A waterproof light-emitting panel detection method and system based on ray tracing

Abstract

The present invention discloses a waterproof light-emitting panel detection method and system based on ray tracing, including obtaining the material type, surface roughness, refractive index, light source position, and light intensity flicker mode of the light-emitting panel; inputting the material type, surface roughness, and refractive index into a reflection feature model to calculate the initial light source intensity and determine the range of reflected light intensity; using a ray tracing algorithm to capture the reflected light intensity, dynamically adjusting the light source intensity in combination with the reflection features, recording the change trend of the light intensity flicker mode to obtain the flicker change amount; judging the distortion of the light intensity flicker mode according to the flicker change amount and optimizing the light source position; recalculating the reflected light intensity and judging whether it meets the defect detection accuracy requirements; if it meets, based on the characteristic data of the light intensity flicker mode, inferring the defect position and size through a preset defect detection model. The present invention realizes high-precision and high-efficiency defect detection of waterproof light-emitting panels.

Description

Technical Field

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

[0002] Currently, in the fields of light-emitting panel manufacturing and quality inspection, with the rapid development of intelligent manufacturing, higher requirements are put forward for the accuracy and efficiency of product defect detection. As a key component, light-emitting panels are widely used in electronic devices, lighting systems, and display technologies, and their performance directly affects the quality of the final products. However, the materials and surface characteristics of light-emitting panels vary significantly, from smooth to rough, from transparent to opaque, and these differences result in very different characteristics of reflected light, posing great challenges to defect detection. Traditional detection methods usually adopt a fixed light source intensity and cannot meet the detection requirements under different materials and surface conditions. To address 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-amplitude light intensity adjustment may lead to tiny flickering phenomena 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 masked or distorted, it will lead to misjudgment or missed detection of defect detection. 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 light, and thus affect the accuracy and stability of light intensity adjustment. Therefore, how to ensure the stability and identifiability 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 an existing technology, there is a static detection method 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 panel is placed on a fixed detection platform, and the light source irradiates the surface of the light-emitting panel at a preset angle. The reflected light is guided through a series of optical lenses and mirrors and enters a high-resolution CCD or CMOS image sensor to form an image of the surface of the light-emitting panel. 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 preset threshold to determine whether there are defects. When the reflected light intensity shows abnormal weakening or strengthening in a certain area, the system will mark this area as a potential defect area.

[0004] The prior art uses a single and fixed light source intensity, which cannot meet the detection requirements under different materials and surface conditions. For example, a smooth surface may cause the reflected light to be too strong, masking small defects; while a rough surface has severe light scattering, making it difficult to capture defect signals. At the same time, the setting of the fixed light source position limits the optimization of the light propagation path and reflection characteristics, further reducing the accuracy and adaptability of detection. Meanwhile, the static detection method cannot achieve real-time dynamic adjustment of the 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 this technology extracts the reflected light intensity distribution characteristics through image processing algorithms and performs threshold analysis, this passive processing method is difficult to cope with complex and changeable surface conditions and is prone to false positives or missed detections. Therefore, the prior art has obvious deficiencies in detection flexibility, adaptability, and accuracy, and it is difficult to meet the requirements 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 light-emitting panel detection method and system based on ray tracing to meet the requirements of high-precision and high-efficiency defect detection.

[0006] In a first aspect, to solve the above technical problems, the present invention provides a waterproof light-emitting panel detection method based on ray tracing, including:

[0007] Obtain the material type, surface roughness, refractive index, light source position, and light intensity flicker mode of the light-emitting panel;

[0008] Input the material type, the surface roughness, and the refractive index into a pre-established reflection feature model to obtain reflection features;

[0009] Calculate the initial light source intensity according to the reflection features and determine the reflected light intensity range;

[0010] According to the initial light source intensity, the material type, the surface roughness, and the refractive index, use the ray tracing algorithm to capture the reflected light and analyze the reflected light intensity;

[0011] 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 mode to obtain the flicker change amount;

[0012] Perform distortion judgment on the light intensity flicker mode according to the flicker change amount, and dynamically adjust the light source position according to the judgment result;

[0013] Recalculate the reflected light intensity according to the optimized light source intensity and the light source position to obtain the new reflected light intensity;

[0014] Determine whether the intensity of the new reflected light meets the accuracy requirements for defect detection. When the intensity of the new reflected light meets the accuracy requirements for defect detection, obtain the characteristic data of the light intensity flicker mode and input it into a preset defect detection model to infer the defect position and defect size, where the characteristic data includes the light source intensity and frequency characteristics containing time series.

[0015] In an alternative embodiment, the inputting the material type, the surface roughness, and the refractive index into a pre-established reflection feature model to obtain a reflection feature includes:

[0016] Input the material type into a pre-established multiple linear regression model to obtain a first reflection feature;

[0017] Input the surface roughness into a pre-established analysis of variance model to obtain a second reflection feature;

[0018] Input the refractive index into a pre-established principal component analysis model to obtain a third reflection feature;

[0019] Integrate the first reflection feature, the second reflection feature, and the third reflection feature through a pre-established weighted integration model to obtain a reflection feature;

[0020] Among them, the reflection feature model includes a multiple linear regression model, an analysis of variance model, a component analysis model, and a weighted integration model.

