Flexible display function film defect detection method and system

Abstract

The invention belongs to the technical field of optical detection, and discloses a defect detection method and system for a flexible display functional film. Comprising the steps that optical response signals of all film layers in the flexible display function film under excitation of different light fields are collected, and multi-dimensional spectral response tensors are formed; monitoring the in-layer deformation displacement and the inter-layer relative slippage of each film layer in real time, and performing time registration fusion with the multi-dimensional spectral response tensor to generate a stress-optical coupling characteristic spectrum; performing tensor decomposition on the stress-optical coupling characteristic spectrum, and establishing a multi-level defect fingerprint database; fusing the multi-level defect fingerprint database and a predefined constitutive relation model, and generating a defect criticality time-varying curve of each film layer; calculating the critical failure time of each film layer according to the defect criticality time-varying curve, and dynamically generating defect management information; according to the invention, intelligent conversion from passive detection to active early warning can be realized, and the quality control level and the product reliability of the flexible display functional film are effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of optical detection, more particularly, to a flexible display functional film defect detection method and system. BACKGROUND

[0002] As the core direction of the new generation of display technology, flexible display technology is widely used in foldable mobile phones, wearable devices, vehicle curved screens and other fields. Flexible display functional film, as a key component of flexible display devices, is usually composed of multiple functional film layers, including flexible substrate layer, transparent conductive layer, polarizing layer, phase difference film layer, protective layer, etc. Each film layer cooperates to realize the display function. Since the flexible display functional film needs to withstand repeated bending, stretching and other mechanical stresses in actual use, micro-cracks, orientation deviation, delamination and other defects are easily generated in the internal film layers and interfacial layers. These defects will directly affect the display effect and product service life. Therefore, it is of great significance to establish an efficient and accurate flexible display functional film defect detection method to ensure product quality and reliability.

[0003] Currently, the defect detection of flexible display functional film mainly adopts optical imaging detection method, which obtains the surface image of the film layer through single light source illumination, and then identifies the surface defects by combining image processing algorithm. However, the existing technology has the following shortcomings: first, single light source illumination cannot obtain the response characteristics of the film layer under different optical conditions, and the detection rate of micro-defects and hidden defects is low; second, the existing method mainly detects the whole film layer, which cannot effectively distinguish the orientation defects in each film layer and the interfacial defects, and cannot realize accurate positioning of defects; third, static optical detection can only reflect the current defect state, and cannot reveal the evolution trend of defects under actual use conditions, lacking the forward-looking assessment ability of defect hazard; therefore, an intelligent flexible display functional film defect detection method is urgently needed to meet the urgent needs of high reliability quality control of flexible display products.

[0004] In view of this, the present application provides a flexible display functional film defect detection method and system to solve the above problems. SUMMARY

[0005] In order to overcome the above-mentioned defects of the prior art and achieve the above-mentioned purposes, the present application provides the following technical scheme: a flexible display functional film defect detection method, comprising: A programmable array light source is constructed to apply different light field excitation modes to the surface of the flexible display functional film, and the optical response signals of each film layer in the flexible display functional film under different light field excitation modes are collected to form a multi-dimensional spectral response tensor. A mechanical micro-stress field with a preset gradient is applied synchronously to the flexible display functional film. The intralayer deformation displacement and interlayer relative slip of each film layer are monitored in real time and fused with the multidimensional spectral response tensor to generate a stress-optical coupling feature map. Tensor decomposition was performed on the stress-optical coupling feature map. Based on the in-plane components obtained by decomposition, orientation defect fingerprints of each film layer were extracted. Based on the out-of-plane components obtained by decomposition and the relative slip between layers, interface defect fingerprints were extracted. A multi-level defect fingerprint library was established. By integrating a multi-level defect fingerprint database with a predefined constitutive relation model, the defect propagation dynamic equations for each membrane layer are constructed, and the temporal evolution trajectory of defects in each membrane layer under preset working conditions is predicted, generating time-varying curves of defect severity for each membrane layer. Based on the time-varying curves of the defect severity of each membrane layer, the critical failure time of each membrane layer is calculated, and defect management information is dynamically generated based on the critical failure time.

[0006] Furthermore, methods for forming multidimensional spectral response tensors include: Under each optical field excitation mode, the reflected optical response signal, the transmitted optical response signal, and the fluorescent optical response signal are acquired simultaneously; the material optical constants and thickness information of each film layer are obtained, and a multilayer film optical transmission model is established based on the material optical constants and thickness information; the acquired reflected optical response signal, transmitted optical response signal, and fluorescent optical response signal are inversely calculated based on the multilayer film optical transmission model to separate the optical response signal of each film layer. For the optical response signals of each film layer under different optical field excitation modes, the corresponding spectral peak wavelength, spectral half width at half maximum, spectral integral intensity and phase gradient are extracted sequentially and used as optical response feature parameters. The dimensional structure of the multidimensional spectral response tensor is defined, the optical response feature parameters of each film layer are normalized, and the multidimensional spectral response tensor is organized and filled according to the dimensional structure of the multidimensional spectral response tensor to form a multidimensional spectral response tensor.

[0007] Furthermore, methods for generating stress-optical coupling feature maps include: Record the actual stress state of the flexible display functional film at each time point during the application of a mechanical micro-stress field to obtain a stress loading time series table; and form a stress-deformation time series dataset based on the intralayer deformation displacement, interlayer relative slip, and stress loading time series table of each film layer. Based on a unified time reference, the stress-deformation time series dataset and the multidimensional spectral response tensor are time-registered and fused to form a time-registered fused dataset. Based on the time-registration fusion dataset, the stress-optical coupling coefficient of each film layer is calculated. The stress-optical coupling coefficient includes the deformation-intensity coupling coefficient and the slip-phase coupling coefficient. Based on the time-registration fusion dataset, the stress response gradient set of each film layer is extracted. The structure of the stress-optical coupling feature map is defined, the stress-optical coupling coefficients and stress response gradient sets of each film layer are normalized, and the structure is filled according to the stress-optical coupling feature map to generate the stress-optical coupling feature map.

[0008] Furthermore, methods for tensor decomposition of stress-optical coupling feature maps include:

[0009] Based on the stress-optical coupling feature map, a high-order coupling feature tensor is constructed. This high-order coupling feature tensor is then decomposed to obtain the core tensor and factor matrices for each dimension. Each factor matrix contains multiple principal component vectors. The in-plane and out-of-plane correlation coefficients for each principal component vector corresponding to each film layer are calculated. The principal component vector with the largest in-plane correlation coefficient for each film layer is taken as the in-plane component tensor of that film layer. The principal component vector with the largest out-of-plane correlation coefficient for each film layer is taken as the out-of-plane component tensor of that film layer. Based on the in-plane and out-of-plane component tensors of each film layer, the in-plane and out-of-plane components of each film layer are calculated.

[0010] Furthermore, methods for establishing a multi-level defect fingerprint database include: The in-plane feature matrix of each film layer is extracted from the in-plane component; the orientation anisotropy index of each film layer is calculated based on the in-plane feature matrix; the polarization extinction ratio of each film layer under polarization switching excitation mode is extracted from the multidimensional spectral response tensor; and the orientation defect fingerprint of each film layer is constructed based on the orientation anisotropy index and polarization extinction ratio of each film layer. The out-of-plane feature matrix of each film layer is extracted from the out-of-plane component; the interfacial adhesion strength index of each film layer is calculated based on the out-of-plane feature matrix and the relative slip between layers; the slip recovery rate of each film layer is calculated based on the relative slip between layers; the angle sensitivity coefficient of each film layer under the angle gradient excitation mode is extracted from the multidimensional spectral response tensor; and the orientation defect fingerprint of each film layer is constructed based on the interfacial adhesion strength index, slip recovery rate, and angle sensitivity coefficient corresponding to each film layer. A multi-level defect fingerprint database was established based on the orientation defect fingerprints and interface defect fingerprints of each film layer.

[0011] Furthermore, methods for constructing the defect propagation kinetic equations for each film layer include: A predefined constitutive relation model is obtained, whose model parameters include elastic modulus, Poisson's ratio, viscosity coefficient, relaxation time, and damage evolution coefficient. Orientation defect fingerprints and interface defect fingerprints corresponding to each film layer are obtained from a multi-level defect fingerprint database and collectively referred to as defect feature indices. A mapping relationship is established between the defect feature indices and the corresponding model parameters of the constitutive relation model to obtain correction factors for each model parameter under each film layer. Based on the correction factors for each model parameter under each film layer, the constitutive relation model is dynamically corrected to form a corrected constitutive relation model corresponding to each film layer. Based on the modified constitutive model, the orientation defect propagation kinetic equations for each film layer are established; based on the modified constitutive model, the interface defect propagation kinetic equations for each film layer are established; based on the modified constitutive model, the cumulative damage evolution equations for each film layer are established; the orientation defect propagation kinetic equations, interface defect propagation kinetic equations, and cumulative damage evolution equations for each film layer are integrated to form the defect propagation kinetic equations for each film layer.

