Waterproof light-emitting plate detection method and system based on ray tracing

Abstract

The invention discloses a waterproof light-emitting plate detection method and system based on ray tracing. The method comprises the steps that the material type, the surface roughness, the refractive index, the light source position and the light intensity flicker mode of a light-emitting plate are obtained; inputting the material type, the surface roughness and the refractive index into a reflection characteristic model, calculating initial light source intensity and determining a reflection light intensity range; capturing reflected light intensity by using a ray tracing algorithm, dynamically adjusting light source intensity in combination with reflection characteristics, and recording a change trend of a light intensity flicker mode to obtain a flicker variable quantity; performing light intensity flicker mode distortion judgment according to the flicker variable quantity, and optimizing the light source position; recalculating the reflected light intensity, and judging whether the reflected light intensity meets the defect detection precision requirement or not; and if yes, deducing the position and size of the defect through a preset defect detection model based on the feature data of the light intensity flicker mode. According to the invention, high-precision and high-efficiency defect detection of the waterproof light-emitting plate is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of light-emitting board detection, and in particular to a waterproof light-emitting board detection method and system based on ray tracing. Background Art

[0002] At present, in the field of light-emitting board manufacturing and quality inspection, with the rapid development of intelligent manufacturing, higher requirements are placed on the accuracy and efficiency of product defect detection. As a key component, light-emitting boards are widely used in electronic equipment, lighting systems and display technologies, and their performance directly affects the quality of the final product. However, the material and surface characteristics of light-emitting boards vary significantly, from smooth to rough, from transparent to opaque. These differences lead to different characteristics of reflected light, which brings great challenges to defect detection. Traditional detection methods usually use fixed light source intensity, which cannot adapt to the detection needs under different materials and surface conditions. In order to meet these challenges, the system needs to have the ability to adjust the light source intensity in real time to dynamically adjust the incident light intensity according to different materials and surface conditions, so as to achieve accurate defect detection. However, the real-time adjustment of light intensity introduces new problems: frequent or large-scale light intensity adjustment may cause slight flickering of light intensity, and this flickering pattern is precisely the key basis for inferring the location and size of internal defects. If the flickering pattern is obscured or distorted, it will lead to misjudgment or missed detection of defects. In addition, the dynamic adjustment of the light source position further exacerbates this contradiction, because the change of the light source position will directly affect the propagation path and reflection characteristics of the light, and thus affect the accuracy and stability of the light intensity adjustment. Therefore, how to ensure the stability and recognizability of the light intensity flickering pattern while adjusting the light source intensity and position in real time has become the core problem in this technical scenario.

[0003] In one prior art, a static detection method is used based on a fixed light source intensity and position. This technology first uses a single and fixed high-intensity light source in the detection system, and the position and angle of the light source remain unchanged during the detection process. The light-emitting board is placed on a fixed detection platform, and the light source irradiates the surface of the light-emitting board at a preset angle. The reflected light is guided by a series of optical lenses and reflectors and enters a high-resolution CCD or CMOS image sensor to form an image of the surface of the light-emitting board. The image is processed by an algorithm to extract the distribution characteristics of the reflected light intensity on the surface. The system compares and analyzes the reflected light intensity through a pre-set threshold to determine whether there is a defect. When the reflected light intensity is abnormally weakened or enhanced in a certain area, the system will mark the area as a potential defect area.

[0004] The existing technology uses a single and fixed light source intensity, which cannot adapt to the detection needs under different materials and surface conditions. For example, a smooth surface may cause the reflected light to be too strong, covering up tiny defects; while a rough surface has severe light scattering, making it difficult to capture defect signals. At the same time, the setting of a fixed light source position limits the optimization of the light propagation path and reflection characteristics, further reducing the accuracy and adaptability of detection. At the same time, the static detection method cannot achieve real-time dynamic adjustment of light intensity, and cannot flexibly adjust the incident light intensity according to the characteristics of the reflected light, which directly affects the accuracy and reliability of defect detection. In addition, although the technology extracts the distribution characteristics of the reflected light intensity and performs threshold analysis through image processing algorithms, this passive processing method is difficult to cope with complex and changeable surface conditions, and is prone to misjudgment or missed detection. Therefore, the existing technology has obvious deficiencies in detection flexibility, adaptability and accuracy, and it is difficult to meet the needs of high-precision and high-efficiency defect detection in the context of intelligent manufacturing. Summary of the invention

[0005] The present invention provides a waterproof luminous plate detection method and system based on ray tracing to meet the needs of high-precision and high-efficiency defect detection.

[0006] In a first aspect, in order to solve the above technical problems, the present invention provides a waterproof light-emitting panel detection method based on ray tracing, comprising: Get the material type, surface roughness, refractive index, light source position and light intensity flashing mode of the light-emitting panel; Inputting the material type, the surface roughness and the refractive index into a pre-established reflection feature model to obtain a reflection feature; Calculate the initial light source intensity and determine the reflected light intensity range according to the reflection characteristics; According to the initial light source intensity, the material type, the surface roughness and the refractive index, a ray tracing algorithm is used to capture the reflected light and analyze the reflected light intensity; Dynamically adjusting the intensity of the light source according to the reflected light intensity and the reflected light intensity range and recording the change trend of the light intensity flickering pattern to obtain a flickering change amount; Performing distortion judgment on the light intensity flicker pattern according to the flicker variation, and dynamically adjusting the light source position according to the judgment result; Recalculate the reflected light intensity according to the optimized light source intensity and the light source position to obtain a new reflected light intensity; Determine whether the intensity of the new reflected light meets the accuracy requirement of defect detection. When the intensity of the new reflected light meets the accuracy requirement of defect detection, obtain characteristic data of the light intensity flickering pattern and input it into a preset defect detection model to infer the defect position and defect size, wherein the characteristic data includes the light source intensity and frequency characteristics including the time series.