[0021] In an alternative embodiment, the calculating the initial light source intensity according to the reflection feature and determining the range of the reflected light intensity includes:

[0022] Calculate the initial light source intensity and the range of the reflected light intensity through the following formula:

[0023]

[0024]

[0025]

[0026]

[0027] Among them, represents the angle between the micro surface normal and the macro normal, represents the surface roughness, represents the incident angle, represents the Fresnel reflectivity, represents the reflection feature, represents the refractive index, represents a preset attenuation coefficient, Represents the preset parameters matched according to the material type, Represents the initial light source intensity, Represents the minimum reflected light intensity, Represents the maximum reflected light intensity.

[0028] In an alternative embodiment, capturing the reflected light and analyzing the reflected light intensity according to the initial light source intensity, the material type, the surface roughness, and the refractive index by using a ray tracing algorithm includes:

[0029] Simulating the light propagation path by a ray tracing algorithm and recording the incident angle and the reflection angle of the light;

[0030] Calculating the reflected light intensity according to the initial light source intensity, the material type, the surface roughness, the refractive index, the incident angle, and the reflection angle;

[0031] Among them, the reflected light intensity is calculated by the following formula:

[0032]

[0033]

[0034] Among them, Represents the angle between the micro surface normal and the macro normal, Represents the surface roughness, Represents the probability density function of the micro normal, Represents the incident angle, Represents the reflection angle, Represents the preset parameters matched according to the material type, Represents the initial light source intensity, Represents the reflected light intensity.

[0035] In an alternative embodiment, 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 flicker mode to obtain the flicker change amount includes:

[0036] Comparing the reflected light intensity with the reflected light intensity range, if the reflected light intensity is within the reflected light intensity range, using the initial light source intensity as the final light source intensity;

[0037] 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 flicker mode during the light source intensity adjustment process to obtain the flicker change amount;

[0038] Among them, the light source intensity is adjusted by the following formula:

[0039]

[0040]

[0041] Among them, represents the light source intensity after the -th adjustment, represents the light source intensity after the -th adjustment, represents a preset adaptive gain coefficient, represents the sign function, outputs a positive sign or a negative sign, represents a preset light source intensity adjustment step size, represents the target reflection intensity, represents the intensity of the reflected light after the -th adjustment, represents the minimum reflected light intensity, represents the maximum reflected light intensity.

[0042] In an alternative embodiment, the method for judging the distortion of the light intensity flicker mode according to the flicker change amount and dynamically adjusting the light source position according to the judgment result includes:

[0043] Compare the flicker change amount with a preset flicker change threshold. If the flicker change amount is greater than the flicker change threshold, it is determined that the light intensity flicker mode is distorted, and the light source intensity adjustment is stopped and the incident angle and propagation path of the light are optimized by using the light source position dynamic adjustment algorithm. At the same time, the light source position is adjusted according to the optimized incident angle and propagation path;

[0044] If the flicker change amount is less than or equal to the flicker change threshold, it is determined that the light intensity flicker mode is not distorted.

[0045] In an alternative embodiment, the method for judging whether the new reflected light intensity meets the accuracy requirement of defect detection, and when the new reflected light intensity meets the accuracy requirement of defect detection, obtaining the characteristic data of the light intensity flicker mode and inputting it into a preset defect detection model to infer the defect position and defect size includes:

[0046] Calculate the detection accuracy according to the new reflected light intensity and compare the detection accuracy with a preset detection accuracy threshold. If the detection accuracy is greater than the detection accuracy threshold, readjust the light source position;

[0047] If the detection accuracy is less than or equal to the detection accuracy threshold, obtain the characteristic data of the light intensity flicker mode and input it into a preset defect detection model to infer the defect position and defect size;

[0048] Among them, the characteristic data includes the light source intensity and frequency characteristics containing time series;

[0049] Among them, the detection accuracy is calculated by the following formula:

[0050]

[0051] Among them, represents the intensity of the new reflected light, represents the preset defect detection intensity threshold, represents the detection accuracy.

[0052] In a second aspect, the present invention provides a waterproof light-emitting panel detection system based on ray tracing, including:

[0053] A data acquisition module for acquiring the material type, surface roughness, refractive index, light source position and light intensity flicker mode of the light-emitting panel;

[0054] A reflection feature analysis module for inputting the material type, the surface roughness and the refractive index into a pre-established reflection feature model to obtain reflection features;

[0055] A light source intensity analysis module for calculating the initial light source intensity and determining the reflected light intensity range according to the reflection features;

[0056] A reflected light analysis module for capturing reflected light and analyzing the reflected light intensity by using a ray tracing algorithm according to the initial light source intensity, the material type, the surface roughness and the refractive index;

[0057] A flicker change analysis module for 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 flicker mode to obtain a flicker change amount;

[0058] A light source position optimization module for judging the distortion of the light intensity flicker mode according to the flicker change amount and dynamically adjusting the light source position according to the judgment result;

[0059] A ray update module 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;

[0060] A defect detection module is used to determine whether the intensity of the new reflected light meets the accuracy requirements for defect detection. When the intensity of the new reflected light meets the accuracy requirements for defect detection, it acquires the characteristic data of the light intensity flicker pattern and inputs it into a preset defect detection model to infer the defect position and defect size. Among them, the characteristic data includes the light source intensity and frequency characteristics containing time series.

