulated elliptical parameters point by point, the polarization response is inverted into stress component data using the inverse Müller matrix transformation, and the three-dimensional stress tensor components at each position are gradually restored. During the tensor reconstruction process, the anisotropic effect of the material and the interface reflection interference are taken into account. By introducing anisotropic correction terms and multi-layer interface models, the physical rationality and spatial continuity of the stress tensor reconstruction are ensured. In order to improve the reconstruction accuracy, a multi-scale iterative optimization method is used, combined with local phase continuity constraints and stress physical smoothing constraints, to iteratively correct the preliminary reconstruction results, eliminate local outliers, and smoothly transition the tensor distribution of different stress areas. The obtained three-dimensional stress tensor component data can not only reflect the stress distribution of each layer inside the screen protective film, but also capture the stress concentration phenomenon near the microcrack initiation point. Dynamic elliptical polarization modulation scanning is performed based on the three-dimensional stress tensor component data to obtain stress damage spatial positioning data. During dynamic scanning, the scanning path and polarization modulation strategy are adjusted in real time based on the spatial variation characteristics of the stress tensor distribution. Areas with drastic stress gradient changes are prioritized, and the scanning point density in these areas is increased, reducing the scanning step size to 2 microns × 2 microns × 1 micron to improve the resolution of areas with minor damage. The elliptical polarization modulation parameters are synchronously updated during the scanning process to ensure real-time matching of local stress states at different scanning positions and enhance the response sensitivity to minor stress anomalies. The scanning path is planned using a spiral, grid, or adaptively encrypted grid, combined with thickness compensation factor correction to ensure that the scanning density matches the stress variation characteristics at different depth levels, avoiding the omission of critical damage information.Through dynamic modulation scanning, the micro-crack initiation position, stress concentration area and potential failure area inside the screen protective film can be located with high precision in three-dimensional space, generating stress damage spatial positioning data.

[0105] In a specific embodiment, the step of performing elliptical polarization parameter modulation based on the stress optical coefficient tensor to obtain the elliptical polarization modulation parameters may specifically include the following steps:

[0106] Calculating an ellipsometric parameter vector based on the stress-optical coefficient tensor to obtain ellipticity distribution data;

[0107] Calculating a stress gradient response coefficient based on the ellipticity distribution data and the three-dimensional stress tensor component data to obtain an adaptive modulation depth parameter;

[0108] Inputting the adaptive modulation depth parameter into the dual-frequency drive configurator to perform frequency separation calculation to obtain the dual-frequency drive parameter;

[0109] Elliptical polarization dynamic tracking is performed based on the dual-frequency driving parameters and the thickness compensation factor to obtain elliptical polarization modulation parameters.