[0012] Furthermore, methods for predicting the temporal evolution trajectory of defects in each film layer under preset operating conditions include: A set of pre-defined working conditions is set, which includes three preset working conditions: static bending, dynamic bending, and composite environment. Based on the pre-defined set of working conditions, the equivalent stress time history curves and equivalent shear stress time history curves of each membrane layer under different preset working conditions are calculated. Initial conditions were set for the defect propagation kinetic equations corresponding to each film layer. These initial conditions included the initial equivalent size of orientation defects, the initial equivalent area of ​​interface defects, and the initial cumulative damage degree. The equivalent stress time history curves and equivalent shear stress time history curves corresponding to each film layer were substituted into the corresponding defect propagation kinetic equations. The fourth-order Runge-Kutta method was used for numerical solution to obtain the time-series evolution trajectory of each film layer under different preset working conditions. The time-series evolution trajectory included the time-series curves of the equivalent size of orientation defects, the equivalent area of ​​interface defects, and the cumulative damage degree.

[0013] Furthermore, methods for generating time-varying curves of defect severity for each film layer include: A defect hazard assessment index system is defined, which includes structural integrity hazard index, optical performance hazard index, and interface reliability hazard index. Based on the time-series evolution trajectory, the structural integrity hazard index, optical performance hazard index, and interface reliability hazard index for each film layer at each time step are calculated sequentially. Corresponding hazard weights are assigned to the structural integrity hazard index, optical performance hazard index, and interface reliability hazard index for each film layer at the same time step. Based on these hazard weights, a weighted summation of the structural integrity hazard index, optical performance hazard index, and interface reliability hazard index for the same film layer at the same time step is calculated to obtain the comprehensive defect hazard level of each film layer at each time step. Based on the comprehensive defect hazard level of each film layer at each time step, a time-varying curve of the defect hazard level for each film layer is generated.

[0014] Furthermore, methods for dynamically generating defect management information based on critical failure time include: Define failure criteria for each membrane layer, including hazard threshold criteria and hazard rate increase criteria; calculate the threshold-type critical failure time for each membrane layer based on the hazard threshold criteria; calculate the rate-increase critical failure time for each membrane layer based on the hazard rate increase criteria; determine the critical failure time for each membrane layer based on the threshold-type critical failure time and the rate-increase critical failure time. A defect risk level classification standard is defined to classify the defect risk of each membrane layer according to the critical failure time, thereby obtaining the defect risk level of each membrane layer; based on the defect risk level of each membrane layer, corresponding defect handling suggestions are generated; the critical failure times of all membrane layers are compared, and the membrane layer with the smallest critical failure time is selected and marked as the critical failure membrane layer; the defect risk level of each membrane layer, the defect handling suggestions, and the critical failure membrane layer are integrated to generate defect management information.

[0015] A flexible display functional film defect detection system, implementing the aforementioned flexible display functional film defect detection method, includes: The light field excitation module is used to construct a programmable array light source, apply different light field excitation modes to the surface of the flexible display functional film, collect the optical response signals of each film layer in the flexible display functional film under different light field excitation modes, and form a multidimensional spectral response tensor. The stress coupling module is used to synchronously apply a preset gradient mechanical micro-stress field to the flexible display functional film, monitor the intralayer deformation displacement and interlayer relative slip of each film layer in real time, and perform time registration and fusion with the multidimensional spectral response tensor to generate a stress-optical coupling feature map. The tensor decoupling module is used to perform tensor decomposition on the stress-optical coupling feature map, extract orientation defect fingerprints of each film layer based on the in-plane components obtained by decomposition, extract interface defect fingerprints based on the out-of-plane components obtained by decomposition combined with the interlayer relative slip, and establish a multi-level defect fingerprint library. The evolution prediction module is used to integrate a multi-level defect fingerprint database with a predefined constitutive relation model, construct the defect propagation dynamic equations for each membrane layer, predict the time-series evolution trajectory of defects in each membrane layer under preset working conditions, and generate time-varying curves of defect severity for each membrane layer. The defect management module is used to calculate the critical failure time of each membrane layer based on the time-varying curve of the defect severity of each membrane layer, and dynamically generate defect management information based on the critical failure time.

[0016] The technical effects and advantages of the flexible display functional film defect detection method and system of the present invention are as follows: By constructing a programmable array light source, multi-dimensional optical field excitation of flexible display functional films is achieved, enabling comprehensive acquisition of the optical response characteristics of each film layer under different wavelengths, polarization states, and incident angles. Compared with traditional single-source illumination methods, this significantly improves the detection sensitivity for minute and latent defects. Simultaneously, by introducing a pre-defined gradient mechanical micro-stress field and simultaneously applying multiple stress modes such as tension, shear, and bending, latent defects can be effectively excited and the mechanical response of the film layer can be monitored in real time, achieving coupled detection of stress and optical signals. By time-registering and fusing multi-dimensional spectral responses with stress-deformation data, a stress-optical coupling feature map is established. Tensor decomposition technology is then used to separate the complex coupling signal into in-plane and out-of-plane components, enabling the detection of orientation defects and interface defects. Precise differentiation and localization: This layered decoupling method effectively overcomes the limitations of existing technologies in distinguishing different types of defects, improving the accuracy of defect identification. More importantly, by integrating defect fingerprint features with material constitutive relationship models, a defect propagation dynamic equation is constructed, which can predict the temporal evolution trajectory of defects in each film layer under actual working conditions and generate time-varying curves of defect severity. This dynamic prediction capability enables the system not only to detect the current defect status but also to assess the development trend and potential hazards of defects, providing a scientific basis for preventive maintenance. By calculating critical failure time and risk level assessment, differentiated defect management strategies are automatically generated, realizing an intelligent transformation from passive detection to proactive early warning, thereby improving the quality control level and product reliability of flexible display functional films. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of a flexible display functional film defect detection system according to Embodiment 1 of the present invention; Figure 2 This is a flowchart of a method for detecting defects in a flexible display functional film according to Embodiment 2 of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example 1:

[0019] Please see Figure 1 As shown in this embodiment, a flexible display functional film defect detection system includes a light field excitation module, a stress coupling module, a tensor decoupling module, an evolution prediction module, and a defect management module; each module is connected via wired and / or wireless means to realize data transmission between modules.

[0020] The light field excitation module is used to construct a programmable array light source, apply different light field excitation modes to the surface of the flexible display functional film, collect the optical response signals of each film layer in the flexible display functional film under different light field excitation modes, and form a multidimensional spectral response tensor.

[0021] Methods for constructing programmable array light sources include: Based on the optical properties and optical detection requirements of flexible display functional films, a multi-band tunable light source array is designed. Specifically, a two-dimensional light source matrix is ​​constructed using micro-light-emitting units, each of which includes multiple independently controllable light-emitting sub-units, each covering a different spectral band. The spectral bands include ultraviolet, visible, and near-infrared bands. The ultraviolet band is used to excite the fluorescence response of the photosensitive material in the flexible display functional film; the visible band is used to detect the light transmittance and color uniformity of the flexible display functional film; and the near-infrared band is used to penetrate the multilayer film structure to detect deep defects. The wavelength, light intensity, and on / off state of each light-emitting sub-unit can be independently programmed and controlled. Each micro-light-emitting unit is equipped with a polarization modulation component and an incident angle adjustment component. Specifically, a rotatable polarizer is provided at the light-emitting end of each micro-light-emitting unit to modulate the polarization state of the output beam. The polarization state includes linear polarization and circular polarization; the polarization angle of the linear polarization state can be adjusted... to The range is continuously adjustable to detect the molecular alignment direction of the alignment layer in the flexible display functional film; the circular polarization state includes left-handed circular polarization and right-handed circular polarization, which is used to detect the chiral optical properties of the flexible display functional film; a micro stepping turntable is set on the mounting bracket of each micro light-emitting unit to adjust the incident angle of the output beam; different incident angles can excite different optical modes of the flexible display functional film to distinguish between surface defects and bulk defects. A light source array control system is established to uniformly schedule and configure the parameters of each micro-light-emitting unit. Specifically, the light source array control system includes a wavelength control unit, a light intensity control unit, a polarization control unit, and an angle control unit. The wavelength control unit is used to set the working wavelength and wavelength switching sequence of each light-emitting sub-unit; the light intensity control unit is used to set the output light intensity of each light-emitting sub-unit; the polarization control unit is used to set the rotation angle and rotation speed of the rotatable polarizer; and the angle control unit is used to set the target angle and movement speed of the micro-stepping turntable. The parameter configurations of each control unit are integrated to form a light source configuration parameter set, which is used for the definition and switching of subsequent light field excitation modes. By integrating the light source array, polarization modulation component, and incident angle adjustment component, and by using the light source array control system to uniformly program and control each micro light-emitting unit, a programmable array light source that can output multiple predefined or dynamically switched light field excitation modes is formed.