[0061] In a third aspect, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the light ray tracing-based waterproof light-emitting panel detection method described in any one of the above.

[0062] In a fourth aspect, the present invention also provides a computer-readable storage medium. The computer-readable storage medium includes a stored computer program. Among them, when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the light ray tracing-based waterproof light-emitting panel detection method described in any one of the above.

[0063] Compared with the prior art, the present invention has the following beneficial effects:

[0064] (1) By establishing a reflection feature model corresponding to the material and surface characteristics, combining the material type, surface roughness, and refractive index, the present invention accurately calculates the initial light source intensity and the range of reflected light intensity, significantly improving the accuracy and adaptability of defect detection of the light-emitting panel.

[0065] (2) Using the ray tracing algorithm to simulate the light propagation path, capture the distribution characteristics of the reflected light, and dynamically adjust the light source intensity and position, avoiding the detection errors caused by fixed light source intensity and position in the traditional method, and improving the flexibility and reliability of detection.

[0066] (3) By real-time monitoring the change trend of the light intensity flicker pattern, judging whether there is distortion caused by excessive adjustment, and optimizing the light source position in combination with the reflection feature model, the stability and identifiability of the light intensity flicker pattern are ensured, and the accuracy of defect inference is improved.

[0067] (4) Inputting the obtained characteristic data of the light intensity flicker pattern into a preset defect detection model to infer the defect position and size, realizing the accurate positioning and quantitative analysis of defects, and providing efficient and reliable technical support for the quality control of the light-emitting panel.

[0068] In summary, the present invention establishes a reflection feature model corresponding to the material and surface characteristics, combines the ray tracing algorithm to dynamically adjust the light source intensity and position, and real-time monitors the light intensity flicker pattern to accurately infer the defect position and size. This method solves the problem that the fixed light source parameters in traditional detection methods 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 defect detection of the light-emitting panel. Description of the Drawings

[0069] Figure 1 is a schematic diagram of the detection process of a waterproof light-emitting panel based on ray tracing provided by the first embodiment of the present invention;

[0070] Figure 2 is a schematic diagram of the structure of a waterproof light-emitting panel detection system based on ray tracing provided by the second embodiment of the present invention. Detailed Embodiments

[0071] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0072] Refer to Figure 1 , the first embodiment of the present invention provides a method for detecting a waterproof light-emitting panel based on ray tracing, including the following steps:

[0073] S11, obtaining the material type, surface roughness, refractive index, light source position, and light intensity flicker pattern of the light-emitting panel;

[0074] S12, inputting the material type, the surface roughness, and the refractive index into a pre-established reflection feature model to obtain a reflection feature;

[0075] S13, calculating an initial light source intensity according to the reflection feature and determining a reflection light intensity range;

[0076] S14, capturing the reflection light and analyzing the reflection light intensity according to the initial light source intensity, the material type, the surface roughness, and the refractive index by using a ray tracing algorithm;

[0077] S15, dynamically adjusting the light source intensity according to the reflection light intensity and the reflection light intensity range and recording the change trend of the light intensity flicker pattern to obtain a flicker change amount;

[0078] S16, performing a distortion judgment on the light intensity flicker pattern according to the flicker change amount, and dynamically adjusting the light source position according to the judgment result;

[0079] S17. Recalculate the reflected light intensity based on the optimized light source intensity and light source position to obtain a new reflected light intensity;

[0080] S18. Determine whether the new reflected light intensity meets the accuracy requirements for defect detection. When the new reflected light intensity meets the accuracy requirements for defect detection, obtain the characteristic data of the light intensity flicker pattern and input it into a preset defect detection model to infer the defect position and defect size, where the characteristic data includes the light source intensity and frequency characteristics containing time series.

[0081] In step S11, obtain the material type, surface roughness, refractive index, light source position, and light intensity flicker pattern of the light-emitting panel.

[0082] Specifically, the material type can be identified by a composition 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.

[0083] In step S12, input the material type, the surface roughness, and the refractive index into a pre-established reflection feature model to obtain a reflection feature.

[0084] In a specific implementation manner, the inputting the material type, the surface roughness, and the refractive index into a pre-established reflection feature model to obtain a reflection feature includes:

[0085] Input the material type into a pre-established multiple linear regression model to obtain a first reflection feature;

[0086] Input the surface roughness into a pre-established analysis of variance model to obtain a second reflection feature;

[0087] Input the refractive index into a pre-established principal component analysis model to obtain a third reflection feature;

[0088] Integrate the first reflection feature, the second reflection feature, and the third reflection feature through a pre-established weighted synthesis model to obtain a reflection feature;

[0089] Among them, the reflection feature model includes a multiple linear regression model, an analysis of variance model, a component analysis model, and a weighted synthesis model.

