7388results about "Testing optical properties" patented technology

The invention discloses an LCD display screen display fault judgment method, and relates to the related technical field of LCD display screen detection. Comprising the steps of synchronous acquisition and preprocessing of multi-source signals, feature extraction, establishment of a fault judgment model, generation of a dynamic test mode, dynamic generation of a targeted test image according to a preliminary detection result to excite a potential fault, iterative optimization of a test sequence by a Q-learning algorithm, and fault diagnosis. The invention also discloses a system for judging the display fault of the LCD screen. The system comprises a multi-source data acquisition module, a central processing unit, a memory and a user interface. Various data including display data, driving voltage / current monitoring data, temperature distribution, environment parameters and the like are synchronously collected through the optical sensor, the electric signal probe, the thermal imaging module and the environment sensor, all-directional information of the LCD display screen in the operation process can be obtained, and limitation and misjudgment possibly caused by a single data source are avoided.

The invention relates to the technical field of visual inspection, and particularly discloses an optical communication filter appearance defect detection method and related device.The optical communication filter appearance defect detection method comprises the steps that polarization image sets of an optical communication filter to be detected at different polarization angles are obtained; preprocessing the polarization image set to obtain a defect enhancement image set; performing defect detection on the defect enhancement image set based on a pre-trained multispectral attention fusion network; according to the method, multi-polarization information, special preprocessing and a deep learning network combined with frequency domain-space feature fusion and a cross-modal attention mechanism are utilized, the detection capacity of the defects which are tiny, low in contrast and interfered by film layer textures on an optical communication filter is improved, and the omission ratio is reduced.

The invention provides an LED light source uniformity and color deviation detection method, which comprises the following steps: setting environmental parameters of a constant temperature and humidity test box, monitoring the environment in the box in real time through a temperature and humidity sensor, and triggering a temperature and humidity control system to adjust when detecting that the temperature and humidity deviate from a set value; according to the initial color characteristic database, placing an LED light source in the constant-temperature and constant-humidity test box for an accelerated aging test, and obtaining spectral data of the light source at different time points by adopting a spectrum analyzer; calculating chromaticity coordinates, color temperatures and color rendering indexes corresponding to the spectral data at different time points, calculating a color deviation value of the LED light source, and fitting a change curve of the color deviation along with time; and according to an accelerated aging test result of the LED light source, calculating the color maintenance life of the light source in a high-temperature and high-humidity environment, and completing color deviation detection through a color stability uniformity index of the LED light source.

The invention relates to the technical field of communication, and discloses an optical fiber performance automatic test method, system and device based on optical power detection. The method comprises the following steps: carrying out intelligent scanning detection on an optical fiber network, generating optical fiber resource mapping data, obtaining an OTDR measurement configuration table through dynamic analysis, executing optical pulse injection and signal acquisition to obtain a time domain response characteristic curve, obtaining an optical fiber performance parameter set through wavelet denoising and peak value identification processing, and obtaining the optical fiber performance parameter set. And performing fault analysis by using deep learning and expert rules to obtain diagnosis decision data, and finally generating an optical fiber state evaluation report through digital twin modeling. According to the invention, remote automatic testing, intelligent fault diagnosis and visual monitoring management of the optical fiber network can be realized, and the operation and maintenance efficiency and reliability of the optical fiber communication network are improved.

The invention relates to the technical field of optical testing, in particular to a silicon optical chip detection system which comprises a structure visual angle regulation and control module, a reflection anomaly capture module, a direction dislocation verification module, a response distribution balance module and a structure state calibration module. According to the invention, through the extraction of the gray difference value and the continuous brightness change point in the image, and in combination with the kick boundary identification and the tangent plane construction, the precise positioning and the incident direction extraction of the microstructure abrupt change area are realized, the collection direction is rotated to suppress the gray fluctuation, and the optical stability of the edge alignment layer is improved. The method comprises the following steps: acquiring a brightness extension track, identifying a fracture position, screening reflection abnormal points in combination with diffusion amplitude difference, effectively enhancing the identification capability of heterogeneous reflection, arranging a brightness trend, carrying out included angle calculation, extracting a direction continuous offset track, realizing dynamic modeling of directional deviation, calculating an illumination difference value inside and outside a structure, and comparing a contour path. And the judgment precision of boundary response evolution and abnormal contour distribution is improved.