[0022] Methods for applying different optical field excitation modes to the surface of flexible display functional films include: Based on the multi-layer structure characteristics of flexible display functional films, multi-dimensional optical field excitation modes are designed. Specifically, the flexible display functional film includes multiple film layers, including but not limited to a flexible substrate layer, a transparent conductive layer, a polarizing layer, a phase retardation film layer, and a protective layer. Optical field excitation modes are designed according to the material properties and defect sensitivities of different film layers. The optical field excitation modes include wavelength scanning excitation mode, polarization switching excitation mode, and angle gradient excitation mode. Specifically, the wavelength scanning excitation mode is mainly used to excite the spectral response characteristics of the flexible substrate, transparent conductive layer, and protective layer at different operating wavelengths to obtain their transmittance, absorption characteristics, and dispersion variation laws; the polarization switching excitation mode is mainly used to excite the selective response of the polarization layer and retardation film to light fields with different polarization states to characterize their polarization transmission characteristics, phase delay characteristics, and polarization anisotropy; the angle gradient excitation mode is mainly used to excite the optical stability and viewing angle dependence characteristics of the flexible substrate, polarization layer, retardation film, and protective layer under different incident angle conditions. In wavelength scanning excitation mode, a continuously varying wavelength optical field is applied to the flexible display functional film. Specifically, a wavelength scanning start value, a wavelength scanning end value, and a wavelength scanning step size are set. The wavelength scanning start value, wavelength scanning end value, and wavelength scanning step size are all preset by those skilled in the art based on the spectral absorption characteristics of the film. Starting from the wavelength scanning start value, the working wavelength is increased sequentially according to the wavelength scanning step size until the wavelength scanning end value is reached. A preset wavelength dwell time is maintained at each working wavelength to ensure that the film produces a stable optical response. Each working wavelength value and the corresponding excitation time (i.e., the time when the excitation mode is applied) are recorded to form a wavelength scanning timing table. In polarization-switching excitation mode, a periodically changing optical field excitation is applied to the flexible display functional film; specifically, a polarization-switching sequence is set, which includes multiple target polarization states that are switched sequentially; for the linear polarization state, a polarization angle switching sequence is set, which includes... , , Multiple angles; for circular polarization states, alternating switching between left-handed and right-handed circular polarization is set; a preset polarization dwell time is maintained in each target polarization state to ensure that the film layer produces a distinguishable polarization response; each target polarization state and its corresponding excitation time are recorded to form a polarization switching timing table; In the angle gradient excitation mode, a light field excitation with a continuously changing incident angle is applied to the flexible display functional film. Specifically, the angle scan start value, angle scan end value, and angle scan step size are set. Starting from the angle scan start value, the incident angle is increased sequentially according to the angle scan step size until the angle scan end value is reached. A preset angle dwell time is maintained at each incident angle. Each incident angle value and the corresponding excitation time are recorded to form an angle scan timing table. It should be noted that the wavelength dwell time, polarization dwell time, and angle dwell time are all preset by those skilled in the art based on the actual situation.

[0023] Methods for acquiring the optical response signals of each film layer under different optical field excitation modes include: Optical signal acquisition devices are deployed on the incident and exit sides of the flexible display functional film, respectively, to synchronously acquire reflection optical response signals, transmission optical response signals, and fluorescence optical response signals under various light field excitation modes. Specifically, a reflection spectral acquisition device is deployed on the incident side to acquire the reflection optical response signal; a transmission spectral acquisition device is deployed on the exit side to acquire the transmission optical response signal; and a fluorescence spectral acquisition device is deployed in a direction perpendicular to the incident plane to acquire the fluorescence optical response signal. The reflection optical response signal includes the reflection spectral intensity distribution and reflection phase information, the transmission optical response signal includes the transmission spectral intensity distribution and transmission phase information, and the fluorescence optical response signal includes the fluorescence spectral intensity distribution and fluorescence lifetime information. The optical constants and thickness information of each film layer are obtained, and a multilayer film optical transmission model is established based on the optical constants and thickness information. Based on the multilayer film optical transmission model, the collected reflection optical response signal, transmission optical response signal and fluorescence optical response signal are inversely calculated to separate the optical response signal of each film layer. Among them, the optical constants of the material include refractive index and extinction coefficient. The multilayer film optical transmission model is a physical model describing the propagation, reflection and transmission behavior of light in the multilayer thin film structure based on the optical constants and thickness information of each film layer. It should be noted that the material optical constants and thickness information were obtained by those skilled in the art from the design documents or material databases of flexible display functional films; the establishment of the multilayer film optical transmission model and the reverse calculation method are well-known technologies in the field, and the specific process will not be elaborated here.

[0024] Methods for generating multidimensional spectral response tensors include: For the optical response signals of each film layer under different optical field excitation modes, the corresponding spectral peak wavelength, spectral half-width at half-maximum (HWHM), spectral integral intensity, and phase gradient are extracted sequentially and used as optical response characteristic parameters. Among them, the spectral peak wavelength is used to reflect the uniformity of material composition, the spectral HWHM is used to reflect the orderliness of material structure, the spectral integral intensity is used to reflect the thickness and density of film layer, and the phase gradient is used to reflect the surface morphology and interface characteristics of film layer. It should be noted that the extraction methods of spectral peak wavelength, spectral HWHM, spectral integral intensity, and phase gradient are all well-known techniques in this field, and the specific process will not be described in detail here. The dimensional structure of the multidimensional spectral response tensor is defined. Specifically, the multidimensional spectral response tensor is a four-dimensional tensor, with the first dimension being the film dimension, the second dimension being the wavelength dimension, the third dimension being the polarization dimension, and the fourth dimension being the angle dimension. Each element in the multidimensional spectral response tensor is a set of optical response characteristic parameters, including the spectral peak wavelength, spectral half-width at half-maximum, spectral integral intensity, and phase gradient. The optical response characteristic parameters of each film are normalized and then organized and filled according to the dimensional structure of the multidimensional spectral response tensor to form the multidimensional spectral response tensor.

[0025] The stress coupling module is used to synchronously apply a preset gradient mechanical micro-stress field to the flexible display functional film, monitor the intralayer deformation displacement and interlayer relative slip of each film layer in real time, and perform time registration and fusion with the multidimensional spectral response tensor to generate a stress-optical coupling feature map.

[0026] Methods for simultaneously applying a preset gradient mechanical micro-stress field to a flexible display functional film include: Based on the mechanical properties and defect detection requirements of flexible display functional films, a multi-axial micro-stress loading device is designed. Specifically, the micro-stress loading device includes an in-plane tensile loading unit, an in-plane shear loading unit, and an out-of-plane bending loading unit. The in-plane tensile loading unit is used to apply tensile stress along the in-plane direction of the flexible display functional film to excite crack-like defects and brittle material defects in the film layer. The in-plane shear loading unit is used to apply shear stress along the in-plane direction of the flexible display functional film to excite delamination defects and interfacial adhesion defects in the film layer. The out-of-plane bending loading unit is used to apply bending stress along the normal direction of the flexible display functional film to excite wrinkle defects and interlayer delamination defects in the film layer. The stress gradient control parameters of each loading unit are configured to form a mechanical micro-stress field with a preset gradient. Specifically, for each loading unit, a stress initiation value, a stress termination value, and a stress step size are set. The stress initiation value, stress termination value, and stress step size are all preset by those skilled in the art based on the yield strength and elastic limit of the flexible display functional film. Starting from the stress initiation value, the stress value is increased sequentially according to the stress step size until the stress termination value is reached, forming a mechanical micro-stress field with a preset gradient. A preset stress residence time is maintained at each stress value to ensure that the film layer generates a stable mechanical response. A stress loading synchronous control system is established to uniformly schedule and control the timing of each loading unit. Specifically, the stress loading synchronous control system includes a tension control unit, a shear control unit, and a bending control unit. The tension control unit controls the loading force and loading rate of the in-plane tension loading unit; the shear control unit controls the loading force and loading rate of the in-plane shear loading unit; and the bending control unit controls the loading curvature and loading rate of the out-of-plane bending loading unit. The loading force or loading curvature of each loading unit, as well as the corresponding loading time (i.e., the moment when the loading force or loading curvature is applied), is recorded. The loading force or loading curvature of each loading unit is converted into the corresponding stress value, and a stress loading timing table is formed based on the stress value of each loading unit and the corresponding loading time. The method for converting the stress value is a well-known technique in the field, and the specific process will not be elaborated here. It should be understood that the stress loading timing table, wavelength scanning timing table, polarization switching timing table, and angle scanning timing table use the same time reference to ensure the synchronization of optical field excitation and stress loading.