[0110] Specifically, the stress-optical coefficient tensor describes the specific effects of stress variations in various directions on a material's optical properties, particularly birefringence. This tensor is used to derive the polarization state variation trend of light propagating within the material. The ellipsometry parameter vector is calculated based on the stress-optical coefficient tensor. The spatial distribution of each component in the stress-optical coefficient tensor is used to derive the variation in the polarization ellipticity of local elliptically polarized light. During polarized light propagation, the direction of the principal stress within the material determines the orientation of the major axis of the elliptically polarized light, while the magnitude of the stress directly affects the ellipticity, which is the ratio of the lengths of the major and minor axes of the polarized light. By analyzing the principal value decomposition of the stress tensor, the maximum principal stress direction and the corresponding stress value are extracted. Combined with the material's photoelastic coefficients, the ratio of the major axis to the minor axis of the polarization ellipse is calculated to obtain the local ellipticity distribution data. This ellipticity distribution data reflects the strength of optical anisotropy at each location and reveals local changes in optical properties caused by stress concentration. The stress gradient response coefficient is calculated based on the ellipticity distribution data and the three-dimensional stress tensor component data. The stress gradient response coefficient reflects the degree of influence of the local stress change rate on the polarized light modulation response. For the micro-damage initiation area, the local stress gradient shows a dramatic change. Therefore, the area with a high response coefficient is the potential location for microcrack formation. In the specific operation, the first-order partial differential of the three-dimensional stress tensor components in space is performed to calculate σ xx , σ yy and τ xyThe gradient amplitudes in the x, y, and z directions are then combined into a unified stress gradient amplitude index. This stress gradient amplitude is then weighted and combined with the ellipticity value at the corresponding location to construct a stress gradient response coefficient that comprehensively reflects the severity of local stress changes. To enhance sensitivity to stress changes at different scales, a multi-scale response analysis strategy is introduced. This strategy simultaneously calculates the gradient amplitude at different spatial scales and weighted averages the results at each scale, thereby taking into account both large-scale stress changes and localized minor stress mutations. Based on the distribution of the stress gradient response coefficients, an adaptive modulation depth parameter is generated. The adaptive modulation depth is increased in areas of intense stress changes to enhance polarization modulation sensitivity and moderately decreased in areas of uniform stress distribution to optimize system stability and scanning speed. The adaptive modulation depth parameter is input into the dual-frequency drive configurator for frequency separation calculation. The polarization modulation signal is frequency-distributed in both the horizontal and vertical directions to achieve finer-grained spatial modulation control. Based on the adaptive modulation depth parameters, the base modulation depth and base frequency are determined. The horizontal and vertical modulation frequencies are then dynamically adjusted based on the strength of the local stress gradient response to achieve frequency separation, thereby forming a spiral or grid-like modulation path coverage pattern in space. During the frequency separation calculation, the frequency offsets of the horizontal and vertical modulation frequencies are dynamically adjusted based on the local response coefficient. This ensures that the modulation frequency is increased in stress concentration areas to enhance sensitivity in detecting microcrack initiation zones, while the frequency is reduced in areas of gentle stress variation to optimize scanning efficiency and data acquisition rate. To ensure spatial continuity of frequency variation and prevent modulation instability caused by frequency jumps, a low-pass filter is introduced during the frequency allocation process to ensure smooth frequency transitions with spatial position, maintaining the overall stability of the modulation system. After the frequency separation calculation is completed and the dual-frequency drive parameters are obtained, elliptical polarization dynamic tracking is performed in conjunction with a thickness compensation factor to generate the elliptical polarization modulation parameters. The thickness compensation factor is used to correct for the effects of material thickness variations on optical path length and polarization state evolution. This is particularly true in multilayer composite materials such as screen protectors, where thickness variations can significantly modulate the light propagation path and polarization state at different depths. Therefore, during the dynamic tracking process, the thickness compensation factor is introduced into the elliptical polarization modulation model in real time to perform depth-dependent corrections on the ellipticity and principal axis direction angle. In specific operations, at each scanning position, the current modulation frequency and amplitude are determined according to the dual-frequency drive parameters, and the ellipticity and polarization principal axis angle are adjusted according to the thickness compensation factor, so that the modulated elliptical polarization state can accurately match the local material thickness and stress environment, ensuring the physical consistency and spatial continuity of the polarization response. During the dynamic tracking process, a real-time feedback mechanism is adopted, that is, according to the measurement results of the polarization state of the current scanning point, the modulation parameters of the subsequent scanning path are dynamically adjusted to form a closed-loop control system, which further improves the modulation sensitivity and spatial resolution.By combining thickness and stress modulation, the system achieves highly sensitive detection of minor stress anomalies and early crack initiation areas while maintaining high scanning speeds, improving the overall performance and engineering applicability of the screen protector micro-damage detection system. The elliptical polarization modulation parameters are output as a spatially continuous parameter field.

[0111] In a specific embodiment, the step of performing dynamic elliptical polarization modulation scanning based on the three-dimensional stress tensor component data to obtain stress damage spatial positioning data may specifically include the following steps:

[0112] performing stress-photoelasticity coupling response variable calculation based on the three-dimensional stress tensor component data and the three-dimensional thickness distribution data to obtain coupling response variable distribution data;

[0113] performing adaptive modulation analysis on the elliptical polarization modulation parameters according to the coupling response variable distribution data to obtain dynamic modulation configuration data;

[0114] Performing scan path planning based on the dynamic modulation configuration data to obtain target scan path data;

[0115] Dynamic tracking of polarization ellipse parameters is performed based on the target scanning path data and the thickness compensation factor to obtain stress damage spatial positioning data.