The invention discloses a display screen image visual angle unevenness correction method and device and a storage medium, which are used for improving the optical measurement precision of a display screen Mura inspection and compensation system. Aligning the central position of the sampling camera to the central position of the calibration screen; inputting the visual angle non-uniform calibration picture with the gray scale of g into a calibration screen; detecting an ROI (Region of Interest) on the calibration screen to generate a brightness array; inputting the pure-color picture with the gray scale of g into the calibration screen, and acquiring the pure-color picture through the sampling camera to generate a pure-color display screen image; calculating a gray average value of the pure color display screen image in the ROI region, and generating a gray average value array; performing centering normalization processing on the brightness array and the gray average array to generate normalized data; calculating a correction coefficient set according to the normalized brightness mean value data and the normalized gray mean value data; generating a group of distance arrays; and according to the distance array and the correction coefficient set, constructing a visual angle non-uniform model of the calibration screen under the gray scale g.

The invention relates to the technical field of industrial product surface quality detection, in particular to a flexible display module surface defect image recognition method, which comprises the following steps: acquiring a plurality of surface images of a flexible display module under different light sources and carrying out distortion removal processing on the surface images; reconstructing and generating three-dimensional reference point cloud data representing the current curved surface form of the module; re-projecting the distorted image to the ideal rigid plane according to the relationship, generating a plurality of corrected images, and generating a plurality of corrected images to eliminate geometric and luminosity distortion introduced by flexible deformation; obtaining a defect candidate area binary image; and extracting a multi-dimensional feature vector of the defect candidate region from the binary image of the defect candidate region, and classifying the feature vector by using a pre-trained defect classification model to obtain a defect identification result. Through the three-dimensional reference point cloud reconstruction and image re-projection technology, the problem of geometric distortion caused by surface deformation of the flexible display module is effectively solved, and misjudgment and missed judgment are avoided.

The invention relates to the technical field of electrical performance testing, and particularly discloses an LED vehicle lamp operation monitoring system and method based on data analysis, and the system can accurately obtain the illumination parameters of the environment where an LED vehicle lamp is located, further scientifically analyzes and determines the reference illumination intensity of the LED vehicle lamp, and on this basis, comprehensively monitors and carefully collects the circuit information of the LED vehicle lamp, thereby improving the reliability of the LED vehicle lamp. Through a data analysis technology, each abnormal lamp bead existing in the LED vehicle lamp is accurately positioned, the abnormal lamp beads are specifically adjusted according to predetermined reference illumination intensity, after adjustment is completed, the running state parameters of the LED vehicle lamp are further monitored, the adjustment adaptation index of the LED vehicle lamp is evaluated accordingly, and the adjustment adaptation index of the LED vehicle lamp is evaluated according to the running state parameters of the LED vehicle lamp. Therefore, whether further performance adjustment needs to be carried out or not is intelligently judged, the adjustment effect is fed back in time, and therefore it is ensured that the made adjustment can fully meet set performance indexes.

The invention discloses an optical cable fault diagnosis system and method based on a vibration filtering algorithm, relates to the technical field of optical cable fault diagnosis, and solves the problems of low efficiency, long response time and the like in the prior art and the technical problem that the health condition of an optical cable is difficult to comprehensively assess through single optical power data. The quality data of the optical cable are acquired; training an artificial intelligence model based on the historical vibration signal data to obtain an optical cable fault identification model; recognizing the vibration data based on an optical cable fault recognition model to obtain a recognition result; calculating an optical cable aging evaluation coefficient based on the vibration signal data and the optical power loss data; constructing an optical cable aging evaluation coefficient correction model based on the environment data to correct the optical cable aging evaluation coefficient obtained through calculation, and obtaining a target optical cable aging evaluation coefficient; and judging whether to carry out fault early warning based on the identification result and the target optical cable aging evaluation coefficient. The technical problem is solved.