[0027] Methods for real-time monitoring of intralayer deformation displacement and interlayer relative slip of each film layer include: The intralayer deformation displacement of each film layer is monitored in real time using digital image correlation (DIC) method; the intralayer deformation displacement includes in-plane tensile displacement and in-plane shear displacement; the interlayer relative slip of each film layer is monitored in real time using optical coherence tomography (OCT) method; the interlayer relative slip is used to characterize the adhesion state and interface defect sensitivity at the interface of adjacent film layers. It should be noted that both digital image correlation measurement methods and optical coherence tomography methods are well-known technologies in this field, and the specific processes will not be elaborated on here.

[0028] Methods for generating stress-optical coupling feature maps include: Based on the intralayer deformation displacement, interlayer relative slip, and stress loading time series table of each membrane layer, a stress-deformation time series dataset is formed. Specifically, the intralayer deformation displacement and interlayer relative slip are collectively referred to as membrane mechanical deformation. According to the monitoring time of the corresponding membrane mechanical deformation of each membrane layer (i.e. the time when the membrane mechanical deformation is monitored), the membrane mechanical deformation and stress values ​​with the same monitoring time and loading time are integrated to form a stress-deformation time series dataset. Based on a unified time reference, the stress-deformation time series dataset and the multidimensional spectral response tensor are time-registered and fused to form a time-registered fused dataset. Specifically, each loading moment in the stress loading time series table is time-aligned with each excitation moment in the wavelength scanning time series table, polarization switching time series table, and angle scanning time series table, and the aligned moments are marked as alignment moments. For each alignment moment of each film layer, the corresponding stress value, film mechanical deformation, and optical response characteristic parameters are fused to obtain a stress-optical joint feature vector. All stress-optical joint feature vectors are summarized to form a time-registered fused dataset. Based on the time-registration fusion dataset, the stress-optical coupling coefficient of each film layer is calculated. The stress-optical coupling coefficient includes the deformation-intensity coupling coefficient and the slip-phase coupling coefficient. Specifically, for each film layer, the Pearson correlation coefficient between the intralayer deformation displacement and the spectral integrated intensity is calculated to obtain the deformation-intensity coupling coefficient; the Pearson correlation coefficient between the interlayer relative slip and the phase gradient is calculated to obtain the slip-phase coupling coefficient. Among them, the deformation-intensity coupling coefficient is used to characterize the sensitivity of the film layer to changes in optical transmittance under stress, and the slip-phase coupling coefficient is used to characterize the sensitivity of the film layer interface to changes in optical phase under stress. Based on the time-registration fusion dataset, the stress response gradient set of each film layer is extracted. Specifically, for each film layer, the rate of change of optical response characteristic parameters with stress value is calculated using a linear regression method to obtain the stress response gradient set. The stress response gradient set includes the stress response gradient of the spectral peak wavelength, the stress response gradient of the spectral half-width, the stress response gradient of the spectral integral intensity, and the stress response gradient of the phase gradient. Among them, the stress response gradient is used to characterize the trend of optical response change of the film layer under different stress levels, providing gradient feature information for subsequent defect fingerprint extraction. It should be noted that the linear regression method is a well-known technique in this field, and the specific process will not be elaborated in detail here. The structure of the stress-optical coupling feature map is defined. Specifically, the stress-optical coupling feature map is a two-dimensional data structure, with the first dimension being the film layer dimension and the second dimension being the coupling feature dimension. The coupling feature dimension includes the stress-optical coupling coefficient and the set of stress response gradients. The stress-optical coupling coefficient and the set of stress response gradients of each film layer are normalized and then organized and filled according to the structure of the stress-optical coupling feature map to generate the stress-optical coupling feature map.

[0029] The tensor decoupling module is used to perform tensor decomposition on the stress-optical coupling feature map. Based on the in-plane components obtained by decomposition, orientation defect fingerprints of each film layer are extracted. Based on the out-of-plane components obtained by decomposition and the interlayer relative slip, interface defect fingerprints are extracted, and a multi-level defect fingerprint library is established.

[0030] Methods for tensor decomposition of stress-optical coupling feature maps include: Based on the stress-optical coupling feature map, a higher-order coupling feature tensor is constructed. Specifically, the stress-optical coupling coefficients and stress response gradient sets of each film layer are extracted from the stress-optical coupling feature map and used as coupling feature components. Based on the time-registered fusion dataset, the stress values ​​corresponding to each coupling feature component under different film layers are obtained. On the basis of the stress-optical coupling feature map, a stress value dimension is added to form a higher-order coupling feature tensor. This higher-order coupling feature tensor is a third-order tensor (i.e., containing three dimensions): the first dimension is the film layer dimension, the second dimension is the stress value dimension, and the third dimension is the coupling feature dimension. For example, the elements in the higher-order coupling feature tensor... , indicating the first Each film layer is under stress value Next The numerical values ​​of each coupled feature component; Orthogonal tensor decomposition is performed on the higher-order coupled feature tensor to separate the in-plane and out-of-plane component tensors of each membrane layer. Specifically, higher-order singular value decomposition is used to decompose the higher-order coupled feature tensor to obtain the core tensor and factor matrices of each dimension. Each factor matrix contains multiple principal component vectors. Intra-layer deformation displacement and inter-layer relative slip of each membrane layer are extracted from the stress-deformation time series dataset. For each principal component vector corresponding to each membrane layer, the Pearson correlation coefficient between the vector and the intra-layer deformation displacement of the corresponding membrane layer, and the vector between the vector and the inter-layer relative slip of the corresponding membrane layer are calculated to obtain the in-plane and out-of-plane correlation coefficients for each membrane layer. The principal component vector corresponding to the largest in-plane correlation coefficient of the same membrane layer is taken as the in-plane component tensor of the corresponding membrane layer. The principal component vector corresponding to the largest out-of-plane correlation coefficient of the same membrane layer is taken as the out-of-plane component tensor of the corresponding membrane layer. Based on the in-plane and out-of-plane component tensors of each membrane layer, the in-plane and out-of-plane components of each membrane layer are calculated respectively. Specifically, the in-plane component tensor and the core tensor are multiplied along the membrane layer dimension to obtain the in-plane component; the out-of-plane component tensor and the core tensor are multiplied along the membrane layer dimension to obtain the out-of-plane component. It should be noted that the higher-order singular value decomposition method and the tensor product operation are well-known techniques in this field, and the specific process will not be elaborated in detail here.

[0031] Methods for extracting orientation defect fingerprints of each film layer based on in-plane components include: The in-plane feature matrix of each membrane layer is extracted from the in-plane components. Specifically, for each membrane layer, the in-plane components are sliced ​​along the membrane layer dimension (i.e., the in-plane components are separated according to the membrane layer) to obtain the in-plane feature matrix of each membrane layer. Based on the in-plane feature matrix, the orientation anisotropy index of each film layer is calculated. Specifically, for the in-plane feature matrix of each film layer, the corresponding tensile response sub-vector and shear response sub-vector are extracted sequentially. The tensile response sub-vector includes the values ​​along the in-plane tensile stress direction in the in-plane feature matrix, and the shear response sub-vector includes the values ​​along the in-plane shear stress direction in the in-plane feature matrix. The Euclidean distance between the tensile response sub-vector and the shear response sub-vector corresponding to the same film layer is calculated and normalized to obtain the orientation anisotropy index of each film layer. The orientation anisotropy index is used to characterize the directional consistency of molecular arrangement within the film layer. The polarization extinction ratio of each film layer under polarization-switching excitation mode is extracted from the multidimensional spectral response tensor; specifically, for each film layer, the polarization extinction ratio is calculated. polarization angle and The ratio of the integral intensity of the spectrum under the polarization angle is normalized to obtain the polarization extinction ratio; Based on the orientation anisotropy index and polarization extinction ratio of each film layer, orientation defect fingerprints of each film layer are constructed.