[0116] Specifically, a coupled response model is established based on the three-dimensional stress tensor component data and the three-dimensional thickness distribution data. The three-dimensional stress tensor component data provides the normal stress σ in each direction inside the material. xx , σ yy and shear stress τ xyThe local stress state, such as the thickness distribution, is determined by the material's thickness distribution, while the three-dimensional thickness distribution data records the thickness variation of the protective film in the x, y, and z dimensions. The calculation of the stress-photoelastic coupled response variable requires considering both the material's stress state and thickness variation. The coupled response variable reflects the degree of birefringence caused by the material under stress and is affected by thickness. By weightedly superimposing the modulus of each stress tensor component with the thickness distribution, a stress-photoelastic response function is constructed. This function incorporates the effects of local stress concentration and optical path length variation on the polarization state, quantifying the intensity of the polarization response at different locations. To enhance the physical significance of the coupled response variable, the calculation incorporates the differences in photoelastic coefficients and refractive index of the various layers of the screen protector. This creates a photoelastic response model that conforms to the characteristics of the glass-PVB-glass composite structure, ensuring a smooth and physically plausible response transition at the interfaces between the different materials. The resulting coupled response variable distribution data is presented as a three-dimensional grid, capturing the local polarization response capability at each point in space. Based on the coupled response variable distribution data, adaptive modulation analysis of the elliptical polarization modulation parameters is performed. The elliptical polarization modulation parameters, including ellipticity, principal axis orientation angle, and modulation depth, determine the polarization state variation pattern of the scanning beam in a local area. To adapt to the stress state and thickness characteristics of different regions, adaptive modulation analysis dynamically adjusts the modulation parameters based on the magnitude of the coupled response variable. In regions with high coupled response variables, indicating stress concentration and dramatic thickness variations, the ellipticity modulation amplitude and modulation depth are increased to enhance sensitivity to minor damage. In regions with low coupled response variables, where stress distribution is more uniform and thickness variations are more gradual, the modulation amplitude and modulation depth are appropriately reduced to optimize scanning efficiency and system stability. To ensure spatial continuity of the modulation parameters and smoothness of the modulation process, spatial smoothing filtering and local continuity constraints are introduced during the adaptive modulation analysis process to avoid sudden changes in the modulation parameters, which could lead to polarization instability or scanning anomalies. The generated dynamic modulation configuration data contains the optimal modulation parameter configuration for each spatial location. Scanning path planning is performed based on this dynamic modulation configuration data to generate target scanning path data. Scanning path planning fully considers the spatial distribution of the coupled response variables, prioritizing coverage of high-response regions and increasing the number of scan points to improve damage detection sensitivity. A response weight map is generated based on the coupled response variable distribution data, assigning higher scanning density to regions with high response values ​​and lowering scanning density to regions with low response values. The weight map is then used for adaptive meshing, dynamically adjusting the scanning step size. In high-response areas, the scanning step size is reduced to 2 microns by 2 microns by 1 micron, while in low-response areas, the step size is moderately increased to 10 microns by 10 microns by 5 microns, achieving a balance between detection accuracy and scanning efficiency. Furthermore, to ensure the continuity and smoothness of the scanning path, a spiral or surface-expanding path planning algorithm is used to avoid positioning errors and wasted scanning time caused by path jumps or rotations.During the path planning process, the device's motion inertia and speed variations are taken into account, and the scanning speed is dynamically adjusted to synchronize changes in the modulation frequency and step size, thereby minimizing scanning errors and improving overall system stability. Dynamic tracking of polarization ellipse parameters is performed based on the target scanning path data and thickness compensation factors to obtain spatial localization data for stress damage. The thickness compensation factor is introduced to correct for optical path differences and phase drift caused by thickness variations within the film material, ensuring that polarization state changes accurately reflect the local stress state when scanning at different depth levels without being affected by thickness variations. At each scanning point, the basic ellipse polarization parameters are determined based on the current dynamic modulation configuration data. The ellipse and principal axis orientation angle are adjusted in real time in combination with the thickness compensation factor, ensuring that the modulated polarized light can maximize its response to stress changes and structural anomalies in the local area. During the dynamic tracking process, a real-time feedback mechanism is introduced to dynamically adjust the modulation parameters and scanning path of subsequent scanning points based on the actual polarization light response results, forming a closed-loop control system that effectively improves the accuracy of the polarization response and the stability of the scanning path. Through joint modeling and dynamic modulation optimization based on three-dimensional stress tensor component data and three-dimensional thickness distribution data, it is possible to locate the microcrack initiation position, stress concentration area and potential failure area inside the screen protective film with high resolution in three-dimensional space, and generate stress damage spatial positioning data.