[0007] In an optional implementation, the inputting the material type, the surface roughness and the refractive index into a pre-established reflection feature model to obtain the reflection feature includes: Inputting the material type into a pre-established multiple linear regression model to obtain a first reflection feature; Inputting the surface roughness into a pre-established variance analysis model to obtain a second reflection feature; Inputting the refractive index into a pre-established principal component analysis model to obtain a third reflection feature; Integrating the first reflection feature, the second reflection feature and the third reflection feature through a pre-established weighted comprehensive model to obtain a reflection feature; Among them, the reflection characteristic model includes a multiple linear regression model, a variance analysis model, a component analysis model and a weighted comprehensive model.

[0008] In an optional implementation, calculating the initial light source intensity and determining the reflected light intensity range according to the reflection characteristics includes: The initial light source intensity and reflected light intensity range are calculated using the following formula: in, represents the angle between the microsurface normal and the macro surface normal, Indicates the surface roughness, represents the angle of incidence, represents the Fresnel reflectivity, Represents the reflection characteristics, represents the refractive index, Indicates the preset attenuation coefficient, Indicates the preset parameters matched according to the material type. represents the initial light source intensity, Indicates the minimum reflected light intensity, Indicates the maximum reflected light intensity.

[0009] In an optional implementation, capturing reflected light and analyzing reflected light intensity using a ray tracing algorithm according to the initial light source intensity, the material type, the surface roughness and the refractive index includes: The ray tracing algorithm is used to simulate the light propagation path and record the incident angle and reflection angle of the light; Calculating the intensity of reflected light according to the initial light source intensity, the material type, the surface roughness, the refractive index, the incident angle and the reflection angle; The reflected light intensity is calculated by the following formula: in, represents the angle between the microsurface normal and the macro surface normal, Indicates the surface roughness, represents the probability density function of the microscopic normal, represents the angle of incidence, represents the reflection angle, Indicates the preset parameters matched according to the material type. represents the initial light source intensity, Indicates the intensity of reflected light.

[0010] In an optional implementation, dynamically adjusting the light source intensity according to the reflected light intensity and the reflected light intensity range and recording the change trend of the light intensity flickering pattern to obtain the flicker change amount includes: Comparing the reflected light intensity with the reflected light intensity range, and if the reflected light intensity is within the reflected light intensity range, taking the initial light source intensity as the final light source intensity; If the reflected light intensity is not within the reflected light intensity range, dynamically adjusting the light source intensity until the reflected light intensity falls within the reflected light intensity range, and recording the change trend of the light intensity flickering mode during the light source intensity adjustment process to obtain the flickering change amount; Among them, the light source intensity is adjusted by the following formula: in, Indicates The intensity of the light source after adjustment is Indicates The intensity of the light source after adjustment is represents the preset adaptive gain coefficient, represents the symbolic function, Output positive or negative sign, Indicates the preset light source intensity adjustment step. Indicates the target reflection intensity, Indicates The intensity of reflected light after adjustment. Indicates the minimum reflected light intensity, Indicates the maximum reflected light intensity.

[0011] In an optional implementation, the step of performing distortion judgment on the light intensity flicker pattern according to the flicker variation, and dynamically adjusting the light source position according to the judgment result, includes: The flicker change amount is compared with a preset flicker change threshold value. If the flicker change amount is greater than the flicker change threshold value, it is determined that the light intensity flicker pattern is distorted, and the light source intensity adjustment is stopped and the light source position dynamic adjustment algorithm is used to optimize the incident angle and propagation path of the light, and the light source position is adjusted according to the optimized incident angle and propagation path; If the flicker change amount is less than or equal to the flicker change threshold, it is determined that there is no distortion in the light intensity flicker pattern.

[0012] In an optional implementation, the determining whether the intensity of the new reflected light meets the accuracy requirement of defect detection, when the intensity of the new reflected light meets the accuracy requirement of defect detection, acquiring characteristic data of the light intensity flickering pattern, and inputting it into a preset defect detection model to infer the defect position and defect size, includes: Calculating the detection accuracy according to the intensity of the new reflected light, and comparing the detection accuracy with a preset detection accuracy threshold, and if the detection accuracy is greater than the detection accuracy threshold, readjusting the position of the light source; If the detection accuracy is less than or equal to the detection accuracy threshold, then acquiring characteristic data of the light intensity flickering pattern and inputting it into a preset defect detection model to infer the defect position and defect size; Wherein, the characteristic data includes the intensity and frequency characteristics of the light source including the time series; The detection accuracy is calculated by the following formula: in, Represents the intensity of the new reflected light, represents the preset defect detection intensity threshold, Indicates detection accuracy.