[0032] Methods for extracting interface defect fingerprints based on out-of-plane components and interlayer relative slip include: The out-of-plane feature matrix of each membrane layer is extracted from the out-of-plane components. Specifically, for each membrane layer, the out-of-plane components are sliced ​​along the membrane layer dimension (i.e., the out-of-plane components are separated according to the membrane layer) to obtain the out-of-plane feature matrix of each membrane layer. Based on the out-of-plane feature matrix and the relative slip between layers, the interfacial adhesion strength index of each film layer is calculated. Specifically, a linear regression method is used to calculate the slope between the relative slip between layers and the stress value to obtain the slip-stress response coefficient. The values ​​corresponding to the slip-phase coupling coefficient are extracted from the out-of-plane feature matrix and their mean values ​​are calculated to obtain the average value. The product of the slip-stress response coefficient and the average value is calculated and its reciprocal is taken to obtain the interfacial adhesion strength index. The interfacial adhesion strength index is used to characterize the adhesion quality of the film layer interface. Based on the relative interlayer slip of each membrane layer, the slip recovery rate of each membrane layer is calculated. Specifically, the difference between the maximum and minimum values ​​of the relative interlayer slip during the stress loading stage (i.e., the stage from the initial stress value to the final stress value) is calculated to obtain the maximum slip change. The relative interlayer slip after complete stress unloading (i.e., stress value of 0) is calculated and marked as the residual slip. The ratio of the residual slip to the maximum slip change is calculated, and the result is subtracted to obtain the slip recovery rate. The slip recovery rate is used to characterize the elastic recovery capability of the membrane interface. Angle sensitivity coefficients for each film layer under angle-gradient excitation mode are extracted from the multidimensional spectral response tensor. Specifically, for each film layer, the spectral integral intensity corresponding to the angle dimension is extracted from the multidimensional spectral response tensor. The difference in spectral integral intensity between adjacent incident angles is calculated and divided by the angle change (i.e., the difference between adjacent incident angles) to obtain the rate of change of spectral integral intensity at each incident angle. The mean of all spectral integral intensity change rates is calculated to obtain the angle sensitivity coefficient. The angle sensitivity coefficient is used to characterize the sensitivity of the film layer's optical properties to changes in the incident angle. The interfacial adhesion strength index, slip recovery rate, and angle sensitivity coefficient of each film layer were normalized, and the interfacial defect fingerprint of each film layer was constructed based on the normalized interfacial adhesion strength index, slip recovery rate, and angle sensitivity coefficient of each film layer.

[0033] Methods for establishing a multi-level defect fingerprint database include: A multi-level defect fingerprint database is established based on the orientation defect fingerprints and interface defect fingerprints corresponding to each film layer. The multi-level defect fingerprint database is organized in a two-level structure. The first level is the film layer level, which is classified according to each film layer in the flexible display functional film. The second level is the defect type level, which stores the corresponding orientation defect fingerprints and interface defect fingerprints under each film layer.

[0034] The evolution prediction module is used to integrate a multi-level defect fingerprint database with a predefined constitutive relation model, construct the defect propagation dynamic equations for each membrane layer, predict the temporal evolution trajectory of defects in each membrane layer under preset working conditions, and generate time-varying curves of defect severity for each membrane layer.

[0035] Methods for integrating multi-level defect fingerprint databases with predefined constitutive relation models include: A predefined constitutive model is obtained, which describes the mechanical response of each layer of the flexible display functional film under stress. Specifically, the constitutive model includes an elastic constitutive model, a viscoelastic constitutive model, and a damage constitutive model. The elastic constitutive model describes the linear stress-strain relationship of the film layer under small deformation conditions; the viscoelastic constitutive model describes the creep and stress relaxation behavior of the film layer under time-varying loads; and the damage constitutive model describes the cumulative damage evolution of the film layer under cyclic loads. The model parameters of the constitutive model include elastic modulus, Poisson's ratio, viscosity coefficient, relaxation time, and damage evolution coefficient, all of which are pre-calibrated by those skilled in the art based on the material mechanics test data of each layer of the flexible display functional film. The orientation defect fingerprint and interface defect fingerprint corresponding to each film layer are obtained from a multi-level defect fingerprint database and are collectively referred to as defect feature indices. A mapping relationship between the defect feature indices and the corresponding model parameters of the constitutive relation model is established to obtain the correction factors for each model parameter under each film layer. Specifically, the product of the orientation anisotropy index and the preset modulus influence coefficient of each film layer is calculated, and each calculated result is subtracted from the product to obtain the correction factor for the elastic modulus of each film layer. The difference between the product and the interface adhesion strength index of each film layer is calculated, and each calculated result is multiplied by the preset viscosity influence coefficient and then added to obtain the correction factor for the viscosity coefficient of each film layer. The difference between the product and the slip recovery rate of each film layer is calculated, and each calculated result is multiplied by the preset damage influence coefficient and then added to obtain the correction factor for the damage evolution coefficient of each film layer. Among them, the modulus influence coefficient and the viscosity influence coefficient are pre-calibrated by those skilled in the art based on the material mechanics experimental data of the flexible display functional film, and the damage influence coefficient is pre-calibrated by those skilled in the art based on the material fatigue experimental data of the flexible display functional film. Based on the correction factors of each model parameter under each film layer, the constitutive relation model is dynamically corrected to form a corrected constitutive relation model for the fusion defect characteristics of each film layer. Specifically, for each film layer, the product of each correction factor and the corresponding model parameter in the constitutive relation model is calculated to obtain the correction value of each model parameter under each film layer. The correction values ​​of each model parameter under each film layer are summarized to form a corrected constitutive parameter set. The corrected constitutive parameter set is substituted into the constitutive relation model to form a corrected constitutive relation model for the fusion defect characteristics of each film layer.

[0036] Methods for constructing the defect propagation kinetic equations for each film layer include: Based on the modified constitutive relation model, the orientation defect propagation kinetic equations for each film layer are established. Specifically, the orientation defect propagation kinetic equations describe the evolution of orientation defect size within the film layer with time and stress. The specific expression of the orientation defect propagation kinetic equations is as follows: ; In the formula, For the first Each film layer at time The equivalent size of the orientation defect, The time rate of change of the equivalent size of the orientation defect. For the first The orientation defect propagation coefficient of each film layer For the first Each film layer at time The equivalent stress, Stress index This is the size index. For the first Factors affecting the orientation anisotropy of each film layer; Among them, the orientation defect expansion coefficient is determined by the modified elastic modulus and the deformation-intensity coupling coefficient; the orientation anisotropy influence factor is determined by the orientation anisotropy index and the polarization extinction ratio. The method for determining the orientation defect propagation coefficient is as follows: Calculate the product of the absolute value of the deformation-strength coupling coefficient and the preset influence weight of the coupling coefficient, and add one to obtain the orientation coupling gain factor; calculate the ratio of the preset reference elastic modulus to the modified elastic modulus (i.e., the modified value of the elastic modulus) to obtain the elastic modulus relative scaling factor; multiply the orientation coupling gain factor, the elastic modulus relative scaling factor, and the preset reference defect propagation coefficient in sequence to obtain the orientation defect propagation coefficient; wherein, the reference defect propagation coefficient, the reference elastic modulus, and the influence weight of the coupling coefficient are all pre-calibrated by those skilled in the art based on the material fracture mechanics experimental data of the flexible display functional film; The method for determining the orientation anisotropy influence factor is as follows: calculate the difference between - and the polarization extinction ratio to obtain the polarization anisotropy defect degree; multiply the polarization anisotropy defect degree, the orientation anisotropy index and the preset anisotropy weight coefficient in sequence and add - to obtain the orientation anisotropy influence factor; wherein, the anisotropy weight coefficient is preset by those skilled in the art according to the actual situation.

[0037] Based on the modified constitutive model, the dynamic equations for the propagation of interfacial defects in each film layer are established. Specifically, these equations describe the evolution of the delamination defect area at the interface between adjacent film layers with time and stress. The specific expression for the dynamic equations for the propagation of interfacial defects is as follows: ; In the formula, For the first Each film layer at time The equivalent area of ​​the interface defect. The time rate of change of the equivalent area of ​​the interface defect. For the first The interface defect propagation coefficient of each film layer For the first Each film layer at time The equivalent shear stress, The shear stress index is... It is the area index. For the first Factors affecting interfacial adhesion of individual film layers; Among them, the interface defect propagation coefficient is determined by the modified viscosity coefficient and the slip-phase coupling coefficient; the interface adhesion influence factor is determined by the interface adhesion strength index and the slip recovery rate. The method for determining the interface defect propagation coefficient is as follows: Calculate the absolute value of the slip-phase coupling coefficient and the product of the preset slip coupling coefficient influence weight, and add one to obtain the interface coupling gain factor; calculate the ratio of the preset reference viscosity coefficient to the corrected viscosity coefficient (i.e., the corrected value of the viscosity coefficient) to obtain the viscosity coefficient relative scaling factor; multiply the interface coupling gain factor, the viscosity coefficient relative scaling factor, and the preset reference interface propagation coefficient in sequence to obtain the interface defect propagation coefficient; wherein, the influence weights of the reference interface propagation coefficient, the reference viscosity coefficient, and the slip coupling coefficient are all pre-calibrated by those skilled in the art based on the interface mechanical experimental data of the flexible display functional film; The method for determining the interfacial adhesion influence factor is as follows: calculate the difference between one and the slip recovery rate to obtain the slip adhesion defect degree; calculate the difference between one and the interfacial adhesion strength index to obtain the interfacial adhesion defect degree; multiply the slip adhesion defect degree, the interfacial adhesion defect degree and the preset adhesion weight coefficient in sequence and add one to obtain the interfacial adhesion influence factor; wherein, the adhesion weight coefficient is preset by those skilled in the art according to the actual situation.

[0038] It should be noted that the stress index, size index, shear stress index, and area index were all pre-calibrated by those skilled in the art based on the material fracture mechanics theory and experimental data of flexible display functional films.