[0117] In a specific embodiment, the process of executing step S5 may specifically include the following steps:

[0118] Constructing damage imaging model parameters based on the stress damage spatial positioning data, the thickness gradient vector field data, the continuous polarization phase distribution data, and the coupled response variable distribution data;

[0119] performing dual-region differential detection on the edge cut region and the central curved region of the screen protective film according to the damage imaging model parameters to obtain region detection configuration data;

[0120] A damage assessment is performed based on the regional detection configuration data to obtain damage assessment index data, and voxelized three-dimensional imaging reconstruction is performed based on the damage assessment index data to obtain a three-dimensional stress damage imaging result.

[0121] Specifically, stress damage spatial localization data provides a preliminary spatial distribution of local stress anomalies in a three-dimensional coordinate system. Thickness gradient vector field data describes the rate of thickness change of the film material in different spatial directions, reflecting local topographical characteristics. Continuous polarization phase distribution data reveals the optical path differences at each point within the material. Coupled response variable distribution data quantifies the coupling strength between stress and photoelastic response. These four data sets are physically interrelated and require a one-to-one correspondence in space. Therefore, using spatial interpolation and coordinate registration methods, the four data sets are mapped onto a unified three-dimensional grid system and synchronized to ensure that each spatial voxel contains complete multi-source feature information. The damage imaging model parameters are constructed based on these multi-source feature data. A multidimensional feature description is assigned to each voxel by defining a set of joint feature vectors describing the degree of local stress anomaly, the rate of thickness change, the degree of phase continuity anomaly, and the strength of the photoelastic response. To enhance the model's sensitivity to micro-damage and microcrack initiation regions, each feature term is normalized and weighted according to its physical importance to form a unified weighted damage factor. The stress damage spatial positioning data mainly reflects the degree of stress concentration, so it is given a higher weight; the thickness gradient vector field is used to identify structural mutations or interface fractures, and its weight is second; the continuous polarization phase distribution data is used to capture local optical anomalies and reflect the potential trend of microcrack formation, and its weight is slightly lower; and the coupled response variable is a supplementary feature because it can integrate stress and optical effects, and is given a moderate weight. By weighted combination of various features, a unified damage imaging model parameter is formed. Based on the damage imaging model parameters constructed above, dual-region differential detection is performed on the edge cutting area and the central bending area of ​​the screen protective film. Since the edge cutting area is susceptible to mechanical shear stress concentration during processing, and the central bending area is subjected to greater tensile and compressive stresses during use, there are significant differences between the two in damage characteristics, stress distribution patterns and microcrack initiation mechanisms. In order to adapt to this characteristic, the differentiated detection strategy sets a high-density scanning mode in the edge area, controls the detection step size to 1 micron × 1 micron × 0.5 micron, and focuses on detecting the shear stress component τ xy and its spatial gradient changes, enhancing the recognition ability of small defects such as interface peeling and incision expansion; while in the central bending area, a moderately relaxed fast scanning mode is adopted, with the step size set to 5 microns × 5 microns × 2 microns, focusing on the normal stress component σ xx , σ yyand its uniformity analysis, focusing on the early identification of tensile cracks and bending fatigue cracks. Based on this dual-mode strategy, regional detection configuration data is dynamically generated to clarify the scanning density, feature priority, and detection sensitivity settings of