[0013] In a second aspect, the present invention provides a waterproof light-emitting panel detection system based on ray tracing, comprising: A data acquisition module is used to obtain the material type, surface roughness, refractive index, light source position and light intensity flickering mode of the light-emitting panel; A reflection feature analysis module, used for inputting the material type, the surface roughness and the refractive index into a pre-established reflection feature model to obtain a reflection feature; A light source intensity analysis module, used to calculate the initial light source intensity and determine the intensity range of the reflected light according to the reflection characteristics; A reflected light analysis module, used to capture reflected light and analyze reflected light intensity using a ray tracing algorithm according to the initial light source intensity, the material type, the surface roughness and the refractive index; A flicker change analysis module, used to dynamically adjust the light source intensity according to the reflected light intensity and the reflected light intensity range and record the change trend of the light intensity flicker pattern to obtain a flicker change amount; A light source position optimization module, used to make a distortion judgment on the light intensity flicker pattern according to the flicker variation, and dynamically adjust the light source position according to the judgment result; A light updating module, used for recalculating the reflected light intensity according to the optimized light source intensity and the light source position to obtain a new reflected light intensity; The defect detection module is used to determine whether the intensity of the new reflected light meets the accuracy requirement of defect detection. When the intensity of the new reflected light meets the accuracy requirement of defect detection, the characteristic data of the light intensity flickering pattern is obtained and input into a preset defect detection model to infer the defect position and defect size, wherein the characteristic data includes the light source intensity and frequency characteristics containing a time series.

[0014] In a third aspect, the present invention further provides an electronic device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the waterproof luminous panel detection method based on ray tracing as described above is implemented.

[0015] In a fourth aspect, the present invention further provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned waterproof luminous panel detection methods based on ray tracing.

[0016] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention establishes a reflection feature model corresponding to the material and surface characteristics, combines the material type, surface roughness and refractive index, accurately calculates the initial light source intensity and the reflected light intensity range, and significantly improves the accuracy and adaptability of light-emitting panel defect detection.

[0017] (2) A ray tracing algorithm is used to simulate the propagation path of light, capture the distribution characteristics of reflected light, and dynamically adjust the intensity and position of the light source. This avoids the detection error caused by fixed light source intensity and position in traditional methods and improves the flexibility and reliability of detection.

[0018] (3) By real-time monitoring of the changing trend of the light intensity flicker pattern, it is determined whether there is distortion caused by over-adjustment, and the position of the light source is optimized in combination with the reflection feature model, thus ensuring the stability and identifiability of the light intensity flicker pattern and improving the accuracy of defect inference.

[0019] (4) The acquired light intensity flicker pattern characteristic data is input into the preset defect detection model to infer the defect position and size, thereby achieving accurate positioning and quantitative analysis of the defects, providing efficient and reliable technical support for the quality control of the light-emitting panels.

[0020] In summary, the present invention establishes a reflection characteristic model corresponding to the material and surface characteristics, combines the ray tracing algorithm to dynamically adjust the light source intensity and position, monitors the light intensity flickering pattern in real time, and accurately infers the defect position and size. This method solves the problem that the fixed light source parameters in the traditional detection method cannot adapt to different materials and surface conditions, and significantly improves the accuracy, flexibility and reliability of detection. The present invention significantly improves the efficiency and accuracy of light-emitting board defect detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic diagram of a waterproof light-emitting panel detection process based on ray tracing provided by the first embodiment of the present invention; Figure 2 It is a schematic diagram of the structure of a waterproof light-emitting panel detection system based on ray tracing provided in the second embodiment of the present invention. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] Reference Figure 1 The first embodiment of the present invention provides a waterproof light-emitting panel detection method based on ray tracing, comprising the following steps: S11, obtaining the material type, surface roughness, refractive index, light source position and light intensity flashing mode of the light-emitting panel; S12, inputting the material type, the surface roughness and the refractive index into a pre-established reflection feature model to obtain a reflection feature; S13, calculating the initial light source intensity and determining the intensity range of the reflected light according to the reflection characteristics; S14, capturing reflected light and analyzing reflected light intensity using a ray tracing algorithm according to the initial light source intensity, the material type, the surface roughness and the refractive index; S15, dynamically adjusting the intensity of the light source according to the reflected light intensity and the reflected light intensity range and recording the change trend of the light intensity flickering pattern to obtain a flickering change amount; S16, performing distortion judgment on the light intensity flicker pattern according to the flicker variation, and dynamically adjusting the light source position according to the judgment result; S17, recalculating the reflected light intensity according to the optimized light source intensity and the light source position to obtain a new reflected light intensity; S18, determine whether the intensity of the new reflected light meets the accuracy requirement of defect detection. When the intensity of the new reflected light meets the accuracy requirement of defect detection, obtain the characteristic data of the light intensity flickering pattern and input it into a preset defect detection model to infer the defect position and defect size, wherein the characteristic data includes the light source intensity and frequency characteristics containing a time series.

[0024] In step S11, the material type, surface roughness, refractive index, light source position and light intensity flickering mode of the light emitting panel are obtained.

[0025] Specifically, the material type can be identified by a component analyzer or a spectrometer, the surface roughness can be accurately measured by a surface profiler or a laser scanner, and the refractive index can be measured by a refractometer or an ellipsometer.