[0090] Specifically, first, as the primary factor affecting the reflection feature, the material type is processed through a multiple linear regression model, and the mathematical expression of this model is:

[0091]

[0092] wherein represents the first reflection feature, represents a preset coefficient for material type matching, , and are regression coefficients obtained by least squares fitting. The training process of the model is based on a large dataset of historical material types and reflection features, and the regression coefficients are iteratively optimized to minimize the prediction error. The surface roughness is processed by an analysis of variance model, and its expression is:

[0093]

[0094] wherein represents the second reflection feature, represents the surface roughness, and are model parameters, is a random error term. The analysis of variance model determines the significant influence of roughness on reflection features through statistical analysis of reflection features at different roughness levels. The refractive index is processed by a principal component analysis model, and its expression is:

[0095]

[0096] wherein represents the third reflection feature, , and are the principal components of the refractive index, , and are the principal component coefficients. The principal component analysis extracts the main features of the refractive index data through dimensionality reduction technology, reduces redundant information, and retains key parameters. Finally, through a weighted synthesis model, , and are integrated, and its expression is:

[0097]

[0098] wherein represents the final reflection feature, , and are preset weight coefficients, and the weight coefficients are normalized to ensure that their sum is 1. The weighted synthesis model comprehensively considers the contributions of material type, surface roughness, and refractive index to the reflection feature. Through multi-model collaborative analysis, the influence of each factor on the reflection feature is accurately quantified, providing a reliable theoretical basis for the design and performance optimization of the light-emitting panel.

[0099] In step S13, calculate the initial light source intensity according to the reflection characteristics and determine the reflection light intensity range.

[0100] In a specific embodiment, the calculating the initial light source intensity according to the reflection characteristics and determining the reflection light intensity range includes:

[0101] Calculate the initial light source intensity and the reflection light intensity range through the following formula:

[0102]

[0103]

[0104]

[0105]

[0106] Wherein, represents the angle between the micro-surface normal and the macro-normal, represents the surface roughness, represents the incident angle, represents the Fresnel reflectivity, represents the reflection characteristics, represents the refractive index, represents the preset attenuation coefficient, represents the preset parameter matched according to the material type, represents the initial light source intensity, represents the minimum reflection light intensity, represents the maximum reflection light intensity.

[0107] Specifically, in step S13, the process of calculating the initial light source intensity according to the reflection characteristics and determining the reflection light intensity range involves the combination of physical optics and mathematical models. The reflection characteristics As the core input parameter, together with the optical properties of the surface, it determines the calculation of the light source intensity and the range of the reflection light intensity. The initial light source intensity The calculation formula is as follows:

[0108]

[0109] Wherein, represents the Fresnel reflectivity, and the calculation formula is:

[0110]

[0111] In this formula, represents the refractive index, represents the incident angle, represents the angle between the micro-surface normal and the macro-normal, Represents the surface roughness, which is a preset parameter matched according to the material type. The calculation of the initial light source intensity takes into account the reflection characteristics, surface roughness, Fresnel effect, and the influence of the material type on the light intensity.

[0112] The minimum reflected light intensity has the following calculation formula:

[0113]

[0114] where, represents the preset attenuation coefficient, which is used to simulate the intensity attenuation of light caused by energy loss during the reflection process. The maximum reflected light intensity is directly equal to the initial light source intensity , that is:

[0115]

[0116] By combining the reflection characteristics with the surface optical properties and utilizing the modulation effects of the Fresnel reflectivity and roughness on the light intensity, the ranges of the initial light source intensity and the reflected light intensity are 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.

[0117] In step S14, according to the initial light source intensity, the material type, the surface roughness, and the refractive index, the ray tracing algorithm is used to capture the reflected light and analyze the reflected light intensity.

[0118] In a specific embodiment, the using the ray tracing algorithm to capture the reflected light and analyze the reflected light intensity according to the initial light source intensity, the material type, the surface roughness, and the refractive index includes:

[0119] Simulating the light propagation path through the ray tracing algorithm and recording the incident angle and reflection angle of the light;

[0120] Calculating the reflected light intensity according to the initial light source intensity, the material type, the surface roughness, the refractive index, the incident angle, and the reflection angle;

[0121] where the reflected light intensity is calculated by the following formula:

[0122]

[0123]

[0124] where, represents the angle between the micro - surface normal and the macro - normal, represents the surface roughness, represents the probability density function of the micro - normal, represents the angle of incidence, represents the angle of reflection, represents the preset parameters matched according to the material type, represents the initial light source intensity, represents the intensity of the reflected light.

[0125] Specifically, the ray - tracing algorithm records the angle of incidence of the light by simulating the propagation path of the light on the surface, and the angle of reflection, and calculates the intensity of the reflected light by combining the surface properties and the initial light source intensity. .