different detection sub-regions, ensuring that the damage detection process can adapt to the physical property differences of different regions, achieving resource optimization and improving detection efficiency. Damage assessment is performed based on the regional detection configuration data to obtain damage assessment index data. During the assessment process, multi-dimensional damage indicators such as stress concentration factor, gradient concentration factor, and interface debonding risk index are introduced. The stress concentration factor quantifies the degree of local stress anomaly by calculating the ratio of the local maximum stress to the surrounding average stress; the gradient concentration factor reflects the unevenness of the stress distribution in the damaged area by evaluating the ratio of the local maximum gradient of stress or thickness change to the global average gradient; the interface debonding risk index evaluates the failure risk of interface layer debonding, peeling, etc. based on the integral of shear stress in the interface area. In addition, polarization phase discontinuity is introduced as an optical anomaly indicator to reflect the degree of damage to the continuity of the optical path caused by microcrack formation. By weightedly combining various indicators, a multidimensional damage assessment vector is formed. Each spatial voxel unit is assigned a comprehensive damage grade, which is divided into a score system, from low to high, representing healthy, slightly damaged, moderately damaged, and severely damaged. Based on the damage assessment index data, voxelized three-dimensional imaging reconstruction is performed, and three-dimensional stress damage imaging results are output. During the reconstruction process, the entire scan area is divided into voxel units of equal size, and the voxel size is set to 2 cubic microns to balance imaging resolution and data processing capacity. Within each voxel, a pseudo-color mapping value is determined based on the comprehensive damage grade. Low damage grades are displayed in blue, medium damage grades are displayed in a green-to-yellow transition, and high damage grades are highlighted in red and purple, creating an intuitive and clearly layered damage visualization effect. To enhance imaging smoothness and detail continuity, a three-dimensional interpolation algorithm is used to spatially smooth the damage grade data, eliminate discrete noise points, and improve image coherence. At the same time, to facilitate subsequent data analysis and engineering applications, the three-dimensional stress damage imaging results are output in a variety of data formats, including three-dimensional mesh models for morphology modeling, pseudo-color images superimposed on three-dimensional voxel data for stress distribution visualization, and statistical data of each damage area in tabular form for risk assessment and life prediction.

[0122] The above describes the damage detection method of the screen protective film in the embodiment of the present invention. The following describes the damage detection system of the screen protective film in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, a system for detecting damage to a screen protective film includes:

[0123] A scanning module is used to perform laser interference thickness scanning on the screen protective film to obtain three-dimensional thickness distribution data and thickness gradient vector field data;

[0124] a detection module, configured to perform multi-layer polarization interference detection on the circularly polarized light beam based on the three-dimensional thickness distribution data to obtain polarization phase difference distribution data;

[0125] a processing module, configured to perform a non-periodic phase de-envelope processing on the polarization phase difference distribution data according to the thickness gradient vector field data to obtain continuous polarization phase distribution data;

[0126] A modulation module, configured to perform stress optical coefficient tensor calculation and dynamic elliptical polarization modulation based on the continuous polarization phase distribution data to obtain stress damage spatial positioning data;

[0127] The reconstruction module is used to reconstruct damage imaging of the edge cutting area and the central bending area of ​​the screen protective film according to the stress damage spatial positioning data to obtain a three-dimensional stress damage imaging result.