[0026] In step S12, the material type, the surface roughness and the refractive index are input into a pre-established reflection feature model to obtain a reflection feature.

[0027] In a specific implementation, the inputting the material type, the surface roughness and the refractive index into a pre-established reflection feature model to obtain the reflection feature includes: Inputting the material type into a pre-established multiple linear regression model to obtain a first reflection feature; Inputting the surface roughness into a pre-established variance analysis model to obtain a second reflection feature; Inputting the refractive index into a pre-established principal component analysis model to obtain a third reflection feature; Integrating the first reflection feature, the second reflection feature and the third reflection feature through a pre-established weighted comprehensive model to obtain a reflection feature; Among them, the reflection characteristic model includes a multiple linear regression model, a variance analysis model, a component analysis model and a weighted comprehensive model.

[0028] Specifically, firstly, the material type, as the primary factor affecting the reflection characteristics, is processed by a multiple linear regression model, and the mathematical expression of the model is: in represents the first reflection feature, Indicates the preset coefficient for material type matching. , and is the regression coefficient, obtained by least squares fitting. The model training process is based on a large number of historical material types and reflection characteristics data sets, and the regression coefficients are iteratively optimized to minimize the prediction error. The surface roughness is processed by the variance analysis model, and its expression is: in represents the second reflection feature, Indicates the surface roughness, and are model parameters, is a random error term. The variance analysis model determines the significant effect of roughness on the reflection characteristics by statistically analyzing the reflection characteristics at different roughness levels. The refractive index is processed by the principal component analysis model, and the expression is: in represents the third reflection feature, , and is the main component of the refractive index, , and is the principal component coefficient. Principal component analysis extracts the main features of the refractive index data through dimensionality reduction technology, reduces redundant information and retains key parameters. Finally, the weighted comprehensive model is used to , and To integrate, the expression is: in represents the final reflection characteristic, , and is a preset weight coefficient, which is normalized to ensure that its sum is 1. The weighted comprehensive model comprehensively considers the contribution of material type, surface roughness and refractive index to the reflection characteristics. Through multi-model collaborative analysis, the influence of various factors on the reflection characteristics is accurately quantified, providing a reliable theoretical basis for the design and performance optimization of the light-emitting panel.

[0029] In step S13, the initial light source intensity is calculated according to the reflection characteristics and the reflected light intensity range is determined.

[0030] In a specific implementation, calculating the initial light source intensity and determining the reflected light intensity range according to the reflection characteristics includes: The initial light source intensity and reflected light intensity range are calculated using the following formula: in, represents the angle between the microsurface normal and the macro surface normal, Indicates the surface roughness, represents the angle of incidence, represents the Fresnel reflectivity, Represents the reflection characteristics, represents the refractive index, Indicates the preset attenuation coefficient, Indicates the preset parameters matched according to the material type. represents the initial light source intensity, Indicates the minimum reflected light intensity, Indicates the maximum reflected light intensity.

[0031] Specifically, in step S13, the process of calculating the initial light source intensity and determining the reflected light intensity range according to the reflection characteristics involves the combination of physical optics and mathematical models. As a core input parameter, it determines the calculation of light intensity and the range of reflected light intensity together with the optical properties of the surface. The calculation formula is as follows: in, Represents the Fresnel reflectivity, and the calculation formula is: In this formula, represents the refractive index, represents the angle of incidence, represents the angle between the microsurface normal and the macro surface normal, Indicates the surface roughness, It is a preset parameter matched according to the material type. The calculation of the initial light intensity takes into account the reflection characteristics, surface roughness, Fresnel effect and the influence of material type on light intensity.

[0032] Minimum reflected light intensity The calculation formula is: in, Represents the preset attenuation coefficient, which is used to simulate the intensity attenuation of light due to energy loss during reflection. Maximum reflected light intensity Directly equal to the initial light intensity ,Right now: By combining the reflection characteristics with the surface optical properties, and using the modulation effect of Fresnel reflectivity and roughness on light intensity, the range of initial light source intensity and reflected light intensity can be accurately calculated. The initial light source intensity reflects the maximum intensity of light under ideal conditions, the minimum reflected light intensity takes into account the energy loss of light during the reflection process, and the maximum reflected light intensity is directly determined by the initial light source intensity as the upper limit.

[0033] In step S14, a ray tracing algorithm is used to capture reflected light and analyze the intensity of reflected light according to the initial light source intensity, the material type, the surface roughness and the refractive index.

[0034] In a specific implementation, the method of capturing reflected light and analyzing the intensity of reflected light using a ray tracing algorithm according to the initial light source intensity, the material type, the surface roughness and the refractive index includes: The ray tracing algorithm is used to simulate the light propagation path and record the incident angle and reflection angle of the light; Calculating the intensity of reflected light according to the initial light source intensity, the material type, the surface roughness, the refractive index, the incident angle and the reflection angle; The reflected light intensity is calculated by the following formula: in, represents the angle between the microsurface normal and the macro surface normal, Indicates the surface roughness, represents the probability density function of the microscopic normal, represents the angle of incidence, represents the reflection angle, Indicates the preset parameters matched according to the material type. represents the initial light source intensity, Indicates the intensity of reflected light.

[0035] Specifically, the ray tracing algorithm simulates the propagation path of light on the surface and records the incident angle of the light. and reflection angle , and calculates the reflected light intensity by combining the surface properties and the initial light source intensity .