[0039] Based on the modified constitutive model, the cumulative damage evolution equation for each film layer is established. Specifically, the cumulative damage evolution equation describes the damage accumulation law of the film material under cyclic loading. The specific expression of the cumulative damage evolution equation is as follows: ; In the formula, For the first Each film layer at time The cumulative damage degree, The rate of change of cumulative damage over time. For the first The corrected damage evolution coefficient (i.e., the corrected value of the damage evolution coefficient) for each film layer. For the first The ultimate strength of each film layer The damage stress index, The damage accumulation index, For the first Factors affecting the angle sensitivity of each film layer; Among them, the ultimate strength, damage stress index and damage accumulation index are all pre-calibrated by those skilled in the art based on the material fatigue test data of the flexible display functional film; the method for determining the angle sensitivity influence factor is: calculate the product of the angle sensitivity coefficient and the preset sensitivity weight coefficient, and add one to the calculation result to obtain the angle sensitivity influence factor.

[0040] The orientation defect propagation kinetic equations, interface defect propagation kinetic equations, and cumulative damage evolution equations corresponding to each film layer are integrated to form the defect propagation kinetic equations for each film layer.

[0041] Methods for predicting the temporal evolution trajectory of defects in each film layer under preset operating conditions include: A pre-defined set of operating conditions is used to describe the mechanical and environmental conditions experienced by the flexible display functional film during actual use. The set includes three preset operating conditions: static bending, dynamic bending, and composite environment. The static bending condition describes a scenario where the flexible display functional film maintains a fixed bending curvature, with parameters including bending curvature and holding time. The dynamic bending condition describes a scenario where the flexible display functional film undergoes repeated bending, with parameters including bending angle, bending frequency, and number of bending cycles. The composite environment condition describes a scenario where the flexible display functional film is subjected to both temperature changes and stress, with parameters including temperature range, temperature change rate, and stress amplitude. All operating condition parameters are pre-set by those skilled in the art based on the product specifications and usage scenarios of the flexible display functional film. Based on a pre-defined set of operating conditions, the equivalent stress time history curves and equivalent shear stress time history curves of each membrane layer under different pre-defined operating conditions are calculated using classical plate and shell theory and thermoelastic mechanics methods. The equivalent stress time history curves are used to describe the variation of normal stress borne by each membrane layer at different times, and the equivalent shear stress time history curves are used to describe the variation of shear stress borne by the interface of each membrane layer at different times. It should be noted that classical plate and shell theory and thermoelastic mechanics methods are well-known technologies in this field, and the specific process will not be elaborated on here. Initial conditions are set for the defect propagation kinetic equations corresponding to each film layer. These initial conditions include the initial equivalent size of the orientation defect, the initial equivalent area of ​​the interface defect, and the initial cumulative damage degree. Specifically, for orientation defects, the product of the orientation anisotropy index and the difference between a factor and the polarization extinction ratio is calculated. The result is then multiplied by a preset size magnification factor and the reference defect size, and finally added to the reference defect size to obtain the initial equivalent size of the orientation defect. For interface defects, the differences between a factor and the interface adhesion strength index and the difference between a factor and the slip recovery rate are calculated. The product of these two differences is then multiplied by a preset area magnification factor and the reference defect area, and finally added to the reference defect area to obtain the initial equivalent area of ​​the interface defect. For cumulative damage, the stress response gradient of the spectral integral intensity and the stress response gradient of the phase gradient are extracted from the stress response gradient set. After normalization, they are weighted and summed based on preset weights to obtain the initial cumulative damage degree. The reference defect size, size magnification factor, reference defect area, area magnification factor, and each weight are preset by those skilled in the art according to the defect detection accuracy requirements. Substituting the equivalent stress time history curves and equivalent shear stress time history curves corresponding to each film layer with the initial conditions into the corresponding defect propagation dynamics equations, the fourth-order Runge-Kutta method is used for numerical solution to obtain the time-series evolution trajectory of each film layer under different preset working conditions. The time-series evolution trajectory includes the time-series curve of the equivalent size of orientation defects, the time-series curve of the equivalent area of ​​interface defects, and the time-series curve of cumulative damage. The fourth-order Runge-Kutta method is a well-known technology in this field, and the specific process will not be described in detail here.

[0042] Methods for generating time-varying curves of defect severity for each film layer include: A defect hazard assessment index system is defined to comprehensively evaluate the impact of defects in each film layer on the overall performance of the flexible display functional film. Specifically, the defect hazard assessment index system includes structural integrity hazard index, optical performance hazard index, and interface reliability hazard index. The structural integrity hazard index is used to assess the impact of orientation defects on the structural strength of the film layer; the optical performance hazard index is used to assess the impact of defects on the optical transmittance and optical uniformity of the film layer; and the interface reliability hazard index is used to assess the impact of interface defects on the adhesion reliability of the film layer. Based on the temporal evolution trajectory, the defect hazard assessment index of each film layer at each time step is calculated. Specifically, for the structural integrity hazard index, the ratio of the equivalent size of the orientation defect to the preset critical defect size at each time step is calculated, and the preset structural hazard index is raised to a power of each calculation result to obtain the structural integrity hazard index of each film layer at each time step. For the optical performance hazard index, the absolute value of the deformation-strength coupling coefficient is calculated and multiplied by the preset optical coupling weight, and the result is incremented by one and multiplied by the cumulative damage at each time step to obtain the optical performance hazard index of each film layer at each time step. For the interface reliability hazard index, the ratio of the equivalent area of ​​the interface defect to the preset critical interface area at each time step is calculated, and the preset interface hazard index is raised to a power of each calculation result to obtain the interface reliability hazard index of each film layer at each time step. Among these, the critical defect size, critical interface area, structural hazard index, optical coupling weight, and interface hazard index are all preset by those skilled in the art according to the quality control requirements and reliability design requirements of flexible display functional films. Corresponding hazard weights are set for the structural integrity hazard index, optical performance hazard index, and interface reliability hazard index. Each hazard weight is preset by a person skilled in the art according to the quality control requirements of the flexible display functional film. Based on the hazard weights, the structural integrity hazard index, optical performance hazard index, and interface reliability hazard index of the same film layer at the same time are weighted and summed to obtain the comprehensive defect hazard degree of each film layer at each time. Based on the comprehensive defect hazard degree of each film layer at each time, a time-varying curve of the defect hazard degree of each film layer is generated.

[0043] The defect management module is used to calculate the critical failure time of each membrane layer based on the time-varying curve of the defect severity of each membrane layer, and dynamically generate defect management information based on the critical failure time.

[0044] Methods for calculating the critical failure time of each film layer include: Failure criteria for each film layer are defined to determine the critical conditions under which a film layer reaches a failure state. Specifically, the failure criteria include a hazard threshold criterion and a hazard rate increase criterion. The hazard threshold criterion is used to determine whether the overall defect hazard level has reached a preset hazard upper limit threshold, which is preset by those skilled in the art based on the quality acceptance standards for flexible display functional films. The hazard rate increase criterion is used to determine whether the rate of change of the overall defect hazard level has reached a preset hazard rate increase threshold, which is preset by those skilled in the art based on the early warning requirements for rapid defect expansion. Based on the hazard threshold criterion, the threshold-type critical failure time of each film layer is calculated. Specifically, the time-varying curves of the defect hazard of the film layer are traversed to obtain the moment when the comprehensive defect hazard first reaches or exceeds the upper limit threshold of hazard, and this moment is taken as the threshold-type critical failure time. If the comprehensive defect hazard does not reach the upper limit threshold of hazard, the threshold-type critical failure time is marked as infinity. Based on the hazard rate increase criterion, the rate-increasing critical failure time of each membrane layer is calculated. Specifically, the time-varying curve of the defect hazard of the membrane layer is differentially calculated to obtain the curve of the rate of change of the comprehensive defect hazard. The specific method of differential calculation is as follows: calculate the difference of the comprehensive defect hazard at adjacent moments and divide it by the time interval to obtain the rate of change of hazard at each moment; traverse the rate of change curve of the hazard of the membrane layer to obtain the moment when the rate of change of hazard first reaches or exceeds the hazard rate increase threshold, and mark it as the rate-increasing critical failure time; if all rates of change of hazard do not reach the hazard rate increase threshold, the rate-increasing critical failure time is marked as infinity. The critical failure time of each membrane layer is determined based on the threshold-type critical failure time and the acceleration-type critical failure time. Specifically, for each membrane layer, the threshold-type critical failure time and the acceleration-type critical failure time are compared, and the minimum value between the two is selected as the critical failure time. The critical failure time is used to characterize the estimated remaining time for the membrane layer to evolve from the current state to the failure state.