The present invention provides a method, device, equipment and storage medium for calibrating an optical detection light source, the method comprising: performing multi-parameter data collection on a target light source, iteratively optimizing light source parameters, and obtaining optimal parameter settings and performance indicators. Based on the optimal parameter settings and performance indicators, the target light source is monitored and processed in real time, the drift trend data of the light source parameters are obtained, and automatic compensation is performed according to the drift trend to generate corrected light source parameters. By cumulatively analyzing the corrected light source parameters, an association model between the light source parameters and environmental conditions is constructed. According to the association model and the corrected light source parameters, a standard reference spectrum matching the current detection task is selected, and the actual output of the target light source is calibrated based on the reference spectrum. The present invention combines multi-parameter data collection and optimization, drift trend monitoring and automatic compensation processing to realize dynamic association modeling of light source parameters and environmental conditions, perform adaptive calibration, and improve the accuracy and stability of the detection system.

The invention discloses a wavefront error detection method for a primary and secondary mirror optical system, which belongs to the technical field of optical detection, and specifically comprises the following steps: establishing a performance prediction model, and calculating ideal wavefront phase distribution; acquiring a point spread function image through a detector, and recovering actual wavefront phase distribution by using an iterative phase recovery algorithm; performing dynamic adaptive calibration, monitoring and updating a wavefront phase in real time, comparing the dynamically calibrated wavefront phase with an ideal wavefront phase, calculating an error and predicting a variation trend by using an adaptive wavefront error compensation algorithm, and correcting the wavefront error in real time by using an adaptive optical method; and repeating the steps until a preset wavefront error threshold value is met. The method improves the performance stability and precision of the primary and secondary mirror optical system, and is suitable for error correction of a high-precision optical system.

The invention belongs to the technical field of lens calibration, and particularly discloses and provides an optical lens production intelligent calibration system which comprises an environment coupling module, an optical detection module, a self-adaptive calibration decision module and an automatic focusing adjustment module. According to the invention, various environmental data are collected in real time through the environmental coupling module to form a time-space correlation parameter set, so that a basis is provided for suppressing environmental interference; the optical detection module generates a dynamic target sequence and synchronously acquires various parameters of the lens, so that a calibration path can be dynamically optimized; the adaptive calibration decision module not only can establish a mapping relation between environment and optical distortion, but also can calculate a focusing adjustment parameter based on multiple parameters when an error exceeds a threshold value; and the automatic focusing adjustment module controls the focusing device in real time according to the adjustment parameters and verifies the adjustment parameters, so that sorting and recalibration of qualified and unqualified lenses are realized, the calibration accuracy is comprehensively improved, and the scene adaptability of an AF algorithm is enhanced.

The invention discloses a joint test system, a silicon carbide metasurface grating detection method and a silicon carbide metasurface grating detection device, and belongs to the technical field of semiconductor detection. A synergistic excitation signal is generated by regulating a light source and a microwave source and is applied to the silicon carbide metasurface grating to be measured to form a light intensity and microwave field interference pattern. The method comprises the following steps: synchronously acquiring data through multiple channels, constructing a multi-dimensional matrix through time alignment, marker feature extraction and coordinate mapping, extracting defect features to establish a reference model, calculating deviation degree to judge quality, and carrying out abnormal point screening, candidate region construction and coupling verification on a defect grating to divide a potential defect region. For a potential defect area, excitation parameters are dynamically adjusted through a gradient descent algorithm, and defect grades are divided by combining the characteristic defect degree and the area. According to the invention, the problems of insufficient single-mode detection, low multi-mode alignment precision and blind adjustment of excitation parameters are solved, cross-band cooperative detection and intelligent grading are realized, and the detection reliability is improved.