[0128] Through the collaborative efforts of these components, a non-periodic unwrapping of polarization phase difference distribution data guided by thickness gradient vector field data is established, effectively addressing the cumulative error problem of traditional 2π phase jump processing methods in thin film materials and achieving high-precision acquisition of continuous polarization phase distribution data. A multi-layer configuration with four-quadrant polarization detectors at different z-axis depths better accounts for interlayer interface effects in glass-PVB-glass composite structures compared to traditional single-layer polarization detection techniques, improving the accuracy and stability of polarization phase difference distribution data. A modified Müller matrix transformation parameter for glass-PVB-glass composite structures is established, accounting for the anisotropic properties of screen protectors and interlayer interface effects. This provides a more accurate numerical conversion of polarization phase to stress components than the standard Müller matrix. An adaptive modulation technique driven by stress-photoelastic coupling response variables, using a dual-frequency drive scheme and a spiral path algorithm, enables preferential scanning and precise localization of stress concentration areas, significantly improving the sensitivity of microcrack initiation detection. A dual-region differentiated detection strategy was established to address the different stress characteristics of the screen protector's edge cut region and central curved region. The edge region focuses on detecting shear stress distribution, while the central region primarily detects normal stress distribution, achieving targeted and efficient detection. By integrating stress tensor component data, thickness gradient information, polarization phase distribution, and coupled response variables, a multi-parameter fusion damage imaging model was established, enabling full-chain detection from geometric thickness changes to stress distribution and damage localization.

[0129] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0130] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0131] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting damage to a screen protective film, characterized in that: include: Perform laser interferometry thickness scanning on the screen protective film to obtain three-dimensional thickness distribution data and thickness gradient vector field data; Performing multi-layer polarization interference detection on a circularly polarized light beam based on the three-dimensional thickness distribution data to obtain polarization phase difference distribution data; specifically comprising: creating circularly polarized light beam configuration parameters of a multi-layer polarization interference optical system based on the three-dimensional thickness distribution data; performing multi-layer depth scanning on the screen protective film according to the circularly polarized light beam configuration parameters to obtain four-quadrant polarization intensity data; performing polarization phase difference calculation on the four-quadrant polarization intensity data to obtain initial phase difference distribution data, and performing polarization stability constraint on the initial phase difference distribution data to obtain polarization phase difference distribution data; The method comprises the following steps: performing non-periodic phase de-envelopment processing on the polarization phase difference distribution data according to the thickness gradient vector field data to obtain continuous polarization phase distribution data; performing depth correlation on the thickness gradient vector field data and the polarization phase difference distribution data to obtain a thickness compensation factor; performing phase jump discrimination on the thickness gradient vector field data according to the thickness compensation factor to obtain true phase jump identification data; dynamically adjusting the window size of the true phase jump identification data to obtain an adaptive window parameter; and performing a non-periodic de-envelopment algorithm on the polarization phase difference distribution data based on the adaptive window parameter to obtain continuous polarization phase distribution data. Based on the continuous polarization phase distribution data, stress optical coefficient tensor calculation and dynamic elliptical polarization modulation are performed to obtain stress damage spatial positioning data; specifically comprising: constructing a modified Müller matrix based on the continuous polarization phase distribution data to obtain Müller matrix transformation parameters corresponding to the glass-PVB-glass composite structure; calibrating the stress optical coefficient tensor of the continuous polarization phase distribution data according to the Müller matrix transformation parameters to obtain a stress optical coefficient tensor; performing elliptical polarization parameter modulation based on the stress optical coefficient tensor to obtain elliptical polarization modulation parameters; reconstructing a three-dimensional stress tensor on the continuous polarization phase distribution data based on the elliptical polarization modulation parameters to obtain three-dimensional stress tensor component data; performing dynamic elliptical polarization modulation scanning based on the three-dimensional stress tensor component data to obtain stress damage spatial positioning data; Damage imaging reconstruction is performed on the edge cutting area and the central bending area of ​​the screen protective film according to the stress damage spatial positioning data to obtain a three-dimensional stress damage imaging result.

2. The method for detecting damage to a screen protective film according to claim 1, wherein: The laser interference thickness scanning of the screen protective film is performed to obtain three-dimensional thickness distribution data and thickness gradient vector field data, including: Perform laser interferometry scanning on the screen protective film point by point to obtain the original thickness measurement data; Performing three-dimensional coordinate mapping based on the original thickness measurement data to obtain three-dimensional thickness distribution data; Partial differential gradient calculation is performed on the three-dimensional thickness distribution data to obtain thickness gradient vector field data.