[0045] Methods for dynamically generating defect management information based on critical failure time include: A defect risk level classification standard is defined to classify the defect risk of each membrane layer based on the critical failure time, thereby obtaining the defect risk level of each membrane layer. Specifically, a first time threshold, a second time threshold, and a third time threshold are set; wherein the first time threshold is less than the second time threshold, and the second time threshold is less than the third time threshold; each time threshold is preset by those skilled in the art based on the production cycle and maintenance cycle; if the critical failure time is less than the first time threshold, the defect risk level of the corresponding membrane layer is marked as an emergency risk level; if the critical failure time is greater than or equal to the first time threshold and less than the second time threshold, the defect risk level of the corresponding membrane layer is marked as a high risk level; if the critical failure time is greater than or equal to the second time threshold and less than the third time threshold, the defect risk level of the corresponding membrane layer is marked as a medium risk level; if the critical failure time is greater than or equal to the third time threshold, the defect risk level of the corresponding membrane layer is marked as a low risk level. Based on the defect risk level of each membrane layer, corresponding defect handling suggestions are generated; Specifically, for membranes with an emergency risk level, an immediate shutdown and maintenance recommendation is generated, and the key defect type is marked. The key defect type is determined based on the structural integrity hazard index, optical performance hazard index, and interface reliability hazard index. If the structural integrity hazard index is the highest, the key defect type is orientation defect; if the optical performance hazard index is the highest, the key defect type is material damage defect; if the interface reliability hazard index is the highest, the key defect type is interface defect. For membrane layers with high risk levels, planned maintenance recommendations are generated, and recommended maintenance time windows are calculated. Specifically, the start time of the recommended maintenance time window is the current time, and the end time of the recommended maintenance time window is the product of the critical failure time and a preset safety factor. The safety factor is preset by those skilled in the art based on maintenance response capabilities. For membranes with medium risk levels, regular monitoring recommendations are generated, and the recommended monitoring cycle is calculated. Specifically, the recommended monitoring cycle is the ratio of the critical failure time to the number of monitoring sessions. The number of monitoring sessions is preset by those skilled in the art based on the configuration of monitoring resources. For low-risk membrane layers, routine inspection suggestions are generated, and inspections are carried out according to the preset routine inspection cycle; the routine inspection cycle is preset by those skilled in the art according to the production management system. The critical failure times of all film layers are compared, and the film layer with the shortest critical failure time is selected and marked as the critical failure film layer. The critical failure film layer is used to indicate the weakest link with the highest risk of failure of the flexible display functional film. The defect risk level of each film layer, defect handling suggestions and the critical failure film layer are integrated to generate defect management information.

[0046] This embodiment constructs a programmable array light source to achieve multi-dimensional optical field excitation of the flexible display functional film. This allows for comprehensive acquisition of the optical response characteristics of each film layer under different wavelengths, polarization states, and incident angles. Compared to traditional single-source illumination methods, this significantly improves the detection sensitivity for minute and latent defects. Simultaneously, a pre-defined gradient mechanical micro-stress field is introduced. By simultaneously applying multiple stress modes such as tension, shear, and bending, latent defects can be effectively excited, and the mechanical response of the film layer can be monitored in real time, achieving coupled detection of stress and optical signals. By time-registering and fusing the multi-dimensional spectral response with stress-deformation data, a stress-optical coupling feature map is established. Tensor decomposition technology is then used to separate the complex coupling signal into in-plane and out-of-plane components, enabling the detection of orientation defects and interface defects. The system achieves precise differentiation and localization of defects. This layered decoupling method effectively overcomes the limitations of existing technologies in distinguishing different types of defects, improving the accuracy of defect identification. More importantly, by integrating defect fingerprint features with material constitutive relationship models, a defect propagation dynamic equation is constructed, which can predict the temporal evolution trajectory of defects in each film layer under actual working conditions and generate a time-varying curve of defect severity. This dynamic prediction capability enables the system not only to detect the current defect status but also to assess the development trend and potential hazards of defects, providing a scientific basis for preventive maintenance. By calculating critical failure time and risk level assessment, differentiated defect management strategies are automatically generated, realizing an intelligent transformation from passive detection to proactive early warning, thereby improving the quality control level and product reliability of flexible display functional films. Example 2:

[0047] Please see Figure 2 As shown, for parts not described in detail in this embodiment, please refer to the description in Embodiment 1. A method for detecting defects in a flexible display functional film is provided, the method comprising: A programmable array light source is constructed to apply different light field excitation modes to the surface of the flexible display functional film. The optical response signals of each film layer in the flexible display functional film under different light field excitation modes are collected to form a multidimensional spectral response tensor. A mechanical micro-stress field with a preset gradient is applied synchronously to the flexible display functional film. The intralayer deformation displacement and interlayer relative slip of each film layer are monitored in real time and fused with the multidimensional spectral response tensor to generate a stress-optical coupling feature map. Tensor decomposition was performed on the stress-optical coupling feature map. Based on the in-plane components obtained by decomposition, orientation defect fingerprints of each film layer were extracted. Based on the out-of-plane components obtained by decomposition and the relative slip between layers, interface defect fingerprints were extracted. A multi-level defect fingerprint library was established. By integrating a multi-level defect fingerprint database with a predefined constitutive relation model, the defect propagation dynamic equations for each membrane layer are constructed, and the temporal evolution trajectory of defects in each membrane layer under preset working conditions is predicted, generating time-varying curves of defect severity for each membrane layer. Based on the time-varying curves of the defect severity of each membrane layer, the critical failure time of each membrane layer is calculated, and defect management information is dynamically generated based on the critical failure time. Example 3:

[0048] This application also provides an electronic device. The electronic device may include one or more processors and one or more memories. The memories store computer-readable code, which, when executed by the one or more processors, can perform a method for detecting defects in a flexible display functional film as described above.

[0049] The method or system according to the embodiments of this application can also be implemented using the architecture of the electronic device shown in this application. The electronic device may include a bus, one or more CPUs, ROM, RAM, a communication port connected to a network, input / output, a hard disk, etc. The storage device in the electronic device, such as a ROM or hard disk, may store a method for detecting defects in a flexible display functional film provided in this application. Furthermore, the electronic device may also include a user interface. Of course, the architecture shown in this application is merely exemplary; when implementing different devices, one or more components in the electronic device shown in this application may be omitted according to actual needs. Example 4:

[0050] One embodiment of this application discloses a computer-readable storage medium. The computer-readable storage medium stores computer-readable instructions. When the computer-readable instructions are executed by a processor, a method for detecting defects in a flexible display functional film according to an embodiment of this application, as described with reference to the above figures, can be performed. The storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0051] Furthermore, according to embodiments of this application, the processes described in the above-referenced flowcharts can be implemented as computer software programs. For example, this application provides a non-transitory machine-readable storage medium storing machine-readable instructions that can be executed by a processor to perform instructions corresponding to the method steps provided in this application, such as a method for detecting defects in a flexible display functional film. When this computer program is executed by a central processing unit (CPU), it performs the functions defined in the method of this application.

[0052] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0053] All formulas in this manual are dimensionless and calculated numerically. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0054] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for detecting defects in a flexible display functional film, characterized in that, include: A programmable array light source is constructed to apply different light field excitation modes to the surface of the flexible display functional film. The optical response signals of each film layer in the flexible display functional film under different light field excitation modes are collected to form a multidimensional spectral response tensor. A mechanical micro-stress field with a preset gradient is applied synchronously to the flexible display functional film. The intralayer deformation displacement and interlayer relative slip of each film layer are monitored in real time and fused with the multidimensional spectral response tensor to generate a stress-optical coupling feature map. Tensor decomposition was performed on the stress-optical coupling feature map. Based on the in-plane components obtained by decomposition, orientation defect fingerprints of each film layer were extracted. Based on the out-of-plane components obtained by decomposition and the relative slip between layers, interface defect fingerprints were extracted. A multi-level defect fingerprint library was established. By integrating a multi-level defect fingerprint database with a predefined constitutive relation model, the defect propagation dynamic equations for each membrane layer are constructed, and the temporal evolution trajectory of defects in each membrane layer under preset working conditions is predicted, generating time-varying curves of defect severity for each membrane layer. Based on the time-varying curves of the defect severity of each membrane layer, the critical failure time of each membrane layer is calculated, and defect management information is dynamically generated based on the critical failure time.

2. The method for detecting defects in a flexible display functional film according to claim 1, characterized in that, Methods for generating multidimensional spectral response tensors include: Under each optical field excitation mode, the reflected optical response signal, the transmitted optical response signal, and the fluorescent optical response signal are acquired simultaneously; the material optical constants and thickness information of each film layer are obtained, and a multilayer film optical transmission model is established based on the material optical constants and thickness information; the acquired reflected optical response signal, transmitted optical response signal, and fluorescent optical response signal are inversely calculated based on the multilayer film optical transmission model to separate the optical response signal of each film layer. For the optical response signals of each film layer under different optical field excitation modes, the corresponding spectral peak wavelength, spectral half width at half maximum, spectral integral intensity and phase gradient are extracted sequentially and used as optical response feature parameters. The dimensional structure of the multidimensional spectral response tensor is defined, the optical response feature parameters of each film layer are normalized, and the multidimensional spectral response tensor is organized and filled according to the dimensional structure of the multidimensional spectral response tensor to form a multidimensional spectral response tensor.