[0126] The calculation of the intensity of the reflected light is based on the probability density function of the micro - normal and the Fresnel reflectivity. The probability density function of the micro - normal describes the distribution of the angle between the micro - surface normal and the macro - normal, and its calculation formula is:

[0127]

[0128] where, represents the angle between the micro - surface normal and the macro - normal, represents the surface roughness. This function reflects the influence of surface roughness on the reflection direction of light. The greater the roughness, the more significant the light scattering.

[0129] The intensity of the reflected light has the following calculation formula:

[0130]

[0131] where, represents the preset parameters matched according to the material type, represents the angle of reflection, represents the initial light source intensity. This formula comprehensively considers the contributions of the micro - normal distribution, Fresnel reflectivity, angle of incidence, angle of reflection, and initial light source intensity to the intensity of the reflected light.

[0132] The implementation process of the ray - tracing algorithm first simulates the propagation path of the light, records the angle of incidence and the angle of reflection, and then calculates the intensity of the reflected light through the above formula. The core of the algorithm lies in accurately describing the interaction between the light and the surface, including the reflection direction, energy distribution, and intensity change.

[0133] In step S15, the light source intensity is dynamically adjusted according to the reflected light intensity and the reflected light intensity range, and the change trend of the light intensity flicker pattern is recorded to obtain the flicker change amount.

[0134] In a specific embodiment, 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 flicker pattern to obtain the flicker change amount includes:

[0135] Comparing the reflected light intensity with the reflected light intensity range. If the reflected light intensity is within the reflected light intensity range, the initial light source intensity is used as the final light source intensity;

[0136] If the reflected light intensity is not within the reflected light intensity range, the light source intensity is dynamically adjusted until the reflected light intensity falls within the reflected light intensity range, and the change trend of the light intensity flicker pattern is recorded during the light source intensity adjustment process to obtain the flicker change amount;

[0137] Wherein, the light source intensity is adjusted by the following formula:

[0138]

[0139]

[0140] Wherein, represents the light source intensity after the -th adjustment, represents the light source intensity after the -th adjustment, represents a preset adaptive gain coefficient, represents the sign function, outputs a positive sign or a negative sign, represents a preset light source intensity adjustment step size, represents the target reflection intensity, represents the reflected light intensity after the -th adjustment, represents the minimum reflected light intensity, represents the maximum reflected light intensity.

[0141] Specifically, first, the reflected light intensity is compared with the reflected light intensity range : If satisfies , it indicates that the reflected light intensity is within the preset range, and there is no need to adjust the light source intensity. The initial light source intensity is used as the final light source intensity. If or , it is necessary to dynamically adjust the light source intensity so that the intensity of the reflected light enters the preset range.

[0142] The process of dynamically adjusting the light source intensity is achieved through iteration. The adjusted light source intensity The calculation formula is as follows:

[0143]

[0144]

[0145] Among them, represents the light source intensity after the -th adjustment, represents the light source intensity after the -th adjustment, represents the preset adaptive gain coefficient, represents the sign function, outputs a plus sign or a minus sign, represents the preset light source intensity adjustment step size, represents the target reflection intensity, represents the intensity of the reflected light after the -th adjustment, represents the minimum intensity of the reflected light, represents the maximum intensity of the reflected light.

[0146] After each adjustment, recalculate the intensity of the reflected light until it satisfies that the intensity of the reflected light falls within the range of the intensity of the reflected light.

[0147] During the process of adjusting the light source intensity, record the change trend of the light intensity flicker mode and calculate the flicker change amount . The flicker change amount is calculated by the following formula:

[0148]

[0149] Among them, represents the flicker change amount, represents the light source intensity after the -th adjustment, represents the light source intensity after the -th adjustment, represents the number of adjustments during the adjustment process. This formula quantifies the change trend of the light intensity flicker mode by accumulating the differences in the light source intensity at adjacent time steps.

[0150] By dynamically adjusting the light source intensity, ensuring that the intensity of the reflected light is within a preset range, providing reliable optical conditions for subsequent defect detection. The recording of the flicker change amount provides a quantitative basis for analyzing the change of the light intensity flicker pattern, which helps to optimize the light source adjustment strategy and improve the system performance. The whole process is realized based on iterative algorithms and mathematical formulas, ensuring the accuracy and efficiency of the light source adjustment.

[0151] In step S16, the distortion of the light intensity flicker pattern is judged according to the flicker change amount, and the light source position is dynamically adjusted according to the judgment result.

[0152] In a specific implementation manner, the judging the distortion of the light intensity flicker pattern according to the flicker change amount and dynamically adjusting the light source position according to the judgment result includes:

[0153] Compare the flicker change amount with a preset flicker change threshold. If the flicker change amount is greater than the flicker change threshold, it is judged 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 at the same time, the light source position is adjusted according to the optimized incident angle and propagation path;

[0154] If the flicker change amount is less than or equal to the flicker change threshold, it is judged that the light intensity flicker pattern is not distorted.

[0155] Specifically, the distortion of the light intensity flicker pattern is judged according to the flicker change amount, and the light source position is optimized according to the judgment result and the light source position dynamic adjustment algorithm. The flicker change amount As the core input parameter, it is used to evaluate the stability and distortion of the light intensity flicker pattern. The flicker change threshold As a preset reference value, it is used to compare with the flicker change amount to judge whether the light intensity flicker pattern is distorted.