[0036] The calculation of reflected light intensity is based on the probability density function of the microscopic normal and Fresnel reflectivity . Probability density function of micro-normal It describes the distribution of the angle between the micro-surface normal and the macro-normal, and its calculation formula is: in, represents the angle between the microsurface normal and the macro surface normal, Indicates surface roughness. This function reflects the effect of surface roughness on the direction of light reflection. The greater the roughness, the more significant the light scattering.

[0037] Reflected light intensity The calculation formula is: in, Indicates the preset parameters matched according to the material type. represents the reflection angle, Represents the initial light source intensity. This formula comprehensively considers the contribution of microscopic normal distribution, Fresnel reflectivity, incident angle, reflection angle, and initial light source intensity to the intensity of reflected light.

[0038] The implementation process of the ray tracing algorithm first simulates the propagation path of light, records the angle of incidence and the angle of reflection, and then calculates the intensity of the reflected light using the above formula. The core of the algorithm is to accurately describe the interaction between light and the surface, including the reflection direction, energy distribution and intensity change.

[0039] In step S15, the intensity of the light source is dynamically adjusted according to the reflected light intensity and the reflected light intensity range, and the change trend of the light intensity flickering pattern is recorded to obtain the flickering change amount.

[0040] In a specific implementation, dynamically adjusting the light source intensity according to the reflected light intensity and the reflected light intensity range and recording the change trend of the light intensity flickering pattern to obtain the flickering change amount includes: Comparing the reflected light intensity with the reflected light intensity range, and if the reflected light intensity is within the reflected light intensity range, taking the initial light source intensity as the final light source intensity; If the reflected light intensity is not within the reflected light intensity range, dynamically adjusting the light source intensity until the reflected light intensity falls within the reflected light intensity range, and recording the change trend of the light intensity flickering mode during the light source intensity adjustment process to obtain the flickering change amount; Among them, the light source intensity is adjusted by the following formula: in, Indicates The intensity of the light source after adjustment is Indicates The intensity of the light source after adjustment is Represents the preset adaptive gain coefficient, represents the symbolic function, Output positive or negative sign, Indicates the preset light source intensity adjustment step. Indicates the target reflection intensity, Indicates The intensity of reflected light after adjustment. Indicates the minimum reflected light intensity, Indicates the maximum reflected light intensity.

[0041] Specifically, first, the reflected light intensity Reflected light intensity range For comparison: If satisfy , indicating that the reflected light intensity is within the preset range, and there is no need to adjust the light source intensity. As the final light source intensity. or , it is necessary to dynamically adjust the light source intensity so that the reflected light intensity falls within the preset range.

[0042] The process of dynamically adjusting the light intensity is achieved through iteration. The adjusted light intensity The calculation formula is as follows: in, Indicates The intensity of the light source after adjustment is Indicates The intensity of the light source after adjustment is Represents the preset adaptive gain coefficient, represents the symbolic function, Output positive or negative sign, Indicates the preset light source intensity adjustment step. Indicates the target reflection intensity, Indicates The intensity of reflected light after adjustment. Indicates the minimum reflected light intensity, Indicates the maximum reflected light intensity.

[0043] The reflected light intensity is recalculated after each adjustment until it satisfies that the reflected light intensity falls within the reflected light intensity range.

[0044] During the light source intensity adjustment process, record the change trend of the light intensity flicker pattern and calculate the flicker change amount The flicker change is calculated using the following formula: in, Indicates the amount of flicker change, Indicates The intensity of the light source after adjustment is Indicates The intensity of the light source after adjustment is Indicates the number of adjustments in the adjustment process. This formula quantifies the change trend of the light intensity flicker pattern by accumulating the difference in the light source intensity of adjacent time steps.

[0045] By dynamically adjusting the intensity of the light source, the reflected light intensity is ensured to be within the preset range, providing reliable optical conditions for subsequent defect detection. The record of flicker changes provides a quantitative basis for analyzing changes in light intensity flicker patterns, which helps to optimize the light source adjustment strategy and improve system performance. The entire process is based on iterative algorithms and mathematical formulas to ensure the accuracy and efficiency of light source adjustment.

[0046] In step S16, the light intensity flicker pattern is subjected to distortion judgment according to the flicker variation, and the light source position is dynamically adjusted according to the judgment result.

[0047] In a specific implementation, the step of performing distortion judgment on the light intensity flicker pattern according to the flicker variation, and dynamically adjusting the light source position according to the judgment result, includes: The flicker change amount is compared with a preset flicker change threshold value. If the flicker change amount is greater than the flicker change threshold value, it is determined that the light intensity flicker pattern is distorted, and the light source intensity adjustment is stopped and the light source position dynamic adjustment algorithm is used to optimize the incident angle and propagation path of the light, and the light source position is adjusted according to the optimized incident angle and propagation path; If the flicker change amount is less than or equal to the flicker change threshold, it is determined that there is no distortion in the light intensity flicker pattern.

[0048] Specifically, the light intensity flicker pattern distortion is judged based on the flicker variation, and the light source position is optimized based on the judgment result and the dynamic adjustment algorithm of the light source position. As a core input parameter, it is used to evaluate the stability and distortion of the light intensity flicker pattern. Flicker change threshold As a preset reference value, it is used to compare with the flicker change amount to determine whether there is distortion in the light intensity flicker pattern.