The present invention relates to the field of defect detection technology, and in particular to an OLED screen defect detection method based on optical-magnetic multimodal fusion, comprising the following steps: S1: synchronous excitation and data acquisition based on pulsed current drive; S2: cross-modal spatial calibration and noise suppression; S3: polarization-magnetic field coupling feature extraction; S4: dynamic correlation decision-making and closed-loop feedback, including realizing defect classification determination through correlation analysis of multimodal data, and verifying the authenticity of defects through current overload testing. This method effectively solves the problems of ambient light interference, missed detection, high cost, low resolution, etc. existing in the prior art, has significant beneficial effects, can improve detection accuracy, efficiency and reliability, meet the needs of large-scale production lines, and can efficiently locate and reduce errors and redundant steps in the detection process.

The invention discloses a matrix layout illumination state detection method, device and equipment, and the method comprises the steps: collecting and analyzing a power supply bus current waveform and a single lamp feedback signal, and generating a node feature cluster; extracting a power consumption difference value of adjacent lamps, identifying an abnormal observation point and constructing a fault diffusion chain; marking a timestamp for the fault diffusion chain, determining a fault source, and marking current by injecting characteristics to delimit an influence domain; deploying monitoring anchor points at the boundary of the influence domain, collecting the light color parameter variation and predicting the residual life; extracting the oscillation envelope of the starting current peak, evaluating the health degree of the driver and generating a maintenance density field; and a three-dimensional detection field is constructed by fusing multi-dimensional detection data, singular points are searched, and coordinates of a fault lamp are accurately analyzed through fault positioning pulses. According to the invention, three-dimensional monitoring from electrical characteristics and optical performance to driver states is realized, a single lamp fault can be accurately positioned, a life trend can be predicted, fault propagation can be tracked, and technical support is provided for intelligent operation and maintenance of a large-scale illumination system.

The invention discloses an ARVR resin wafer process which comprises the following steps: preparing a to-be-detected resin wafer and a reference test piece, and carrying out positioning marking on a micro-nano structure area of the to-be-detected resin wafer to obtain a detection sample; performing multi-dimensional spectrum characterization on the detection sample and the reference test piece, determining a material non-uniform distribution area of the detection sample through comparative analysis, and obtaining molecular structure characterization data; carrying out stress field detection and dynamic response analysis on the material non-uniform distribution area to obtain mechanical property characterization data and high-risk defect points; carrying out microstructure and morphology analysis on the high-risk defect points to obtain defect feature data; and performing system evaluation according to the molecular structure characterization data, the mechanical property characterization data and the defect characteristic data to obtain a health degree evaluation result of the resin wafer. According to the technical scheme, multi-scale characteristic characterization can be carried out on the micro-nano structure area in the resin wafer for AR / VR, and systematic detection of the characteristics such as the molecular state, the interface stress and the phase change of the material is achieved.

The invention relates to the technical field of laser calibration, in particular to a laser optical axis calibration device and method, and the device comprises an optical axis offset detection module, a calibration parameter calculation module, a dynamic adjustment implementation module and a calibration effect evaluation module. According to the invention, the response speed and precision are enhanced by monitoring the output of the laser emitter in real time, evaluating the instant deviation of the optical axis and dynamically calibrating the optical axis, the deviation trend of the optical axis is predicted by using a data analysis technology, the future deviation path is effectively controlled, and non-critical calibration is reduced, so that the long-term performance and stability of equipment are improved; dynamic adjustment measures are adopted, the positions of an angle adjuster and an optical element are finely adjusted, so that high calibration precision is ensured, energy loss and equipment abrasion are reduced, calibration effect evaluation of a vibration sensor provides immediate feedback for operation, transparency of the calibration process is improved, an operator can make a more accurate decision based on detailed data, and the operation efficiency is improved. Therefore, the reliability and the operation efficiency of the calibration task are enhanced.