[0156] The logic of the distortion judgment is as follows: If the flicker change amount is greater than the flicker change threshold , that is , it is judged that the light intensity flicker pattern 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 distortion degree of the light intensity flicker pattern.

[0157] If the flicker change amount is less than or equal to the flicker change threshold , that is , it is judged that the light intensity flicker pattern is not distorted, and there is no need to further adjust the light source position or optimize the light propagation path.

[0158] The implementation process of the light source position dynamic adjustment algorithm is based on the optimization of the incident angle of light and the propagation path. The optimization goal is to minimize the flicker variation , thereby improving the stability of the light intensity flicker pattern. The optimization algorithm iteratively adjusts the light source position, calculates the flicker variation after each adjustment, and compares it with the target threshold until the flicker variation reaches or is lower than the preset flicker variation threshold.

[0159] Through the distortion judgment and the light source position adjustment algorithm, dynamically optimize the light propagation path and the incident angle, reduce the distortion degree of the light intensity flicker pattern, and improve the stability and performance of the optical system. The setting of the flicker variation threshold is based on theoretical analysis and experimental data,

[0160] In step S17, recalculate the reflected light intensity according to the optimized light source intensity and the light source position to obtain the new reflected light intensity.

[0161] Specifically, first, the optimized light source intensity and the light source position will directly affect the incident angle and the reflection angle of the light. Re-simulate the light propagation path 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.

[0162] By recalculating the reflected light intensity, verify the influence of the optimized light source parameters on the light propagation effect, and ensure the stability of the light intensity flicker pattern and the performance optimization of the optical system.

[0163] In step S18, determine whether the new reflected light intensity meets the accuracy requirements for defect detection. When the new reflected light intensity meets the accuracy requirements for defect detection, obtain the characteristic data of the light intensity flicker pattern and input it into the preset defect detection model to infer the defect position and the defect size, where the characteristic data includes the light source intensity with time series and the frequency characteristics.

[0164] In a specific implementation manner, the determining whether the new reflected light intensity meets the accuracy requirements for defect detection, and when the new reflected light intensity meets the accuracy requirements for defect detection, obtaining the characteristic data of the light intensity flicker pattern and inputting it into the preset defect detection model to infer the defect position and the defect size, includes:

[0165] Calculate the detection accuracy according to the new reflected light intensity and compare the detection accuracy with the preset detection accuracy threshold. If the detection accuracy is greater than the detection accuracy threshold, readjust the light source position;

[0166] If the detection accuracy is less than or equal to the detection accuracy threshold, obtain the characteristic data of the light intensity flicker pattern and input it into the preset defect detection model to infer the defect position and the defect size;

[0167] Among them, the characteristic data includes the light source intensity and frequency characteristics containing time series;

[0168] Among them, the detection accuracy is calculated by the following formula:

[0169]

[0170] Among them, represents the intensity of the new reflected light, represents the preset defect detection intensity threshold, represents the detection accuracy.

[0171] Specifically, first, the calculation formula of the detection accuracy is as follows:

[0172]

[0173] Among them, among them, represents the intensity of the new reflected light, represents the preset defect detection intensity threshold, represents the detection accuracy. The detection accuracy 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.

[0174] Secondly, compare the detection accuracy with the preset detection accuracy threshold : If , it indicates that the intensity of the new reflected light does not meet the accuracy requirements for defect detection, and the light source position needs to be readjusted; if , it indicates that the intensity of the new reflected light meets the detection accuracy requirements, and enter the feature data extraction and defect detection stage.

[0175] The characteristic data includes the light source intensity and frequency characteristics containing time series. The light source intensity of the time series records the numerical values of the light source intensity changing with time, and the frequency characteristics are obtained by performing a Fourier transform on the light source intensity, and the calculation formula is as follows:

[0176]

[0177] Among them, represents the angular frequency, represents the frequency characteristics, represents the light source intensity, is a pure mathematical symbol representing the imaginary unit.

[0178] After obtaining the feature data, it is input into a preset defect detection model to infer the defect location and size. The defect detection model is constructed based on a training dataset. During the training process, by inputting the feature data of the light intensity flicker pattern and its corresponding defect information, the model parameters are optimized to enable accurate prediction of the defect location and size. The trained model outputs the defect location coordinates and size by inputting new feature data.

[0179] By accurately evaluating the quality of the new reflected light intensity, the accuracy of defect detection is ensured. The calculation formula and comparison logic of the detection accuracy guarantee the effective evaluation of the light intensity, and the extraction of feature data and the application of the defect detection model achieve the automatic inference of the defect location and size. The entire process is implemented based on mathematical models and algorithms, ensuring the reliability and efficiency of defect detection.