[0049] The logic of distortion judgment is as follows: If the flicker change Greater than flicker change threshold ,Right now , it is determined that the light intensity flickering mode is distorted. At this time, the light source intensity adjustment is stopped, and the light source position dynamic adjustment algorithm is used to optimize the incident angle and propagation path of the light. The optimized incident angle and propagation path are used to adjust the light source position to reduce the degree of distortion of the light intensity flickering mode.

[0050] If the flickering amount changes Less than or equal to flicker change threshold ,Right now , it is determined that there is no distortion in the light intensity flickering mode, and there is no need to further adjust the light source position or optimize the light propagation path.

[0051] The implementation process of the light source position dynamic adjustment algorithm is based on the optimization of the incident angle and propagation path of the light. The goal of the optimization is to minimize the flicker change. , thereby improving the stability of the light intensity flicker pattern. The optimization algorithm iteratively adjusts the light source position, calculates the flicker change after each adjustment, and compares it with the target threshold until the flicker change reaches or falls below the preset flicker change threshold.

[0052] Through the distortion judgment and light source position adjustment algorithm, the light propagation path and incident angle are dynamically optimized to reduce the distortion of the light intensity flicker mode and improve the stability and performance of the optical system. The flicker change threshold is set based on theoretical analysis and experimental data. In step S17, the reflected light intensity is recalculated according to the optimized light source intensity and the light source position to obtain a new reflected light intensity.

[0053] Specifically, first, the optimized light source intensity and light source position will directly affect the incident angle and reflection angle of the light. Re-simulate the propagation path of the light and record the new incident angle and reflection angle. Then, based on the probability density function of the microscopic normal and the Fresnel reflectivity, calculate the new reflected light intensity.

[0054] By recalculating the intensity of reflected light, the influence of optimized light source parameters on light propagation is verified to ensure the stability of the light intensity flickering mode and the performance optimization of the optical system.

[0055] In step S18, it is determined whether the intensity of the new reflected light meets the accuracy requirements of defect detection. When the intensity of the new reflected light meets the accuracy requirements of defect detection, the characteristic data of the light intensity flickering pattern is obtained and input into a preset defect detection model to infer the defect position and defect size, wherein the characteristic data includes the light source intensity and frequency characteristics containing a time series.

[0056] In a specific implementation, the determining whether the intensity of the new reflected light meets the accuracy requirement of defect detection, when the intensity of the new reflected light meets the accuracy requirement of defect detection, acquiring characteristic data of the light intensity flickering pattern, and inputting it into a preset defect detection model, and inferring the defect position and defect size, includes: Calculating the detection accuracy according to the intensity of the new reflected light, and comparing the detection accuracy with a preset detection accuracy threshold, and if the detection accuracy is greater than the detection accuracy threshold, readjusting the position of the light source; If the detection accuracy is less than or equal to the detection accuracy threshold, then acquiring characteristic data of the light intensity flickering pattern and inputting it into a preset defect detection model to infer the defect position and defect size; Wherein, the characteristic data includes the intensity and frequency characteristics of the light source including the time series; The detection accuracy is calculated by the following formula: in, Represents the intensity of the new reflected light, represents the preset defect detection intensity threshold, Indicates detection accuracy.

[0057] Specifically, first, the detection accuracy The calculation formula is as follows: Among them, among them, Represents the intensity of the new reflected light, represents the preset defect detection intensity threshold, Indicates the detection accuracy. Detection accuracy It reflects the relative value of the intensity of the new reflected light relative to the detection threshold and is used to evaluate the quality of the light intensity.

[0058] Secondly, the detection accuracy With the preset detection accuracy threshold For comparison: If , indicating that the intensity of the new reflected light does not meet the accuracy requirements of defect detection, and the light source position needs to be readjusted; if , indicating that the intensity of the new reflected light meets the detection accuracy requirements and enters the feature data extraction and defect detection stage.

[0059] The characteristic data includes the intensity and frequency characteristics of the light source in the time series. Records the value of light source intensity changing over time, frequency characteristics The intensity of the light source is obtained by Fourier transform, and the calculation formula is as follows: in, represents the angular frequency, Represents the frequency characteristics, Indicates the intensity of the light source, It is a purely mathematical symbol representing an imaginary unit.

[0060] After acquiring the feature data, it is input into the preset defect detection model to infer the defect location and defect size. The defect detection model is built based on the training data set. During the training process, the feature data of the light intensity flicker pattern and its corresponding defect information are input to optimize the model parameters so that it can accurately predict the defect location and size. The trained model outputs the defect location coordinates and defect size by inputting new feature data.

[0061] The accuracy of defect detection is ensured by accurately evaluating the quality of the newly reflected light intensity. The calculation formula and comparison logic of the detection accuracy ensure the effectiveness of the light intensity evaluation, and the extraction of feature data and the application of defect detection models realize the automatic inference of defect location and size. The entire process is based on mathematical models and algorithms to ensure the reliability and efficiency of defect detection.