The invention relates to the technical field of display screen detection, in particular to a liquid crystal display screen module performance detection method and system, and the method comprises the steps: collecting an image sequence of pure color pictures displayed by a display screen module at a full brightness level, and obtaining a screen display image of each pure color picture according to the image sequence; extracting a feature vector of the screen display image, performing feature analysis on the screen display image according to the feature vector, obtaining an abnormal point of each display pure color picture, and recording a spatial position and a deviation direction of the abnormal point; if at least one display pure color picture has the abnormal point, performing secondary judgment on the abnormal point by combining the spatial continuity and time stability characteristics of the adjacent frame of the abnormal point, and obtaining the abnormal type of the abnormal point; and generating an anomaly detection report of the display screen module. According to the method, the accuracy and robustness of detection are improved, misjudgment and missing detection can be effectively reduced, and the quality control level of the liquid crystal display screen module is remarkably improved.

The invention relates to the technical field of optical cable fault positioning, in particular to an optical cable fault positioning method and system and a storage medium. The method comprises the following steps: constructing an optical cable operation link topological graph by obtaining optical cable communication link operation data and combining optical cable transmission line distribution conditions and operation transmission link parameters; according to the abnormal trend data of the transmission signal of the optical cable and the link topological graph, measuring abnormal transition gradient distribution data of the link, and further detecting the abnormal state of the dynamic operation jump point of the optical cable; according to a detection result, analyzing abnormal data of an optical cable operation jump point structure, and identifying an optical cable transmission load imbalance condition; the optical cable operation performance degradation trend is predicted by evaluating the unbalanced load, finally, optical cable fault type division is performed, fault positioning processing is performed on a link topological graph, and optical cable fault positioning data is obtained; according to the invention, the optical cable fault is positioned, so that the optical cable fault identification is more accurate.

The invention relates to the technical field of mobile phone detection, in particular to an OLED mobile phone screen linear defect detection method and system. According to the method, the vibration time domain signal on the surface of the screen within the preset time period is obtained and does not depend on the display brightness of the screen, and the defect position is obtained through the abnormal signal interval, so that misjudgment caused by non-uniform brightness of the display image is avoided, the spectral data of each pixel is captured by using the spectral image, and the detection accuracy is improved. The influence of ambient light and display brightness can be effectively eliminated, defects are analyzed through the gradient magnitude of spectral data, misjudgment caused by light change and screen brightness difference can be reduced, abnormal pixels and normal pixels are distinguished by analyzing the gradient magnitude, subtle differences between the pixels can be recognized more accurately, and the accuracy of the detection result is improved. By acquiring the parameter features of each abnormal pixel, the characteristics of the defect can be described more comprehensively, so that the accuracy of defect identification is improved, the defect degree is evaluated through the parameter features, and more accurate defect degree evaluation can be obtained.

The invention discloses an RGB LED light source calibration mode optimization method and system, and the method comprises the steps: collecting the color coordinates and brightness data of a three-primary-color light source of an RGB LED, and recording the actual optical characteristics; based on the collected data, establishing a physical model of the light mixing effect of the RGB LED light source, and calculating an initial PWM duty ratio corresponding to a target color coordinate and brightness; inputting the initial PWM duty ratio into the intelligent calibration algorithm model, and optimizing and calculating the optimal PWM duty ratio; the optimized PWM duty ratio is written into an MCU, and the MCU controls mixed light output of the RGB LED according to the written duty ratio; and testing and verifying the calibration effect of the RGB LED light source, and adjusting the parameters of the intelligent calibration algorithm model according to the test result. According to the invention, the PWM duty ratio can be dynamically optimized to realize high-precision light mixing output, and rapid repair and real-time adjustment are supported. The invention belongs to the technical field of photoelectricity, and aims to solve the core problem of the existing RGB LED light source calibration technology and improve the consistency of the light source performance and the production efficiency.