3. The method for detecting defects in a flexible display functional film according to claim 2, characterized in that, Methods for generating stress-optical coupling feature maps include: Record the actual stress state of the flexible display functional film at each time point during the application of a mechanical micro-stress field to obtain a stress loading time series table; and form a stress-deformation time series dataset based on the intralayer deformation displacement, interlayer relative slip, and stress loading time series table of each film layer. Based on a unified time reference, the stress-deformation time series dataset and the multidimensional spectral response tensor are time-registered and fused to form a time-registered fused dataset. Based on the time-registration fusion dataset, the stress-optical coupling coefficient of each film layer is calculated. The stress-optical coupling coefficient includes the deformation-intensity coupling coefficient and the slip-phase coupling coefficient. Based on the time-registration fusion dataset, the stress response gradient set of each film layer is extracted. The structure of the stress-optical coupling feature map is defined, the stress-optical coupling coefficients and stress response gradient sets of each film layer are normalized, and the structure is filled according to the stress-optical coupling feature map to generate the stress-optical coupling feature map.

4. The method for detecting defects in a flexible display functional film according to claim 3, characterized in that, Methods for tensor decomposition of stress-optical coupling feature maps include: Based on the stress-optical coupling feature map, a high-order coupling feature tensor is constructed. This high-order coupling feature tensor is then decomposed to obtain the core tensor and factor matrices for each dimension. Each factor matrix contains multiple principal component vectors. The in-plane and out-of-plane correlation coefficients for each principal component vector corresponding to each film layer are calculated. The principal component vector with the largest in-plane correlation coefficient for each film layer is taken as the in-plane component tensor of that film layer. The principal component vector with the largest out-of-plane correlation coefficient for each film layer is taken as the out-of-plane component tensor of that film layer. Based on the in-plane and out-of-plane component tensors of each film layer, the in-plane and out-of-plane components of each film layer are calculated.

5. The method for detecting defects in a flexible display functional film according to claim 4, characterized in that, Methods for establishing a multi-level defect fingerprint database include: The in-plane feature matrix of each film layer is extracted from the in-plane component; the orientation anisotropy index of each film layer is calculated based on the in-plane feature matrix; the polarization extinction ratio of each film layer under polarization switching excitation mode is extracted from the multidimensional spectral response tensor; and the orientation defect fingerprint of each film layer is constructed based on the orientation anisotropy index and polarization extinction ratio of each film layer. The out-of-plane feature matrix of each film layer is extracted from the out-of-plane component; the interfacial adhesion strength index of each film layer is calculated based on the out-of-plane feature matrix and the relative slip between layers; the slip recovery rate of each film layer is calculated based on the relative slip between layers; the angle sensitivity coefficient of each film layer under the angle gradient excitation mode is extracted from the multidimensional spectral response tensor; and the orientation defect fingerprint of each film layer is constructed based on the interfacial adhesion strength index, slip recovery rate, and angle sensitivity coefficient corresponding to each film layer. A multi-level defect fingerprint database was established based on the orientation defect fingerprints and interface defect fingerprints of each film layer.

6. The method for detecting defects in a flexible display functional film according to claim 5, characterized in that, Methods for constructing the defect propagation kinetic equations for each film layer include: A predefined constitutive relation model is obtained, whose model parameters include elastic modulus, Poisson's ratio, viscosity coefficient, relaxation time, and damage evolution coefficient. Orientation defect fingerprints and interface defect fingerprints corresponding to each film layer are obtained from a multi-level defect fingerprint database and collectively referred to as defect feature indices. A mapping relationship is established between the defect feature indices and the corresponding model parameters of the constitutive relation model to obtain correction factors for each model parameter under each film layer. Based on the correction factors for each model parameter under each film layer, the constitutive relation model is dynamically corrected to form a corrected constitutive relation model corresponding to each film layer. Based on the modified constitutive model, the orientation defect propagation kinetic equations for each film layer are established; based on the modified constitutive model, the interface defect propagation kinetic equations for each film layer are established; based on the modified constitutive model, the cumulative damage evolution equations for each film layer are established; the orientation defect propagation kinetic equations, interface defect propagation kinetic equations, and cumulative damage evolution equations for each film layer are integrated to form the defect propagation kinetic equations for each film layer.

7. The method for detecting defects in a flexible display functional film according to claim 6, characterized in that, Methods for predicting the temporal evolution trajectory of defects in each film layer under preset operating conditions include: A set of pre-defined working conditions is set, which includes three preset working conditions: static bending, dynamic bending, and composite environment. Based on the pre-defined set of working conditions, the equivalent stress time history curves and equivalent shear stress time history curves of each membrane layer under different preset working conditions are calculated. Initial conditions were set for the defect propagation kinetic equations corresponding to each film layer. These initial conditions included the initial equivalent size of orientation defects, the initial equivalent area of ​​interface defects, and the initial cumulative damage degree. The equivalent stress time history curves and equivalent shear stress time history curves corresponding to each film layer were substituted into the corresponding defect propagation kinetic equations. The fourth-order Runge-Kutta method was used for numerical solution to obtain the time-series evolution trajectory of each film layer under different preset working conditions. The time-series evolution trajectory included the time-series curves of the equivalent size of orientation defects, the equivalent area of ​​interface defects, and the cumulative damage degree.

8. The method for detecting defects in a flexible display functional film according to claim 7, characterized in that, Methods for generating time-varying curves of defect severity for each film layer include: A defect hazard assessment index system is defined, which includes structural integrity hazard index, optical performance hazard index, and interface reliability hazard index. Based on the time-series evolution trajectory, the structural integrity hazard index, optical performance hazard index, and interface reliability hazard index for each film layer at each time step are calculated sequentially. Corresponding hazard weights are assigned to the structural integrity hazard index, optical performance hazard index, and interface reliability hazard index for each film layer at the same time step. Based on these hazard weights, a weighted summation of the structural integrity hazard index, optical performance hazard index, and interface reliability hazard index for the same film layer at the same time step is calculated to obtain the comprehensive defect hazard level of each film layer at each time step. Based on the comprehensive defect hazard level of each film layer at each time step, a time-varying curve of the defect hazard level for each film layer is generated.

9. The method for detecting defects in a flexible display functional film according to claim 8, characterized in that, Methods for dynamically generating defect management information based on critical failure time include: Define failure criteria for each membrane layer, including hazard threshold criteria and hazard rate increase criteria; calculate the threshold-type critical failure time for each membrane layer based on the hazard threshold criteria; calculate the rate-increase critical failure time for each membrane layer based on the hazard rate increase criteria; determine the critical failure time for each membrane layer based on the threshold-type critical failure time and the rate-increase critical failure time. A defect risk level classification standard is defined to classify the defect risk of each membrane layer according to the critical failure time, thereby obtaining the defect risk level of each membrane layer; based on the defect risk level of each membrane layer, corresponding defect handling suggestions are generated; the critical failure times of all membrane layers are compared, and the membrane layer with the smallest critical failure time is selected and marked as the critical failure membrane layer; the defect risk level of each membrane layer, the defect handling suggestions, and the critical failure membrane layer are integrated to generate defect management information.

10. A flexible display functional film defect detection system, implementing the flexible display functional film defect detection method according to any one of claims 1-9, characterized in that, include: The light field excitation module is used to construct a programmable array light source, apply different light field excitation modes to the surface of the flexible display functional film, collect the optical response signals of each film layer in the flexible display functional film under different light field excitation modes, and form a multidimensional spectral response tensor. The stress coupling module is used to synchronously apply a preset gradient mechanical micro-stress field to the flexible display functional film, monitor the intralayer deformation displacement and interlayer relative slip of each film layer in real time, and perform time registration and fusion with the multidimensional spectral response tensor to generate a stress-optical coupling feature map. The tensor decoupling module is used to perform tensor decomposition on the stress-optical coupling feature map, extract orientation defect fingerprints of each film layer based on the in-plane components obtained by decomposition, extract interface defect fingerprints based on the out-of-plane components obtained by decomposition combined with the interlayer relative slip, and establish a multi-level defect fingerprint library. The evolution prediction module is used to integrate a multi-level defect fingerprint database with a predefined constitutive relation model, construct the defect propagation dynamic equations for each membrane layer, predict the time-series evolution trajectory of defects in each membrane layer under preset working conditions, and generate time-varying curves of defect severity for each membrane layer. The defect management module is used to calculate the critical failure time of each membrane layer based on the time-varying curve of the defect severity of each membrane layer, and dynamically generate defect management information based on the critical failure time.

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