[0062] Reference Figure 2 The second embodiment of the present invention provides a waterproof light-emitting panel detection system based on ray tracing, comprising: A data acquisition module is used to obtain the material type, surface roughness, refractive index, light source position and light intensity flickering mode of the light-emitting panel; A reflection feature analysis module, used for inputting the material type, the surface roughness and the refractive index into a pre-established reflection feature model to obtain a reflection feature; A light source intensity analysis module, used to calculate the initial light source intensity and determine the intensity range of the reflected light according to the reflection characteristics; A reflected light analysis module, used to capture reflected light and analyze reflected light intensity using a ray tracing algorithm according to the initial light source intensity, the material type, the surface roughness and the refractive index; A flicker change analysis module, used to dynamically adjust the light source intensity according to the reflected light intensity and the reflected light intensity range and record the change trend of the light intensity flicker pattern to obtain a flicker change amount; A light source position optimization module, used to make a distortion judgment on the light intensity flicker pattern according to the flicker variation, and dynamically adjust the light source position according to the judgment result; A light updating module, used for recalculating the reflected light intensity according to the optimized light source intensity and the light source position to obtain a new reflected light intensity; The defect detection module is used to determine whether the intensity of the new reflected light meets the accuracy requirement of defect detection. When the intensity of the new reflected light meets the accuracy requirement of defect detection, the characteristic data of the light intensity flickering pattern is obtained and input into a preset defect detection model to infer the defect position and defect size, wherein the characteristic data includes the light source intensity and frequency characteristics containing a time series.

[0063] It should be noted that a waterproof light-emitting panel detection device based on ray tracing provided in an embodiment of the present invention is used to execute all process steps of a waterproof light-emitting panel detection method based on ray tracing in the above embodiment. The working principles and beneficial effects of the two correspond one to one, and thus will not be described in detail.

[0064] The embodiment of the present invention further provides an electronic device. The electronic device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a waterproof light-emitting panel detection program based on ray tracing. When the processor executes the computer program, the steps in the above-mentioned embodiments of the waterproof light-emitting panel detection method based on ray tracing are implemented, such as Figure 1 Alternatively, when the processor executes the computer program, the functions of the modules / units in the above-mentioned device embodiments are realized, such as a waterproof light-emitting panel detection module based on ray tracing.

[0065] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the electronic device.

[0066] The electronic device may be a computing device such as a desktop computer, a notebook, a PDA, and a smart tablet. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the above components are merely examples of electronic devices and do not constitute a limitation on the electronic device. The electronic device may include more or fewer components than the above components, or may combine certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0067] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the electronic device, and uses various interfaces and lines to connect various parts of the entire electronic device.

[0068] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the electronic device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0069] Wherein, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0070] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0071] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A waterproof light-emitting panel detection method based on ray tracing, characterized in that: include: Get the material type, surface roughness, refractive index, light source position and light intensity flashing mode of the light-emitting panel; Inputting the material type, the surface roughness and the refractive index into a pre-established reflection feature model to obtain a reflection feature; Calculate the initial light source intensity and determine the reflected light intensity range according to the reflection characteristics; According to the initial light source intensity, the material type, the surface roughness and the refractive index, a ray tracing algorithm is used to capture the reflected light and analyze the reflected light intensity; Dynamically adjusting the intensity of the light source according to the reflected light intensity and the reflected light intensity range and recording the change trend of the light intensity flickering pattern to obtain a flickering change amount; Performing distortion judgment on the light intensity flicker pattern according to the flicker variation, and dynamically adjusting the light source position according to the judgment result; Recalculate the reflected light intensity according to the optimized light source intensity and the light source position to obtain a new reflected light intensity; Determine whether the intensity of the new reflected light meets the accuracy requirement of defect detection. When the intensity of the new reflected light meets the accuracy requirement of defect detection, obtain characteristic data of the light intensity flickering pattern and input it into a preset defect detection model to infer the defect position and defect size, wherein the characteristic data includes the light source intensity and frequency characteristics including the time series.

2. The waterproof light-emitting panel detection method based on ray tracing according to claim 1 is characterized in that: The step of inputting the material type, the surface roughness and the refractive index into a pre-established reflection feature model to obtain the reflection feature comprises: Inputting the material type into a pre-established multiple linear regression model to obtain a first reflection feature; Inputting the surface roughness into a pre-established variance analysis model to obtain a second reflection feature; Inputting the refractive index into a pre-established principal component analysis model to obtain a third reflection feature; Integrating the first reflection feature, the second reflection feature and the third reflection feature through a pre-established weighted comprehensive model to obtain a reflection feature; Among them, the reflection characteristic model includes a multiple linear regression model, a variance analysis model, a component analysis model and a weighted comprehensive model.

3. The waterproof light-emitting panel detection method based on ray tracing according to claim 1 is characterized in that: The step of calculating the initial light source intensity and determining the reflected light intensity range according to the reflection characteristics includes: The initial light source intensity and reflected light intensity range are calculated using the following formula: in, represents the angle between the microsurface normal and the macro surface normal, Indicates the surface roughness, represents the angle of incidence, represents the Fresnel reflectivity, Represents the reflection characteristics, represents the refractive index, Indicates the preset attenuation coefficient, Indicates the preset parameters matched according to the material type. represents the initial light source intensity, Indicates the minimum reflected light intensity, Indicates the maximum reflected light intensity.