[0180] Refer to Figure 2 , the second embodiment of the present invention provides a waterproof light-emitting panel detection system based on ray tracing, including:

[0181] A data acquisition module for acquiring the material type, surface roughness, refractive index, light source position, and light intensity flicker pattern of the light-emitting panel;

[0182] A reflection feature analysis module for inputting the material type, the surface roughness, and the refractive index into a pre-established reflection feature model to obtain reflection features;

[0183] A light source intensity analysis module for calculating the initial light source intensity based on the reflection features and determining the range of the reflected light intensity;

[0184] A reflected light analysis module for capturing the reflected light and analyzing the reflected light intensity using the ray tracing algorithm according to the initial light source intensity, the material type, the surface roughness, and the refractive index;

[0185] A flicker change analysis module for dynamically adjusting the light source intensity according to the reflected light intensity and the range of the reflected light intensity and recording the change trend of the light intensity flicker pattern to obtain a flicker change amount;

[0186] A light source position optimization module for making a distortion judgment on the light intensity flicker pattern according to the flicker change amount and dynamically adjusting the light source position according to the judgment result;

[0187] A light ray update module 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;

[0188] A defect detection module is used to determine whether the intensity of the new reflected light meets the accuracy requirements for defect detection. When the intensity of the new reflected light meets the accuracy requirements for defect detection, the characteristic data of the light intensity flicker mode is obtained and input into a preset defect detection model to infer the defect position and defect size. Among them, the characteristic data includes the light source intensity and frequency characteristics including time series.

[0189] It should be noted that a waterproof light-emitting panel detection device based on ray tracing provided by an embodiment of the present invention is used to execute all the 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 by one, so they will not be repeated here.

[0190] An embodiment of the present invention also 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 each of the above embodiments of the waterproof light-emitting panel detection method based on ray tracing are implemented, such as Figure 1 Step S11 shown. Alternatively, when the processor executes the computer program, the functions of each module / unit in each of the above device embodiments are implemented, such as a waterproof light-emitting panel detection module based on ray tracing.

[0191] Exemplarily, the computer program can be divided into one or more modules / units. The one or more modules / units are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device.

[0192] The electronic device can be a computing device such as a desktop computer, a notebook, a palm computer, and a smart tablet. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above components are only examples of the electronic device and do not constitute a limitation on the electronic device. It may include more or fewer components than the above, or combine some components, or different components. For example, the electronic device may also include input / output devices, network access devices, a bus, etc.

[0193] The so-called processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the electronic device and connects all parts of the electronic device through various interfaces and circuits.

[0194] The memory can be used to store the computer programs and / or modules. The processor realizes various functions of the electronic device by running or executing the computer programs and / or modules stored in the memory and by calling the data stored in the memory. The memory mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the mobile phone (such as audio data, phone book, etc.). In addition, the memory may include high-speed random access memory and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0195] Among them, if the modules / units integrated in the electronic device are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-mentioned embodiment methods of the present invention, it can also be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice within the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0196] It should be noted that the device embodiments described above are only illustrative. The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the attached drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that they have a communication connection, which can be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art can understand and implement it without creative work.

[0197] The specific embodiments described above further elaborate on the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only the specific embodiments of the present invention and is not used to limit the protection scope of the present invention. It is particularly pointed out that for those skilled in the art, any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A waterproof light-emitting panel detection method based on ray tracing, characterized in that Including: Obtain the material type, surface roughness, refractive index, light source position, and light intensity flicker mode of the light-emitting panel; Input 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 according to the reflection feature and determine the reflection light intensity range; Capture the reflection light and analyze the reflection light intensity by using a ray tracing algorithm according to the initial light source intensity, the material type, the surface roughness, and the refractive index; Dynamically adjust the light source intensity according to the reflection light intensity and the reflection light intensity range and record the change trend of the light intensity flicker mode to obtain a flicker change amount; Judge the distortion of the light intensity flicker mode according to the flicker change amount and dynamically adjust the light source position according to the judgment result; Recalculate the reflection light intensity according to the optimized light source intensity and the light source position to obtain a new reflection light intensity; Judge whether the new reflection light intensity meets the accuracy requirements for defect detection. When the new reflection light intensity meets the accuracy requirements for defect detection, obtain the characteristic data of the light intensity flicker mode and input it into a preset defect detection model to infer the defect position and defect size, where the characteristic data includes the light source intensity and frequency characteristics containing a time series; Among them, the dynamically adjusting the light source intensity according to the reflection light intensity and the reflection light intensity range and recording the change trend of the light intensity flicker mode to obtain a flicker change amount includes: Compare the reflection light intensity with the reflection light intensity range. If the reflection light intensity is within the reflection light intensity range, use the initial light source intensity as the final light source intensity; If the reflection light intensity is not within the reflection light intensity range, dynamically adjust the light source intensity until the reflection light intensity falls within the reflection light intensity range, and record the change trend of the light intensity flicker mode during the light source intensity adjustment process to obtain a flicker change amount; Among them, the light source intensity is adjusted by the following formula: Among them, represents the light source intensity after the -th adjustment, represents the light source intensity after the -th adjustment, represents a preset adaptive gain coefficient, represents the sign function, outputs a plus sign or a minus sign, represents a preset light source intensity adjustment step size, represents the target reflection intensity, represents the -th adjusted reflected light intensity, represents the reflection angle, represents the minimum reflected light intensity, represents the maximum reflected light intensity; Among them, during the process of adjusting the light source intensity, record the change trend of the light intensity flicker mode and calculate the flicker change amount , and the flicker change amount is calculated by the following formula: Among them, represents the flashing change amount, represents the light source intensity after the th adjustment, represents the light source intensity after the th adjustment, represents the number of adjustments during the adjustment process.