The invention discloses a lens production defect detection method and equipment thereof, and relates to the technical field of visual inspection.The equipment comprises an information acquisition module, a central processing unit, a process regulation and control module and an interactive communication module.The information acquisition module acquires multi-source sensing information at regular time, so that both comprehensiveness and accuracy are improved; high accuracy of visual detection is guaranteed; through an information processing model, quantification is accurate and traceable, defect degree visualization and defect accurate classification are realized, then process defects are positioned, the interference degree of the environment on a detection result is determined, and misjudgment of the defects due to environmental factors is avoided; through linkage of defect data, process precision and environmental interference, a process optimization scheme is generated in a targeted manner, closed-loop response from defect generation to process adjustment is realized, and the production line response speed is improved; and finally, the lens production yield is remarkably improved, and the production cost of long-term detection is reduced.

The invention relates to the technical field of screen quality detection, and discloses a dead pixel detection method, system and device for a liquid crystal display screen and a storage medium, and the method comprises the steps: obtaining the pixel distribution information of a to-be-detected display screen, and marking the corresponding pixel coordinates of each pixel point based on the pixel distribution information; after the detection signal is received, pixel points of the display screen to be detected are divided into a plurality of pixel blocks based on the pixel coordinates, and each pixel block is marked with a block identifier; based on the pixel coordinates and the block identifiers, determining block coordinates of each pixel point, dividing each pixel point into a plurality of pixel groups based on the block coordinates, and marking group identifiers for each pixel group; setting a detection sequence based on the group identifier of each pixel group, and controlling each pixel group to display a preset detection image group one by one based on the detection sequence; obtaining display effect images of the display screen to be detected one by one and inputting the display effect images to a preset image dead pixel recognition model to generate dead pixel detection result information; the method has the effect of improving the dead pixel detection efficiency of the liquid crystal display screen.

The invention relates to the field of optical cable early warning, in particular to a DVS-based optical cable early warning management and control method and an early warning system. Analyzing the brightness change data, performing path identification on the brightness change data, and determining a target position of the brightness change data; acquiring environment data of the target position, and verifying the brightness change data according to the environment data; based on a verification result, when the target position meets an abnormal condition, analyzing an abnormal parameter of the target position; predicting an abnormal change parameter of the target position according to the abnormal parameter of the target position; and determining a management and control strategy according to the abnormal parameters and the predicted abnormal change parameters, generating early warning information from the abnormal data of the target position based on the management and control strategy, and sending the early warning information to a management end. By considering environmental factors, the abnormity of the optical cable can be accurately detected, possible faults can be predicted, efficient management and control are provided, and accurate monitoring of the optical cable is realized.

The invention relates to the technical field of optical fiber communication, in particular to a digital twin model parameter updating method applied to an optical cable. The method comprises the following steps: collecting optical fiber laying data; performing laying structure division based on the optical fiber laying data to obtain flat structure optical fiber data and layer-stranded optical fiber data; evaluating the tensile strength of the optical cable based on flat structure optical fiber data; detecting the optical signal transmission intensity of the flat-structure optical fiber data based on the tensile property of the optical cable; performing intelligent loss compensation on the flat structure optical fiber data according to the optical signal transmission intensity to obtain signal compensation data; calculating the distribution uniformity based on the layer-stranded optical fiber data; determining optical fiber dislocation based on the distribution uniformity to obtain optical fiber dislocation data; and performing optical fiber Brillouin scattering detection based on the optical fiber dislocation data to obtain Brillouin scattering data. The accuracy and real-time performance of optical cable performance evaluation are improved based on the optical fiber communication technology, and therefore the stability and reliability of optical cable signal transmission are remarkably improved.

The invention relates to the technical field of display screen detection, and discloses a liquid crystal display screen color difference detection system and method.The system comprises a multispectral imaging module, a curved surface deformation modeling module, a coupling tensor decomposition module, a biological excitation feature extraction module, a dynamic compensation control module and a technological parameter interface module; the method comprises the following steps of synchronously collecting a multispectral image and screen deformation data, constructing and decomposing a multidimensional tensor containing geometric constraints, extracting biological excitation visual features, and generating and applying voltage compensation through model prediction control so as to dynamically correct the color difference of the flexible screen. According to the method, through multispectral and geometry synchronous perception, multidimensional tensor constraint decomposition, biological excitation and deformable convolution feature extraction, time-varying model prediction control and dynamic weight adjustment of fused manufacturing parameters, high-precision capture and personalized compensation of the dynamic chromatic aberration of the flexible screen are realized. The defects of dynamic perception, quick response and individual adaptability are overcome.