4. The waterproof light-emitting panel detection method based on ray tracing according to claim 1 is characterized in that: The method of capturing reflected light and analyzing the intensity of reflected light using a ray tracing algorithm according to the initial light source intensity, the material type, the surface roughness and the refractive index includes: The ray tracing algorithm is used to simulate the light propagation path and record the incident angle and reflection angle of the light; Calculating the intensity of reflected light according to the initial light source intensity, the material type, the surface roughness, the refractive index, the incident angle and the reflection angle; The reflected light intensity is calculated by the following formula: in, represents the angle between the microsurface normal and the macro surface normal, Indicates the surface roughness, represents the probability density function of the microscopic normal, represents the angle of incidence, represents the reflection angle, Indicates the preset parameters matched according to the material type. represents the initial light source intensity, Indicates the intensity of reflected light.

5. The waterproof light-emitting panel detection method based on ray tracing according to claim 1 is characterized in that: The dynamically adjusting the light source intensity according to the reflected light intensity and the reflected light intensity range and recording the change trend of the light intensity flickering mode to obtain the flicker change amount includes: Comparing the reflected light intensity with the reflected light intensity range, and if the reflected light intensity is within the reflected light intensity range, taking the initial light source intensity as the final light source intensity; If the reflected light intensity is not within the reflected light intensity range, dynamically adjusting the light source intensity until the reflected light intensity falls within the reflected light intensity range, and recording the change trend of the light intensity flickering mode during the light source intensity adjustment process to obtain the flickering change amount; Among them, the light source intensity is adjusted by the following formula: in, Indicates The intensity of the light source after adjustment is Indicates The intensity of the light source after adjustment is Represents the preset adaptive gain coefficient, represents the symbolic function, Output positive or negative sign, Indicates the preset light source intensity adjustment step. Indicates the target reflection intensity, Indicates The intensity of reflected light after adjustment. Indicates the minimum reflected light intensity, Indicates the maximum reflected light intensity.

6. The waterproof light-emitting panel detection method based on ray tracing according to claim 1 is characterized in that: The step of performing distortion judgment on the light intensity flicker mode according to the flicker variation, and dynamically adjusting the light source position according to the judgment result, includes: The flicker change amount is compared with a preset flicker change threshold value. If the flicker change amount is greater than the flicker change threshold value, it is determined that the light intensity flicker pattern is distorted, and the light source intensity adjustment is stopped and the light source position dynamic adjustment algorithm is used to optimize the incident angle and propagation path of the light, and the light source position is adjusted according to the optimized incident angle and propagation path; If the flicker change amount is less than or equal to the flicker change threshold, it is determined that there is no distortion in the light intensity flicker pattern.

7. The waterproof light-emitting panel detection method based on ray tracing according to claim 1, characterized in that: The determining whether the intensity of the new reflected light meets the accuracy requirement of defect detection, when the intensity of the new reflected light meets the accuracy requirement of defect detection, obtaining characteristic data of the light intensity flickering pattern, and inputting it into a preset defect detection model to infer the defect position and defect size, includes: Calculating the detection accuracy according to the intensity of the new reflected light, and comparing the detection accuracy with a preset detection accuracy threshold, and if the detection accuracy is greater than the detection accuracy threshold, readjusting the position of the light source; If the detection accuracy is less than or equal to the detection accuracy threshold, then acquiring characteristic data of the light intensity flickering pattern and inputting it into a preset defect detection model to infer the defect position and defect size; Wherein, the characteristic data includes the intensity and frequency characteristics of the light source including the time series; The detection accuracy is calculated by the following formula: in, Represents the intensity of the new reflected light, represents the preset defect detection intensity threshold, Indicates detection accuracy.

8. A waterproof light-emitting panel detection system based on ray tracing, characterized in that: include: A data acquisition module is used to obtain the material type, surface roughness, refractive index, light source position and light intensity flickering mode of the light-emitting panel; A reflection feature analysis module, used for inputting the material type, the surface roughness and the refractive index into a pre-established reflection feature model to obtain a reflection feature; A light source intensity analysis module, used to calculate the initial light source intensity and determine the intensity range of the reflected light according to the reflection characteristics; A reflected light analysis module, used to capture reflected light and analyze reflected light intensity using a ray tracing algorithm according to the initial light source intensity, the material type, the surface roughness and the refractive index; A flicker change analysis module, used to dynamically adjust the light source intensity according to the reflected light intensity and the reflected light intensity range and record the change trend of the light intensity flicker pattern to obtain a flicker change amount; A light source position optimization module, used to make a distortion judgment on the light intensity flicker pattern according to the flicker variation, and dynamically adjust the light source position according to the judgment result; A light updating module, used for recalculating the reflected light intensity according to the optimized light source intensity and the light source position to obtain a new reflected light intensity; The defect detection module is used to determine whether the intensity of the new reflected light meets the accuracy requirement of defect detection. When the intensity of the new reflected light meets the accuracy requirement of defect detection, the characteristic data of the light intensity flickering pattern is obtained and input into a preset defect detection model to infer the defect position and defect size, wherein the characteristic data includes the light source intensity and frequency characteristics containing a time series.

9. An electronic device, characterized in that: The method comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the waterproof light-emitting panel detection method based on ray tracing as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the waterproof light-emitting panel detection method based on ray tracing as described in any one of claims 1 to 7.

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