2. The method for detecting a waterproof light-emitting panel based on ray tracing according to claim 1, wherein The inputting the material type, the surface roughness, and the refractive index into a pre-established reflection feature model to obtain a reflection feature includes: Input the material type into a pre-established multiple linear regression model to obtain a first reflection feature; Input the surface roughness into a pre-established analysis of variance model to obtain a second reflection feature; Input the refractive index into a pre-established principal component analysis model to obtain a third reflection feature; Integrate 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 feature model includes a multiple linear regression model, an analysis of variance 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, characterized in that, The calculating the initial light source intensity according to the reflection feature and determining the reflection light intensity range includes: Calculate the initial light source intensity and the reflection light intensity range by the following formula: Among them, represents the angle between the micro-surface normal and the macro-normal, represents the surface roughness, represents the incident angle, represents the Fresnel reflectivity, represents the reflection characteristic, represents the refractive index, represents the preset attenuation coefficient, represents the preset parameter matched according to the material type, represents the initial light source intensity, represents the minimum reflected light intensity, represents the maximum reflected light intensity.

4. The waterproof light-emitting panel detection method based on ray tracing according to claim 1, characterized in that, Capturing the reflected light and analyzing the reflected light intensity according to the initial light source intensity, the material type, the surface roughness, and the refractive index by using a ray tracing algorithm includes: Simulating the light propagation path by a ray tracing algorithm and recording the incident angle and the reflection angle of the light; Calculating the reflected light intensity according to the initial light source intensity, the material type, the surface roughness, the refractive index, the incident angle, and the reflection angle; Among them, the reflected light intensity is calculated by the following formula: Among them, represents the angle between the micro-surface normal and the macro-normal, represents the surface roughness, represents the probability density function of the micro-normal, represents the incident angle, represents the reflection angle, represents the preset parameter matched according to the material type, represents the initial light source intensity, represents the reflected light intensity.

5. The waterproof light-emitting panel detection method based on ray tracing according to claim 1, characterized in that Judging the distortion of the light intensity flicker pattern according to the flicker change amount and dynamically adjusting the light source position according to the judgment result includes: Comparing the flicker change amount with a preset flicker change threshold. If the flicker change amount is greater than the flicker change threshold, it is judged that the light intensity flicker pattern is distorted, and the light source intensity adjustment is stopped and the incident angle and propagation path of the light are optimized by using a light source position dynamic adjustment algorithm. At the same time, 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 judged that the light intensity flicker pattern is not distorted.

6. The waterproof light-emitting panel detection method based on ray tracing according to claim 1, characterized in that Judging whether the new reflected light intensity meets the accuracy requirements of defect detection. When the new reflected light intensity meets the accuracy requirements of defect detection, obtaining the characteristic data of the light intensity flicker 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 new reflected light intensity and comparing the detection accuracy with a preset detection accuracy threshold. If the detection accuracy is greater than the detection accuracy threshold, the light source position is readjusted; If the detection accuracy is less than or equal to the detection accuracy threshold, obtaining the characteristic data of the light intensity flicker pattern and inputting it into a preset defect detection model to infer the defect position and defect size; Among them, the characteristic data includes the light source intensity and frequency characteristics containing time series; Among them, the detection accuracy is calculated by the following formula: Among them, represents the intensity of the new reflected light, represents the preset defect detection intensity threshold, represents the detection accuracy.

7. A waterproof light-emitting panel detection system based on ray tracing, characterized in that, For implementing a waterproof light-emitting panel detection method according to any one of claims 1 to 6, including: A data acquisition module for acquiring the material type, surface roughness, refractive index, light source position, and light intensity flicker pattern of the light-emitting panel; A reflection feature analysis module for inputting the material type, the surface roughness, and the refractive index into a pre-established reflection feature model to obtain reflection features; A light source intensity analysis module for calculating the initial light source intensity according to the reflection features and determining the reflected light intensity range; A reflected light analysis module for capturing the reflected light and analyzing the reflected light intensity by 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 for 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 flicker pattern to obtain a flicker change amount; A light source position optimization module for judging the distortion of the light intensity flicker pattern according to the flicker change amount and dynamically adjusting the light source position according to the judgment result; A light ray update module, configured to recalculate the reflected light ray intensity according to the optimized light source intensity and the light source position to obtain a new reflected light ray intensity; A defect detection module, configured to determine whether the new reflected light ray intensity meets the accuracy requirements for defect detection. When the new reflected light ray intensity meets the accuracy requirements for defect detection, obtain the characteristic data of the light intensity flicker 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 time series.

8. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the light ray tracing-based waterproof light-emitting panel detection method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the light ray tracing-based waterproof light-emitting panel detection method according to any one of claims 1 to 6.

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