The invention relates to the technical field of lens correction, and discloses an intelligent correction method and system for the optical performance of a functional lens, and the method comprises the steps: obtaining the original data of the lens, and carrying out the preprocessing of the original data of the lens, and obtaining the surface data of the lens; performing surface parameter calculation according to the lens surface data to obtain three-dimensional surface parameters; performing weighted residual calculation according to the three-dimensional surface parameters to obtain a residual matrix; performing spatial correlation analysis according to the three-dimensional surface parameters and the residual matrix to obtain an error region and a normal region; performing compensation analysis according to the residual matrix, the error region and the normal region to obtain a parameter compensation amount; and performing multi-objective optimization according to the parameter compensation amount to obtain an optimal compensation parameter, and correcting the lens according to the optimal compensation parameter. The method has the following effect that the correction accuracy of the optical performance of the functional lens can be improved.

The invention discloses a color analyzer which is used for filtering stray light entering a detection path and improving the accuracy of a measurement result. The analyzer comprises a lens, an analyzer main body and a cut-off filter, the lens is connected with the analyzer main body, and the analyzer main body is used for detecting a light beam transmitted from the lens; a beam splitting assembly, a light filtering assembly and an analysis module are sequentially arranged in the analyzer body in the light beam transmission direction, and three light filtering positions are arranged in the analyzer body. The three light filtering positions are located between the lens and the beam splitting assembly, between the beam splitting assembly and the light filtering assembly and between the light filtering assembly and the analysis module respectively, and the cut-off light filter is arranged at any light filtering position or arranged in the lens. When the light beam penetrates through the cut-off filter, stray light in the light beam is filtered out by the cut-off filter, and the stray light is one or more kinds of invisible light.

The invention relates to the technical field of display screen defect detection, and discloses a mobile phone display screen defect detection method, device and equipment and a storage medium, and the method comprises the steps: collecting display images of a to-be-detected mobile phone display screen at a plurality of observation angles; the reflection intensity distribution of the display image is analyzed by using polarization optical characteristics, and a de-reflection image is generated after surface reflection components are separated; transforming the pixel brightness of each observation angle in the de-reflection image to a unified reference viewpoint to obtain a unified reference viewpoint image, and extracting a first defect feature vector of each pixel in the unified reference viewpoint image; and fusing the first defect feature vectors extracted from multiple observation angles to obtain a second defect feature vector, comparing the second defect feature vector with a preset threshold, and outputting a defect detection report. According to the application, multi-angle information advantages are utilized, and a defect classification mechanism based on RGB channel response differences is established; and various defect types of bright spots, dark spots, color cast and line defects can be accurately distinguished.

The invention relates to the technical field of focus testing, and particularly discloses a laser cutting head zero focus testing method based on reflected light detection, which comprises the following steps: S1, acquiring an optical signal reflected by a processed plate in a cutting process; s2, adjusting the position of a focusing lens to enable a laser focus to move along the optical axis direction relative to the surface of the plate; s3, recording reflected light intensity values corresponding to different focus positions, obtaining a function relationship between the reflected light intensity and the focus positions, and drawing a light intensity-focus position relationship curve; s4, determining a corresponding focus position when the intensity of the reflected light reaches the maximum value as an optical zero focus position of the system; s5, automatically recording and storing an optical zero focus position; the reflected light detector arranged in the cutting head or the laser reads the intensity of the reflected light in the cutting process, the function relation between the focus position and the intensity of the reflected light can be established, and the focus position corresponding to the maximum value of the intensity of the reflected light is the most accurate optical zero focus position.