3. The method for detecting damage to a screen protective film according to claim 1, wherein: The performing phase jump discrimination on the thickness gradient vector field data according to the thickness compensation factor to obtain true phase jump identification data includes: constructing a phase jump discriminant function based on the thickness compensation factor; performing gradient amplitude comparison on the thickness gradient vector field data according to the phase jump discriminant function to obtain thickness gradient threshold screening data; performing phase difference amplitude calculation on the thickness gradient threshold screening data and the polarization phase difference distribution data to obtain phase mutation candidate point data; Based on the phase mutation candidate point data, dual conditional logic judgment is performed to obtain true phase jump identification data.

4. The method for detecting damage to a screen protective film according to claim 1, wherein: The step of performing elliptical polarization parameter modulation based on the stress optical coefficient tensor to obtain elliptical polarization modulation parameters includes: Calculating an ellipsometric parameter vector based on the stress-optical coefficient tensor to obtain ellipticity distribution data; Calculating a stress gradient response coefficient based on the ellipticity distribution data and the three-dimensional stress tensor component data to obtain an adaptive modulation depth parameter; Inputting the adaptive modulation depth parameter into the dual-frequency drive configurator to perform frequency separation calculation to obtain the dual-frequency drive parameter; Elliptical polarization dynamic tracking is performed based on the dual-frequency driving parameters and the thickness compensation factor to obtain elliptical polarization modulation parameters.

5. The method for detecting damage to a screen protective film according to claim 1, wherein: The performing of dynamic elliptical polarization modulation scanning based on the three-dimensional stress tensor component data to obtain stress damage spatial positioning data includes: performing stress-photoelasticity coupling response variable calculation based on the three-dimensional stress tensor component data and the three-dimensional thickness distribution data to obtain coupling response variable distribution data; performing adaptive modulation analysis on the elliptical polarization modulation parameters according to the coupling response variable distribution data to obtain dynamic modulation configuration data; Performing scan path planning based on the dynamic modulation configuration data to obtain target scan path data; Dynamic tracking of polarization ellipse parameters is performed based on the target scanning path data and the thickness compensation factor to obtain stress damage spatial positioning data.

6. The method for detecting damage to a screen protective film according to claim 5, wherein: The damage imaging reconstruction of the edge cutting area and the central bending area of ​​the screen protective film is performed according to the stress damage spatial positioning data to obtain a three-dimensional stress damage imaging result, including: Constructing damage imaging model parameters based on the stress damage spatial positioning data, the thickness gradient vector field data, the continuous polarization phase distribution data, and the coupled response variable distribution data; performing dual-region differential detection on the edge cut region and the central curved region of the screen protective film according to the damage imaging model parameters to obtain region detection configuration data; A damage assessment is performed based on the regional detection configuration data to obtain damage assessment index data, and voxelized three-dimensional imaging reconstruction is performed based on the damage assessment index data to obtain a three-dimensional stress damage imaging result.

7. A damage detection system for a screen protective film, characterized in that: A method for detecting damage to a screen protective film according to any one of claims 1 to 6, wherein the damage detection system for the screen protective film comprises: A scanning module is used to perform laser interference thickness scanning on the screen protective film to obtain three-dimensional thickness distribution data and thickness gradient vector field data; a detection module, configured to perform multi-layer polarization interference detection on the circularly polarized light beam based on the three-dimensional thickness distribution data to obtain polarization phase difference distribution data; a processing module, configured to perform a non-periodic phase de-envelope processing on the polarization phase difference distribution data according to the thickness gradient vector field data to obtain continuous polarization phase distribution data; A modulation module, configured to perform stress optical coefficient tensor calculation and dynamic elliptical polarization modulation based on the continuous polarization phase distribution data to obtain stress damage spatial positioning data; The reconstruction module is used to reconstruct damage imaging of the edge cutting area and the central bending area of ​​the screen protective film according to the stress damage spatial positioning data to obtain a three-dimensional stress damage imaging result.

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